Building the Foundation for MES Services in the New Era

Technology
Explanation

Building the Foundation for MES Services in the New Era
YUBUKI Kento, GABRIELLA Anak Magin

Abstract
With the advancement of digital technology, the manufacturing industry is becoming increasingly digitalized.
Companies all over the world are using the Internet ofThings (IoT) to build “smart factories” where each device
in the factory is connected to the Internet to improve theefficiency of the manufacturing process.
Japan’s manufacturing industry has maintained quality
through improvement activities and worker training. For
this reason, there has been little progress in digitalization
efforts. However, in recent years, with the decline in theworking population and rapid changes in the international
market, production systems need to be more productive
and flexible than ever before. This is why MES, whichanalyzes data from manufacturing processes to improve
productivity and support workers, and SCADA, whichmonitors and automatically controls equipment data, areattracting attention.
1

Introduction

With the recent rapid advancement in digital technology, the world's manufacturing industry has changed significantly. Companies are actively introducing digitaltechnology to use the Internet of Things (IoT) Note 1) for
building "smart factories" Note 2) where all devices andequipment are connected with each other via the Internet.
Such a smart factory can collect and accumulate data fromits manufacturing process and analyze it using advanced
technologies including artificial intelligence (AI) Note 3).
This system can be expected to provide the following
effects:
・To identify any inefficient parts of the manufacturing
process and solve problems, achieving higher productivity, higher product quality, and lower cost・To create a database of techniques and expertise ofskilled technicians to allow for automation and transfer of their skills to younger technicians・To use the accumulated data to predict the demandand supply and plan predictive maintenanceHowever, Japan's manufacturing industry has been left
behind on digitalization. Japan's manufacturing (often
called "Monozukuri") has maintained quality throughKYB is also working on MES and SCADA, and has
several systems in operation to acquire and utilize datafrom production lines and equipment. In order to collect,
accumulate, analyze, and utilize data, an analysis platform
called “IoT Platform” has been developed in-house.
However, the systems that have been in operation for along time are not linked to the IoT Platform, so only
limited analysis can be done within the systems, and they
are not being fully utilized.
Therefore, in this development, we have developed a
new service that solves these problems by first linking the
IoT Platform to a single production data collection system.
This system utilizes IoT and cloud technologies to build
its functions. This paper describes the integration with the
IoT Platform and the functions we have developed toutilize data in the manufacturing process.

human efforts including (skilled technicians' improvement activities leveraging their skills and experience andworker training to enforce workplace discipline. Only a
few companies have heavily invested in digitalization
programs. Quality maintenance has mainly been assured
with human-based approaches relying on the expertise oftechnicians. In recent years, however, Japan has failed tosuccessfully deal with the decline in the working population with fewer children and aged adults as well as the
rapid changes in the international market, resulting inlower competitiveness. Owing to such situation, digitalization efforts are attracting attention in the Japanesemanufacturing industry as well.
Today, many systems to promote enterprise digitalization are available. Among them, the following three areconsidered significant in the manufacturing industry:・Enterprise Resource Planning (ERP)・Manufacturing Execution System (MES)・Supervisory Control And Data Acquisition (SCADA)
The ERP is the integrated management of main business processes. The ERP system centralizes managementof business resources including humans, things, money
and information. General systems to collect and control
information necessary for financial, customer, inventory―8―

