Dong Sub Kim
Dean & Head of Institute for 4th Industrial Revolution
UNIST, Korea

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ASEM-EMM Seoul Initiative on the 4th Industrial Revolution
ASEM-EMM (Asia-Europe, Economic Minister’s Meeting) Sept 21-22, 2017 Seoul Korea“Innovative Partnership for Inclusive Prosperity”
COMMON PRINCIPLESPOLICY RESPONSES– Sustainable growth throughinclusiveness– Diffusion of creativity and innovation– Collaboration based on openness– Fairness and transparency incompetition– Cooperation for an innovation-friendly
regulatory framework– Fostering favorable conditions for digitaltransformation– Capacity building for MSMEs– Facilitating R&D collaboration– Improving human capital and workplaces» MSME: Micro, small, medium enterprise2

Future of Production
Convergence of OT & IT+design
reprocessing

material extraction& processing
Sustainable
Societydisassembly

production

w/Renewable
Energyrecoveryservice

assembly& packaging

sales & distribution

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Economic Impact from Productivity Improvement could reach$1.5 Trillion USD ($1.2- 3.7T) but only captured $0.05T so far

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Table of Contents
1. Trilemma in Korea Manufacturing Industry

2. Initiatives of Transformation by Innovation in Korea- RoadMap- Use case (Light House)- Smart Manufacturing Level Assessment Tool

3. Transformation of Industrial Cities into Smart Industrial Cities
4. Concluding Remarks
6Manufacturing In Korea – Signs of crisis (Manufacturing product declines)

7Manufacturing in Korea – Signs of crisis (2)Average Operating Rate in Korea Manufacturing
Manufacturing Growth Rate (%)

8Transformation by Innovation
Tech Innovation

Business Model &ProductInnovation

Process Innovation• Smart Factory• Supply Industry

HR Innovation
GlobalCollaboration

Corporate Culture
Innovation

GlobalcompetitionQualitywork
Infra Innovation• Finance• Regulation9

Process Innovation

Zn Coating Optimization of Automotive Steel by Using AI Model

Molten Zinc
PotZn coating Line

Coating Thickness control

POSCO

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IOT/AI Machine Learning Based
Coating Weight Control System
Regression Model+ Manual

AI Based Model

Thickness measurement

Thickness measurement

On-line dataacquisition

Regression Model

Manual operation

Decrease accuracy when changing
Steel type and equipment typeAI machine learning +operator’s know-how

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[ Coating Weight Deviation ]

6.00

4.80

4.75

5.00

3.64

4.00
3.00
2.00
1.00

5.52

Conventional2.42

2.39

AI

1.53
0.12

0.10

0.21

0.17

0.15

0.14

0.26

ABCDEFG0.00

Reference: POSCO12UNIST developed Smart Manufacturing Level Assessment Tool
▣ 5 Phase Approach for Smartization of SME
Diagnosis

Product- Understand 4IR Concepts- Develop Smart Products- Diagnose & Build Strategy- Develop Smart Services

Strategy
Development

Process

BusinessModel

BusinessSuccess- Develop Global Eco-System- Build Smart Prod. System- Innovate Business Model- Become a Global leader

Smart Process
Development

Business Model
Innovation

Globalization

Smart Product &ServiceDevelopment▪ Manufacturing Innovation with the 4IR Concepts,
Training Material (O)▪ SME Development Program - Phase I (O)▪ Smart Product/Service Development Guide (~2017.12)▪ Digital Business Model Guide (~2017.12)▪ SME 4IR Business Strategy Guide▪ Smart Manufacturing Level (SML) and Strategy
Planning Module (O)13Smart Manufacturing Level Assessment Tool
▣ Common level of understanding, where & how to implement

Sustainable Society디지털 전략 (플랫폼 생태계)Areas디지털 비즈니스 모델 (새로운 가치)스마트 제품 및 서비스

Digital Strategy

Smart Product & Service

Smart Factory/Process Innovation

Digital Business Model

Product/Culture Innovation

Smart Manufacturing Platform
ProcedureStrategyManIoTDrivingForceMeasurementMachine
Big Data

