KAYABATECHNICAL APR. 2023
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REVIEWKAYABA TECHNICAL REVIEW No. 65 OCT. 2022

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KAYABA TECHNICAL REVIEW
No. 66 APR. 2023
CONTENTS
Foreword
Artificial Intelligence Will Change Industries

TAMURA Satoshi

1

DEGUCHI Mikio

3

Oil Seal and Technology for Detecting the Orientation.
TSURUMI Takuya
Incorporation of Processing of Base Plates for Piston Motors Into FMS Lines HANAEDA Ken
Technology Explanation

8
13

Use of AI Technology in Development of SA ElementsProduct Introduction

17

Editorial
Thoughts on the Degradation of Oil
Technology Introduction

OHUCHIDA ShunMIYAUCHI Yuuki
SAGEHASHI Ryota

Development of Anti-cavitation Valve for Travel Motor of 7-ton Hydraulic Excavator
SUZUKI Jun
Development of Vane Pump for AT
GOMI Hiroki
Explanation
Initiatives to Develop Digital Personnel
MIYAUCHI Yuuki

ISASHI RyousukeTAKINO Shinsuke
Essay
Account of Residence in Indonesia
SHIMENO Yoshiro
Glossary
1. FMS
2. Counterbalance Valve
Related Patents
Editors Script

HANAEDA Ken
SAITO Keiji

28
32
38

47
51
52
53

KAYABA TECHNICAL REVIEW No. 66 APR. 2023

Foreword

Artificial Intelligence Will Change Industries
TAMURA Satoshi*

Deep learning is a kind of artificial intelligence (AI)that has rapidly become popular in recent years. Bylearning enormous amounts of data sets using a multilayered neural network that imitates the human brain, thetechnology can execute natural language processing, image recognition and other various tasks with high accuracy. In the history of AI, deep learning has particularly
gained the spotlight with its high performance in achieving different tasks including image recognition and natural language processing. This technology is also expected
to be further improved and applied to a variety of fields.
Now, what do you feel about the above text after having read through it? The above paragraph is actually that
automatically created by AI after I told it to "explain
what deep learning is." You probably see the text as if it
had naturally been written by a human being, grammatically correct, and properly describing the subject. Next,
look at the image in Fig. 1. This is also a piece of graphicthat I asked AI to create just with the keywords "automobile", "future", "night", and "Milky Way". Like this, images with a quality that can be compared favorably withthose drawn by human beings can be swiftly completed
by AI in just several seconds.
Deep learning has been used not only in research anddevelopment (R&D) on natural language processing andimage recognition, but also in R&D on speech processing. Familiar examples include voice commands tosmartphones and voice interfaces of smart speakers. Furthermore, some have tried to apply deep learning to signal processing or data analysis. These applications havestarted to be introduced in chemical, medical, and mechanical industries.
Now let me expand on the meaning of the words "Artificial Intelligence", "deep learning", and "Machine
Learning" as shown in Fig. 2. First, artificial intelligence(AI) means to artificially implement intelligence at a level equivalent to or even higher than human intelligence.
AI covers various fields ranging from fundamental research to application engineering, including the development of humanoids and computer based Igo and Shogi.
“Machine learning” is one AI approach. For implementing human learning mechanisms and functions on a computer system, machine learning pursues appropriate

Artificial
intelligence

Machine learning
Deep learning

Fig. 1

Image drawn by AI

Fig. 2*

Associate Professor, Gifu University―1―

Artificial intelligence, machine learning, and deeplearning

Artificial Intelligence Will Change Industries

mathematical models and their algorithms as well as theirapplication. Machine learning is also related to the above
mentioned natural language processing, image processing, and speech processing as well as statistics. “DeepLearning” is a type of machine learning that uses a “deepneural network (DNN)” as a mathematical model.
It is in just the last decade that deep learning has rapidly advanced. This was achieved with the proliferationof the Internet and the higher performance of computers,
which allowed collection of large amounts of data andhigh-speed processing of the collected data, althoughdeep learning models themselves had been proposedsince olden times. With a focus on industrial applicationsof deep learning, the following introduces several examples.
Efforts have arisen to implement “Anomaly Detection”
to automate and optimize inspection of industrial products or status monitoring of manufacturing machinery.1)
With this technology, computers can judge products OK
or not OK just by scanning their images, thereby enabling systemization of inspection tasks by humans thatare quite individual skills. This may eventually alleviate
the lack of labor caused by the low birthrate and aging
society. Manufacturing machinery can be installed withmicrophones and vibration sensors for continuous monitoring of operating status, which allows the detection ofsigns of failures or the performance of machinery maintenance at optimal timings. Plant owners can expect
higher availability of production equipment and lower
maintenance cost.
Detecting human errors or potentially dangerous tasks
in the assembly process will improve product quality andhelp create a safer work environment. In addition, collecting and analyzing information about employees’ tasks
and the traffic line of moving machines and then conducting a PDCA (Plan, Do, Check, Action) cycle to develop
and execute an improvement plan will probably improvein making decisions. Then, to inform people of the behavior of AI, an effort called “Explainable AI (XAI)” hasgained attention from the viewpoint of application to industry and medicine.3) In a deep learning model for image analysis for instance, the parts of the image focusedby the computer in making decisions can be disclosed.
Another example is a system to analyze information obtained from many different sensors that is designed to beable to calculate the importance of each piece of information. Furthermore, an attempt is widely underway thatwill effectively use the findings obtained for developing
new industrial products or projecting the effectiveness ofdrugs.
Promoting these effective uses of AI described above
in industry should enhance the possibility of technical innovation and new business development. To do so, “Digital Transformation (DX)” is a must to digitize all information at the site, connect the digital information with AI
technology, and establish a new information utilizationmeans in the whole business flow. During the COVID-19
pandemic, we were physically separated from our workplace and became acutely aware of the necessity of DX
for online meetings and teleworking as well as for information exchange with sites or among employees. Beyond
DX lies AI. Toward the age of living under or even after
the pandemic as well as to be able to respond to theworld's dramatically changing circumstances, I believethat we need to use AI as much as possible.
References
1) ASAHI, et al.: "Proposal of failure prediction method of factoryequipment by vibration data with Recurrent Autoencoder",Transactions of the JSME, Vol.86, No.891, 2020.
2) TAMURA, et al.: "Multi-modal service operation estimation using DNN-based acoustic bag-of-features", EUSIPCO (international conference), 2015.
3) MIYOSHI, et al.: "Machine learning using clinical data at base-

operations and their efficiency. These efforts are called"Service Engineering". R&D related to such service engineering is underway by leveraging AI technology. 2)
Concrete examples of R&D include an analysis of images captured by monitoring cameras to notify any misoperation or dangerous tasks and an analysis of information
obtained from employees' wearable sensors to identify
any issues.
Deep learning has the problem that its mathematic
models are likely to be a black box and people cannot
exactly know the information or logic used by computers―2―line predicts the efficacy of vedolizumab at week 22 in patientswith ulcerative colitis", Scientific Reports 11, 2021.

KAYABA TECHNICAL REVIEW No. 66 APR. 2023

Editorial

Thoughts on the Degradation of Oil
DEGUCHI Mikio*

1.

Introduction
The author has been involved in a joint research project with KYB Corporation for several years. The projectis intended to develop a sensor that can detect changes in
the properties of oil caused by its degradation by using a
low-cost simple device. Oil is used in mechanical equipment for various purposes including lubrication, cooling,
electrical insulation, and rust prevention. It is also widelyused as a working fluid in hydraulic systems virtually everywhere in the world. However, oil gradually changes inproperty with time as the systems are operated as seen in
the familiar example where the engine oil used in automobiles gets black little by little as the mileage increases.
Such changes generally progress unfavorably. Therefore,
this is called "degradation".
Oil degradation is mainly caused by oxidation andcontamination. The degradation appears as changes invarious physical parameters.1)-6) The degree of oxidation
can be evaluated by total acid value but we are focusedon "permittivity", which is an electrical parameter that
may be relatively highly correlated with total oxidation.
The permittivity of a material can be determined as thecapacitance (a parameter indicating how easily the material can charge electricity) between two electrodes filledwith the material. Capacitance measurement itself is oneof the basic electrical measurement techniques and may
be carried out using various methods. In fact, there is sufficient space for exploring an appropriate method for detecting changes in oil properties from various angles.
This paper briefly introduces our related efforts and describes my various thoughts about the word "degradation" of oil.
2.

What is Permittivity?
The “permittivity” of a material can be plainly described as how easily the material can be electricallydrawn. Electricity borne by an object is called "electriccharge". Electric charge can be positive (+) or negative(-). It is well known that like charges (positive charges ornegative charges) repel each other and unlike charges*

Professor emeritus, National Institute of Technology KOSEN,
Niihama College(positive and negative charges) attract each other. All
matter consists of elements that are combinations of atoms as a basic unit. Each atom includes a positively
charged nucleus surrounded by negatively charged electrons. In other words, matter contains countless positive
and negative charges. Normally, matter has the sameamount of positive and negative charges. The center ofgravity of positive charges is aligned with that of negative charges. These two types of charges are evenly distributed in the matter as a whole.
When matter is filled between two electrodes and applied with a voltage, the positive charges in the matterare repelled by the positive electrode and attracted by thenegative electrode. The negative charges are applied witha force in the opposite direction. As a result, the center ofgravity of the positive charges in the matter is misalignedwith that of the negative charges. This is called "polarization". Thus, permittivity is a parameter indicating howeasily this polarization takes place.
There are several possible causes of polarization. One
is that the electron cloud surrounding the nucleus of each
atom is attracted by the positive side to cause displacement. This is called electron polarization, which is a phenomenon that always takes place in all matter as long as
matter consists of atoms. Some kinds of matter consist of
atoms that are divided into positive and negative ions andare bound together by attractive forces between the positive and negative ions. In this case, if a force is applied tothe positive and negative ions in opposite directions toeach other, the ions each move from a position of equilibrium in the opposite direction, resulting in a positional
difference in the center of gravity between the positive
and negative charges. This is called ionic or atomic polarization.
Some other kinds of matter originally consist of molecules in which the center of gravity of their positive
charges is dislocated from that of their negative charges.
Molecules that have originally been polarized are called"permanent dipoles". Matter consisting of permanent dipoles, when viewed as a whole, are not particularly biased in terms of polarity, because the dipoles are usuallyoriented at random. However, when the positive/negativepoles are applied with a force in the opposite direction,―3―

Thoughts on the Degradation of Oil

the dipoles are aligned in a direction parallel with theforce. As a result, the matter as a whole is polarized. Thisis called orientation polarization.
It can be said that the majority of molecules constituting matter consist of permanent dipoles. One typical andfamiliar example is water molecules. A water moleculeconsists of two hydrogen (H) atoms and one oxygen (O)atom. Hydrogen is assigned the atomic number 1, whichmeans that it has only one electron. This electron is used
to bond to the oxygen atom. This uncovers the positive
charge of the nucleus (proton) of the hydrogen atoms to
make them positive and the oxygen atom negative. The
two hydrogen atoms and the oxygen atom are not aligned
in a line but bonded together at an angle of 104.5°. Thismeans that the center of gravity of the positive charge isdislocated from that of the negative one. Therefore, watershows a notably high permittivity among liquids.
3.

Detecting Minute Changes in Permittivity
The capacitance between two electrodes is proportional
to the permittivity of the insulation between the electrodes. Any change (increase) in permittivity due to oil
degradation is as small as several percent at most, although it depends on the extent of the degradation. Furthermore, the electrodes of the sensor only show a small
capacitance themselves because the sensor cannot be solarge. So, it is necessary to detect tiny changes in such asmall value. These minute changes in permittivity may
be detected in several ways.
In general, when you try to measure a physical quantity using an electronic technique, you always end up measuring the magnitude of the target quantity in units ofvoltage or time. A challenge you must eventually overcome is how you can practically convert the magnitude
of capacitance into a voltage or time.
For example, it is useful to remember that the voltage
between two electrodes can be determined by dividing
the amount of charges accumulated between the electrodes by the capacitance between the electrodes. Measuring the voltage between the electrodes when a certain
amount of charges is present there will give the capacitance. To accumulate a certain amount of charges between the electrodes, you can just supply a certain
amount of current for a certain time. If the current has aknown fixed value, you may either supply the current fora certain time to measure the voltage of the charged electrodes or measure the time you need to complete thecharging. Anyway, the rate of change in capacitance isvery small and is similar to the rate of change of the measurement indicator. When trying to detect any minutechange, the measurement performance directly depends
on how you can suppress unavoidable noise to ensure an
appropriate signal-to-noise (S/N) ratio.
To resolve this challenge, a device should be preparedthat can convert minute changes in capacitance into muchlarger changes in another physical quantity. One of themeans to implement this is to make use of “resonance”.
Resonance refers to a phenomenon in which a systemwith a natural frequency (a resonance frequency) is excited at a frequency close to its natural frequency to vibrate with a large amplitude even with weak excitation.
In an electric circuit, resonance may occur with a combination of capacitance and “inductance”, which constitutethe two major parameters of electromagnetism. Inductance is normally implemented by a coil. A coil is a spiralconductor wrapped around any core. Since capacitance isrepresented by the letter C and inductance by the letter L,
resonance with capacitance and inductance is generally
called "LC resonance".
When resonance occurs, the phase relationship between the signal exciting the resonance and the vibration
caused by the excitation substantially changes around theresonance frequency. The phase is a quantity indicating
the timing at which the vibration swings in whichever direction. Therefore, when phase differences are plottedwith the horizontal-axis showing frequency and the vertical-axis showing the phase difference between the exciting signal and the vibration caused by the signal, thecurves (representing the phase characteristics) show asteep slope around the resonance frequency. On the other
hand, the resonance frequency changes as the capacitancechanges. With the frequency of the exciting signal kept at
a fixed value close to the resonance frequency, any minute change in resonance frequency can be expanded andFig. 1	Principle that a capacitance change is expanded to achange in phase difference and how it is observed―4―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

captured as a phase difference because of the steep slopeof the curves (Fig. 1).
To enable sensitive detection of changes in capacitanceusing this method, it is desirable that the phase characteristics curve has a slope as steep as possible at the resonance frequency. When inductance is usually implemented by a coil, however, the coil does not necessarily havecomponents only for inductance, but also those for winding resistance or capacitance between the windings,
which can reduce the sharpness of the resonance. Another challenge is that the magnetic field generated by a current flowing through the coil is always expanded to thesurroundings because of its inherent nature, leading to an
unavoidable problem of interference with the surroundings.
To resolve these problems, we use an electronic circuit
to implement the characteristics equivalent to those of
the inductance usually implemented by the coil.7) This
does not mean using special electronic devices but only a
combination of generally available devices. This circuit
is called a General Impedance Converter (GIC) and canvirtually convert capacitance into inductance. In the sensor we are developing, we can cause LC resonance totake place between the capacitance of the sensor electrodes and the equivalent inductance with GIC, thereby
enabling sensitive detection of very minute changes inpermittivity caused by changes in oil property. The GIC
thus features the excellent benefit that the whole device
can be set up only with general materials at low costwithout using special components.
4.

Consideration of Oil Degradation
Then, why does the permittivity of oil change (increase) when the oil degrades? One major factor of oil
degradation or change in material properties is the oxidation of oil molecules. In other words, the question is why
the permittivity of oil changes when the oil molecules areoxidized.
An oil basically consists of a number of combinationsof carbon (C) atoms and hydrogen (H) atoms. Unlike water molecules, oil molecules are not permanent dipoles
themselves and do not have polarity. This is one of thereasons why water and oil cannot be mixed.
When oil molecules are bonded with oxygen atoms
due to oxidation, however, the parts of the oil moleculesthat are bonded with oxygen atoms will be charged negative. This is because oxygen is located around the top
right corner of the periodic table, which means that its atoms have relatively high electronegativity. As a result,the oil molecules will be polarized. With this acting as anadditional factor of orientation polarization, the oil molecules will increase in permittivity as a whole.
There are literally many kinds of oil. I find it somewhat strange that countless types of oil are basicallymade from only two elements: C and H. Incidentally, acomputer program is similar to oil in that it also consistsof numerous combinations of two types of elements: zero(0) and one (1). Moreover, it is well known that the DNA
information of living organisms consists of a sequence offour kinds of bases: adenine (A), guanine (G), thymine(T), and cytosine (C). In fact, these bases can only generate two types of pairs: A-T and G-C. So, the DNA information also consists of only these two patterns of basesequence. In short, all things existing in the world consistof a few or limited number of types of elements. Theircharacteristics or differences are implemented by numerous combinations of these elements.
In a computer program, 0 and 1 when alone only givethe information that they are present there. Then, combining 0s and 1s in a series can represent a meaning as anumber or a command. The relationship between the
combination and the meaning is not fixed or certain. In
language for instance, Japanese is expressed by a combination of 50 notes and English by combinations from a
26-letter alphabet. Even the sound of an identical combination of "a" and "i" may indicate "love" in Japanese or"I" in English.
As human genome analysis has progressed and genediagnosis technology has advanced, it has become possible to learn which specific diseases you are likely to suffer from in future by examining your DNA. This meansthat you are now able to understand the meaning of abase sequence of A-T and G-C just by reading it. But I
wonder what links the base sequence with its meaning tobegin with.
The mechanism by which oil permittivity increases
with oxidation is as described above. However, whatgave oxygen atoms the property of being likely to be
negatively charged in the first place? Of course, this isbecause oxygen is located around the top right corner ofthe periodic table, but why do elements located in the top
right corner of the periodic table have higher electronegativity? This can be explained through calculation of theelectron orbit of atoms based on quantum mechanics as
you know, but why are electrons negatively charged to
begin with? When you pursue the answer to these questions in this way, you may finally reach a point where nobody can explain what it is all about.
A discipline that pursues the source of matter is particle physics. According to theory, an atom can be divided
into quarks, leptons and other elemental particles thathave different characteristics. However, nobody can explain why those elemental particles have such characteristics. Different combinations of these elemental particles
can constitute various types of atoms or matter, but nobody can explain why a specific combination of the elemental particles forms a specific material or generates theunique property of the material. A familiar example may
be metallic elements. The metal with the atomic number
26 is iron and that with the atomic number 29 copper.
Iron and copper have obviously different properties. How
can you explain the difference in property between the―5―Thoughts on the Degradation of Oil

