The dyeing process in the textile industry is a business that is highly dependent on the hidden know-how of workers in a harsh environment and is a difficult environment to integrate with information communication technology. Accordingly, the Korean government has established an innovation strategy to raise the world's best level of global competitiveness by applying smart manufacturing innovation to the textile industry. The smart manufacturing innovation solution of the dyeing industry applies global remote monitoring in real time, manufacturing execution, quality prediction, predictive maintenance, and digital twin technology through the integration of production resource data(4M1E:Man, Machine, Material, Method, Energy) in real time based on international standards to increase productivity through convergence between physical and cyber systems brings more than 15% improvement is expected.

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2020-04-20 1
Moving from traditional
to smart factory
Suk Keun Cha
(sk_cha@acs.co.kr)
Cofounder/CTO
ACS Corp.
5 May, 2020

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Who is ACS..
DABOM® means “See all in Factory”‘, ACS Trademark
ACS has been successfully completed more than 1,500 project that started from KIA, Hyundai Motors for ALC
(Assembly Line Control) and POSCO for real time monitoring of production management and slab yard automation
project since its established in 1988 . ACS solution has been certified NeT, NeP, Industrial Excellent Software, Good
Software from Korea Government under multiple patents and local and international R&D project.

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Agenda
1. Manufacturing environment changes
2. Smart factory in Korea
3. Smart factory project for Dyeing process in Textile industry
4. Future factory model

4. 4
1. Manufacturing environment changes

5. 5
1. Manufacturing environment changes
But the reality is …

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1. Manufacturing environment changes
Manufacturing companies must change to survive …

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2. Smart factory for dyeing process in Textile
Industry
New emerging information technologies such as IIoT and 5G
are evolving the architecture of manufacturing systems.

8. 8
1. Manufacturing environment changes
How it works …

9. 9
1. Manufacturing environment changes
Highly recommendation for right way to go to smart factory
IEC 62264/ISO22400
(MES/KPI)
ISO20140
(Energy)
ISO/AWI23247
(Digital Twin)
TTAK.KO-11.0227
(4M1E data integration)
NIST SMRM RAMI 4.0
IoT, AI, Big Data

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1. Manufacturing environment changes
Cloud services
VietnamChina
VPN/Intranet
DABOM-Gateway
(Edge computing)
DABOM-Gateway
(Edge computing)
DABOM-Gateway
(Edge computing)
XMLXMLXML
Database
WBT
Machine PLC
IoT WBT
Machine PLC
IoT WBT
Machine PLC
IoT
DABOM-MW
Myanmar
DABOM-MW DABOM-MW DABOM-MW
Digital Twin support
Cyber Physical System provides on-line against with COVID-19

11. For Large, medium, and
small businesses Based
on Connected
Enterprise
· Collect all data from manufacturing companies
Build a data center-based cloud big data DNA platform
that can be stored and analyzed
· HPC-based DNA platform to develop new technologies
and new products by challenging from Fast Follower
of the 3rd IR to First Mover of the 4th IR
G4 in Global Mfg.
To achieve

12. 226
791 1,122
1,844
2,384
3,336 3,640 3,900 3,900 3,500
4,000
4,500
44
141
416
354
475
1,540
1,680
1,800 1,800
1,750
2,000
2,250
7
31
22
5
41
257
280
300 300 1,400
1,600
1,800
0
0
0
0
0
-
-
- -
350
400
450
-
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
14년 15년 16년 17년 18년 19년 20년 21년 22년 23년 24년 25년
Lv 1 ~ 2 Lv 3 Lv 4 Lv 5
Level1
Ready
Sensing,
Automation
IIoT
Level2
Automation
MES,ERP
PoP, DAQ,
Robot, AGV
Level3
Optimization
Cloud/Edge
IIoT, AR/VR,
3D Printer,5G
Level4
AI Brain
AI, Big Data
Blockchain
Level5
Autonomous
CPS,
Connected
Enterprise
Cloud
Computing
Done Plan Prediction

14. Mfg. 1 Mfg. 2 Mfg. 3 Mfg. 4 Mfg. 5 Mfg. 6 Mfg. 7 Mfg. 8
Mfg. 9 Mfg.
10
Mfg.11 Mfg.12 Mfg.13 Mfg.14 Mfg.15 Mfg.16 Mfg.17 Mfg.18 MFg.19
Mfg.20 Mfg.21 Mfg.22 Mfg.23 Mfg.24 Mfg.25 Mfg.26 Mfg.27 Mfg.28 Mfg.200
Cloud data
center
Pilot Project
HPC based
cloud
Data center
expansion