KAYABA TECHNICAL REVIEW No. 64 APR. 2022

and human resource management are packed in an ERP
system to help companies make decisions.
The MES is used to identify, manage and support manufacturing processes. The system makes use of data on
production equipment, production control and productquality for improving productivity and quality and forsupporting workers. While the ERP system covers management of an entire enterprise, the MES can be said to bea management system tailored to its manufacturing
process. With this difference in mind, the MES can belinked to the higher-order ERP system to allow decision
making based on real-time data collected from the manufacturing process.
The SCADA system monitors and controls manufacturing processes. It monitors how production devices arebeing operated and measured and, if necessary, controls
them. While the MES analyzes and utilizes production
data, the SCADA system monitors what is happening in
the manufacturing process in real time. With this difference in mind, the SCADA system can be linked to thehigher-order MES to allow for management of the manufacturing process and its automatic control in case ofabnormality.
These three systems linked to each other will enable all
employees and management to get a whole grasp of datafrom upstream to downstream and to carry out various
activities based on the data, including decision making,improvement, and new business development.
KYB has also promoted efforts to manage and utilize
data collected from its production lines and devices froman earlier time. The typical systems of this kind include
the Point of Production Information Collection System(POPICS) and the line monitoring system (the details ofthese systems will be described in the following chapter).
These systems that collect and utilize operation data fromproduction lines and devices are considered to be positioned within the production system as shown in Fig. 1.
Our POPICS has certainly achieved data sharing among
the ERP, MES and SCADA regions, but only to a limited
extent. Our line monitoring system is being reviewed toprovide various functions for the SCADA region by introducing new technologies. However, its integration withhigher-order systems such as MES or ERP has not yet
been discussed, resulting in insufficient use of data fromthe manufacturing process.
We have built a foundation to provide new MES services (Fig. 1) using a SCADA collecting data from theline monitoring system linked to an MES that has been
designed to be able to have additional functions. The following describes the details of the foundation and its
related systems.

lected from the devices is analyzed and utilized in a
sophisticated manner to optimize the factory/production
management.
Note 3) An acronym for Artificial Intelligence.

MES services(newly developed)

Equipment

Scheme of systems for MES services (KYB's effort)

Fig. 1

2

Line monitoring system(Data collection
in businesses)

Current Systems in KYB

2.1 POPICS (Fig. 2)
KYB developed and introduced a production line datacollection system called POPICS 20 or more years ago 1).
Via panel computers installed on the production lines,
POPICS transfers production instructions and other datafrom higher-order systems, collects cycle time data using
device I/O, and collects nonconformance reports by
operators and other data from lower-order systems.
POPICS summarizes collected data into KPIs Note 4) such as
productivity and presents them to manager-class personnel using a visualization application program.
Part of POPICS has already been linked to higher-ordersystems so that POPICS data can also be viewed on thesystems that manage cost data and inventory control
information.
A problem is that POPICS only collects data in production lines. Collected data for each line is not sufficient todevelop measures against device failures or conduct
improvement activities, failing to satisfy user needs.

Note 1) An acronym for Internet of Things. The IoT refers togeneral attempts to connect things to the Internet andutilize them.
Note 2) A factory where devices therein are connected with eachother via the Internet to improve the manufacturing
process and enhance the operation efficiency. Data col-―9―Note 4) An acronym for Key Performance Indicator. This major
performance evaluation indicator is intended to evaluateachievements against goals.

Fig. 2

Example of POPICS window (sample data shown)Building the Foundation for MES Services in the New Era

2.2 Line Monitoring System
KYB is promoting Innovative Monozukuri mainly on
the production lines in its factories for manufacturing
shock absorbers, which are one of the company's key
products. This activity aggressively makes use of AI andIoT technologies to recreate a manufacturing system fromdesign to production, with the aim to achieve the following goals:① To double productivity② To halve design-to-production lead time
③ To achieve zero nonconformance
Then, KYB introduced IoT technology to the production lines and developed a new line monitoring system forvisualizing the manufacturing process in an easy-tounderstand way to ensure higher productivity and higher
quality. This system was developed in 2017 as an improved
version of the POPICS described in the previous section
and has been sequentially introduced to KYB facilities.
While the conventional POPICS can only collect data inproduction lines, the new line monitoring system cancollect data in production devices, thereby enabling realtime monitoring of individual devices.
In this line monitoring system, PLCs Note 5) for individual
devices collect operation data, which will be put together
by a general PLC installed on each line and stored in a
database (DB) built on a line server. Furthermore, a visualization software program running on the line server
displays data on a large-sized monitor in an easy-tounderstand way (see section 4.3 for the system configuration).
The monitor displays data as shown in Fig. 3. Production information including KPIs and the operating statusof each device, quality information including measurements, and processing condition information can beviewed on the screen. Note 6) Personnel can easily view
these types of information in real time to identify any
anomaly in each device and take appropriate measures.
However, the current line monitoring system cannot
provide line comparison or long-time data analysis,
posing a challenge of diversified analysis to be available.

