TECHNICAL REPORTIoE Initiatives
Y. YAMAGUCHI

Industry is facing the problem of worsening labor shortages on the production shop floor due to factors suchas a decline in the working population and shortage of successors to seasoned technicians. Meanwhile, there are
increasingly high expectations that rapidly-advancing IT technologies and utilization of information such as big
data, learning and AI will dramatically solve such problems affecting monozukuri and bring about a paradigm shift
in the manufacturing industry. This paper will report on JTEKT’s IoE (Internet of Everything) activities and our
initiatives for solving monozukuri issues which we intend on reflecting in future activities.
Key Words: IoT, AI, IoE, smart factory, line builder

Believing these to be important technologies thatwill transform monozukuri, JTEKT has conductedinvestigations and utilized consulting and group venturecompanies since 2012 to promote IoE (Internet ofEverything − term coined by JTEKT) so that we may use
it to further grow our Machine Tools & Mechatronics
business. In contrast to IoT, IoE is a concept clarified by
JTEKT which expresses the connection between “things”
to “everything” (people, information, etc.), based on ourbelief that we could also incorporate information on thepeople who work in factories to unlock the potential ofpeoples’ roles (Fig. 2).

1. Introduction
In recent years, advancements in information
technology such as IoT (Internet of Things), big data
and AI have aroused expectations that there will bemajor changes to the fundamental way we work and live.
Moreover, in the industrial sector, such technologicaladvancements have been referred to as triggers of a fourthindustrial revolution, and studies for their utilization invarious fields have been ongoing since around 2011. In
Japan, there are many manufacturers who obtain datafrom systems and production equipment, however there1)
are reports that such data is not being properly analyzed
in some cases, therefore there is an urgent need to build
smart factories in which all elements of a factory areconnected via a computer network (Fig. 1).

Mission of a line builder

Utilization of IoT technologies

1. Timely supply of production assets
2. Construction of a line based on TPS＊
3. Creation of customer value
・ Creation of a line that outputs
no defects
・ Creation of a line that never stops
・ Improve productivity＊
Toyota Production System

1. Ability to accurately draw out the objectives(vision) and issues of customers
Then, the ability to provide IT to suit such objectives/issues
2. The ability to see MUDA (waste) as MUDA
Data/information
IT(Information Technology)
OT
TPS(Operational Technology)

Shop floor management

IoT
Integration of the shop floor and IT

OT ability based on the TPS
IT ability to solve thisPursuit of equipment/
people productivity

Build smart factories
Fig. 1 Smart factory

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2. 2 IIC (Industrial Internet Consortium)

Connection of things

Connection of people

Achieve visualization to make improvements

In the U.S., many companies participate in the
IIC. General Electric Company (GE), International
Business Machines Corporation (IBM), Cisco System,
Inc. (CISCO), AT & T Inc. and Intel Corporation are
the main pioneers providing participating corporations
with verification environments targeting a wider scope
encompassing Industry 4.0. At this point of time,no established regulations and standards exist, andtechnological advancements by IIC are setting precedent.

2. 3 Connected Industries

Increase shop floor capability/improvement capability
Evolve both equipment and people

Fig. 2 The IoE concept

2. Strategies of Various Countries
The growing trend to evolve factories into ‘smart
factories’ leveraging IoT technologies, etc. has to someextent been driven by national-level strategies. With theaim of stimulating new growth in the monozukuri fieldand creating change in terms of industrial compositionand product configuration, initiatives are being led bynational governments and through a top-down approachwith the involvement of influential corporations.
Meanwhile, IT technologies have widely spreadthroughout common society and there is a growing
bottom-up trend whereby proposals for new technologies
aimed at achieving smart factories originate from a wider
range of sources, including venture companies.