15. Textile DB
AI Datalake
EE DB Root DB Metal DB
Food DB
Chemicl
DB
Fab DB
Ass’y
DB
제조 AI Cloud
In small and medium-sized enterprises, the value of data utilization increases, it becomes a vitality of manufacturing competitiveness,
and a high-performance computer (HPC) infrastructure required for modeling and virtual production is used to develop new products
and new technologies, and AI solutions are introduced and developed.
Big corporations will build public & private clouds exclusively for group companies, or global companies will create data value using
global public clouds, and SMEs will maximize economic cost by utilizing cloud data centers provided by the country.
POSCO, Samsung, Hyundai, LG etc.
Mfg. specific AI Cloud Data Center
7,500 SMEs
Group Co.
Global Mfg.

16. Manufacturing companies operating on the platform
IaaS
PaaS
Mfg.
Big
Database
MES ERP SCMPLM
Failure
Prediction
Process
Prediction
Quality
Prediction
Cost
Prediction
Pollution
Prediction
Energy loss
Prediction
Mgt.
Prediction
Market
Prediction
Market customer
Big
Database
SaaS
IIoT
Sensor
PLC
Device
M2M
Device
Edge Gateway
Connected to tens
of thousands of
SME smart factories
IIoT
Sensor
PLC
Device
M2M
Device
Edge Gateway
IIoT
Sensor
PLC
Device
M2M
Device
Edge Gateway

17. Robot
CNC
Mold
Dyeing
Robot equipment failure, part life
prediction Robot operation and
error rate prediction
Predicting CNC failure and part life
Predicting CNC machining
accuracy and quality
Predict injection failure, part
life, injection productivity,
defect rate, quality prediction
Dyeing equipment failure, part
life prediction Dyeing
equipment productivity, defect
rate, quality prediction
Productivity
Quality
Cost
Delivery
AAS
AAS
AAS
AAS
Big
Data
R
O
I
Data
Generation
Data
Collection
Data Store Data Analytic and Data value creation
Big
Data
Big
Data
Big
Data
Manufacturing companies operating on the platform

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3. Smart factory for dyeing process in Textile Industry
https://www.youtube.com/watch?v=eaM5WcPlHMM
Duration: 2019. 07 ~ 2021. 12 (2.5 years)
R&D Budget: 70Million USD
9 Organizations R&D Consortium

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3. Smart factory for dyeing process in Textile Industry
Smart factory status of textile dyeing factories in Korea
SF Level 5
SF Level 3
SF Level 1
SMEs
Company
Scale
Most of Dyeing
Mfg in Korea
Hyundai
Samsung
SF Level 1 SF Level 3 SF Level 5
SF
Level
SF Level 2.3
Large
Less than 50 employees in dyeing companies-mostly ICT not applied(Level 0)
More than 50 ~ 200 employees of dyeing companies- Level 1
ACS-DABOM® have been successfully deployed Global Dyeing, Hansol Textile Co. Vietnam 2 years from
smart factory level 1 to 2.3

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3. Smart factory for dyeing process in Textile Industry
Use case in Global Dyeing Co. Vietnam in Hansol Textile
Global manufacturing bases in Vietnam, Cambodia, Indonesia, Guatemala, and Nicaragua produce more than 37
million pieces of clothing per month and operate 3 million kg of fabrics per month in Vietnam, Global Dyeing and
Global Hantex. Increased sales by 200 times over the past 20 years [Global No. 4 Company]

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3. Smart factory for dyeing process in Textile Industry
Manufacturing IT system configuration
4M1E Real Time data integration
MES
Actual
Process history
Process
Monitoring
Shipping
LOT tracks
WIP
Material In
Equipment
Monitoring
Equipment
Status
Equipment
History
Prevent
Maintenance
Process Management
Maintenance ManagementQuality(SPC, SQC)
히스토그램, X-BAR R 관리도, 정규분포도,
공정능력관리, 공정조건이력, 변경점 관리.
수입, 공정, 출하검사
Production
plan
Work order
Production Management
Outsourcing
management
Outsourcing
Work Order
Outsourcing
performance
management
Other IT
ERP)
Lab. Management
Receipt historyReceipt entry
Warehouse
management
Outgoing
Receipt
Legacy System
Outsourcing
payment
management
Outsourcing
payment
management
Inventory
KPI
Quality
Monitoring
Time and attendance
management
Time and
attendance
[WIP & Raw Material]
 PDA(Incoming/outgoing
(RFID)
Tender Lab, TestDyeing Others Manual
[Main Factory/Plant 1/Plant 2]
 Equipment (Dyeing/Tender/Tester/Manual)
[Product shipping]
 PDA