two metals with different atomic numbers? How could
you describe the reason why the element with the atomic
number 26 has the property of "iron", not that of "copper"?
I teach my students computer programming. I insistently tell them to always put comments on programs
they are writing. The term comment here means words tobe added to the relevant parts of a program to explain
what is processed in the parts. Comments are made withwords describing, for example, what a specific variable
here expresses or the meaning of a specific calculation
written there. By putting comments on your program,you can re-organize ideas in your mind, being moreaware of errors. During writing, you may certainly feelOK with your program while you are thinking in various
ways for the program. With no comments, however, you
may often forget what made you write this part of the
program in this way after a while. In some cases, you
might even forget the fact that you wrote the program
yourself.
In a computer program in which each line comes withadequate comments, you can ideally read the comments
like a series of text describing what the program is processing. In other words, making a program is comparable
to writing a paper, as I always tell my students. A program written with alphanumeric characters and mathematical expressions is practically the same as language.
Processes of programs can be expressed in words. Machine-level instructions of computer programs consist of
combinations of 0s and 1s. Various patterns of a series of
0s and 1s are connected to meaning indicated by theircorresponding words.
A specific sequence of 0s and 1s could be reproducedby randomly putting 0s and 1s together. However, such asequence is made by chance and does not have any specific meaning. For computers, programmers intentionallycreate a pattern of 0s and 1s to represent the meaning of
the program. By using the means of different combinations of elements, programmers can express their intention.
As mentioned above, is it known that base sequencesof DNA have their own meaning and the combination including 26 protons, and 26 electrons indicates an element
having the properties of a metal called "iron". These are
the facts in the real world. Any combinations made bychance should not have any meaning. If such a combination has a meaning, this is contradictory to the assumption that the combination was made by chance. Given
that the words "by chance" or "randomly" denote that athing takes place with no reason or no cause-and-effectrelation, evolutionism is an incoherent theory in thissense.
Anything with meaning should involve an entity who
has given the meaning as in computer programs that always involve their programmer. The entity who has given
the meaning must be a being with intelligence as in the

programmer who exercised their wits to create the program. The "meaning" of things is usually expressed by"words". Let me here collectively call "meaning" that can
not necessarily be expressed by voice or text (so-calledlanguage) "words". Without these "words", all matter inthis world is just random assemblies of atoms and molecules.
The Bible says, "In the beginning was the Word". The
beginning of the Bible also includes the phrase: "In the
beginning God created the heavens and the earth". In Japan where Bible-based philosophy has seldom been proliferated in the local culture, the term "God" (Kami inJapanese) may remind people of somewhat "cheap"
words such as Kamiwaza (literally meaning acts of God)or Kamitaiou (super-excellent response). God in the Bible in turn refers to the Creator. The famous phrase "In
the beginning was the Word" is followed by "and theWord was with God, and the Word was God". Namely,
what created heaven and earth (the Creator) is the Word
itself. The Bible declares that the meaning of everythingcan be sourced to the Word, that is, God.
Even if the base sequence of DNA accidentally represents the DNA pattern of human beings, no living humanbeing could have been created without the “Word” of"life". I heard that 23 types of amino acids were found inasteroid samples brought back by the Japanese spaceprobe Hayabusa. Amino acids are just a small part of thecomponents of the human body. Without activation of aprogram (i.e., words) to select and combine the necessary
parts (levorotatory amino acids), no human body can becreated. Even if a human body could be created by thismethod, it would just be a physical object called a humanbody without "life" breathed in.
People, particularly Japanese who have grown up witheducation heavily centered in Evolutionism, usually haveno idea about the Creator. This is noted as "original sin"by the Bible. However, the Bible says, "God saw everything that he had made, and behold, it was very good".
What was very good when God created heaven and earthchanged, which means that everything tended to getworse. When oil changes in property due to oxidation,
the phrase of the Bible is elicited as the "degradation" ofoil.
The Bible also says, God created man in “his own image". In other words, man was created to concretely express how wonderful the wisdom of God is and how glorious the nature of God is. This can explain the decisivedifferences between human beings and other animals thatcan obviously be recognized in the real world. Some species of plant have beautiful flowers. They may come into
flower for the purpose of attracting insects for easier pollination. But, if that is the only purpose, do they have tobe decorated with those petals that all differ in color, pattern and shape? We feel a sense of beauty when we see
flowers. This is because we are what God created in his
own image. Is there any other reason?

―6―

KAYABA TECHNICAL REVIEW No. 66 APR. 2023

There is one thing that I have long doubted. Music, especially Western music, may be played in a major scale
or in a minor scale. Music played in a major scale generally sounds bright and cheerful while that played in a minor key sounds depressing or sorrowful. The only difference in main chords between the major and minor scales
is the third note, i.e., half-tone higher or not. I wonder
why these notes sound cheerful or sorrowful just byslightly changing the note pattern. We, as human beings,
have been connected to a program (words) that can makeus have such specific feelings in response to particularpatterns of notes. I cannot understand this in any otherway. We can be moved by or feel beauty from a piece ofmusic because we were created by God in his own image. Is there any other reason?
We, who used to be "very good" in the beginning, became unaware of the Creator because of our own "sin".
However, the Creator had known very well from the beginning that we would become so. We do not have thecapability of making amends for our own "sin". The Bible says, "the wages of sin is death". We were separated
from the Creator because of “sin”. As a result, our body"deteriorates" with time and eventually dies. We cannot
do anything about this fate ourselves. Then, the Creator
prepared an astonishing plan to resolve our fate. That is,behold, he planned to come to the earth as a human being, and to die as a scapegoat for us. This was implemented by Jesus Christ about two thousand years ago.
Furthermore, he died by Crucifixion on a cross, which
was probably one of the most barbaric ways of dying.
Still, the death was beyond his death as he was the Creator. He still exists with the phrase, "I am who I am".
Apostle John, who directly saw Jesus Christ and lived
together with him for a while, wrote in the gospel-book,"For God so loved the world that he gave his
one and only Son, that whoever believes in him
shall not perish but have eternal life".
Of course, the only Son here means Jesus Christ himself.
John also wrote in the letter: "Whoever does notlove does not know God, because God is love.
This is how God showed his love among us:
He sent his one and only Son into the world that
we might live through him.
This is love: not that we loved God, but that heloved us and sent his Son as an atoning sacrifice for our sins".
In other words, man was created by God "in his own image" to concretely express "God is love" as a visible form
to all.
If you believe in Evolutionism assuming that God is
nowhere, the oil should change in property with time asyou use it, and amino acids should be generated at somepoint in time, leading in the end to the birth of life. You
may believe that oil "evolves", not "deteriorates". All
materials necessary to make up amino acids are avail-able: C and H contained in oil and O and N available in
the air. Then, assuming that life was created by chancefrom these materials, does that life-form have “love” onearth?

References
1) KATAYAMA Hiroshi: "Oxidation of lubricating oil", Journal of
Oleo Science Vol. 5 (1956), pp. 261-270.
2) FURUMOTO Keizi: "The Oxidation Properties of Non-Additive Lubricating Oils", Journal of the Marine Engineering Society in Japan, Vol.19 (1984)，pp. 590-596.
3) HONDA Tomomi: "Deterioration Diagnosis and Inspection
Technology for the Lubricating Oil", Journal of the Japan Society for Precision Engineering, Vol.75 (2009), pp. 359-362.
4) C.T. DERVOS, et al.: "A Complex Permittivity Based Sensor
for the Electrical Characterization of High-Voltage Transformer
Oils", Sensors Vol. 5 (2005)，pp. 302-316.
5) A.T. PEREZ and M. HANDFIELD: "Low-Cost Oil Quality
Sensor Based on Changes in Complex Permittivity", Sensors
Vol. 11 (2011), pp. 10675-10690.
6) L. SU, et al.: "Analytical Method to Estimate the Complex Permittivity of Oil Samples", Sensors Vol. 18 (2018) ，pp. 984995.
7) M . DEGUCHI: "A simple method for detecting very smallchanges in capacitance or inductance", Microelectronics Journal―7―

101(2020), 104802.

Technology for Detecting the Orientation of Oil Seal

Technology
Introduction

Technology for Detecting the Orientation of Oil Seal
TURUMI Takuya

1Introduction

Recent production sites are required to automate theirinspection process due to higher product quality requirements and reduced work force. In KYB, the Production
Technology R&D Center and Production Engineering
Department are jointly promoting the development of inspection technologies to automate the inspection process.
Among those is the development of an automatic inspection technology to replace human inspectors allocated tothe manufacturing process of oil seals (hereinafter"seals") that are one of the components of shock absorbers (hereinafter "SA"). The technology has been introduced in mass production. This paper describes the overview.

2of human inspectors to prevent worsening of the cycle
time.
Table1

Target4

Evaluation error [%]Over-inspection [%]Inspection time [sec.]

0.000

Not more than 0.3

Not more than 2.1

Outline of Target Part

Photo 1 shows an enlarged view of the SA and seal assembly, the seal to be inspected, and the front and reverse
sides of the metal.

Purpose of Development

SA

The purpose of the technical development is to automate the inspection process for inspector labor saving. A
technology for detecting the orientation of the insertmetal(hereinafter the "metal"), which is one of the seal components, has been developed.
Human inspectors are allocated to the process ofchecking finished seals. The inspection technology wehave developed is introduced into the process that may
be the source of reversed metals, not the process ofchecking finished seals, with the aim of reducing the loss
caused by non-conformities.

3

Target parameters of development

Enlarged view of
seal section

Target Parameters of Development

The target parameters for inspection capability andtime were set as shown in Table 1. Evaluation error
means recognizing a non-conforming item as a conforming one by mistake. In case of an evaluation error, nonconforming items will be released to the subsequent process, which may lead to claims in the market. Contrary toevaluation error, over-inspection refers to recognizing a
conforming item as a non-conforming one. Over-inspection prevents work from being released to the subsequent
process, resulting in a halt in the production. This eventually leads to lower productivity. The target inspection
time was set based on the current visual inspection time

Seal

Identification
grooveFront side of metal
Reverse side of metal
Photo 1 SA, seal, and metal

The seal is a part for preventing oil leakage throughthe sliding part of the piston rod of SA. The metal, which
is one of the seal components, is molded integrally withrubber material to form the seal. The metal has front andreverse sides that can be differentiated from each other.
Molding the metal into the seal with its wrong side up
will result in a higher risk of oil leakage. To prevent this,the metal has an identification groove on one side. In this―8―

KAYABA TECHNICAL REVIEW No. 66 APR. 2023

document, the side of the metal with the identification
groove is called the front side.

5

 verview of Process with Inspection
O
Technology Introduced

set-up modes can be switched over with a push-button
switch.
This loop-running inspection is automatically started
when the operator's hand leaves the imaging area.

The inspection technology was introduced into theprocess in which human operators manually set metals
and rubber pieces on the jig Note 1) before molding. Photo
2 shows the work bench and jig in the target process. The
work bench had to be replaced by a device for automatedinspection.

Metal

Inspection PC

Equipment

Image processing andinspection software

Push-button switch

Communication
software

Interlocking

Digital I/O board

PLC

Fig. 1 Configuration of inspection system
RubberpiecesFig. 2 shows the flow chart of operation of the inspection software that was introduced in mass production:
Note 2) Acronym for Programmable Logic Controller.

Work bench

Start

Jig

Capture camera
information

Photo 2 Work bench and jig

Inspection

The operator puts the jig on the work bench and sets
metals with the side with the identification groove facing
up in the circular pockets one by one. Then, the operator
places rubber pieces on each metal and sets the jig in themolding machine.

Wait signal
No signal

Note 1) The jig is used to set metals and rubber pieces in themolding machine.

6

Image
processing

Start inspection
Wait trigger

Details of development

6. 1 Inspection Method
The inspection used an image processing system thatcan not only capture images from a position where thesystem cannot obstruct the operator but also examines all
metals on the jig at a time. It was decided to determine
whether the metals are front or reverse facing throughimage processing, superficially by detecting the presenceof the identification groove, which is the most distinctive
feature among the differences between the front and reverse sides.
6. 2 Inspection System
Fig. 1 shows an example of the configuration of the inspection system. Internally built communication software
was used to transmit signals from the image processing
and inspection software to the digital I/O board within
the inspection PC. The digital I/O board and PLC Note 2)
were interlocked so that metals could not be released tothe subsequent process unless they passed the inspection.
The image processing and inspection software has inspection, calibration, and set-up modes as described later.
The software was designed so that the calibration and

Signalreceived
Metal orientation
check
NG(Not OK)

Calibration
signal received

Calibration
operationStorecalibration data

Set-upSet-upoperation
Read machinemodel information

Send calibration

Send set-up

completed signal

completed signal

Judgement
OK

Store data
Send OKsignalFig. 2 Flow chart of software operation

In mass production, the push-button switch can beused to switch the operation mode from inspection to
calibration or set-up. Inspection mode is run in loop anddoes not need to be started up with the switch. The system is configured to trigger the inspection when the operator's hand leaves the imaging area, and the molding machine has work in position. The image processing―9―Technology for Detecting the Orientation of Oil Seal

CameraCameraLighting

Lighting

Lighting

Jig

Jig
Photo 3 Actual inspection machine

Fig. 3 General layout of
optical system

Photo 4 shows images captured by the system on theactual inspection machine. Conditions for the inspection
were set under the constraint that the layout of the lighting and camera system was limited by the equipmentlayout of the production line.
The inspection machine is likely to be affected by disturbance light because the machine cannot be covered
with blackout curtain as this may lead to workability deterioration and the ingress of contaminants during molding. Then, an inspection algorithm has been developedthat is unlikely to be affected by these factors.

6. 4 Inspection Algorithm
6. 4. 1 Flow of Image Processing and Inspection
Fig. 4 shows the general flow of the processes fromimage capturing to inspection.

Judge
Inspection result
outputDetection

Pretreatment

Detect identification
grooveInspection image
cut-out

Inspection

Pretreatment

Detect metal OD
Inspection image
capturing

technology is used to locate the operator's hand and determine whether work is set in the machine or not.
This paper focuses on introducing the metal check(front/reverse side) in the flow chart.
6. 3 Optical Equipment
Photo 3 shows the actual inspection machine. Fig. 3
shows the general layout of the optical system. This optical system consisted of a camera and two lighting units.
The camera was installed directly above the jig at aheight where the camera could not interfere with the operators. The resolution of the camera and its lens wereselected to enable the detection and imaging of the identification groove of the metals set in the jig. The lighting
units were located in such a manner that allowed irradiation of the whole area of the jig from the right and left
sides.

Fig. 4 General inspection flow

After an inspection image is captured, the outside diameter of the metals is detected to determine the positionand number of metals. Then, only the area around thecircular identification groove of each metal is cut out toallow detection of the groove. The number of grooves iscompared with the number of metals to make a judgement. When these numbers match, "OK" is displayed.
When they do not match, "NG" (Not OK) is displayed
along with the location of the NG metal(s). For NG, theoperator flips the reversed metal(s), automatically turning
NG into OK.
6. 4. 2 Pretreatment
In practice it is difficult to directly detect the identification groove on the captured image. So, the image must
be processed to highlight the features to be detected. In
this project, a band-pass filter was introduced. The bandpass filter passes frequencies within a certain range andis used to extract the outside diameter and identification
groove. As shown in Photo 4, the contour of the metalson the jig and their identification groove appears darker
than the surroundings. The contour (outside diameter)
and identification groove of metals can be extracted using the band-pass filter.
There is a difference in gray value Note 3) between thecontour of the metals on the jig and their identification
groove and the surroundings. This difference is considered unlikely to greatly diminish even if the metals areaffected by disturbance light. So, the use of the band-passfilter allows the detection of elements of the outside diameter and identification groove of metals without being
substantially affected by disturbance light.
The band-pass filter was applied with commands that
had been prepared in the image processing software.
Note 3) The level of brightness. The white-to-black level is given by a number between 0 and 255.

Entire image

Enlarged view of image

Photo 4 Images

Photo 5 shows an example of an image captured before treatment and another subjected to processing withthe filter and automatic binary processing that allocatesblack or white to individual pixels according to theirbrightness. In the image after treatment, the areas inwhite indicate the parts that were extracted by the pro-― 10 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

cessing. Hereinafter the band-pass filter processing andthe automatic binary processing are collectively called
the pretreatment.

Before treatment

After pretreatment

eter. From the image, a rectangular section is cut out in
dimensions larger than the diameter of the circular identification groove indicated in each drawing. Then, theimages shown in right of Photo 7 are obtained as many
as metals are captured in Photo 4. Each of the cut-out images is subjected to pretreatment and then the Houghtransform in terms of the diameter of the circular identification groove. This will detect the identification grooves.
Photo 8 shows an image after the pretreatment and another image after the Hough transform in which the center of the circle has been detected and dilated. The number of identification grooves can be determined bycounting these center points.

Photo 5 Images before and after image processing

6. 4. 3 Detection Method
Feature extraction from images subjected to pretreatment was done with the Hough transform technique. The
Hough transform is a feature extraction technique used inimage processing and can be used to detect lines and circles in the image. Circle detection finds any circles within the target image that match the diameter informationthat has been given in advance. If an applicable circle isfound, the coordinate of the center of the circle is detected. In this project, the outside diameter of the metal andthe diameter of the identification groove indicated in thedrawing are used as the diameter information to be given
to the system.
6. 4. 4 Detection of the Outside Diameter ofMetalsThe outside diameter of the metals is detected in thecaptured images that have been subjected to pretreatment
and the Hough transform in terms of the outside diameter. Photo 6 shows an image after the band-pass filter
processing and another image after the Hough transformin terms of the outside diameter. The dots in red appearing in the image subjected to the Hough transform are thedilated center points of the metals. The automatic inspection system determines the number of metals by counting
the number of these red dots.

After pretreatment

Before cut-out

Photo 7 Cut-out inspection images

After pretreatment

6. 4. 5 Detection of Identification Grooves
Photo 7 shows inspection images of the identification
groove. This inspection uses the center of the circle detected by the Hough transform of the metal outside diam-

After Hough transform

Photo 8 Detected identification groove

6. 4. 6 Evaluation
After detection of the identification grooves has been
completed, the inspection results should be evaluated.
Evaluation criteria have been established so that the jig
passes the inspection (OK) when the number of metaloutside diameters detected matches the number of identification grooves while the jig fails the inspection (NG)when it does not. For mass production machines, the jig
is locked and cannot be taken out of the work bench as
long as the result is NG. The jig cannot be released fromthe work bench until the result is turned to be OK.