2. 1 Industry 4.0
Industry 4.0 was announced in 2012 as Germany’s newnational strategy for economic growth and its essence isthe construction of a cyber-physical* industrial society
through digitalization and computerization. Concrete
manifestations of Industry 4.0 have been presented asprocess improvement and better traceability in production,
the transfer of consumption information enabling
immediate response to the individual needs of consumers,
and the realization of mass customization.
* This refers to a service of making events conventionallyreliant on “experience and intuition” more efficient inorder to realize a highly-advanced society

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In Japan, the strategy is “Connected Industries”
announced by the Ministry of Economy, Trade andIndustry (METI). As Fig. 3 shows, the basic concept ofConnected Industries comprises three main elements. An
industrial society where people play active roles is being
incorporated in the ideology and is consistent with theIoE promoted by JTEKT.
Basic concept
Industrial society in which new added values are created throughvarious connections.
Amidst advancing digitalization, leverage Japan’s strengths of high“technological capability” and sophisticated “shop floor capability in an
attempt to build a new, solution-orientated industrial society.
Create a people-centered industrial society in which case-by-caseproblem-solving ability, ongoing improvement activities, etc. backed bythorough shop floor knowledge can be leveraged.
Three main elements
1. Realize a new digital society in which people, machines andsystems do not oppose one another, but rather collaborate together
2. Problem solution through cooperation and collaboration
3. Adhering to a “people-focused” approach, proactively promote
development of professionals in line with advancements in digitaltechnology
Source: METI press release
http://www.meti.go.jp/press/2016/03/20170320001/20170320001.html

Fig. 3 Connected industries

3. Status of Various Companies Observedat the 2018 Hannover Messe
JTEKT had the opportunity to exhibit at the Hannover
Messe held in Germany in April 2018 and took advantageof this to investigate the status of various companies’
initiatives relating to IoT technologies and Industry
4.0. Both in Japan and abroad, there are more and morecases of IT companies approaching the “edge layer”(equipment/factory side) and multiple manufacturers must
liaise with one another.

3. 1 Manufacturer Trends
Industry-leader, Siemens AG, was emphasizing that
now is not the time to contemplate the concept of Industry
4.0, but rather to realize it. As such, there is growing
awareness of practical application in actual production
sites.

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There is an impression that major IT companies havebegun approaching areas closer to the edge layer, however
this cannot be achieved by one company in isolation,
therefore the mainstream approach is to form consortiums
comprising platform providers and platform users(Fig. 4).
This is the case not only in Europe, but also in Japan,
where there is much activity surrounding the FIELD
System by Fanuc Corporation, and Edgecross, which
was established by six companies including Mitsubishi
Electric and Omron (Fig. 5).
Fig. 5 Cooperative companies 2

3. 2 IoT & AI
Regarding IoT, the term itself was less visible, possibly
due to the spread of the concept, and there was an AIcentered shift towards robot advancements and unmanned
operation. There were many robots on display at the2018 Hannover Messe overall, giving the impression of a
weakened focus on people. Advancements are being madein the AI-controlled 2-arm robot (Fig. 6) and table tennis
robot, with the mainstream theme of exhibits being cobots
able to work together with humans on manufacturing
shop floors.

Back

Right
arm

Left
arm

Utilizes AI, etc. to control
two arms, just like a human,and perform detailed movements

Fig. 6 Two-arm robot

Fig. 4 Cooperative companies 1
World/regions

Internet/cloud services/platforms

Companies/
organizations

Core systems

Production
management
divisions

Factory management systems

Factories

Servers/internal platforms

Customers/
individuals

Management information
Accounting
Human resources
Customers
Production planning
Production progress
Loading results/Actual
versus forecast evaluation
Production efficiency
Operating rate/
Operational availability
Environment
Change points
Human capacity
Improvement

Personal computers/smartphones

Large-scale system
Built by major IT manufacturers⇒Promote cooperation with monozukuri sites

Cooperation rather than competition

Delay in digitization of shop floor in most companies
・Intuitive-based work/craftsmanship
・Delay in the transfer of skills/shortage of successors⇒Areas where coordinators are required/areas
which coordinators aim forHigh efficiency/professional development throughthe promotion of digitalization and utilization of data
⇒To improvement-proposal type businesses
Spread of smartphones/mobile phone
manufacturers surround digital information