Fig. 3

Example of display on the line monitor screen(sample data shown)

Note 5) An acronym for Programmable Logic Controller. This
control device developed as an alternate to a relay circuit
is often used to control production devices.
Note 6) The information includes undisclosed information thathas been intentionally deleted or blurred.

2.3 KYB-IoT Platform (Fig. 4)
In order to analyze and utilize all in-house data, KYB
internally developed a data analysis base called KYB-IoT
Platform Note 7) in 2020. The Platform was developed under
the concept that "anyone can easily analyze and use data
anywhere anytime". Storage of collected data as well as
data analysis and use with AI or BI Note 8) can be started
easily and quickly.
The KYB-IoT Platform has been built on the public
cloud Amazon Web Service (AWS) where the storage andprocessing capability can be scaled up/down depending
on data volume and throughput. The cloud-based platform
can be used anywhere and can easily be deployed throughout the world. Leveraging the abundant cloud services
available on the AWS will efficiently develop new services and provide additional functions.
One of the systems operating on the KYB-IoT platform
is the equipment predictive maintenance system. 2) Thissystem collects data for identifying the equipment status
such as vibration and temperature and then analyze it withAI, thereby enabling prediction of failure signs. The
results are visualized with BI tools to be available to thedepartment users belong to, implementing predictive
maintenance.
In this case example, saving, AI analysis and visualization with BI tools of collected data are all implemented on
the KYB-IoT Platform. Beside these, the platform implements the function that issues an alarm when a failure
exceeds a threshold level and has an improved visualization monitor. The KYB-IoT Platform has thus been addedwith new functions and has been improved as necessary.
Note 7) A system base to collect, visualize, analyze and control
large volume of data from IoT devices connected to the
network.
Note 8) An acronym for Business Intelligence. It refers to collecting, accumulating and analyzing data to support
decision making on enterprise activities.

2.4 Problems with the Current Internal Systems
KYB has different systems shown in Fig. 5. However, itcannot be said that these systems are properly interfaced
to each other so as to optimize the company's total operation. If these systems could share and exchange data, wewould be able to identify more clearly what the company
is actually doing or what we have not noticed so far. The
company should leverage the potential of the systems.
Some production systems have been developed anddeployed recently, including the line monitoring systemdescribed in section 2.2 and the KYB-IoT Platform
described in section 2.3. Unfortunately, these systems
have not been linked to each other, failing to use data
effectively.
― 10 ―KAYABA TECHNICAL REVIEW No. 64 APR. 2022

Collect

Analyze/Visualize

Accumulate

Production info.

Management

Employees

Design info.

Developers

Edge computing

Equipment info.

Products

Users
Process

Automobile

Customers

ManageAgitating truck

Partners
Construction
machineryFig. 4

Cost management system

Overview of IoT Platform

what format, such as the standard data set including "CT
Note 9), MT Note 10) and anomaly time".
In this development, we have built a foundation of a
total system to centralize manufacturing process data in
the KYB-IoT Platform and to link the platform to othersystems. The following sections explain it in detail.

Design management system

No system linkage establishedTypical combinations of linked systems[Design, Cost and Production]

Production
management
system・ To calculate costs and simulate
production using designed CAD
data・ To automatically create process
charts, part list and production
schedules[Production and Quality]

Note 9) An acronym for Cycle Time. It refers to the operation
cycle time from when a task is completed to when a next
task is completed.
Note 10) An acronym for Machine Time. It refers to the machining time of machine tools.