After Hough transform

Photo 6 Metal outside diameter detection process

After cut-out

7

Results of Development

The results of the evaluation of the inspection capability are shown in Table 2. 62,000 parts currently in production were used in the evaluation of the inspection capability during the period between January 8 andFebruary 1, 2022.

― 11 ―

Technology for Detecting the Orientation of Oil Seal

the Hough transform.
 he inspection capability was proven for massT
production with an evaluation error rate of 0%
and an over-inspection rate of 0.005%.
(5) he inspection time was maximum 2.0 seconds,
which is equivalent to the visual inspection time
for human operators.
(6) The technology was introduced in mass production and inspector labor saving was achieved.

Table 2 Results of evaluation
Evaluation error [%]Over-inspection [%]Inspection time [sec.]

Target0.000

Not more than 0.3

Not more than 2.1

Result

0.000

0.005

2.0

Evaluation

○

○

○

The targets for all the items were achieved.
The automatic inspection system was introduced in
April 2022. Inspection labor saving, which was established as the purpose of this development project, wasachieved.

8

In Closing

This project successfully developed technology for detecting the orientation of oil seal metals. The following
summarizes the project:(1) The inspection was made during the process forsetting metals in the jig.
(2) The presence/absence of the identification groove
was identified by image processing for inspection.
(3) The inspection algorithm included edge detection
with the band-pass filter and circle detection with

(4)

The inspection technology described in this paper canbe applied not only to the detection of the identification
groove of the metals but also to other inspection processes with circle detection such as for assembly error of circular parts.
Finally, I would like to take this opportunity to sincerely thank all those concerned who extended cooperation to this development project.

Author 
TURUMI Takuya
Joined the company in 2015.
R&D Sect. No.2, Production Technology R&D Center, Engineering
Div.
Took present post after working in
Production Engineering Sect., Steering Business Dept., Automotive
Components Operations, Gifu North
Plant.

Engaged in development of appearance inspection technology.

― 12 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

Technology
Introduction

Incorporation of Processing of Base Plates for Piston Motors
into FMS Lines
HANAEDA Ken

1 Introduction

2 Purpose

As excavators in the Chinese construction equipment
market have become larger, there has been a demand forboosting production of large excavators. Under this situation, KYB Corporation has received more orders forpiston motors (Fig. 1) manufactured in its Sagami Plant(Fig. 2). It was decided to establish a plant-wide production system in Sagami Plant, requiring enhanced production capacity for the base plate (the part in red shown in
Fig. 1). Another demand was to reduce the selling pricewhile needing to develop competitive products. To increase the profit margin, it is essential to carry out activity to reduce the cost of the base plate that accounts for a
substantial proportion of the product cost.

To achieve the target manufacturing cost of the cost
reduction activity and to establish a new production system for base plates.

3 Targets- Manufacturing cost
- Base plate production capacity

Down 22%
Up 66%

4 Requirements[1] To cut back capital investment by optimizing production lines.
[2] To implement preventive maintenance using sensing
technology and internal automatic evaluation of machining centers.
[3] To ensure the process capability for precision deephole drilling.

5 Overview of Lines

Fig. 1 Piston motor
Production system established(two-shift operation)

Production [units/month]

Shortage of capacity

Production
Capacity with overtime
Capacity without
overtime

Target capacity

FY19

FY20

FY21

FY22

FY23

FY24

Fig.2 Projected production of base plates and production
capacity

The base plate processing line consists of a machining
process with machining centers (hereinafter the "MC")and a finishing process including deburring, inspection,honing, surface grinding, and jet cleaning. Among these,
the MC machining process may use the serial (Fig. 3) orparallel (Fig. 4) processing line configuration dependingon the number of types of work. These lines have the following features:[1] Serial line
Fast processing line with less set-ups for limited types
of work.
[2] Parallel line
FMS-based Note1) line with less set-ups for a variety ofwork. The use of FMS allows the production of manydifferent parts and unattended operation. Fig. 5 shows the
FMS operation screen.
Note 1) Acronym for Flexible Manufacturing System.

― 13 ―

Incorporation of Processing of Base Plates for Piston Motors into FMS Lines

Fig. 3

Table 1Comparison of proposed approaches

Item

Mark

Mark

Proposal [2] Parallel line

Characteristics―

Fast line with less set-ups―

FMS-based line with lessset-ups for a variety of work

Machine model―MSF-340 *One model―MAG-14 to MSF-340 *11
models×

Positioning is required in eachprocess. Some processes cannot
be divided to ensure theprecision requirements.

○

Single-chuck machining. Not so
affected by the positioning
accuracy.

Quality Quality

Overview of serial processing line for base plates

Cost

Additional
equipment×3 units○

2 units

Extra personnel―+1 person/shift―+1 person/shift

Division of processing timecauses time loss○

Manufacturing cost

×

Processing time

×

Productivity Set-up

Initial and final
pieces check
Piecework

OthersOverview of parallel processing line for base plates

Fig. 5

FMS operation screen

6 Implementation
6. 1 Optimization of Production Lines
6. 1. 1 Overview of Improvement
To establish a base plate production system, an approach was introduced that added two more MCs to theexisting parallel line to achieve the target cost and thetarget production capability. Before deciding on the approach, two proposed approaches were compared witheach other: one was to add equipment to the existing serial line and the other to add equipment to the existing
parallel line, because building a brand new line requiredhuge capital investment.
6. 1. 2 Results of Comparison of Proposed Approaches
Table 1 shows the results of the comparison. The serial
and parallel line approaches had their own advantages
and disadvantages and both approaches could satisfy thetarget production capability. In this project, the parallel
line approach was selected because it was judged to beable to satisfy the target cost with a minimum number of
equipment units with no time loss for dividing the processing time.

○
No division of processing time,
no time loss
Minimum tool changes○

A single product requires no
extra set-up

×Extra small set-ups in finishingprocess○

Only parts machined in therelevant process to be measured

×All machined parts to bemeasured in each equipment unit―

Less vulnerable to process
trouble―Relatively easy to increase
capacity with additional
equipment―

Simple physical and information
flows

―

Easy to implement unattended
operation due to long processingtime○

Advantages

Total evaluation

Fig. 4

Proposal [1] Serial line

×

×

○

 utomation of Jig Inclination Measurement and6. 2 A
Automatic Internal Evaluation
6. 2. 1 Current Problems
The base plate is subject to a stringent tolerance for thesquareness between the reference plane and the bearing
bore. To maintain the accuracy, it is essential to always
achieve the squareness of work to the MC spindle (Fig.
6). Conventionally, operators have tried to ensure the accuracy by manually measuring the accuracy of the MC
spindle and jig. However, such manual measurement involves destabilizing factors including misadjustment,
mismeasurement and forgetting to measure.
6. 2. 2 Automatic Measurement Using Touch Sensor
Higher capital investment leads to higher cost. Then,
we built a software program to automatically measuredisplacement and evaluate equipment accuracy by using
the touch sensor installed in the MC process. The following describes the measurement flow and Fig. 7 shows theflow chart of the measurement program.
[1] If the last accuracy measurement was in the previous
month or earlier, proceed to the measurement sequence (monthly measurement)[2] Using the touch sensor, measure the reference planeof the jig that is clamping work (Fig. 8).

Fig. 6― 14 ―

Positional relation between work and MC spindle

KAYABA TECHNICAL REVIEW No. 66 APR. 2023

[3] If the measurement result is within the specification
limits, proceed to the machining sequence. If the result is out of the limits, issue an alarm to urge operators to take remedies.

Fig. 7

 nsuring Process Capability by Improving the
6. 3 E
Honing Stone
6. 3. 1 Current Problems
The spool bore, which is an important part of the baseplate, is roughly machined in the MC process and thenfinished by the honing machine. In the initial quality
check, however, the process failed to meet the spool bore
cylindricity requirements. A comparison of cylindricity
before and after honing revealed that the cylindricity actually worsened after honing (Figs. 10 and 11).

Flow of measurement program

Fig. 10

Fig. 11

Fig. 8

Measuring point of touch sensor

6. 2. 3 Verification of Proposed Approaches
We compared the measurements of actual work withthe jig specifications because we could not directly measure actual work. We determined that the measurements
satisfied the work specifications when they met the jig
specifications (Fig. 9).

Fig. 9Before honing

After honing (before improvement)

6. 3. 2 Causes of Lower Honing Accuracy
A cause investigation identified two possible causes oflower honing cylindricity:[1] Bore profile specific to the base plate
Fig. 12 shows the cylindrical section of the spool bore.
Problems occurred in the parts c and d in Fig. 12. In therelevant parts, the circumference of the circle is partiallygrooved. The presence of the machined grooves affects
the processing area, resulting in substantial variations in
cutting load.

Fig. 12

Relation of measurements between jig and actual work

Section view of spool bore

[2] Hardness of the bond of honing stones
Adjustment work must be carried out every time thehoning stone is replaced. So, a relatively hard bond has― 15 ―

Incorporation of Processing of Base Plates for Piston Motors into FMS Lines

been conventionally used to extend the stone change cycle. While the service life of the stone has certainly been
longer, the self-sharpening effect has been reduced, worsening the honing performance.
6. 3. 3 Improvement of Working Accuracy by Changing the Stone Bond
As mentioned above, there has been a conventionaltendency that relatively hard bond is used to extend thestone life. To address the problem that dull stones areused to hone the parts with substantially variable cutting
load, it was decided to use a softer bond. The use of softer stone bond improved the self-sharpening to ensure that
new abrasives are always exposed. This has improved thehoning performance, achieving stable processing not depending on the work profile.
6. 3. 4 Verification of the Proposed Approaches
A verification of the accuracy after improvement hasdetermined that the cylindricity has been substantially
improved (Fig. 13). Furthermore, a quality check after
continuous processing (N = 20) has determined that thecylindricity, which had been around the upper limit of thespecifications, was substantially improved, satisfying theprocess capability requirements (Fig. 14). Despite theconcern with the softer bond, the stone adjustment time
per replacement has been shorter. The total tool change
time has remained the same because the frequency ofstone replacement has increased.

7 Results
Table 2 shows the results of the improvement.
Table 2

Results of improvement

Item

TargetResultManufacturing cost

Down 22%

Down 19%

Evaluation
×

Production volume

Up 66%Up 64%△

Possible causes of failing to achieve the targets are:[1] Higher manufacturing cost due to lower availability
A major cause of lower availability was that work
waiting for finishing had to be temporarily placed at
the point where several types of work join after the
FMS area. To improve the situation, we plan to install
shelves for work waiting for finishing. This improvement is expected to help achieve the target.
[2] Deviation from the initial production plan
The reason for failing to achieve the target production
volume was that the initial production plan for the target month for evaluation was not achieved. Still, thetarget production capacity was achieved.

8 Conclusions
Fig. 13

We have successfully implemented stable preventive
maintenance using a new measurement method, thereby
establishing a product satisfying the process capability
which was conventionally difficult to achieve. From now
on, we will carry out activities that can develop preventive maintenance into predictive maintenance based on
accumulated data and will also continuously improve theavailability whose target has not yet been achieved.

After honing (after improvement)

9 In Closing

Fig. 14

Finally, I would like to take this opportunity to express
my appreciation to the related functions that extended
cooperation in building the production line as well as
those who extended guidance and support to us.

Cylindricity before and after improvement

Author 
HANAEDA Ken
Joined the company in 2008.
Production Engineering Dept., Sagami Plant, Hydraulic Components
Operations
Mainly engaged in machining process engineering for PPM products.

― 16 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

Technology
Explanation

Use of AI Technology in Development of SA Elements
OHUCHIDA Shun, MIYAUCHI Yuuki, SAGEHASHI Ryota

Abstract
Although there has been a third AI（artificial intelligence）boom in recent years, few organizations in theworld have been able to gain competitive advantage
through the use of AI.
In addition, KYB is focusing on the development ofsliding parts for shock absorbers（SA）to achieve bothride comfort and maneuverability at a high level. In orderto carry out this development efficiently, we have been
providing data-driven support for the development of SA
fluid.
This paper introduces the SA Element Development x
AI initiative led by Digital Transformation Improvement
Dept for these reasons.
When utilizing digital technologies such as AI, it isimportant to carry out data quality control and provide
user-friendly applications. Therefore, we have constructed a platform to safely manage and operate the driving

1

Introduction

We have been experiencing the third AI boom in recent years. Companies and research institutes throughout
the world have addressed social implementation Note 1) of
AI technology to resolve challenges in all fields.
Of the companies who have introduced AI, not lessthan 60% are still at the stage of Proof of Concept (PoC).
An investigation1) has revealed that only 12% of organizations in the world have been able to gain competitive
advantage through the use of AI.
Major reasons why they have not been able to actively
promote the use of AI are:[1] they have no proper knowledge and technology ofAI, and[2] they have not constructed a platform for AI operation.
Item [1] implies that they cannot step ahead out of thetest data collected during the evaluation of developed SA
products in auto vehicles, and developed an application
to easily search and analyze the data managed by theplatform.
With this platform at our disposal, we can now focus
on driving tests and data analysis, freeing us from the laborious data management tasks that used to be necessary.
We are already using this platform in some auto vehicle evaluations. Data useful for future SA development isbeing accumulated in the platform, and we feel that we
can realize a sustainable data-driven system to improve
development capability.
This paper describes AI-based frequency analysis technology that is the result of joint research with universities, along with the technology and philosophy behind
the AI services that utilize such frequency analysis technology for further development, and data analysis platform thus constructed.

PoC as they are not able to determine whether their challenges should be resolved by AI or not. In KYB, that is
why Digital Transformation Improvement Dept is addressing an AI human capital development activity Note 2)
for employees to learn not only AI technology but also
how to set challenges (for more information, refer to“Initiatives to Develop Digital Human Capital” includedin this issue of KAYABA Technical Review).
Item [2] above leads to cases where they cannot proceed to the operation phase because the development ofAI technology has advanced without establishing a system to collect and manage the necessary data for AI
learning. In addition, there may be another case of failingto utilize AI. AI technology can originally prove its worth
when combined with other digital technology, which finally resolves issues. However, optimal solutions or services may not be proposed for lack of knowhow on othernecessary technologies.

― 17 ―

Use of AI Technology in Development of SA Elements

This paper explains the SA Element Development x AI
Initiative, rather than describing the human capital development.
Recently, KYB has been focusing on the developmentof sliding parts for SAs to achieve both ride comfort andmaneuverability at a high level 2),3),4). Digital Transformation Improvement Dept has provided data-driven support
to the development of hydraulic fluids since its foundation in 2019. Specifically, the Department has analyzed
the driving test data collected for fluid evaluation using avariety of analysis approaches to compare the developed
fluid with conventional ones for verification. Based on
the results of the data analyses, the Department has supported the creation of ideas about evaluation techniques
and product development.
The analysis approaches that the Department has adopted for trial include frequency analysis using deeplearning, which is one of the latest AI technologies. Several analysis approaches including this AI-based analysis
method have turned out to be useful for the future development of SA elements. To establish a sustainable datadriven system to improve the development capability, we
have developed a “platform”, “application software”, and“AI services”, which will be described in the following
chapters.
Note 1) To apply and develop results of research to resolve social issues.
Note 2) K
 YB prefers to use the term "human capital " instead of"human resources".

2

dardization of vehicle measurement and that automateddata processing and permanent data management on theplatform have been implemented by effectively using
Amazon Web Services (hereinafter "AWS"). We havealso developed a test condition recording application
with which anyone can record test conditions in the sameformat using the same wording. Details of the application
will be explained in the following chapters.
2. 2 Data Analysis Application
Data can deliver its value only after it is analyzed andutilized for decision making. The following describes therequirements for the “automatic analysis reporting application” that has been developed to be generally used forany kind of driving test.
The application shall:[1] allow for retrieval of data to be analyzed,[2] allow data analysts to automatically create graphsthat may be frequently referred to,[3] be able to promote the use of AI and Business Intelligence (BI) and to support idea creation,[4] be able to be intuitively operated, and,[5] be stably operated.
The easy-to-operate application we have developed
can provide several functions including “data retrieval”,“analysis reporting”, and “support to idea creation”. Withconsideration given to the micro serviceNote 3), the application was redesigned not to affect other functions during
modification of some functions. This application uses
AWS to ensure stable operation. The following chaptersprovide details of the application.
Note 3) An engineering method that divides a single application
into small services to enhance the development efficiency and minimize the affected range.

Requirements

In this development activity, we have constructed aplatform for implementing centralized management ofdriving test data including data retrieval and analysis.
The construction of the data analysis platform focusing on “data quality control” and the development of user-friendly data analysis applications were applied withthe following requirements.
2. 1 Data Analysis Platform
The requirements to ensure data quality control are:[1] Collected driving test data shall be standardized
and able to be saved in the platform.
[2] Records of test conditions and other descriptions
on the data in item [1] above shall be standardized
and able to be saved in the platform.
[3] Driving test data shall be linked to the test conditions and able to be managed on the platform.
[4] Data pretreatment including the linkage above shallbe able to be automated.
[5] No tampering or loss of data under management of
the platform shall occur.
The driving test data has been standardized in such amanner that sensor measurements are saved in the sameformat irrespective of who carried out the measurement
by using a dedicated logger that was developed for stan-

3 Overview of Data Analysis Platform
3. 1 System Configuration
Fig. 1 shows an overview of the system we developed.
The. system constructed on the AWS cloud is designed to
implement data collection, saving, visualization, andanalysis.
3. 2 Data Collection
For proper analysis of the driving test results, it is necessary to appropriately link and manage measurements ofthe driving test data to the spreadsheet meta data recording the test conditions. Thus, this system has a data collection line for the driving test data and another line forthe meta data.
The driving test data is measured using a dedicatedlogger developed with KYB's smart road monitoring system5). Unprocessed driving data measured with this dedicated logger is uploaded to AWS by an Edge PC. Withconsideration given to the expandability of the dedicatedlogger, Amazon S3 Note 4) has been selected as the data upload destination because S3 can save data in various formats including image and audio data sets that are not― 18 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

currently collected.
The meta data can easily be recorded by test personnel
just by connecting to a dedicated website from their own
tablet or other similar data terminal and then inputting
the necessary information there. Information items to becollected as meta data have been standardized throughpreliminary discussion among those concerned. The dedicated website, particularly the information input screen,
has been designed to be user-friendly based on opinions
collected through interviews with those who are working
on the site. With the aim of reducing the burden of website operation and management as well as the operation
cost, the static website hosting function Note 5) of Amazon
S3 was introduced. The website is only allowed to be accessed by authorized users who have passed a user authentication through the in-house network, ensuring security as well.
Note 4) A data storage service that can save and protect datawith no limit on data type and capacity.
Note 5) A static website can be constructed by uploading web
contents to Amazon S3.