Fig. 7 Positioning of factories

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4. Activities of Service Providers/Service
Users and JTEKT

5. IoE Initiatives and the Technologies
ThereofThe trends discussed in Section 3 are also the casewithin Japan, and many companies from across the
spectrum are already engaging in initiatives to realize
the digitalization proposed by Industry 4.0 and IIC. On
one end of the spectrum, major IT and NC manufacturers
are injecting cloud services and platforms, and adding toareas up to deployment to the edge layer.
On the other hand, digitalization in the edge layer isbehind overall. Production shop floors seek more realistic
results and do not recklessly promote digitalization,
therefore often take a “wait-and-see” stance. Cases havebeen emerging whereby major manufacturers first collectdata then proceed with initiatives while performing
learning and analyses, however small-and-medium
manufacturers are unable to allocate dedicated personnel
to such a task, therefore no progress is made.
On the factory side, there is a lack of a function tocoordinate digitalization and it is up to line builders suchas JTEKT to gather strength.
From our position of providing equipment and systems,
JTEKT is engaging in an ongoing activity to digitalize
production information in factories and gather use cases
in which production has been improved as a result inorder to not only create equipment and systems, but also
added value for JTEKT. The key phrase of this initiative
is “smart factories in which people play a leading role.”
Factories must address the urgent issues of dealing
with a declining working population and passing oncraftsmanship. While handling these issues, JTEKT is
helping form a vision for the higher efficiency of factories
and the people who work in them.

5. 1 Smartification of Machines

Machined portions

5. 1. 1 Symptom Management
Emphasis is placed on the management of equipment
condition and planned maintenance in order to prevent
production stoppages due to sudden breakdowns.
Seasoned veterans are able to sense problems inequipment from subtle sounds, vibrations, machining
results and so on, however it is not possible to incorporate
human judgment such as this in more automatedproduction lines, therefore sudden breakdowns do occur.
Moreover, there is a rapid decrease in the number ofseasoned workers able to sense problems in equipment.
If equipment behavior is digitalized using sensors,
etc. and equipment is able to learn combining equipment
behavior, breakdown information and machining
quality information, it is possible to establish symptom
management not reliant on human senses. JTEKT’s IoE
initiatives have also resulted in acquiring knowledge
leading to preventive maintenance through analysis.
Below are some examples of these.
①Detection of grinding chatter symptoms (Fig. 8)②Detection of grinding seizure symptoms (Fig. 9)③Detection of spindle bearing abnormalities (Fig. 10)④Prediction of drill/end mill tool life (Fig. 11)[Detection 1] Clustering of wheel spindle power
Cluster no.

− Camshaft grinding −Manufacturers are aiming to develop production
equipment with more advanced autonomy, or in otherwords, “smartification.” In reality, up until now, themaintenance of equipment operability, assurance ofmachining accuracy and quality have been achieved at ahigh standard due to human skill. However, we envisiona future where these things will be achieved at a highstandard by equipment becoming autonomous throughutilization of IoE, etc.

Detects abnormal data

Machining
count[Detection 2] FFT analysis of wheel spindle vibration
Threshold
Fail waveform
Grinding chatter
Forecast logic

Pass waveform
Warning is displayed when there is a high possibility of chattering occurrence

Fig. 8 Chattering judgment for camshaft grinding

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Machined Based on the threshold value of the wheel spindle power
portions
Detection
16 cases detected, of which 6 were grinding seizure・Judgment accuracy: 38%＊
Detects all grinding seizure
Considers impact of other measurement values[New judgment method] Add the timing of when the symptom appeared to the judgment
NormalImproved detection accuracy
7 cases detected, of which 6 were grinding seizure・Judgment accuracy: 85%＊
Detects all grinding seizure