Procurement
management
system・ To strengthen product traceability

3
Maintenance information system

Fig. 5

Quality management system

Current internal systems

In addition to the line monitoring system, the company
has also discussed or developed other data collection
systems to be deployed in internal source locations. Still,these systems have been designed to display and store
data in different ways because they use their own data
formats. This is one of the reasons why the systems canhardly share data.
To overcome these challenges, KYB is discussing tocentralize data in the KYB-IoT Platform. In addition, tosolve the problem that several data collection systems
gather different data items from internal source locations,
it is necessary to decide what data is to be collected in

Requirements

The following shows the requirements for ensuring thatthe total system is operated properly for effective use of
production data:① To standardize data items to be collected so that collected data can be saved in the KYB-IoT Platform② To ensure that all necessary data items are collected
and accumulated in the KYB-IoT Platform③ To enable data analysis in devices and long-time data
analysis④
To link the KYB-IoT Platform to other internal
systems to share design and cost information⑤ To build a total universal system for global use⑥ To ensure that horizontal deployment of and function
addition to the system can easily be done

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Building the Foundation for MES Services in the New Era

4

Development of MES Services

4.1 System Overview
This development has the purpose of building a total
system linking the aforementioned KYB-IoT Platform to
the line monitoring system for analyzing and utilizing
manufacturing process data. The development is underway with another future goal of achieving company-wideand even global deployment of the total system.
Fig. 6 illustrates how the total system is configured. Theline monitoring system collects data from individual
devices and save the data in a predetermined format. All
the collected data is saved in the KYB-IoT Platform forcentralized control of company-wide production data.
Once saved, the data will be immediately visualized to beavailable for analysis.
The KYB-IoT Platform can easily be linked to othersystems because of its collective data management andcan also provide diversified analysis using data from othersystems.
This development roughly covers the following four
major tasks. The details will be explained in the following
sections:・To standardize data to be collected and data format
・To determine how to collect/transfer data・To determine how to save data・To determine how to display and analyze data
4.2 Standardizing Data to Be Collected and Data
FormatWe have standardized data to be collected to ensure thatdata collection systems at various source locations canwrite common data items to the KYB-IoT Platform in thesame data format. This makes it possible to utilize data for
analysis with a unified set of indicators. We have selected
important data items needed by all locations to carry out
improvement activities. These data items can be categorized by data collection timing and data content into fourgroups shown in Table 1. We have specified a data format
for each data group, achieving standardization of data collection.
The first data group is production results (including
actual CT & MT and setup change time) to be stored in the
KYB-IoT Platform. With these types of data available, theuser can find possible causes of lower production while
viewing CT/MT, setup change time and availability dataon the screen.
The second data group is equipment alarm (including
alarm date and time, alarm type and downtime) to be
stored in the KYB-IoT Platform. With these types of data
available, the user can narrow down equipment alarms tobe handled in higher priority and check the equipment
alarm log.
The third one is jig and tool change data (including date
and time of change and the remaining number of times ofuse) to be stored in the KYB-IoT Platform. With thesetypes of data available, user can identify what caused thejigs and tools to be changed.
The fourth one is measurement data (including measurement values and items) to be stored in the KYB-IoT
Platform. With these types of data available, the user canmanage the daily data trend using control charts and findpossible causes of an anomaly in connection with thealarm information. In addition, some devices may measureand save multiple measurement items at the same time.
The style of tables accepting data in this case has beenstandardized to "vertical" Note 11), thereby enabling the user
to easily switch over devices and measurement items or to
analyze data more conveniently.
On the other hand, some source locations may collectdata in a data format other than that stated above in somecases. Then, we, in this development, have decided tosave data collected from individual source locations in acommon file format. In the format, first comes the identification information including production line, production
device, date and time of data collection, and type of datacollected. This general information is followed by sourcespecific data. Although data items to be collected and thenumber of data items vary by target device or object, theKYB-IoT Platform identifies data and executes subsequent processing (including pretreatment and DB storage).
Note 11) A kind of data table structure. It refers to a type of tables
where data is added in the longitudinal (line) direction.