3. 3 Data Processing
Data measurement by the dedicated logger is automatically started at the time when the logger switch is turned
on. This means that even driving data of a vehicle running out of the testing section is measured too. Then, aprogram to only extract driving data of a vehicle runningfrom the testing section was built as a workflow of AWS
Step Functions. Note 6)
With input of the meta data and unprocessed driving
data, this workflow refers to the meta data and extracts
the driving data collected in the testing section. The extracted data is processed into an easy-to-handle format
and then saved in Amazon S3. The meta data can be
stored in a relational database (hereinafter the "RDB")
linked to the date and time of measurement of the driving
test data. This data management allows users to retrieve
the driving test data they want to analyze whenever necessary (Fig. 2).
The use of the cloud service has not only enabled thefast processing of the workflow but has also improved
fault tolerance and has established a backup environment
at low cost. The cloud service can also be used to relatively easily build and operate a workflow in which cost
only arises for using the necessary resources. For conventional data processing, the meta data has been prepared in a spreadsheet software application, from which
the driving test data has been manually extracted in several days. It has needed a number of man-hours to complete the data processing for organizing the driving test
data just for one day. From now on, the established workflow will automatically carry out a series of data process-Fig. 1 Overview of data analysis platform― 19 ―

Use of AI Technology in Development of SA Elements

ing tasks just with manual data entry of test conditions by
test personnel, substantially reducing the man-hours fordata processing.

3. 4. 2 Ad Hoc Analysis Using BI Tools
While the analysis reports certainly characterize thedriving test data, an ad hoc analysis environment using
BI tools is available to enable even deeper analyses.
KYB provides a data analysis environment using Tableau
not only for this development activity but also across thecompany.
We have also developed and provided a function
whereby anyone can easily retrieve any given driving test
data by connecting the RDB managing the meta data toTableau (Fig. 3). With this search function, analyzers can
now efficiently conduct statistical analysis of driving test
data sets collected under similar test conditions or comparison and verification of similar driving test data setsthat are only different in specific conditions. Anotherfunction available is the downloading of search results.
This may be useful for sharing the search results or data
pretreatment for “advanced analysis using AI”, which
will be described later.

Fig. 2 Overview of workflow
Note 6) A service with which users can create a series of workflows by allocating two or more AWS services.

3. 4 Data Analysis
The data analysis platform provides the following
analysis approaches applicable to the managed driving
test data, so that analyzers can proceed with the analysis
step by step:[1] Simplified analysis using standard reports[2] Ad hoc analysis Note 7) using BI tools[3] Advanced analysis using AI
Note 7) One-off data analysis that is conducted as necessary
with no analysis items or details predetermined.

3. 4. 1 S
 implified Analysis Using Standard Reports
Once the driving test data is managed on the platform,
data analyzers can first view the analysis report automatically output by an internally built web-based application.
This web-based application was developed by consulting
KYB's analysis techniques. Just by selecting any given
driving test data, anyone can easily create a standard report on the test results with the analysis knowhow accumulated in the past. Details of the functions provided bythis web-based application will be explained in Chapter
5.
With the web-based application, the creation of standard reports, which was difficult without dedicated tools
or well-informed people, has now been standardized. In
addition, the safe data management by the platform releases analyzers from management work on data anddedicated tools and allows them to concentrate on analysis, research, and development tasks.

Fig. 3 Driving test data search screen

3. 4. 3 Advanced Analysis Using AI
An environment to implement machine learning Note 8)
is available to support more advanced analysis approaches for the driving test data. Digital Transformation Improvement Dept is promoting an activity to develop AI
human capital capable of effectively utilizing Amazon
SageMaker. Note 9) In liaison with the promotion work, theDepartment has also advanced the development of thissystem.
Currently, the Department provides SageMaker Notebook Note 10) as a data analysis environment in the test
phase. In the development phase with the aim of proceeding to the product phase including machine learning
implementation, the Department recommends carryingout development from local PCs using a dedicated Software Development Kit (SDK) for AWS. Not only bysimply providing an environment for machine learning
implementation but also by distributing sample codes already organized and actively disclosing the know-how
for Amazon SageMaker use accumulated in the company,
the Department supports the promotion of AI utilization.
The environment provided by the Department allows human capital who have already utilized Amazon SageMaker to quickly obtain any given driving test data man-― 20 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

aged by the platform and conduct advanced analysis byleveraging various analysis technologies including AI.
Finally, the AI that was developed in this activity has
been incorporated into an AI service, which is now available. The AI service includes a function with which anyone with no knowledge about AI can freely obtain analysis results given by AI so long as data is available.
Details of the AI that was developed as well as the AI
service will be described in Chapter 6 onward.
Note 8) A technology with which a computer can learn rules
and patterns from a variety of data including numericvalues and text to determine the current condition andprospect the future.
Note 9) A service that provides an environment to quickly develop, learn, and distribute machine learning models.
Note 10) A service that can interactively implement a series oftasks including data visualization and machine learning model building.

4E ffort for Establishing an Appropriate
Development and Operation System

4. 1 D evelopment Taking Expandability Into AccountWe carry out system development using Infrastructure
as Code (hereinafter "IaC") taking subsequent expandability and maintainability into account. IaC provides away of managing the configuration of infrastructure using
source codes. It uses source codes to define server environments and application settings. When building a system, IaC can be used to reduce the man-hours, increase
efficiency in reutilization, and reduce human errors inmanual operation. This system uses Serverless Framework for AWS Step Functions and other applications (including the workflow described above) and HashiCorp
Terraform for network- or security-related infrastructure.
4. 2 Scheme for Team Development
Besides IaC, we use another scheme for team development in various applications. That is the source code version management tool GitLab with which we can promote daily development jobs safely and quickly. Source
codes created by development personnel are reviewed bywell-informed people before being merged into the production environment. Once a service is formally released
under a CI/CD Note 11) environment, the latest versionof source codes is tagged, which is one of the GitLabfunctions. The use of this rule ensures that, should a service release fail in future, the service can be swiftly
rolled back to the last version that has proven to provide
normal operation (Fig. 4).
Note 11) Refers to a system that automates the build, test, anddevelopment processes. CI and CD are acronyms forContinuous Integration and Continuous Delivery respectively.

Fig. 4 System development using tagging

4. 3 Multi-account Cloud Operation
As the number of systems running in the company increases in future, it will be necessary to establish an appropriate operation rule for AWS accounts. KYB is promoting a multi-account operation that uses the single
sign-on method to switch over multiple AWS accounts
depending on the type and environment of the system(Fig. 5). Developers and maintainer are only allowed toaccess specific operations according to their own set of
authorizations invested to individual service accounts.

Fig. 5 Overview of multi-account operation

Distribution of authorizations for services and functions to different accounts can help control cloud security
and eliminate the need of setting maximum usage of eachaccount. This can be expected to reduce the burden of
AWS administrators and users. This operation rule is also
applied to the construction of this system.

 evelopment of Automatic Analysis Re5 D
porting Application

As amounts of data increase, data visualization requires
more time and more man-hours. Then, we have developed a web-based data analysis application that canquickly visualize the results of the analysis of driving test
data and then automatically output a report (hereinafterthe "web-based analysis application") without the laborious tasks that used to be necessary.

― 21 ―

Use of AI Technology in Development of SA Elements

the characteristics of the data obtained from more than
one sensor, substantially reducing the time needed tocomplete the process from data collection to visualization.

Fig. 6 Screens of the web-based analysis application

Using the web-based analysis application, you can easily access the driving test data uploaded in the cloud (Fig.
6). Just by selecting a set of driving test data you want toanalyze, the web-based analysis application automatically visualizes the data set, eliminating the need for complicated setting or operation. You may also extract data
you want to analyze in detail (for example, a data set collected for a certain period immediately after the start of atest) as necessary, and then view the data in different
scales. The driving test data may also be filtered by test
conditions, which also serve as a description of the data
to be analyzed, on the Tableau screen shown in Fig. 3,
Chapter 3. Data retrieved in this way will also be automatically visualized on the application. We assume thatthe web-based analysis application will be used in theseways.
There are three modes in the web-based analysis application as described later. You can select the desired mode
depending on the application.
5. 1 General Analysis Mode
General analysis mode is available for the typical visualization formats, which data analyzers frequently use to
create drawings. Through hearing from those concerned
who were involved in data analysis, data visualization
formats that were popular among them were selected.
Specifically, these formats include line graphs, scatter diagrams, and histograms. In addition to these views, theapplication is designed to be able to output sensor measurement statistics, correlation maps, and other relational
data just with a simple mouse operation on the webbased application.
Fig. 7 shows an example of the visualization of thedriving test data collected for the evaluation of SA fluids
using actual auto vehicles. The use of the web-based
analysis application made it possible to quickly identify

Fig. 7 Case example of using the web-based analysis
application (general analysis mode): (a) Histogram of Sensor
A, (b) Scatter diagram with X-axis for Sensor A and Y-axis
for Sensor B, (c) Scatter diagram with X-axis for Sensor A
and Y-axis for Sensor C

5. 2 Frequency Analysis Mode
Frequency analysis mode allows users to view spectrograms of power spectra and time-frequency analysis. Detailed parameters for creating frequency analysis graphs
can be individually set. Basically, the web-based analysis
application automatically sets parameters in response to
the data input, allowing users to easily visualize the data
without paying attention to detailed settings.
5. 3 AI Analysis Mode
AI analysis mode is where all users can easily carryout frequency analysis with AI. Detailed information
about the AI-based approach we developed will be described in the next chapter.
5. 4 Downloading of Driving Test Data
A function that allows users to separately download
the driving test data selected on the web-based analysis
application as CSV files is also available. A signed URL
with an expiration date is issued to target users so thatthey can download the data just through a simple mouse
operation.
This function can meet the needs of users who want tovisualize data in their own way, using familiar analysis
tools.

― 22 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

6

Note 12) The spectrograms were generated with Fourier trans-

Use of AI and Setting-up of Challenges

form to visualize vibration. Part of the information is

Deep learning is one of the latest AI technologies anda general-purpose method to be utilized to resolve any
challenge. On the other hand, in comparison with conventional proven technologies, deep learning delivers justequivalent or possibly inferior performance depending on
the challenge. Therefore, it is important to discuss thefollowing questions before starting to develop an AIbased technology:[1] Is the use of AI is the best way of resolving thechallenge?
[2] Can the challenge be adjusted so that the use of AI
is the best solution?
You can easily answer question [1] if you have proper
knowledge about AI. You may hardly be able to answer
question [2] unless you have general knowledge and experience in interpreting challenges in addition to knowledge about AI. The following describes specific examplesof setting up challenges:
6. 1 Background and Challenges
KYB has promoted the development of SA sliding
parts to achieve both ride comfort and maneuverability ata high level. It was known that sensory factors including
ride comfort would be substantially affected by a changeof SA fluids only. However, the relationship between thefluid and the vehicle behavior had not been fully clarified.
At first, we had the existing product and a new productthat was identical to the existing one except for an improved fluid. These products were tested on actual auto
vehicles for evaluation and frequency analysis (Fig. 8). A
comparison of the results of fluid analysis between theexisting and new products only identified a minor difference between the two. Was this minor difference attributable to the fluids or to any environmental factors such as
road noise? Or might it be caused by differences in driving manner? Note 13) There arose the problem that the causeof the minor difference was difficult to determine.

Fig. 8 Results of analysis of SA sprung frequency for
different fluids Note 12)

confidential and has been intentionally deleted or
blurred.
Note 13) Even under the same test conditions, the operation of
the accelerator and/or steering wheel of auto vehicles
may slightly vary.

6. 2 Setting up Challenges for AI
KYB has addressed the development of advanced
anomaly detection technologies6),7) utilizing deep learning, which is one of the latest AI technologies, including“appearance inspection through image processing” and“poor weld detection”. By effectively using insights fromthis experience, we decided to treat the acceleration information, among the driving test data items related to
the SA fluid, as follows:[1] Acceleration of existing product: Reference data[2] Acceleration of new product: Comparative data
The AI-based anomaly detection technologies wereapplied to develop a technology to only learn the acceleration information (reference data) of the existing productand detect what is new in the new product. Note 14)
In short, the challenge of "detecting what is new in the
new product" was interpreted as "comparing the resultsof frequency analysis between the existing and new products and only detecting the differences attributable to thefluids". The latter was further replaced by the challengeof "anomaly detection for which the use of AI is effective". These considerations were made in the initial stageof the development phase before the full-scale development was launched.
Note 14) An AI-based technology that compares acceleration
between the existing and new products and identifies
frequency bands with substantial differences.

G eneral AI-based and Proposed Ap7 
proaches for Anomaly Detection

The newly developed approach is an application of AIbased encoder and decoder. The approach is generally
used to input image or other data that is dense with information to an encoder where the information is compressed and then further input the compressed information to a decoder where given data can be reconfigured.
This approach has the following two major advantages:[1] Difficult-to-handle high dimensional data can beconverted into low dimensional data, which can beused as a feature value for machine learning.
[2] The data compression/reconfiguration process is
expected to deliver a noise removal effect. (In otherwords, only distinctive data can be reconfigured).
If the encoder and decoder learn to reconfigure input
data Note 15), determining the difference between the reconfigured data (output data) and the input data can locate
noise. This noise corresponds to flaws or stains that arefound in appearance inspections. Thus, this approach isoften used at sites requiring anomaly detection (Fig. 9).

― 23 ―

Use of AI Technology in Development of SA Elements

Fig. 9 AI-based approach for fault detection ofhand-written text
Note 15) An approach for an encoder and a decoder to learn toensure that the input data is identical to the output datais called an autoencoder.

7. 1 Proposed Approach
In the proposed approach, the encoder learns to receive
input of spectrograms of the unsprung acceleration of theexisting product and the decoder learns to output (or reconfigure) spectrograms of the sprung acceleration (Fig.
10).

Fig. 10 Overview of proposed approach

Learning huge amounts of data from the existing product alone can generate a dedicated model for the existingproduct. The model here means a computing unit that
outputs the sprung spectrogram of the existing productafter being input with its unsprung spectrogram.
If part of the existing product data that was not used

for learning is input to this model, the sprung acceleration with noise removed can be output. Identifying thedifference between this output data and the actual measurement data allows visualization of the noise (Fig.
11(a)). This visualized noise is expected to be able to beinterpreted as "test errors including road noise".
If data from the new product is input to this model inturn, only the frequency bands that correspond to thoseof the existing product data can be output. Identifying thedifferences between this output data and the actual measurement data allows observation of the frequency bands
that failed to be reconfigured well as noise (Fig. 11(b)).
This visualized noise is expected to be able to be interpreted as "differences in frequency bands attributable tothe fluids".
When visually checking the spectrograms for reconfiguration errors, however, users may discover minor variations in color by unavoidably relying on their subjective
determination. Then, we have proposed another plotting
method that averages spectrograms out in the direction of
the axis for frequency and visualizes shifts in frequency
bands using a line graph (Fig. 12). We believe that thisplotting method allows users to determine the differences
between fluids regardless of users' expertise.
Another advantage of this proposed approach is that
only a relatively small amount of data from the new
product is needed while large amounts of learned data (theexisting product data in this case) need to be available.
This means that, as long as large amounts of driving test
data to be benchmarked are collected in the initial stageof the development phase, AI-based frequency analysis
can be made even with small amounts of data from the(a) Learned model with existing product data as input(b) Learned model with new product data as input
Fig. 11 Overview of proposed approach― 24 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

Fig. 12 AI-based visualization of differences in sprung frequency bands between existing and new products

new product. Note that the model generated in this proposed approach is a black box. The grounds on which thedata was reconfigured is unknown. It must be remembered that analysis results should be used for reference
purpose only.

8 AI Support for Development of SA Elements
Digital Transformation Improvement Dept uses Python
for development of AI-based technologies including the proposed approach described in Chapter 7. Therefore, expertise on AI and Python as well as a dedicatedoperating environment are needed for effective use of the
proposed approach. We thought that, in fact, many people
faced a hurdle to obtain expertise and prepare the operating environment. We then developed an application embedded with AI (the proposed approach) to establish anenvironment where anyone can try the AI-based frequency analysis.
Note 16)

Note 16) One of the general-purpose programming languages.
Python is the de facto standard language for AI development.

8. 1 C ase Example of Utilizing Internally Built
AI Services
The AI service we developed is available as one of thefunctions of the “automatic analysis reporting application” described in Chapter 5. One thing that is different
from the other functions is that the AI service also supports data that is not managed by the platform Note 17) Any
users can temporarily upload their own data via the webbased application to analyze the data using the AI service.
This AI service has the following objectives:[1] To allow users to use the AI service only with thetest data available even if they are unable to easily
carry out a driving test, lowering the hurdle for AI
technology.
[2] To implement AI-based analysis of virtual driving
test data generated by simulation, based on the as-

sumption that a high-precision physical SA model
including fluid will be created in future.
[3] To allow expanded usage of the AI service to takeplace by not limiting users or data types.
Finally, Fig. 13 shows an example of using the AI service for any given driving test data. The accuracy of detecting what is new in the new product is expected to risethrough comparison of analysis results between the conventional and proposed approaches.

Fig. 13 Comparison of results of frequency analysis between
conventional and proposed approaches
Note 17) Must be in a specified data format.

8. 2 Technologies Supporting the AI Service
The development of this AI service has used Container, which is a virtualization technology. Container technology specifically refers to the method of collectively
managing and operating AI applications and its operating
environment in a single package. A Container containing
applications and operating environment can be started upeither locally or in the cloud, minimizing environmentdependent problems. Note 18)
AWS provides many different Container-related services. Users can freely select these services according totheir needs.
We do not actually use the AI service (the proposed
approach) so often in our daily development activity. So,
we selected the AWS Lambda service for which we only
pay for what we use. Although it takes several minutes to― 25 ―

Use of AI Technology in Development of SA Elementscomplete the start-up process with AWS Lambda, containers can be started and used at minimum cost, implementing the operation and management of an environment where anyone can use AI services safely wheneverneeded (around No.9 in Fig. 1).
Note 18) In some cases, modification is needed depending on
the container start-up environment.