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3. Smart factory for dyeing process in Textile Industry
Production Resources 4M1E integration
Client
PC
- Real time monitorug
Dyeing
M/C
TCP/IP
Digital
I/O
Tender
Dabom-Gateway
(#MAIN)
Dabom-Gateway
(MAIN/Factory #2)
Dabom-Gateway
(Factory #1 )
Agent
Protocol
Comm.
Manual Data
(20EA)
Dyeing
M/C
Digital
I/O
Tender
Agent
Manual Data
(7EA)
Digital
I/O
Tender
Manual Data
(26EA)
Digital
I/O
Tender
Manual Data
(7EA)
GD MES / Monitoring
MES
Protocol
Comm.
Protocol
Comm.
Protocol
Comm.

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3. Smart factory for dyeing process in Textile Industry
Vision and strategy of Made in Korea for G4
In the Korean government, textiles are used to raise the added value of the flagship industry to the world's highest
level. In the field of clothing, the production innovation smart pilot plant was selected and announced the
manufacturing vitality and innovation strategy in 2019.
Raise the added value of the flagship industry to the world's highest
level.
Change
Strategy
ICT ECO Innovation
Textile
White
24hrs order-
shipping
Fashion Eco
Super Textile
High functional
cloths
Smart Factory
for Dyeing and
sewing process
IoT Big data
center
Air White
Home care
White
Large-small
collaboration
model

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3. Smart factory for dyeing process in Textile Industry
Raw
material
incoming
Washing
Prepare
raw
material
Pre-
process
dyeing Fab.
Q.CShipping
MES
ERP/SCM/PLM
4M1E Data
Improvement of Quality in dyeing process
-Dyeing parameter control in real time
· Dyeing ending, Point of entry, Washing
2 set
(500,
1,000kg)
Real time control in fab process
- Fab parameter control in real time
2 set
3D Visualization-Digital twin
Quality prediction – Industrial AI
Quality >15%
OEE > 15%
Productivity >15%
Industrial Big Data application
International Standard
World
First
case
Scope of R&D and goal
4M1E data integration – IIoT & Edge computing
Real time
Data
Integration
Goal for performance

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3. Smart factory for dyeing process in Textile Industry
<Dyeing work data>
-Temperature
- Pressure
- Nozzle pressure
-Material speed
-Energy(Power, steam)
-Run/no Run data
← Absorbent ratio data
Dyeing end
point
Alkyl entry
point
Washing
end point
pH measure
Real time data
for
Dyeing process
Alkyl entry data
Dyeing end
Real time data
for
Washing start
Washing end
Real time pH
Super density control for dyeing machines Dyeing process control
Dying Machines
IIoT in Dyeing machine
(Edge computing)
IIoT into Dyeing Machine with edge computing
← Adding new sensors

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3. Smart factory for dyeing process in Textile Industry
Humidity control
Density, Overfeed, Stripping control
1 Optimal heat, temp. control2 3
IIoT into Tenders with edge computing

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3. Smart factory for dyeing process in Textile Industry
HD Camera HD Camera
Autonomous Configuration
https://www.youtube.com/watch?v=HuBQs-QUg78
Power
line
Current
Transducer
Run/No Run,
count
Run/No Run,
count
Current
Transducer Count, usages, work
type
Count, usages, work
type
Count, usages, work type
IIoT into Sewing machine with CT & HD Camera with Industrial AI

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3. Smart factory for dyeing process in Textile Industry
Various Robotics into textile industry for unmanned
Bobbin desorption process Yarn test / inspection process Fabric roll transfer process
Leather transfer processFabric roll transfer process

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4. Future factory focuses on

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4. Future Factory focuses on

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4. Future Factory focuses on
• Data attribute standardization: CDD (Common Data Dictionary) / eCl@ss
• Data utilization/operation standardization: AAS for Cyber Physical System (CPS)
• Data communication standardization: OPC-UA, Automation ML
System integration using OPC-UA
Device
(Asset)
AAS
IIoT
Product
(Asset)
AAS
IIoT
Asset Administration Shell
Asset
Definition
How to build Digital Twin
Based on AAS

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Thank you to listen!
More detailed: sk_cha@acs.co.kr