Table 1
Data group
Production

Data to be collected
Data to be collected
・Actual CT
・Actual MT・Setup change time

Equipment alarm

・Date and time of alarm・Type of alarm・Downtime

Jig change

・Date and time of change・Remaining number oftimes of use after change

Measurement data

・Measurement item
・Measurement value

4.3 Data Collection/Transfer
This section explains the line monitoring system,
although several other data collection systems are being
discussed in various sites. It should be noted that any datacollection system could be linked to the KYB-IoT Platform even if the system does not have the same configuration as that of the line monitoring system.
The line monitoring system is generally configured asshown in the Data Collection region in Fig. 6. The line
monitoring system centralizes operation data held by theequipment PLCs to the general PLC and stores data in the
database (DB) built in each line server. By using a visualization software program running on each line server, thesystem displays data on a large monitor in real time. It
also transfers data from the general PLC to the KYB-IoT― 12 ―KAYABA TECHNICAL REVIEW No. 64 APR. 2022

Data Reading
Visualization
softwareData Accumulation

Data Collection
Dashboard Views
FTP server

General PLC

Visualize withvisualization
softwareLine server

Large monitor

Standardized data collection format
Users

Device PLC

Device PLC

Fig. 6

Device PLC

Data
Visualization
and Analysis

Configuration of MES services (overview)

Platform in the following two methods to store data in the
Platform (Fig. 6, ① and ②):① Directly write data from the general PLC into the DB
on the KYB-IoT Platform② Transfer file data in CSV or other format created in
the general PLC by using the file transfer protocol (FTP)
The method ① should be selected for structured data
Note 12)occurring infrequently (in several seconds) that will
be utilized frequently (i.e., accessed) after saved. Specifically, CT, MT and equipment alarms will be transferred inthis method and written into the DB on the Platform one
by one when the equipment cycle is completed or any
alarm is reset. It should be remembered that this method
can only be used with a PLC that supports data writing toa database. It is thus necessary to prepare in advance a
PLC supporting the data writing.
In method ②, the system saves data gathered by thegeneral PLC in a file format and transfers it to an internal
FTP server using the FTP before saving in the storage on
the KYB-IoT Platform. This method should be selected
for data that cannot be accepted by the DB, for example,
data that is generated in a large size per unit time such as

millisecond or non-structured data. Specifically, measurement data and equipment machining condition data
(current and temperature) will be recorded in the general
PLC as required at a certain sampling rate. Several data
sets will be put together to be saved in a file when a setupchange or a production session has been completed. Suchfiles will be periodically transferred using the FTP. In fact,
this type of data saved in files can be viewed at a lower
retrieval speed than that for the DB. Still, our understanding is that no significant problem with system operation
will arise because data utilization (access) has been
assumed to take place infrequently. This method has beenverified to be supported by a wide range of PLCs. How tostore data in these two methods will be described in detailin the following section.
Note 12) "To structure data" means to preliminarily define thetype and sequence of data items and arrange them in a
specified structure.

4.4 Data Storage
As described in the previous section, we have established two different ways of storing data (Fig. 6).
For method ① in Fig. 6, a database (DB) has been

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Building the Foundation for MES Services in the New Era

created on the KYB-IoT Platform (cloud) to store acquired
data. The DB uses an AWS fully managed Note 13) highperformance RDB Note 14) service called "Amazon Aurora"featuring high performance, high expandability, highsafety and high availability. Thanks to its high data reading
performance, Amazon Aurora allows user to quickly
retrieve data by linking multiple data sets using SQL. Note
15)

Method ② in Fig. 6 uses a cloud storage service called"Amazon S3" (hereinafter "S3") to store data saved by thegeneral PLC in files. This service features high durability,
high safety and high availability. Furthermore, S3 canoffer many other benefits including virtually infinite
storage capacity and lower cost than Amazon Aurora. One
disadvantage is that the data retrieval service for S3 is notdesigned to allow the user to easily retrieve data in anadvanced way, resulting in lower retrieval speed than for
RDB.
Furthermore, it costs more for S3 to store large amountsof data than for Aurora as shown in Table 2. The data
storage cost may be reduced by changing where to store
data depending on the data use frequency. It is vital toselect a better one from these two destinations with consideration given to frequency of data occurrence and frequency of data use.
Table 2shows how these screens are configured. All the screensshown in Fig. 7 are standard views for all the sites. A totalof 18 screens are available at this moment. Some of thesescreens cover two or more types of data to allow for diversified analysis. The screens are linked with each other sothat the user can view several screens to find more detailed
analysis screens for deeper analysis. This section will
explain some of these screens we have developed.
Note 18) This industry’s leading BI tool allows the user to easily
visualize and analyze data. KYB is also introducing
and deploying the tool.
Within each of the screens
enclosed with a title ended by theword "Analysis", the user canfreely navigate through sheets bypressing the tab key.
Production Results
CT/MT Analysis
Today’s CT/MT
CT variations
Analysis of manual process
CT histogram
MT variations
MT-error_distribution