Visualization ofgrinding seizure
Detection

Fig. 9 Seizure judgment for end-face grinding
Cannot judge based on stand-alone datasuch as spindle power and temperature

Isolate symptoms by combining multiple data
Front side

Rear side

Visualization of failure symptoms

Fig. 10 Symptoms of main spindle bearing failure
Tip wears

Tool life

Time in use, minutes

Time in use, minutes<Comparison data> <Learning data>

・On high-mix machining lines, the same toolmachines parts of different material, therefore
tool life varies.
・The appropriate timing for tool replacement
cannot be predicted from conventional tool
operating time.

?
?

?

?

Aluminum
Carbon steel
Tool steel
Stainless steel
Rolled steel

Learns patterns and gives tool replacement
instructions with greater accuracy
・Learns patterns of material differences
・Recognizes which patterns are similar before
machining and predicts life from similar
patternFig. 11 Forecast of tool life for drills/end mills

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5. 1. 2 JTEKT Smart Cutting

5. 1. 3 Real-time Thermal Displacement Correction

In the cutting process, selection of machining
conditions is an important point in order to achieve ahigh-quality machined surface free of chatter marks.
To date, operators would observe the conditions of themachine, repeatedly carry out trial machining based on
their experience and, ultimately, settle on machining
conditions.
However, such an approach requires a great deal of
preparation time, and some ambiguity remains regardingwhether or not the machining conditions are optimal, withregards to productivity as well. The JTEKT Smart Cutting
function featured on JTEKT’s machining centers digitallypresent the optimal machining conditions for stableaccuracy by easily acquiring vibration characteristics ofthe spindle system, including tools, and analyzing data inline with machining phenomena.

The thermal displacement of machine tools has been alongstanding issue in mechanical machining. Temperaturechanges in the equipment’s environment and heatgenerated by the machine itself causes the machine todistort overall, and deteriorates machining accuracy. As
such, we measured the machine body’s temperature using
multiple sensors embedded in the machine, analyzed heatdistortion in real-time and enabled the calculation of thesuitable correction amount.
In JTEKT’s thermal displacement analysis logic, theFEM analysis method which conventionally required
several hours to complete can be performed in mere
seconds, thus allowing correction to be carried out inreal-time during machining. This is a technology thatis pioneering IoE activities by digitally connecting
equipment information and machining quality.
Optimal machining conditions

Analysis
Profile error/
surface roughness indicator

Hammering & measurement/analysis

Roughness indicator (chattering)

0

3 000

Easily incorporates vibration
characteristics of tools/spindle
system and executes optimization
analysis on the machine

4 000

Profile error
5 000 6 000 7 000 8 000
Spindle RPM, min−1

9 000 10 000

Instantly calculates the optimal machining conditions(spindle RPM) for chatter-free, high accuracy cutting
Determine good partconditions in 90%
less time than theconventional method
Machined surface where Good machinedchattering has occurredsurface

Spindle displacement sensor

Real-time analysis
of complex thermal
distortion using
FEM analysis logic

InterfaceTemperature sensor

Fig. 12 JTEKT smart cutting

Optical scale

Real-time position control

Thermal displacement correction effect (XYZ direction machining error)
Machining error rate

1
1.0

0.75

0.8
0.6

12% reduction

0.4
0.2
0.0

90% reduction

87% reduction

Without
correction■Actual machining example when

0.10
0.09

0.08

0.13

X axis

Y axisZ axisroom temperature change is 20℃
Thermal displacement improvedby 87% through correction