9

Outlook

Under this development project, the construction of adata analysis platform for improved capability for SA development has been completed. In fact, it is difficult todetermine whether the platform has contributed to improved development capability or not at this moment because the platform has little track record of operation yet.
Still, the platform did provide users with the following
value:[1] Users have been released from data managementwork.
[2] An environment where users can focus on driving
tests and data analysis has become available.
The platform has been constructed to be able to manage and operate a variety of driving test data. If a driving
test that cannot be assumed at this moment is carried out
in future, however, the platform may fail to cope with theanalysis. So, we would like to develop a maintenancesystem ensuring that the platform can be operated over along time and can handle even unexpected problems.
The “AI service” described in this paper was developed by applying the results of the joint research of Gifu
University and Digital Transformation Improvement
Dept of KYB. The service is available in a user-friendly
manner even to users who are not AI experts. From now
on, we would like to introduce AI-based technologies
and algorithms developed not only by Digital Transformation Improvement Dept but also by other functions
into the service. To achieve this as well, we plan to establish a scheme to respond to inquiries on how to use theplatform or the development environment from AI human capital or advanced IT human capital in various
functions.

10 Concluding Remarks
This development project has constructed a system toeffectively use driving test data. We understand that some
employees may have inhibitions on the Work Style Reform using digital technology. Still, we will promote digital transformation (DX) by adequately explaining thefull value of accepting DX.
The know-how accumulated in this development project can be also applied to building platforms for types ofdata other than driving test data. Any functions facing
difficulties with data utilization can collaborate with us
for resolving their challenges.
Finally, I would like to take this opportunity to sincerely thank all those concerned in the related functions
who extended great support and cooperation to this development project.

References
1) Accenture: Survey Report, https://www.accenture.com/us-en/
insights/artificial-intelligence/aimaturity-and-transformation(Survey period: August through September 2021).
2) MURATA: "Development of Sliding Parts for Shock Absorber(Introduction of ProsmoothTM)", KYB Technical Review
No.58 (April 2019) .
3) SANO: "Development for Analytical Technology of Shock Absorber Valve Characteristics", KYB Technical Review No.58(April 2019) .
4) KATO, SASAKI: "Study of Evaluation Index Characterizing
Dynamic Friction Characteristics in Shock Absorber", KYB
Technical Review No.59 (October 2019) .
5) SHUTO, TAKAMATSU: "Development of a Smart Road Monitoring System", KYB Technical Review No.61 (October 2020) .
6) NAITO: "AI x IoT Initiatives in the Production Technology Domain at KYB", KYB Technical Review No.60 (April 2020) .
7) FURUKAWA, ISASHI: "Development of an Equipment Predictive Maintenance System", KYB Technical Review No.63 (Oc-

― 26 ―

tober 2021) .

KAYABA TECHNICAL REVIEW No. 66 APR. 2023

Authors 

OHUCHIDA ShunMIYAUCHI Yuuki

Joined the company in 2013.
Digital Transformation Improvement
Dept, Engineering Div.
Engaged in development of AI systems

Joined the company in 2017.
Digital Transformation Improvement
Dept, Engineering Div.
E ngaged in construction of data
analysis platforms.

SAGEHASHI Ryota
Joined the company in 2019.
Digital Transformation Improvement
Dept, Engineering Div.
E ngaged in development of backends related to data analysis.

― 27 ―

Development of Anti-cavitation Vane for Travel Motor of 7-ton Hydraulic Excavator

Product
Introduction

Development of Anti-cavitation Vane for Travel Motor of
7-ton Hydraulic Excavator
SUZUKI Jun

1Introduction

The existing hydraulic travel motor for 7-ton hydraulicexcavators is equipped with an add-on shockless relief
valve as standard. The shockless relief valve (hereinafterthe "relief valve") has the same structure as that of thehydraulic travel motor for mid-size excavators. Thismeans that the relief valve consists of many parts and isexpensive.
Then, we have developed another valve for 7-ton hydraulic excavators that can replace the existing relief
valve. This paper introduces this new, simple anti-cavitation valve (hereinafter the "anti-cavitation valve").

2

cles. It has thus been difficult to use the anti-cavitation
valve in this motor. Still, in response to the recent market
demand for cost reduction, we have developed a simple
anti-cavitation valve for the travel motor for 7-ton hydraulic excavators that can replace the relief valve. Fig. 1
shows the appearance of the product.

Overview of the Product2. 1 Background
MAG Series hydraulic travel motors are available in a
product lineup of 11 models for 1-ton to 35-ton hydraulicexcavators (Table 1). While motors for mini excavatorsof 6-ton or smaller are equipped with an anti-cavitation
valve as standard, those for 7-ton or larger excavators areequipped with a relief valve as standard. We tried tomount the anti-cavitation valve that is used in the smallerclass motors on the hydraulic travel motor MAG-50VP1100F for 7-ton class excavators but it could not preventthe occurrence of cavitation because a large inertia force
is applied to the motor during the braking of large vehi-

Table 1MAG Series product lineup

Fig. 1 Appearance of the product(MAG-50VP-1100F with anti-cavitation valve)

2. 2 Functions and Features of Relief Valve
The existing relief valve plays the role of relieving thepressure surge during the vehicle's braking, suppressing
the cavitation, and adjusting the braking feeling. Whenthe brake is applied, the counterbalance valve mounted
on the travel motor closes its opening on the outlet side
earlier. The relief valve is then operated to generate abraking torque and absorb the inertia force during braking. It also adjusts the shockless operation pressure andtime to obtain the desirable pressure rise characteristics
during braking, achieving the braking feeling demanded
by customers.
[During traveling]
Fig. 2 shows the hydraulic circuit diagram of the relief
valve during traveling. When the pressure oil flows into
the Pin port, the counterbalance valve is in the travel position. The oil is guided into the hydraulic circuit, starting
the motor.

― 28 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

Fig. 4

Fig. 2

Hydraulic circuit diagram of relief valve(during traveling)[During braking]Fig. 3 shows the hydraulic circuit diagram of the relief
valve during braking. While the supply of the oil to thePin port is interrupted, the motor is kept running due tothe inertia force of the vehicle. This raises the braking
pressure to generate a braking torque, absorbing the inertia force. When the braking pressure is equal to or higher
than the relief valve settings, the pressure escapes to theother side as indicated by the arrow (green), suppressing
cavitation. The shockless relief valve shows a two-stepincrease in braking pressure as shown in Fig. 4. The pressure waveform shown in Fig. 4 represents measurements
obtained with a flywheel testing machine.

Fig. 3

Braking pressure characteristics of motor with reliefvalve

2. 3 F unctions and Features of Anti-cavitation
Valve
Unlike the relief valve, the anti-cavitation valve does
not have a surge relief function supposed to work during
braking. That is why it is necessary to tune the opening
characteristics of the counterbalance valve to generate abraking torque, absorb the inertia force during braking,and keep the braking pressure within the allowable limits. Cavitation is suppressed by bypassing the high-pressure fluid to the low-pressure side using the anti-cavitation and counterbalance valves.
Figs. 5 and 6 show the hydraulic circuit diagram of theanti-cavitation valve during traveling and braking respectively. Adjusting the opening characteristics of the counterbalance valve enables various pressure rise characteristics to be obtained during braking, achieving thebraking feeling demanded by customers. Table 2 shows acomparison in functions between the relief and anti-cavitation valves.

Hydraulic circuit diagram of relief valve(during braking)Fig. 5 H ydraulic circuit diagram of anti-cavitation
valve (during travelling)― 29 ―

Development of Anti-cavitation Vane for Travel Motor of 7-ton Hydraulic Excavator

Fig. 83

Fig. 6

Hydraulic circuit diagram of anti-cavitation valve(during braking)Table 2Comparison of functions between relief andanti-cavitation valvesFig. 7

Section view of relief valve

Technical Challenges in Introducing Anti-cavitation Valves

The challenges in introducing the anti-cavitation valve
to the motor for 7-ton excavators are to ensure that thevalve can keep the braking pressure from rising up to theupper limit, absorb the inertia force, and attain the braking feeling demanded by customers by tuning the opening characteristics of the counterbalance valve as well as
by suppressing cavitation during braking of the 7-ton vehicle.

4

2. 4 Comparison of Valve Structure
Figs. 7 and 8 show the structure of the relief and anticavitation valves respectively. While the relief valve consists of 33 parts and is expensive, the anti-cavitation
valve is simple and consists of only 10 parts.

Section view of anti-cavitation valveF eatures of Anti-cavitation Valve for
7-ton Hydraulic Excavators

As mentioned above, unlike the relief valve, the anticavitation valve can adjust its opening characteristics andclosing time to achieve various pressure rise characteristics during braking. With the anti-cavitation valve, it ispossible to achieve a moderate increase in braking pressure as shown in Fig. 9, thereby enabling the vehicle's
driver to feel good braking and keeping the pressure
surge within the allowable limits. Besides this, it has
been confirmed that other pressure rise characteristics asshown in Figs. 10 and 11 can be obtained. Note that this
newly developed valve offers motor performance and durability that are equivalent to those of the existing relief
valve since this new product is an alternative to the existing counterpart.

Fig. 9― 30 ―

Braking pressure characteristics of motor with
anti-cavitation valve [1]KAYABA TECHNICAL REVIEW No. 66 APR. 2023

5

To introduce the anti-cavitation valve to the travel motor, it is necessary to match the motor with the vehicle byadjusting the opening characteristics of the counterbalance valve. In reality, drivers may encounter various
types of excavator crawler (steel, rubber) and various
types of road surface (sheet steel, soil, concrete) depending on the vehicle class and model, so it is diﬃcult to exactly estimate the braking feeling only through verification with flywheel testing.
The test data obtained in this development project will
be applied to analysis modeling, reducing the time needed to match motors with vehicles. This will certainly improve the estimation technique. In the future, we would
like to determine, through simulation, the motor behavior
in operation modes that are difficult to reproduce in abench test, contributing to the clarification of failure phenomena occurring in commercially available excavators.

Fig. 10 Braking pressure characteristics of motor with
anti-cavitation valve [2]Fig. 11In Closing

Braking pressure characteristics of motor with
anti-cavitation valve [3]AuthorSUZUKI Jun
Joined the company in 2007. Pump
and Motor Design Sect., Sagami Hydraulic Engineering Dept., Engineering Headquarters, HC Operations
Engaged in design and developmentof hydraulic motor products.

― 31 ―

Development of Vane Pump for AT

Product
Introduction

Development of Vane Pump for AT
GOMI Hiroki

1

Table 1Introduction

The vane pump for AT Note 1) introduced in this paper is
to be used as a hydraulic source of the new AT mounted
on the new SUV Note 2) that has been developed by Mazda
Motor Corporation. Manufacturing of this product was
launched in December 2021.
Note 1) Automatic Transmission.
Note 2) Sport Utility Vehicle.

2

The AT unit (Photo 1) on which the newly developed
vane pump will be mounted is a step-type automatictransmission (hereinafter “the AT"). The AT uses a powertransmission system that is different from that used in
CVT Note 3) for which KYB has developed and produced
vane pumps so far. The pump used for the AT is required
to deliver a discharge pressure diﬀerent from that of thepump used for CVT. KYB is preparing its first vanepump product lineup for the AT. Table 1 compares the
speciﬁcations of these two types of transmission.
Note 3) Continuously Variable Transmission.

Type

AT

CVT

Speed change byGearsetBelt

Hydraulic pressure
requirement

Up to 2.1 MPa

Up to 6.0 MPa

3About AT Unit

Comparison of speciﬁcations of AT and CVT

Newly Developed Vane Pump

The newly developed vane pump is based on the existing product for CVT. Since the pump speciﬁcations for
the AT are different from those for CVT as describedabove, we reviewed all the speciﬁcations of the existingvane pump for CVT to set up optimal speciﬁcations for
the AT during the development stage.
The first point to be considered in the development
stage was that the vane pump for the AT is only required
to deliver a low discharge pressure. Then, we reduced thefriction of the existing product as far as possible while
maintaining the required durability, contributing to improved fuel eﬃciency of the vehicle.
We also improved NVH Note 4) which is essential for thepump start-up characteristics and the vehicle ride comfort, achieving an optimal design to satisfy the required
speciﬁcations.
Photo 2 and Table 2 show the appearance and detailed
speciﬁcations of the new vane pump respectively.

Photo 1 Appearance of transmission unit ** The use of the photo has been approved by Mazda
Motor Corporation. All rights reserved.

Photo 2 Appearance of new vane pump― 32 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

Table 2

Speciﬁcations of new vane pump

Type

Balanced vane pump

Basic discharge

15.9cm3/rev

Pump revolutions

Max. 7,420 rpm

Discharge pressure

Max. 2.1 MPa

Oil temperature range-40˚C to 165˚C

Production site

Japan

Note 4) Noise, Vibration, and Harshness.

4

Performance Improvements

4. 1 Improvement of Volume Efficiency
In the newly developed vane pump, the clearances ofthe sliding parts have been optimized, specifically reduced, to match the discharge pressure. The smallerclearances lead to less leakage or lower ﬂow loss in thepump, resulting in higher volume efficiency but lower
durability, such as seizure of the sliding parts, is unavoidable. Still, a deformation study through FEM analysis(Fig. 1) and a critical durability test helped us set an optimal clearance. As a result, the volume eﬃciency has been
improved while the required durability is maintained.
DeformationHigh

For item [1], lowering the working pressure of the
ﬂow control valve can reduce the loss torque due to pressure loss. This causes the ﬂow control valve to internallycirculate excess ﬂow, thereby enabling the pump to leverage the flow to improve the suction capability (Fig. 2).
However, the reduced working pressure naturally lowers
the hydraulic pressure in the internal circuit, resulting in
the disadvantage of lower resistance to cavitation. Cavitation is a phenomenon in which the air dissolved in thehydraulic fluid is released as air bubbles. Repeated release and dissipation of such air bubbles causes wear ordamage to the pump components.
To resolve the problem, the suction part of the camring was machined to have notches, expanding the suction oil path. This reduced the pressure loss to improve
the suction capability (Fig. 3).
For item [2], the cam ring bore, which decides the basic discharge, has been enlarged in some parts from thatof the existing product. With this design change, thewidth of the cam ring has been reduced by 24% (Fig. 4).
This reduced the area of vanes to which pressure is applied, resulting in a lower sliding torque.
For item [3], KYB introduced its thinnest vanes (29%thinner than the existing vanes) for the ﬁrst time to further reduce the area to which pressure is applied and thesliding area (Fig. 5).
These improvements reduced the loss torque by about
20% from the existing product that performs equivalentwork, successfully improving the mechanical eﬃciency.
Excess flow

Spool

Suction port

Discharge port

Increase in suction
pressure

Low
Suction port
Discharge

Fig. 1

SuctionExisting productNew productOrifice

Discharge
port

Example of FEM analysis

4. 2 Improvement of Mechanical Efficiency
The driving torque of a vane pump is the sum of thetheoretical torque and the loss torque (friction). To improve the mechanical eﬃciency, it is primarily necessary
to reduce the loss torque. Major components of the loss
torque include the torque consumed for pressure loss inoperating the flow control valve Note 5) and the sliding
torque for the vanes to maintain contact with the walls of
the cam ring. To reduce these two kinds of loss torque,the following improvements were made.

Working pressure of flow control
valve -> Pressure difference
between P1 and P2

Fig. 2

Oil circuit in vane pumpNote 5) When the pump has an integrated ﬂow control valve.

Existing product[1] Lowering the working pressure of the ﬂow control
valve[2] Using a thinner cam ring
[3] Using thinner vanes― 33 ―

New productFig. 3 Comparison of cam ring speciﬁcations

Development of Vane Pump for AT

ShoulderExisting productNew product24% thinner

Existing productFig. 6

Existing productNew productRotor geometry

New product

Oil seal

Illustration of thinning of cam ring

Fig. 4

View from the direction of the arrow
24% shorter

Direction to view

Existing product(With equivalent basic
discharge rate)

29% thinner
New productFig. 5Thinning of vanes

Fig. 7

4. 3 Improvement of Start-up Characteristics
As described above, reduction of the loss torque wasachieved by thinning the vanes to deliver a lower contactpressure against the walls. The trade-oﬀ was lower startup capability. As the transmission pump has recently
been required to deliver rapid start-up from the viewpointof improvement of automobile functionality, the start-up
characteristics needed to be improved.
Then, we changed the rotor design to eliminate the"shoulders", reducing the sliding resistance of the sticking-out vanes (Fig. 6). We also optimized the back pressure for pushing the vanes out and the clearance of thesliding parts of the vanes to improve the start-up capability at low temperatures, successfully achieving start-up
characteristics that were superior to those of the existingproduct. Furthermore, the pump cover has been fittedwith an oil seal to attain improved airtightness, preventing oil release from the pump during halts and reducing
the time needed to suck the fluid again during restart.
These measures contribute to further improved start-up
characteristics (Fig. 7).
4. 4 Improvement of NVH
As automobiles have recently become quieter year after year, the demand for quieter transmissions has been
rising. It is also a must for pumps to have improved NVH
characteristics.
In the newly developed vane pump, the port proﬁle inthe side plate was optimized to suit the environment
where the transmission unit is used (Fig. 8). The optimized port helped reduce the discharge pulsation, sup-Oil sealpressing vibration. The notches in the side plate, whichconnect the vane chamber with the port and help build apressure in the vane chamber, were tuned through simulation (Fig. 9). This improved the quietness of the pumpduring both normal and high-speed rotations.
While the existing product had these notches only inside plate A, the new product has the notches in both sideplates A and B. This design change increased the supplyof high-pressure ﬂuid to the vane chambers to alleviate
the delay in pressure rise during high-speed rotation or
during the use of ﬂuid with much entrained air, serving
as measures for cavitation (Fig. 10).

― 34 ―

Optimized port
& notch profile

Fig. 8

Ports and notches of side plate

KAYABA TECHNICAL REVIEW No. 66 APR. 2023

Pump internal pressure [MPa]The rate of change in pump internalpressure (pressure in the vanechamber) was estimated throughsimulation before tuning.

6

The vane pump for the AT was developed according to
specifications that KYB has never experienced in its
product development history. Mass production of thevane pump has been achieved through great cooperationof all those who were involved in the development project.
I would like to take this opportunity to deeply thank allpartners including those involved in the program from
Mazda Motor Corporation as well as all personnel in therelated functions of KYB.