Production
progressanalysis

MT-error_time-series
MT histogram

Comparison of data storage

Operation analysis
Set-up change log

AuroraS3

Set-up change analysis

Data volume

Low

High

Frequency of use

High

Low

GeneralProduction
ScreenEquipment Alarm

Storage cost Note 16)

0.12 USD/GB/month

0.025 USD/GB Note 17)(Top page)

Error analysis

Note 13) AWS undergoes server/operating system (OS) management and failure correction for users. Users can focus
on their use of service, leading to higher development
efficiency and lower operation cost.
Note 14) An acronym for Relational Data Base. An RDB
manages data in multiple tables and defines the relationships among the tables to be able to handle therelation among complex data sets.
Note 15) An acronym for Structured Query Language. SQL is aninternationally standardized database language used tooperate and control the RDB management software.
Note 16) The figure shows the price in Tokyo Region as ofDecember 21, 2021. The figure for Aurora only indicates the data storage cost.
Note 17) The price for S3 becomes lower in stages as the datacapacity becomes lower. The figures shown in the tableindicate the service fee for 50 TB/month.

4.5 Data Visualization and Analysis
We have developed a data display system using a BI
tool called Tableau Note 18) to visualize and analyze collected
data.
This visualization and analysis system reads data on the
KYB-IoT Platform. Once data is saved in the system, thedata immediately becomes available on the screens. Fig. 7

Today's error
Error results
Error log
Intensive error countermeasures

Jig Change Results
Jig Analysis
List of remaining number of times of jig changes

Event log
(appears
every hour on
top page)

Measurement Data
Quality Analysis
Control chart (under development)

Fig. 7

Linkage of visualization and analysis screens

4.5.1 General Production Screen (Top Page)
Fig. 8 shows the general production screen where theuser can view actual results of production. Views showing
CT, MT, setup change, availability, alarm and jig changes
for each device are tiled on the screen, enabling the user tonarrow down possible causes of any lower productivity
from various angles. Note 19) This screen displays how dailycompiled data changes day by day. The user can look at
the graphs on the screen to be able to easily identify any― 14 ―KAYABA TECHNICAL REVIEW No. 64 APR. 2022

data showing an anomaly (for example, longer CT or
more errors than the criteria). If this is the case, the user
can move on to another analysis screen linked to the top
page for deeper investigation.
Note 19) The information on the screen includes undisclosed
information that has been intentionally deleted or
blurred.

Error occurrences

Availability

Set-up change time

Jig change

Fig. 84.5.3 Alarm Screen for Intensive Measures
Fig. 10 shows the alarm screen for intensive measures
where the user can identify device alarms in the form of
Pareto charts. The Pareto charts are intended to show theoccurrences of device alarms (the left chart on the screen)
and their downtime (the right chart on the screen). If adevice has an alarm of frequent occurrence involving
short downtime, the device should have been frequently
stopped. If a device has an alarm of non-frequent occurrence involving long downtime, the device should havebeen troubled with major stoppages. As a general rule,focusing frequent alarms involving long downtime will
relatively easily improve productivity. First, it is good tonarrow down device alarms into those involving poor
productivity. Once this is done, you can now tackle
improvement activities including device adjustment andwork improvement.