With correction

Fig. 13 Real-time thermal displacement correction

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5. 2 Visualization of Production
I n o r d e r t o i m p r ove p r o d u c t iv i t y, J T E K T i s
promoting an initiative to vitalize production shop floor
improvements through visualization of actual vs. forecast
production results in relation to the production plan. To
date, automotive production lines, etc. have used theandon system, whereby indicators such as production
quantity, equipment operating rate and abnormal
stoppages are displayed in real-time on andons so thatsupervisors can immediately take the necessary response.
The andon system is advancing while establishing
the necessary visualization requirements in line withadvancements in TPS.
As part of our IoE initiatives, JTEKT is rolling out
TOYOPUC-Hawkeye as a universal andon systemthat enables operational status for not only automotive
production lines but also the general-purpose machinesof FMCs (flexible manufacturing cells), and multiple
equipment.
To give an example, one or two operators are in chargeof eight machining centers, however each machine
performs high-mix, small-volume machining, therefore
machining time varies. The operators load the next
workpiece into the loading station in line with machining
progress and operate eight machines, however in reality
there is wait time as the operators travel back and fortheach time machining ends.
Here, we introduced TOYOPUC-Hawkeye for thevisualization of remaining machining time, the partnumber of the next workpiece required, and the loading
status. The process was improved so that operators could
make preparations prior to the end of machining, thus

Fig. 14 TOYOPUC-Hawkeye

greatly improving productivity.
Moreover, as a simple method of achieving visualizationof equipment operational status, JTEKT released JTEKTSignalHop, a solution that reads and records the color of
status indicator lamps. The respective colors of a statusindicator lamp already have set meanings, such as “inoperation,” “stopped,” and “fault,” therefore visualizationof equipment operational status can be easily achieved bysimply recording these colors (Fig. 14).
JTEKT-SignalHop performs communication wirelessly,
and can be mounted with tape. The power source is abuilt-in battery, therefore electric wires are not required.
The transmitter attached to the top of the status indicator
lamp transmits illumination information to receivers fixedin an arbitrary position inside the factory, which is thenrecorded. One receiver can support up to 50 transmitters(Fig. 15).
The collected illumination information is used tolist up machine operational information such as which
equipment has performed what amount of machining,

Sensor portion

Wireless
portion

JTEKT-SignalHoptransmitter

JTEKT-SignalHop
receiver1 receiver supports up
to 50 transmitters
Only transmitters can beadditionally purchased

Customer PC＊1

Easy setting of illumination conditions
together with customer equipment

Visualization of the operational
status for up to 50 units

Chronological visualization ofequipment operational status

Fig. 15 JTEKT-SignalHop

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which equipment is stopped, and whether or not there
were any faults. As such, in the same way as TOYOPUCHawkeye, JTEKT-SignalHop enables production status tobe easily ascertained so that areas for improvement can be
narrowed down. Customers who have actually introduced
these products to their lines are benefiting by utilizing
information through creating their own original screens,etc. and leveraging information to improve time wastage.

6. Conclusion
JTEKT is already facing the issues of a declining
working population, shortage of skilled labor, and delayin the transfer of craftsmanship.
While a significant part of the territory relies on
advancements in IT technology and digitalization, it is
JTEKT’s major mission in our role as a line builder to dowhat we can to transform the monozukuri shop floor.
Currently, for our IoE initiative, we are pushingahead with visualization and digitalization of production
status both internally and externally and contributing to
improvements in production and quality while trying toestablish it as a business, however we believe we still havea long way to go insofar as accumulating use cases on the
shop floor. If each of our activities can be converted into
solutions solving our customers’ true problems than they
will surely become essential to monozukuri in the future,so JTEKT will keep firmly focused on this task andcontinue exerting effort in this area.
*1 TOYOPUC-Hawkeye and JTEKT-SignalHop areregistered trademarks of JTEKT Corporation.
*2 FIELD System is a registered trademark of FANUC
Corporation.
*3 Edgecross is a registered trademark of Mitsubishi
Electric Corporation.

References
1)

S. TAKETO: SMART･FACTORY−SENRYAKUTEKI“KOJO MANEJIMENTO” NO SHOHOSEN, EIJI
PRESS (2010) (in Japanese).

Y. YAMAGUCHI**

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Line Control Engineering Dept., Machine Tools &Mechatronics Operations Headquarters

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