Existing
product
Proposed
improvement 1
Proposed
improvement 2

Rotation angle [deg]Fig. 9

Example of simulation of pressure in vane chambers

Notch added

Existing productFig. 105In Closing

New productNotches added

Conclusions

We have developed KYB's ﬁrst vane pump for the AT
and achieved the following:[1] Development of a vane pump optimized for the AT[2] About 20% lower loss torque than existing product[3] Achievement of both durability and low driving
torque[4] Improved start-up characteristics[5] Lower noise
The improvements discussed in this development project are shown in the inclined development views of theexisting and new products (Fig. 11).

― 35 ―

Development of Vane Pump for AT

Existing
既存品
product

New
product
Oil seal added
Lower profile
Lower profile
Geometry changed

Optimized clearance

Optimized backpressure
Additional notch
Optimized ports
and notches□：Improved efficiency
start-up□：Improved
characteristics□：Improved NVH

Fig. 11Lower working pressure offlow control valve

Inclined development views of existing and new products― 36 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

Author 

GOMI Hiroki
Joined the company in 2012.Pump
Engineering Dept., Steering Business
Dept., Automotive Components Operations Engaged in design of vane
pumps.

― 37 ―

Initiatives to Develop Digital Human Capital

Explanation

Initiatives to Develop Digital Human Capital
MIYAUCHI Yuuki

1

ISASHI Ryosuke

Note 3) A technology to learn regularity and patterns of datafrom a variety of data including alphanumeric charactersso that computers can determine the current conditionand predict the future.
Note 4) A technology to automatically extract features to be focused on from data and use them for determination of thecurrent condition and future prediction.

Introduction

These days, all industries need to obtain or develop
digital human capitalNote 1). KYB has also systemized internal education and training to develop its own digital
human capital. This report introduces KYB's initiatives
to develop digital human capital.
Note 1) KYB prefers to use the term "human capital" instead of"human resources". This report uses "human capital" accordingly.

1. 1 The Outset of Development of Digital Human CapitalThe outset of the development of digital human capital
was a cross-company activity project in 2016 that applied
data miningNote 2) to analysis of casting failures in thegroup companies. The activities included learning statistics and promoting the use of data mining tools. The
project eventually helped employees understand the necessity of data analysis in the company. Then, anotheractivity was launched in 2018 to develop artificial intelligence (AI) human capital.1) The participants learned theknowledge and technologies necessary for more advanced analysis using machine learning Note 3) or deeplearningNote 4).
In this activity, KYB gathered participants who wereinterested in AI throughout the company and asked engineers who had AI knowledge and technology to give lectures. A regular meeting was held every month to provide
programming courses using e-learning and to carry out
original small tests for participants along with their explanation. Based on the results of their daily learning,participants used various approaches to try to resolve
challenges related to AI implementation given by Administration. The final part of the activity was group work to
resolve actual administration challenges left unsolved in
the company by means of AI. For a challenge related tovibration data of active suspensions for railroad applications, many participants built machine learning models
taking into account cost and even processing speed on
the assumption that the models would be introduced tothe actual system. Thus, the activity yielded marvelous
human capital development. The first term of the activity
in FY2018 was followed by the second term in FY2019.

TAKINO Shinsuke

1. 2 DX Promotion and KYB-IoT Platform
During these activities, the world has been focused on
digital transformation (DX). In Japan, the government
and industry insisted on the necessity of using data anddigital technology. KYB established the Digital Transformation Improvement Dept. in 2019 to accelerate the useof digital technology. Fig. 1 shows KYB's original datautilization stepsNote 5). The first step is digitization thatturns analog information into data. This is followed bydata collection and data saving in databases. The processthus advances toward digitization. It is further assumed
that the process evolves into digital transformation basedon the premise that all business communications andtransactions will be done digitally .

Fig. 1 Data utilization steps

To accelerate the data utilization, KYB constructed itself a KYB-IoT platform on the cloud. The platform supports Steps 3 and 4 of the data utilization process. At theoutset, KYB promoted "defensive DX" mainly in the
production domain.2) Now it has just begun with preparation for "offensive DX" in the product development domain and new business development.3)

Note 2) The process of analyzing large amounts of data using
statistics and other analysis techniques to obtain useful
insights such as hidden patterns of data.

― 38 ―

Note 5) In 2021, some functions had already promoted the useof clouds and AI, but the whole company was still in Step 2.

KAYABA TECHNICAL REVIEW No. 66 APR. 2023

1. 3 Implementation of Digital Human Capital
Development
Along with the construction of the KYB-IoT platform
where employees can flexibly use data with no constraints on time or location, the company is addressing
the development of human capital who can effectively
use the platform. These human capital should be familiar
with business intelligence (BI) toward data-democratization, which is indispensable for the data utilization steps,
and AI that enables more advanced analysis. Besides
these technologies, employees are required to understandthe significance of DX and foster proper IT literacy. They
are given an explanation as to possible business losses
that may arise without the use of data and digital technology and educated to raise their awareness of the necessityof preventing such losses.
In this way, we have established the digital humancapital development program from a broader perspective
covering not only AI but also BI, IT, and clouds. We arealso trying to systemize these activities into a cross-company project through collaboration with Engineering
Planning and the Human Capital Development Center.

2

DX Basics is a lecture course aimed at ensuring that theconcept and understanding of DX take root properly
throughout the company. Trainees learn why the company needs digital technology and why they need to beaware of digital transformation. They also take a lecture
on how to reform the organization to implement DX. Executive Training is conducted with support from Amazon
Web Services, Inc. (AWS)
2. 3 Systemization of Digital Human Capital
Development
Fig. 3 shows the relationship of scale and specialty
among the courses. Centering on the AI and BI humancapital development, the figure indicates DX Basics andother training courses to be provided to employees who
are temporarily sent to the Digital Transformation Improvement Dept. for "studying abroad". As the digital
human capital development is expanded, the map in Fig.
3 will be updated accordingly.

 verview of Digital Human Capital DeO
velopment

2. 1 Definition of Digital Human Capital
Before the start of the digital human capital development, the Digital Transformation Improvement Dept.
preliminarily discussed which digital human capital weshould try to develop with the related functions. As a result, the digital human capital KYB should develop were
defined as "human capital who have both the technicalskill to use digital technology and business transformation skill". This is because, to implement DX, KYB
needs human capital who not only have acquired technical skills by participating in internal and external training
courses but also have business transformation skills withwhich they can continue addressing challenges to achieve
their purpose.
2. 2 Roadmap of Digital Human Capital Development
Fig. 2 shows a roadmap of digital human capital development established in 2020. In addition to IT Education
for improving AI, BI and IT literacy, KYB has started
DX Education to teach the basics of all necessary subjects for DX implementation.

Fig. 3

To establish a scheme or system of digital human capital development, the Digital Transformation Improvement Dept. has worked with the Engineering Planning
Department and Human Capital Development Center
since 2022 to create a skill level chart as shown in Fig. 4.
Its creation is based on our idea that such a chart will
help employees figure out a specific skill level theyshould try to reach next and will appropriately support
their growth as individuals. Besides this chart focusing
on AI and BI, we plan to develop additional skill level
charts for other digital technologies.

Fig. 4
Fig. 2S cale and specialty of digital human capital development

Roadmap of digital human capital development― 39 ―

Digital human capital skill level chart(under discussion)

Initiatives to Develop Digital Human Capital

2. 4 Year-round Digital Human Capital Development Curriculum
Fig. 5 shows the current year-round education curriculum in 2022. The first course of the curriculum is DX
Basics that lectures the necessity of DX and an outline ofdigital technology. Trainees will broadly understand the
purpose of learning about these issues. The curriculum isdesigned to connect this DX Basics to AI and BI humancapital development and further to IT Education as ameans of implementing DX. We will describe AI humancapital development in Chapter 3 and BI human capitaldevelopment in Chapter 4.

Fig. 5

3

IT system with such a machine learning model is recognized as a function involving many issues to be considered. It is impossible for a single role, such as data scientists, to cover all domains. To resolve the issue, data
scientists, data engineers, and machine learning engineers
should technically cooperate with each other throughsmooth mutual communication toward a final common
goal, rather than independently promote their own development work. Then, an education curriculum with
MLOps taken into account was started for all trainees.
This allows them to imagine during their education what
will specifically take place after the introduction of AI/
ML and to build the knowledge and skills necessary forestablishing a sustainable machine learning system.
The lecture materials used in the AI Education Curriculum, except for programming courses, have been prepared by in-house engineers. With these internally prepared materials, the lectures can provide familiar topics
including in-house failure cases.
Note 7) A paradigm that aims to connect the development process of machine learning with the operation process of thesame to achieve continual improvement after the supply ofservices.

FY2022 digital human capital development
education program

AI Human Capital Development

3. 1 AI Human Capital Development Initiative
Currently, KYB has two pillars of AI human capitaldevelopment: AI Education Curriculum and AI Community. The AI Education Curriculum covers a wide rangeof education from basic courses designed to learn knowledge and skills to ensure that no employee is ignorant of
AI/MLNote 6) to practical courses to learn the knowledge
and skills necessary for appropriately operating the machine learning models that have been implemented.
These education courses will be described in detail in
section 3.2. AI Community provides places for employees to openly communicate with each other or to actively
use the knowledge and skills they have obtained througheducation courses for resolving challenges facing thecompany. This will be described in detail in section 3.3.
Note 6) AI services that only need data are differentiated fromML (machine learning) that can build machine learningmodels itself.

3. 2. 2 Track Record
The AI Education Curriculum in 2022 has four courses
including those launched in 2021:(1)AI Basics
AI Basics is an entry-level course of the AI Education
Curriculum and intended to make AI widely popularamong employees. This course has been provided to ensure that no employee is ignorant of AI/ML.
The course consists of lectures by chapter that begin
with data collection, followed by data preprocessing/visualization, feature extraction learning, hyperparameter
Note 8)tuning, and inference, according to the proper machine learning workflow. In the introduction of the lectures, the difference in definition between AI and machine learning is explained. In addition, the lectures
widely cover different specific approaches of machinelearning and the basic theory of deep learning. Materials
used in the lectures include not only simple explanationsof individual technologies but also actual cases in KYB,
for example, what employees doubted in the past AI hu-

3. 2 AI Education Curriculum
3. 2. 1 Background
The AI human capital development initiative launchedin 2018 has yielded certain results so far. To further expand the AI human capital and further increase the practical cases contributing to the company's business, KYB
decided to introduce MLOpsNote 7), which had gained recent attention, to the education system and provide opportunities for employees to learn the operation of machine learning models. This decision was made with thebackground that, although a constructed machine learning model increases in value only if it yields results to
end users as expected, the building and operation of an― 40 ―

Fig. 6

Education materials for AI Basics

KAYABA TECHNICAL REVIEW No. 66 APR. 2023

man capital development and what they were confused
about during implementation. Thus, these materials havebeen designed to be suitable for the current skill level ofthe company's employees. Some of the textbooks provided in the lectures are shown in Fig. 6.
Note 8 ) Parameters that are not automatically learned by machine learning algorithms. Hyperparameters are generally
decided based on the developers' experience and/or optimization methods used.

(2)Programming Basics
The Programming Basics course provides a place fortrainees to output the knowledge they obtained in the AI
Basic course. Trainees who finished the AI Basic course
can implement machine learning through programming.
Based on what they learned in AI Basics, they try to do
programming to build a machine learning model. This
course does not involve a dedicated lecturer teaching in aroom like hands-on training, although it does start at a
specified date and time. Instead, individual trainees access webinars that have been prepared in advance andlearn online. Instructors will only respond to trainees
who have a question. Trainees can look into what they
are not sure about at their own pace and receive support
from instructors whenever they like to resolve the problem right away. The use of this online learning is intended to improve the practical skill of trainees.
(3) AWS Basics
KYB widely uses AWSs as a base to implement machine learning, including the KYB-IoT platform. Trainees who have finished the education curriculum are thus
required to smoothly get ready for the development environment provided for AWSs. In addition to this background, the AWS Basics course is intended to explain thebasic knowledge and techniques about AWS to trainees
before they attend the following AI Practice and AI
Hackathon courses.
It is very important to learn the necessity of using thecloud environment to implement machine learning and
MLOps. If a machine learning system is built in an existing on-premises environment, some technical liabilities
would be generated in future. This course presents suchliabilities and explains the advantages of the cloud environment where data scientists and machine learning engineers can concentrate on essential tasks including development. Like the Programming Basics course, this course
has been designed to allow trainees to freely access webinars within a specified course period and to allow instructors to only respond to trainees who have a question.
Fig. 7 shows some of the materials provided in thecourse.
(4) AI Practice
AI Practice is a hands-on training course where trainees can build machine learning models in a cloud environment based on the knowledge obtained in the AWS
Basic course and then implement the operation of thesemodels. This course was internally developed in 2022.
At the beginning of this hands-on course, trainees aresupposed to carry out implementation of machine learning models in an assumed existing on-premises environ-Fig. 7

Education materials for AWS Basics

ment. They not only simply implement machine learningmodels but also learn effective visualization methods
during preprocessing as well as precautions for dividing
data sets. The course presents case examples of implementation that can be applied by trainees to development
work immediately after they finish the course. Next, they
are supposed to use Amazon SageMaker Note 9) to implement machine learning models in an assumed cloud environment. We have tried to prepare materials for thiscourse to present an overview of the implementation
range as needed, with which trainees can clearly identify
the functions they have implemented at the moment.

Note 9 ) A cloud service that provides an implementation environment for rapid development and deployment of machine learning models.

(5) AI Hackathon
AI Hackathon is an event for trainees to output inteams the knowledge and skills they have obtained
through the year-round education curriculum. Trainee
teams try to solve hypothetical challenges presented by
Administration by using machine learning. This activity
involves not only implementation of machine learningmodels but also the design of peripheral machine learning systems by taking into account the operation system
of machine learning models and the Well-Architected
FrameworkNote 10) proposed by AWS.
During the activity period, an "office hour" for eachteam is available once a week so that the team can consult with AWS Solution ArchitectsNote 11) about any questions about implementation of the design or machinelearning under discussion in the team . Individual members of each team are given a specific role and required
to show check items they should achieve. This check-out
system is used to quantitatively evaluate how close theteam members are to the goal set by Administration after
the completion of the Hackathon. In the Hackathon presentation attended by management and AWS, individual
teams report the results of implementation of machinelearning models and the unique thoughts they put inwhen designing the machine learning system. Photo 1
shows how the AI Hackathon presentation was held. Fig.

― 41 ―

Initiatives to Develop Digital Human Capital

8 shows some of the materials available in the presentation.

Photo 1AI Hackathon presentationcompany, with the aim of further expanding our AI human capital.
3. 3. 2 Track Record
Since its establishment in 2021, human capital withadvanced AI/ML knowledge and skills have gatheredfrom various domains including product development
and production engineering to be members of AI Community.
(1) Information sharing and promotion support
Discussions among AI Community members using
chatting tools are opened within the company. Examples
in the past include introduction of AI/ML development
themes addressed by Community members, troubleshooting support for other members based on member's own
experience in development, and deployment of manuals
for building a PythonNote 12) environment for easier implementation of machine learning. AI Community also plays
the role of supporting the promotion of latest technologies, including verification of pilot versions.
Note 12) A general-purpose programming language that is thede facto standard for AI development.

Fig. 8Hackathon presentation materials

Note 1 0) Major concepts and design principles for designingand executing solutions on the cloud proposed by AWS.
Note 11) A professional who provides appropriate solutions forcustomer needs including cloud services.

3. 3 AI Community
3. 3. 1 Background and Purpose
Independent AI development by AI human capital
within their own department would be inefficient fromthe viewpoints of proliferation of technology and formation of culture. This might generate barriers to immediate
contribution to business. the Digital Transformation Improvement Dept. thought that a medium or a continual
hub for all employees to communicate with each otherbeyond their functions or titles was needed. Then, we decided to plan and operate a place for employees with acommon passion to openly share technologies by discussing what they were concerned about and introducing
the latest technical information and newly publishedbooks to each other. This is AI Community. An initiative
to use your own knowledge and skills to resolve concrete
challenges that was launched in 2022. We thought that AI
Community would become a group contributing to business, thereby enabling the members to continue challenging new things all the time. We will disseminate the success stories of AI Community both inside and outside the(2) Group work
The group work program, which was launched in
2022, is intended to contribute to the company by utilizing the AI/ML knowledge and skills owned by the Community members. The program solicits concrete challenges faced by individual members during their daily
development work. Other members then participate to resolve selected challenges through mutual cooperation.
The following introduces some of these activities:[1] Research on a new analysis approach where structural
analysis with FEM has been reduced for machinelearning
CAE Improvement Dept. has been discussing integrating a detailed FEM (finite element method) based modelof laminated leaf valves into the SA analysis system toachieve high-accuracy prediction of the performance
characteristics of shock absorbers (hereinafter "SA").
FEM can take into account detailed physical phenomenathat cannot be covered by conventional theoretical calculations, such as the fastening axial force and the partial
contact of leaf valves. However, it takes a long time tocomplete the FEM calculation. Then, the department has
improved the prediction accuracy without increasing the
calculation time by reducing the order of the FEM-basedlaminated leaf valve model to a machine learning modeland integrating it into the SA analysis system. This technology has been highly rated both inside and outside thecompany.
AI Community implemented and verified various machine learning models proposed by its members, trying toenhance the prediction accuracy. This activity eventually
helped substantially improve the accuracy of predicting
the SA performance characteristics.
[2] Improving the product stamp inspection performancethrough deep learning
The Production Technology R&D Center is promoting
the automation of appearance inspection in the SA mass
production system through deep learning. The current ac-― 42 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

curacy of identifying stamped characters on products using deep learning is 99.92%. However, the current deeplearning method has not been adequately verified throughcomparison with other similar methods.
To achieve an even higher accuracy of the stamping
identification, AI Community has implemented and verified various methods other than the one that was alreadyscheduled to be introduced into the mass production system. Unfortunately, none of them was found to be superior to the current candidate. However, many of them were
the first ever methods implemented by the members who
participated in the activity including YOLONote 13). Community members could distinctly feel their own technicalgrowth through the group work.
Note 13) One of the physical object detection algorithms thatcan recognize the contour of an object at a high speedwith high accuracy.