General production screen (Top page)

4.5.2 CT Histogram Screen
Fig. 9 shows the CT histogram screen that displays the
CT results over a specified period of time in the form of atime-series two-dimensional histogram. The upper half ofthe screen provides the CT histogram over a specified
period with the X-axis showing CT bins in the unit of one
second and with the Y-axis showing the magnitude. The
lower half of the screen indicates how CT changes by
each day in light and dark in color. A dark colored cell
represents a high magnitude. The Y-axis shows the date inunits of one day (time elapses from top to bottom with the
top oldest and the bottom newest), representing daily CT
variations (distribution in a day). User can first identify
normal CT on the histogram over the entire period andthen check variations for each day to determine whether
any worse CT than the normal level is attributable to a
spontaneous or chronic cause. If spontaneous, it is advisable to narrow down possible causes on the screen statedin the previous section and take appropriate measures. For
chronic ones, it is effective to review the work andmachining programs and check any other chronic error.

CT histogram over a specified time

Daily histogram expressedin light and dark in color

Pareto chart of error countPareto chart of error timeError list

Fig. 10

Alarm screen for intensive measures

4.5.4 Screen Customization
The visualization screen system we have developed
provide standard screens for all sites. Only using thesestandard screens allows for basic data analysis, but somesites may have to carry out more detailed analysis. For
such sites, an environment is available for users to be able
to create their own necessary visualization screens using
Tableau. Once having created a visualization screen, theuser can easily share it with personnel from other departments via the Internet or easily download any screenscreated by personnel from other departments and thencustomize them so that they can easily use within theirown department.
The screen creation procedure (how to use Tableau) has
been designed so that users can build programs as they
like as a scheme of developing human capital Note 20) is
established to promote evolvement of this system.
Note 20) KYB uses the term "human capital", instead of "humanresources".

Fig. 9CT histogram screen― 15 ―

Building the Foundation for MES Services in the New Era

5

Future Prospects

Through this development, we have built the foundation of a system that utilizes manufacturing process data.
We are now improving the system and adding functions to
it based on user feedback on the lines whose data is savedon the KYB-IoT Platform. We are also promoting thelinkage between the system and other data collection
systems than the line monitoring system, thereby enabling
us to collect data from existing devices that have long
been operated and then to utilize the data.
From now on, we will further improve the system andadd functions to it while promoting its global deployment.
In promoting the global deployment, we are facing somechallenges. As the global deployment progresses, data
will be saved more frequently, which will require us toreview the processing capacity and the way of writing
data from data collection terminals. The visualization
screen system is also anticipated to have lower display
speed and lower operability as it handles more data. Thesepossible problems will have to be discussed as required.
We are also going to discuss establishing a linkage
between the system and other systems. The systems thathave already been put into service and have collected data
should be put together to collectively save their data on
the KYB-IoT Platform. For systems to be built and introduced in future, we will sequentially develop their linkage
mechanisms.
Our final goal is to establish a comprehensive scheme tocentrally control data sets from different functions of thecompany, closely link these data sets, and allow the user
to utilize the data as necessary and make decisions basedon the data. Through the scheme, we will aim at strengthening the engineering chain including strengthening theinter-functional connection and reducing the production
lead time as well as at strengthening the supply chain
including enhancing the product reliability and making
the production scheme flexible.

6

Concluding Remarks

Through this development, we have successfully established a scheme to utilize manufacturing process data.
MES can connect upstream systems and downstream
devices in promoting digitalization of manufacturingindustry. The function we have developed is part of the
MES in the production management system. With this inmind, we will continue promoting the system improvement and function addition and the linkage with othersystems, contributing to the higher productivity andhigher quality.
Finally, we would like to take this opportunity to sincerely thank all those concerned from internal related
functions who extended great support and cooperation tothis development project.

References
1) YAMAMOTO: Establishment of a Process Management
System, KYB Technical Review No. 14 (April 1997).
2) FURUKAWA, ISASHI: Development of an Equipment
Predictive Maintenance System, KYB Technical Review No. 63(October 2021).

Author YUBUKI Kento

GABURIELLA Anak Magin

Joined the company in 2016.
DX Dept., Engineering Div.
Engaged in development of analysis
screen systems using BI tools

Joined the company in 2015.
Group 2, Production Engineering
Sect. No. 2, SA Production
Engineering Dept., Automotive
Components Operations.
Engaged in production preparation― 16 ―