3. 4 AI Human Capital Development Challenges
and Their Solutions
This section describes challenges related to the AI education curriculum and AI Community as well as solutions
to these challenges.
3. 4. 1 AI Human Capital Development Challenges(1) Follow-up support of the curriculum
Currently, continual follow-up support to employees
who have finished the education curriculum is not available. These employees may fail to maintain the skills
they learned if they are not involved in AI/ML in theirdevelopment work.
(2) Group work activity period
The term of a single course of group work activity of
AI Community is as short as three months. In many cases
members failed to fundamentally resolve challenges.
(3) Evaluation with objective measures
No specific measures have been established to evaluate the education curriculum or AI Community. What results the total human capital development initiatives havebrought about is unclear.
3. 4. 2 Solutions to Challenges
To resolve these challenges, we reviewed the total activities and discussed the following solutions:(1) Encouraging trainees to take part in AI Community
Among trainees who have finished the education curriculum, some do not have an opportunity of getting involved in development work despite being interested in
AL/ML. It is effective to encourage such employees toactively take part in AI Community. Once involved in theCommunity, they can receive continual follow-up support through group work after finishing the curriculum. It
is also expected they will maintain the skills they havelearned.
(2) Reviewing the group work period
The group work activity period of AI Community
should be changed to one year so that members can try tofundamentally resolve challenges. Challenges to be selected should be quantitatively evaluated for business
impact, necessary resources, and other factors using theirown methods. Then, themes that are believed to be mosteffective should be selected.
(3) Strengthening the group work scheme
With an eye toward operation as a machine learning
system, the group work scheme should use AWSs as its
development environment. Group work should be promoted with technical support from AWS. The results ofgroup work activities should be evaluated by determining
whether AI/ML challenges have been resolved by Community members (trainees of AI Education).

4

BI Human Capital Development

4. 1 BI Human Capital Development Initiative
Like the AI human capital development initiative,
KYB's BI human capital development initiative has twopillars: BI Education Curriculum and BI Community.
4. 1. 1 BI Education Curriculum
The BI Education Curriculum provides employeeswith training courses to build important skills for datautilization, including data preprocessing, visualization,
and analysis while practically using TableauNote 14), which
has been introduced into the company as a standard BI
tool.
Note 14) A BI tool provided by Salesforce Japan Co., Ltd.

4. 1. 2 BI Community
BI Community is an in-house community consisting oftrainees who are taking or have finished the education
curriculum as well as those who are interested in inhouse data utilization. Community members share theirknowhow, case examples both inside and outside thecompany, and BI-related information.
4. 2 BI Education Curriculum
4. 2. 1 Background
BI originally refers to the process of "collecting data,
putting it together and accumulating it in a location, analyzing it according to a purpose, and visualizing it into auser-friendly format". However, the BI Basics course
provided in 2020 mainly focused on how to use tools.
The course might have misled its trainees to believe that
BI is just data visualization using tools. Moreover, thecourse was rather focused on attracting new users, failingto provide an adequate approach for trainees to "self-propelling" the data utilization themselves.
After learning this lesson, we modified the curriculumfor 2022 so that trainees can learn step-by-step according
to their interest in BI.
4. 2. 2 Track Record
The BI education curriculum in 2022 has three courses: BI Overview, BI Practice (Entry-level), and BI Practice (Advanced-level). Firstly, the following describes thebreakdown of trainees in different courses of the curriculum in 2022.

― 43 ―BI Overview
BI Practice(Entry-level)
BI Practice(Advanced-level)

Fig. 9Trainees of BI education by fiscal year

Initiatives to Develop Digital Human CapitalFig. 9 shows the number of trainees of the BI education curriculum in these fiscal years. The accumulated total number of trainees is 337. In 2022, 160 employees
took the courses. The majority were employees from theEngineering Division, AC Operations, or Production Division. These functions are those involved in data analysis in their research and development or improvement activity. Still, participation in the curriculum has been
gradually expanded to include affiliated companies andmanagement divisions. We have found more and more
employees from different functions being interested in BI
education.
Now let us explain the details of these BI courses:(1) BI Overview
To provide an opportunity for employees to be interested in BI, it is essential to make them understand thecurrent situation in which we are surrounded by a dataabundant environment and for them to have data literacyNote 15) for implementing BI to begin with. Then, this BI
Overview course was set up for all employees to deepen
their understanding of the preconditions for the use of BI,such as the definition of BI and data literacy with support
from Salesforce Japan Co., Ltd. (hereinafter "Salesforce
Japan").
Data literacy involves analyzing data, which can be
implemented by Tableau. Lectures of this course cover
data analysis. Lecturers present trainees with familiar
data examples such as weather reports and sales data, sothat they can learn, for example, why data visualization
is effective for the analysis. The latter half of the lectures
includes a recreation program for trainees to answer anentertainment quiz by operating screens created on Tableau. The program makes trainees easily understand what
they can do with Tableau, helping them to proceed to thenext step, namely, the BI Practice (Entry-level) course.
(2) BI Practice (Entry-level)
In the BI Practice (Entry-level) course, trainees can receive hands-on practice of basic operation and data classification of Tableau, including simple plotting such as
drawing line and bar graphs, data filtering, and learning
differences between continuous and non-continuous data.
Each section of the course has exercises. Two dedicated assistant instructors support a group of five or six
trainees and respond to their questions. Assistant instructors consist of volunteers from BI Community so thatthese individual instructors can also improve their understanding of BI.
The course uses lecture materials that have been prepared by Salesforce Japan. These materials are brushed
up reflecting feedback from trainees and lecturers.
Some of the results of trainees are shown in the following figures. Note that these results are in the preparation stage before being put in service. They were temporarily created to verify practicality in the case of using inhouse actual data. Fig. 10 shows the dashboard ofcommunication terminals for oil status, vibration, andtemperature sensors along with their battery status. Fig.
11 shows the dashboard for changes in patent applications of different countries that has been developed by

Fig. 10

Layout of sensor communication terminals andtheir battery status

Fig. 11

Analysis of changes in patent applications ofdifferent countriesNote16)

the Intellectual Property Department.
(3) BI Practice (Advanced-level)
The most likely difficulty for users in performing datacollection, analysis, and visualization may be the development of a data environment. Particularly when users
have just started using Tableau, they often handle existing data. That is' why the BI Practice (Advanced-level)
course is focused on how to organize existing data. We
designed the course to include data splitting and data
coupling for linking two or more data sets using Tableau
DesktopNote 17) and Tableau PrepNote 18) as well as data preprocessing such as name-based aggregation by correcting
orthographic variants.
Using a data set consisting of several files, the lecturers explain in a storytelling style how to organize the data
set by identifying any inconsistent parts of the data. All
materials used in the lectures were internally prepared.
We believe that trainees can vividly experience theprocess of data processing, which is important for proper
visualization and analysis of BI data. We have received
feedback from trainees that they have successfully resolved remaining issues.

― 44 ―

Note 15) The generic name for the capability to read, analyze,
use, and describe data.
Note 16) Concrete numbers and names have been blurred.
Note 17) A specially designed tool for data analysis and visualization. One of the Tableau products.
Note 18) A specially designed tool for data pretreatment. One of
the Tableau products.

KAYABA TECHNICAL REVIEW No. 66 APR. 2023

4. 3 BI Community
4. 3. 1 Background
It may be difficult for trainees alone to identify challenges or organize data of their own function. Then, across-function community was established to support
them to achieve "self-propelling". This BI Community
mainly consists of trainees of the BI Education curriculum. Community members can freely consult with eachother about their concerns over how to use Tableau ordata-related issues.
4. 3. 2 Current Challenge
BI Community has 177 members consisting of 101
CreatorsNote 19) and 76 ViewersNote 20). However, active users of Tableau in the last three weeks are not more than
50% of licensed users.

⒜Fig. 12Creator⒝ Viewer

Ratio of active users to licensed users

Thus, the Community activity has not been vitalized asplanned. We recognize that a data-driven culture has not
yet been successfully developed.
Note 19) A type of license that authorizes the use of Tableau
products. Developer license.
Note 20) A type of license that authorizes the access to screensthat have been created.

4. 3. 3 Cause Analysis
We analyzed the behavior of users to figure out thecause of the challenge. The analysis has revealed the following:
About Creators[1] 1 6 Creators make their own results open to thecommunity.
[2] Creators do access the results [1] (within thesame function).
[3] Creators do use Tableau but have not yielded
many results.
About Viewers[4] Viewers access the screens that have been madeopen to the community by the Digital Transformation Improvement Dept.
- Equipment predictive maintenance support system- Equipment data collection/analysis system (MES
service) 4)[1] and [2] imply that Creators have started to proactively act in the functions. According to [3], however,they have not yet reached the stage of creating screens to
be made open to the community. They may face somechallenge. Otherwise, they may have completed analysis,
but just produced results that are locally accessed by alimited number of users.

On the other hand, Viewers usually use Tableau to access screens they want to view. It can be estimated from
[1] and [2] that Viewers are likely to use Tableau if dataor screens that relate to themselves are available. In otherwords, the screens made open to the community may not
be those wanted to view by the Viewers who do not use
Tableau.
From the above, it can be concluded that a support
system for the user group applicable to [3], which is abottleneck, must be developed.
4. 3. 4 Solutions
To resolve the challenge, the operation of the education curriculum should be revised to focus on user support. We discussed the following solutions:(1) Providing on-demand learning contents
The live lectures, which have been prepared and heldby members from the Digital Transformation Improvement Dept. on an as-needed basis, will be changed to avideo streaming service, ensuring the support man-hours.
With this service, trainees can take on-line lectures whenever they like. It can be expected that the number of inhouse users will increase.
(2) Creating a skill map
Along with the video streaming service describedabove in (1), a skill map will be created and made available. The skill map should be linked to the existing lectures so that trainees can obtain visualizations of theirown skill set and maintain their motivation for self-learning.

5

Future Prospects

Since its launch of full-scale initiatives to develop digital human capital in 2021, KYB has promoted the development of an education curriculum and the operation ofcommunities. Through these activities, the company has
enjoyed an increase in AI and BI human capital and newcases of data utilization that have never been seen before.
We will continue considering measures to increase thein-house digital human capital. For AI human capital development, we will build a development platform where
even more AI human capital, ranging from beginners tomasters, can flexibly use AI. We would also like to generate more cases of establishing an MLOps environment
for AI's contribution to business. To do so, it is necessary
to establish a cloud environment operation rule for wider
deployment throughout the company. Besides this, it will
be even more important to carry out DX promotion to
expand the KYB-IoT platform appropriately according to
the scale of function or project. For BI human capital development, we would like to facilitate data linkage
among the business functions centered on the improvement of data analysis skills of individuals. To achievethis, we should discuss the company's general data governance, including how data should be, how data should
be available, where data should be compiled, and who is
responsible for data management, to provide data to users in an easier-to-use way.

― 45 ―

Initiatives to Develop Digital Human Capital

6

In Closing

This report has introduced KYB's initiatives to develop
digital human capital. The true purpose of education isachieved only if employees apply the knowledge andskills they have learned to their daily development work
contributing to business. Toward the implementation ofDX, we would like to continue to generate more cases of
in-house data utilization and expand the education curriculum needed by the company being aware of world
trends.
Finally, we would like to take this opportunity to sincerely thank all those concerned in the related functions
who extended great support and cooperation to the promotion of the initiatives.

3) OHUCHIDA, MIYAUCHI, SAGEHASHI: "Use of AI Technology in Development of SA Elements", KYB Technical Review
No.66 (April 2023)
4) YUBUKI, GABURIELLA: "Building the Foundations for MES
Services in the New Era", KYB Technical Review No.64 (April
2022)

References
1) NAITO: "AI x IoT Initiatives in the Production Technology Domain at KYB", KYB Technical Review No.60 (April 2020)
2) FURUKAWA, ISASHI: "Development of an Equipment Predictive Maintenance System", KYB Technical Review No.63 (October 2021)

AuthorMIYAUCHI Yuuki

ISASHI Ryosuke

Joined the company in 2017.
DX Improvement Dept., EngineeringDiv.
Engaged in system developmentusing AI and promotion of AI humancapital development.

Joined the company in 2017.
DX Improvement Dept., EngineeringDiv.
Engaged in building of data visualization/analysis foundations andpromotion of BI human capitaldevelopment.

TAKINO Shinsuke
Joined the company in 2006.
DX Improvement Dept., EngineeringDiv.
Was engaged in promotion of digital
human capital development.

― 46 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

Essay
Account of Residence in Indonesia
SHIMENO Yoshirou

1. Introduction
I was sent to PT. KYB Hydraulics Manufacturing Indonesia (hereinafter "KHMI") located in Indonesia in
October 2015 and worked for the company as an expatriate for about six years and eight months until my repatriation in June 2022. During the expatriation, I definitely
experienced various things. In this essay, I've written
several episodes I remember rather freely like a collection of short stories. I will be happy if you take time toread them.

2. Indonesian is the Second Easiest Language in the World
When I asked the then President of KHMI "is there
anything I should prepare for expatriation?", I was told,"First of all, learn Indonesian to be able to have conversations in everyday life". Before expatriation, I took an
Indonesian course for about 90 hours. The teacher was a
Japanese who used to live in Indonesia for quite a longtime and taught me not only the language but also local
culture and customs. This information was very usefulfor me to live in Indonesia during my expatriation. One
thing that particularly impressed me in the Indonesiancourse was the phrase "Indonesian is the second easiest
language in the world" as seen in the title of this section.
Probably when my learning came to a deadlock, theteacher abruptly told me, "Indonesian is the second easiest language in the world". This phrase was followed by
the question "What do you think is the easiest languagein the world?" I answered, "I think it's English", because
it is widely used as an official language in the world. The
teacher gave me an unexpected answer full of humor,"Unfortunately no, the correct answer is your mother language". Those were the teacher's words to encourage me
to have confidence since Indonesian is the next easiest
language to your mother language that you are familiarwith.

3. No Orders
In October 2015 when I moved to Indonesia, the Southeast Asian Region including Indonesia saw a significant
slowdown in demand for construction equipment. Only
less than one year had passed since KHMI had started operation. During that time, the company had no product delivery at all in some months partially because it was able toproduce only one model of construction equipment. I wastold by the President as soon as I arrived at KHMI, "Youdo not need to report to duty on Friday since we've just decided to make Friday a no-work day to reduce production".
I then recalled those days when I had joined KYB as a
newcomer. When I reported to work at Gifu South Plant
which was my temporary workplace in that July, the General Affairs Manager told me that, "Those who have been
assigned to Hydraulic Engineering should take a paid leaveon next Monday. Full-time employees belonging to Hydraulic Engineering will be off for lower production, but
trial employees will not be covered". History was repeated.
The words of the President made me feel insecure about
the start of my work in Indonesia which would begin witha no-work day for lower production. I managed to switch
my mind by recognizing the situation as "I will only riseup from the current worst of times" and then started towork.
On those days on which workers had nothing to directly produce, we provided group education. But we almost
ran out of suitable topics for lectures. Workers were under accumulated stress as they continued taking lectures
sitting in a classroom. We thought it better that workers
should do some physical exercise and then decided to ask
them to develop a futsal ground on an expanded space ofthe premises for nearly half of each working day. I also
tried to take time to work together with them in developing the ground so that they could recognize me. Finally,
the futsal ground was properly completed, and I sometimes found employees playing futsal after work. However, as they gradually came to work harder with overtime and a two-shift operation, the futsal ground fell into
disuse and eventually fully deteriorated. While I regretted
the deterioration in spite of our efforts to develop theground, I also felt happy with the increase in production.

4. When You Are in Trouble...
I sometimes feel acutely aware that an important thingin living in an unfamiliar place is the link among people.
KHMI operates a welding process using CO2 gas. One
day, a rectifier installed on a CO2 gas cylinder had a failure, which interrupted the gas supply resulting in a production shutdown. We informed Gifu South Plant of thefact, but they replied they did not use the rectifier used by
KHMI because their gas supply system for welding wasdifferent from ours. We then had to manage to obtain arectifier of the same type in Indonesia. Since the target
equipment was a product made in Japan, the Indonesianstaff were at a loss with no prospect of obtaining the― 47 ―

Account of Residence in Indonesia

equipment. Then, I happened to recall the face of a person from a trading company from which we bought hydraulic fluid and welding wires. When I got in touch withhim right away, he told me he would check it out quickly.
After just a few hours, I was informed that he would senda unit that had just arrived at the airport out to us. Thanks
to his arrangement, we successfully minimized the line
shutdown. After that, he helped us over and over again
when we were in a tight corner. We are gratefully obliged
to him.
Indonesia saw the outbreak of COVID-19 around April
2020. Its Delta variant raged in July 2021. Under the circumstances, we exchanged information about COVID-19
with our customers, suppliers, and friends and acquaintances, and then cooperated with each other to manage toovercome the difficulty. We finally did it thanks definitely
to the network of people we had built. The pandemic reminded me anew that networks are so important for expatriates working far away from Japan.

5. Delivering Products to Customers
KHMI manufactures hydraulic cylinders for construction equipment. The company has only one assembly
line. In order to avoid the risk of delay in delivery due toequipment failure or other trouble, KHMI operates theplant with a certain amount of product inventory on hand.
However, in the event of a major equipment failure involving part replacement during a period with many orders, I had to spend several days feeling uneasy until the
repair was done. If I found the inventory having gradually decreased in the course of making rounds of the plant,
I checked out the upcoming delivery schedule in the nextmorning meeting. I was often waiting for replacement
parts to arrive at the plant while trying to figure out until
when we would be able to continue delivering productswith the existing inventory. That was quite stressful indeed. When the parts arrived and we completed the replacement work to resume production, I felt very happy
together with the local employees. I breathed a sigh ofrelief when I heard the production equipment starting to
make a sound. Then I went back to work in the office.
A hydraulic cylinder consists of about 40 kinds ofparts when they are counted by item number. Naturally,
the cylinder cannot be assembled even if only a single
part is missing. In the morning meeting one day, I wastold that the production schedule had to be postponeddue to a lack of seal parts. A seal product is generallycompatible with other counterparts as long as they are
identical in size. Unfortunately, the seal part we used had
no other counterpart of the same outside and inside diameters. I heard that, if the next sea freight arrived as scheduled, the product delivery would be made with no problem at all. I knew things would usually get harder undersuch a situation. In fact, the freight was delayed as expected. Our staff from Production Management eventually went out to the forwarder's warehouse to meet the arrival of the container at the warehouse and receive thenecessary parts from the container. They hurried back to
KHMI to bring them to the assembly line and managed
to successfully deliver the product at the last minute by
the delivery time.
Another experience I remember was a local supplierranking for delivery performance announced at a suppliermeeting of our customer. In addition to the conventional
announcement of quality failures and worst suppliers, theresults of their evaluation of delivery performance wereindicated at that meeting. As I was confident that we had
never delayed a delivery, I tried to find the name of
KHMI in the list from the top one by one, but I couldn’t
see it. I finally found our name around the middle of thelist. Actually, the customer evaluated suppliers by marking their delivery as "on time", "early", or "delayed".
KHMI had certainly never delayed any delivery but
showed a relatively high rate of early delivery. This was
the cause of the lower than expected rank of KHMI.
Then, first of all, we interviewed the customer to hear theevaluation criteria, successfully identifying, among theinformation provided by the ordering system, the parameters used to determine whether a delivery is late or early
along with the reference date. Next, we looked back at
the delivery performance in the past to investigate possible factors leading to the evaluation results of "early" deliveries. The investigation revealed that KHMI moved
forward some deliveries in order to raise the loading efficiency of motor trucks, which were then evaluated as"early" deliveries. KHMI originally operated the plantwith a certain amount of product inventory on hand andthe customer was located around only 10 km away fromthe KHMI plant. From these reasons, we determined that
we could make delivery on time by transporting the products of the models in the quantity as instructed by the ordering system in auto trucks we arranged every day. With
this new delivery system, KHMI actually had to deliverproducts more often. So, we changed the forwarder toanother located in the same industrial park as KHMI for
freight cost reduction and then started to make deliveries
according to the exact delivery date, item number andquantity instructed by the customer's ordering system. In
the next supplier meeting, KHMI won the No. 1 prize foron-time delivery with 100% delivery achievement. I'mvery glad to hear that KHMI still continues to achieve
100% on-time delivery.

6. Clothing, Food and Living
The first is "clothing". As you know, Indonesia is located in the tropical zone right on the equator. The year
can be divided into two seasons: rainy and dry seasons.
Since there are almost no daily temperature variations
throughout the year, you do not need to change clothingby season. Still, a big and famous Japanese apparel shopthat I often found in shopping malls in Jakarta sold down
jackets and clothing with functions such as moisture absorption and heat generation during the Japanese winter.
While these products were definitely convenient for me
to temporarily go back home in the winter to Japan, I
doubted if Indonesians really needed to use these goods.
The winter in Japan generally corresponds to the rainyseason in Indonesia. In the rainy season, the average temperature is slightly lower than that in the dry season. I actually felt the intense sunlight in the dry season and chillyin the rainy season. Taking into account these changes inclimate in Indonesia, I had a hunch that's why such winter clothing was in stores even in Indonesia.
The next topic is "food". Many Japanese-owned companies had branched out into Jakarta where I lived andaround the industrial park in Bekasi where KHMI was― 48 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

located. These places had a variety of Japanese restaurants. Some of them directly bought airfreighted seafoodfrom the Japanese market. As I describe in detail in theparagraph for "living" later, after work I used to take dinner at a Japanese restaurant in the industrial park before
going back home because the Jakarta suburban area often
had traffic jams. That restaurant served a variety of Japanese food cooked by the full-time Japanese chef. I went
to the restaurant almost every night on weekdays. The
Japanese meals in the restaurant always appealed to me
and conversations with familiar Indonesian staff there allowed me to refresh my mind.
I often had Indonesian food for lunch after playing
golf on weekends. I looked back on how I had been playing while eating Satay (skewered meat; salty or marinated chicken with coconut milk is popular) or Tahu Goreng(fried tofu). It was common practice for me to finish off anight of drinking with Nasi Goreng (Indonesian style
fried rice), Me Goreng (Indonesian style fried noodle), or
Soto Ayam (curry-flavored soup with chicken and rice
vermicelli, sometimes containing rice). What I personally
loved was Sop Buntut, which is a rather light taste, spicy
soup made with oxtails. You may take Sop Buntut withplain rice and add Sambal (chili sauce) or lime to enjoy
taste variations. This is one of my recommendations, although I did not eat it so often.

approximately 40-minute ride to report to duty using aneasy-to-drive highway, but heavy traffic jams frequently
occurred due to traffic accidents or heavy rain. Somepeople say that Jakarta is the world's worst city for traffic
jams. Particularly, three transportation systems were under construction at that time: the Jakarta-Bandung highspeed railway, the Jakarta-Bekasi-Bogor suburban railway, and the Jakarta-Karawang high-speed railway.
When roadworks related to these lines were conducted simultaneously in the same area, it often took over threehours each way for commuting, which really frustrated me.
The car I used in Indonesia was not equipped with anavigation system. When I was involved in a traffic jam
or moved to a place I did not know, I used map applications, which had evolved with the spread of smartphones,
to figure out the best route or predict the time to arrive at
the destination. These applications were very convenient
tools but required me to take care when driving on an unfamiliar open road. This is because, while map applications indicate busy traffic in color, I was often caught in a
traffic jam where cars could not move an inch even after
selecting a "busy" route along open roads rather than a"jammed" route. While Indonesian highways cannot be
accessed by motorbikes, its open roads are available forboth four-wheeled cars and motorbikes. On an open roadwith a traffic jam, cars certainly could not move at all, but
motorbikes could drive through the jam. This apparently
causes the map applications to indicate that this road is"busy". In spite of this precaution, one of my good memories was of working together with my driver trying toreach the destination by giving navigation instructions to
him with my smartphone in one hand saying, for example,"Turn left at the next corner" and "Go straight for a while".
Looking back on the expatriation period, the person withwhom I spent the longest time was my driver. I really
thank him for getting me to various destinations safely forover six years.

7. Birthday

Photo 1

Sop Buntut (in the right bowl)

I think that most Japanese like the typical taste of Indonesian cuisine. However, those who are not fond of
spicy food (like me) should be careful of some Indonesian dishes because they use a good amount of red pepper. On the other hand, most Indonesian beverages taste
sweet. Even coffee and tea are very sweet as they areserved with sugar already mixed in as standard. When ordering, I needed to ask them to give me a "non-sweet"
drink.
The final topic is "living". I lived in an apartment in
the center of Jakarta for all the six years of my expatriation. The 1st to 3rd floors of the office and apartmentcomplex had a small-sized shopping mall including Japanese-operated supermarkets, Japanese restaurants, andramen shops. I never felt any inconvenience during mystay in the apartment on holidays.
The industrial park where KHMI is located was about
40 km away from the apartment. It was "normally" an

In Japan, the person whose birthday is celebrated usually
receives birthday presents from their family and friends. In
Indonesia, on the contrary, the person whose birthday iscelebrated usually gives presents or buys food for theirfamily and friends. Since I had learned this custom before
my expatriation, I asked local staff to order a pizza delivery
for my birthday before my first birthday after being sent toIndonesia. On the day, when I was back at my desk after amorning assembly, I suddenly heard a voice singing theHappy Birthday song and saw a staff member approachingme carrying a birthday cake. All members in the office celebrated my birthday. I still remember that I was very surprised because I had not expected such a celebration at all
while I was overwhelmed by the great joy of being a member of KHMI. Thereafter, all staff members continued tocelebrate my birthday every year with a birthday cake they
had prepared.
In the last year of my expatriation, I wanted to give thestaff a gift that they could use for a long time. Indonesian
people generally bring a drink bottle ("my bottle") totheir workplace or a place to go out. So, I gave a plastic
drink bottle as a gift to all employees, drivers, janitors,
and cleaners working in the premises of KHMI, expressing my gratitude for helping me so far.

― 49 ―

Account of Residence in Indonesia

commemoration of the 100,000th cylinder, we decided to
exhibit it in the entrance lobby along with the first massproduced cylinder that was already being exhibited. We
also decided to post the name of all 95 employees (including retirees) who had been involved in the production of the 100,000 cylinders beside the actual cylinder.
We asked them to make a banner to indicate their name. I
am very proud of having been present at this memorable
event that added another page to the history of KHMI.

Photo 2Birthday cake and KHMI staff on my birthday inthe last year

Photo 3

The 100,000th cylinder (gold color) and banner

8. The 100,000th Cylinder

9. In Closing

KHMI rounds up actual production every month. At
the beginning of 2021, we had almost achieved a total
production of 100,000 cylinders. I was deeply moved by
the fact that we had managed to accumulate productionin spite of many different things happening up to then.
Hoping to hold a company-wide celebration event, I
came up with an idea. How about a quiz event for all employees to ask them "What model will the 100,000th cylinder be?". We listed up all possible models that could be
produced at that time. Individual employees were supposed to vote for which model would be the 100,000th
cylinder. Actually, only I had known about which cylinder on which day would be the 100,000th cylinder basedon the planned and actual daily production data. Still, I
was looking forward to finding out what model would be
the 100,000th cylinder along with employees as the production schedule might change due to an abrupt change
in orders for instance. Finally, the 100,000th cylinder was
the model that was being produced most at that time, andwhich had been voted for by the highest number of employees. The prize money funded from my pocket was
divided amongst those employees who voted for thatmodel before the end of the 100,000th Cylinder Quiz. In

When I was sent to KHMI, there were three expatriates including me. I was the only expatriate when I was
about to be repatriated. In those days, I was in charge ofa wider range of operations and had taken on heavier responsibility. Now I would like to appreciate anew theKHMI employees, who were always cheerful, for supporting me in continuing to work for KHMI until the end.
I also feel that I was able to grow as a KAYABA personnel in such an environment where expatriates had to definitely do whatever they had to do.
On the other hand, I regret that I could not visit theWorld Heritage and other famous sites dotted throughout
Indonesia partially because I was working on weekdays
and went for golfing on weekends as well as being an expatriate away from my family. I hope I will visit Indonesia again with my family to enjoy the local culture before
I forget the language and will take the opportunity of introducing the living environment during my expatriation
to my family.

Author 

SHIMENO Yoshirou
Joined the company in 1999.
Management Manager, Sagami Plant,
Hydraulic Components Operations
Took present post after repatriationfrom KHMI in June 2022.
― 50 ―KAYABA TECHNICAL REVIEW No. 66 APR. 2023

ary

s
los

G

FMS
Refer to “Incorporation of Processing of Base Plates for Piston Motors into FMS Lines” (page 13)

HANAEDA Ken
Production Engineering Sect., Production Engineering Dept., Sagami Plant, HC Operations

1

What is FMS?

FMS is the acronym for “Flexible Manufacturing System” and refers to a highly flexible production systemthat can efficiently produce batches of many different
parts. The main features of FMS include systematic interfacing among parallel processing equipment and various
devices including stockers, and efficient production of avariety of products by leveraging unattended operation.

2

used as guided vehicles.
[5] Set-up station
An area used to attach or detach workpieces. Work, after being attached or detached, is automatically transferred to equipment units for processing with a commandfrom the system PC. Unattended operation is enabled bysupplying work waiting for processing to the stocker.

Examples of Configuration

Based on an example of configuration of FMS systems(Fig. 1) manufactured by Makino Milling Machine Co.,
Ltd., the following introduces the functions:[1] System PC
A personal computer (PC) for controlling the FMS
system. The PC is linked to individual equipment units
via communication lines. The system PC issues production commands, based on which instructions are sent toequipment units. The operator can view the operating
status of equipment units and work instructions to the
set-up station, etc., on the PC screen (Fig. 2).
[2] Stocker
Several types of jig can be stored in a stocker so as toproduce many different parts that cannot share the same
jig. For a set-up change, the system PC can call the relevant jig to complete the set-up. The stocker capacity is
decided by the types of parts, the number of lots, the timezones of unattended operation, and other factors. The
stocker can house jigs with their work installed.
[3] Machining center (MC)In many cases, parallel type machining centers are introduced. The number of machining centers is decided by
the work processing time and production volume.
[4] Guided vehicle
A vehicle used to automatically transfer materials toequipment units. Stacker cranes, loaders, and robots are

Fig. 1 Example of FMS configuration

Fig. 2 System PC screen
Reference
1) Pallet Transfer System, MODULE MMC 2https://www.makino.co.jp/ja-jp/machine-technology/automation/pallet-system― 51 ―

Counterbalance Valve

ary

s
los

G

Counterbalance Valve
Refer to “Development of Anti-cavitation Vane for Travel Motor of 7-ton Hydraulics Excavator” (page 28)

SAITO Keiji
Editor of KAYABA Technical Review

12What are Counterbalance Valves?

Counterbalance valves are used to prevent hydraulicactuators installed in construction machinery or machine
tools from dropping with their own weight or to maintainthe descending speed of such actuators. The counterbalance valve limits the flow rate in one direction and lets
fluid flow freely in the other direction. Actuator controls
speed by generating back pressure so that is does not exceed the control speed.
Fig. 1 shows a structural drawing of a counterbalance
valve. When the inlet pressure in the valve is not morethan the pressure setting of the spring, the spool is keptpressed down. When the inlet pressure is higher than thepressure setting, the spool is pushed up to open the outlet
port, releasing oil. If it is necessary to let pressured oilflow from the outlet port side to the inlet port side, acheck valve should be installed in the circuit.
For example, the counterbalance valve can be used toprevent a vertical press machine from dropping with its
own weight. Another example of an application is a drilling machine using a cylinder where the counterbalance
valve is installed in a hydraulic circuit designed to prevent the piston rod from abruptly sticking out when theload resistance suddenly decreases upon completion of adrilling process.

Counterbalance Valves for Travel Motors

Travel motors for hydraulic excavators or other open
circuit applications are equipped with counterbalance
valves. Fig. 2 shows a circuit diagram of a travel motor.
The counterbalance valve for travel motors has the following two functions:[1] Motor braking
The counterbalance valve is combined with a relief
valve or an anti-cavitation valve to constitute a braking
circuit that can apply a braking force to the piston motor
so as to bring the motor gradually down to a stop.
[2] Overrun prevention
Where a piston motor is forced by an external load to
be rotated at a speed higher than the rpm decided by the
supply flow rate (pumping effect), the counterbalance
valve is used to control the motor speed to a level suitable for the supply flow rate.

カウンタ
Counterbalancevalve
バランスバルブ

P1 P2

DrFig. 2 H ydraulic circuit diagram ofcounterbalance valve for travel motor(relief valve type)Fig. 1 Counterbalance valve― 52 ―

Editors Script
This issue reports KAYABA's initiatives for digitization and the use of AI for manufacturing (or Monozukuri) that converts
two-dimensional data, which has been rapidly evolved, developed, and improved, into three-dimensional products contributing
to society. As the size of product development data has likely grown larger in recent years, it has become diﬃcult to determine
the physical aspect of such data (i.e., parameter correlation). It is now possible to determine such parameter correlation more
quickly and more exactly by the use of AI. As a craftsman of the Showa era, I am proud of my juniors who have a good command of AI using both their hands and mind simultaneously.
(YAMAGATA)
I sometimes remember the words of one of my senior colleagues: "Engineers should be simple and stupidly honest". Thisphrase might have a bad meaning like having no wisdom or no ability to behave as circumstances demand. However, with thesewords, I think he wanted to encourage engineers to "keep a simple and even stupidly honest attitude to tackle everything withrelentless drive to accomplish their mission until the technology is transformed into product". As surging prices and supply
shortages of fuels and materials have become even more ﬁerce due to various factors including the outbreak of the COVID-19
pandemic, conﬂicts, and variations in the exchange rate, measures against these challenges need to be taken. However, I also
believe that engineers should keep their attitude to promote technical development initiatives in an even stupidly honest way
with an eye toward the future.
(UMEDA)As an editor, I read some issues of KAYABA Technical Review back again. Although I thought I knew the product families of
the company, I noticed anew how wide the ﬁelds covered by the product lineup are. Particularly I found individual businesses primarily leveraging their own expertise for product development. With my experience in concentrating on the specialty of my own
business unit, I have not been interested so much in other businesses. Nevertheless, when focusing on the essence of some technologies, I noticed that they could be eventually applied to other products as well. I want to be engaged in publishing this issue
with an expectation that the information contained herein will give readers helpful hints or ideas about their job. (OKUMURA)

Editorial members◎ITO Takashi
KABASAWA
RyoichiBasic Technology R&D Center, Engineering Div.

UMEDA Yoshinori

Engineering Headquarters, HC Operations
Mie Engineering Dept., HC Operations

Basic Technology R&D Center, Engineering Div.

YONEKAWA
Norihide

HAYASE
Tomonori

Production Technology R&D Center, Engineering Div.

YAMAGATA
Hideki

Quality Assurance Dept., Aircraft Components Div.

SUO Shiro

Intellectual Property Dept., Engineering Div.

KAWASHIMA
ShigeruEngineering Dept., Kumagaya Plant, Special Purpose Vehicles
Div.

AMANO Genki

Corporate Planning Dept., Corporate Planning Headquarters

OKUMURA
Kazuyuki

Design Sect., No.3, KYB Motorcycle Suspensions (KMS)OTA Yasuhiro

Engineering Headquarters, AC Operations

KAWANO
YoshihikoDevelopment Dept., Engineering Div., Takako Industries, Inc.

MIYATANI
Osamu

Engineering Headquarters, AC Operations

KOBAYASHI
Hirotaka

Design Dept., KYB-YS Co., Ltd.

SASAKI Kazuhiro

Engineering Headquarters, AC Operations

NOGUCHI Yoichi

Production Engineering Dept., PS Business Operations, AC
Operations

SAITO Keiji

Engineering Headquarters, HC Operations〇KOBATA Hiroshi〇OBAYASHI
Yoshihiro

Engineering Planning Dept., Engineering Div.
Engineering Planning Dept., Engineering Div.

◎Editorial Chief〇Editorial Secretariat
HC Operations: Hydraulic Components Operations
AC Operations: Automotive Components Operations
KAYABA TECHNICAL REVIEW No.66[All rights reserved] [NFS]
Published on April 1, 2023
Editor and Publisher: KAYABA Technical Review Editorial Board
Publishing Oﬃce: KYB Corporation(KYB Corporation adopted the common nameof KAYABA Corporation on April 1, 2022).
World Trade Center Building South Tower 28F,
2-4-1 Hamamatsu-cho, Minato-ku, Tokyo
105-5128, Japan
Tel: 03-3435-3511
Fax: 03-3436-6759
Published by SHOBI Printing Co., Ltd. (Hakusan, Tokyo)

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