Digitalization

Analysis

MaterialAI

VR, AR,MR

Retrospect

MethodDigitalTwin

Connectivity

Blockchain

Transformation

EnergyRobot

Environment

3DPrintingIntelligent
UNIST 4차 산업혁신연구소, 한국인더스트리4.0협회

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Smart Manufacturing Level Assessment Tool (Structure)▣ Scope of Assessment
Leadership
Service (Platform service – customer, partners, internal decision making)Customer/Eco-System
Smart Product/ Technology(Customer)(Management)

Reciept/Payment/Stocks

Partners/Purchasing

Production Process

Production management

Equipment Management

Quality Management

Supply/Logistics

SHE(Supplier)

Culture/Structure15

Smart Manufacturing Level Assessment Tool (Criteria)▣ 6 levels of Smart Manufacturing Readiness

Definition of SML
Level 5(value expansion)Level 4▪ 연결된 데이터 분석을 통한(Advanced)

Level 3수익성 및 지속성 확보▪ 플랫폼 생태계, 고객, 협력▪ 플랫폼 생태계의 리더(intermediate)

Level 2사, 기업 내부업무 및 생산▪ 디지털 비즈니스 모델 및

▪ 기업 내부의 모든 업무 영공정의 디지털화와 연결전략 활용(Basic)역에 확산 적용▪ 플랫폼 생태계 참여(제공)▪ 지속 성장 경영 가능

Level 1▪ 비전 및 목표 수립▪ 고객과 협력사에 연결 준비▪ 고객 맞춤형 스마트 제품▪ 스마트 제조 수준 80% 이(step of interest)▪ 단위 프로젝트 진행및 단위 프로젝트 진행및 서비스 제공상▪ 스마트 제조 수준▪ 스마트 제조 수준

40% ~ 60%

60% ~ 80%

Level 0▪ 경영자의 초기 관심▪ 확산을 위한 표준화(at Risk)▪ 구체적 목표 없음▪ 경영자 및 임직원의 적극적▪ 스마트 제조 수준인 참여▪ 관심 없음▪ 경영자 위주의 경영▪ 스마트 제조 수준 5% 미만

5% ~ 20%▪ 스마트 제조 수준
20% ~ 40%

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Smart Manufacturing Level Assessment Tool (Criteria - example)수준 구분

Level 0Smart Manufacturing
Leadership관심 없다.

Manufacturing
Automation Level

Level 1

Level 2

Level 3

Level 4

Level 5경영자 초기관심비전 및 목표 수립내부 업무 확산 적용고객 맞춤형 서비스연결 가치 최적화구체적인 목표 없다.

단위 프로젝트 진행고객, 협력 사 연결 준비스마트제조생태계조성

새로운 BM 및 전략공장 및 업무 자동화공장 및 업무 자동화공장 및 업무 자동화공장 및 업무 자동화공장 및 업무 자동화공장 및 업무 자동화5% 이하

5%~20%20%~40%40%~60%60%~80%80%~100%디지털화디지털화디지털화디지털화디지털화

디지털화

5% 아하

5%~20%20%~40%40%~60%60%~80%80%~100%

연결/지능화

연결/지능화

연결/지능화

연결/지능화

연결/지능화

연결/지능화

5% 이하

5%~20%20%~40%40%~60%60%~80%80%~100%스마트 제조스마트 제조스마트 제조스마트 제조스마트 제조스마트 제조5% 이하

5%~20%20%~40%

40%~60%60%~80%80%~100%

Digitalization Level

Connectivity/Intelligence
Level

SML : Smart
Manufacturing level17

Table of Contents
1. Trilemma in Korea Manufacturing Industry

2. Initiatives of Transformation by Innovation in Korea- RoadMap- Use case (Light House)- Smart Manufacturing Level Assessment Tool

3. Transformation of Industrial Cities into Smart Industrial Cities
4. Concluding Remarks
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Which type of industrial city we want to build?
Flexible
Society

Diligent society

weak

SustainableSocietystrong
Tech &innovation

Polarized/no job
society

Ref: 디지털과 미래도시: 이명호Transform a city heavily dependent on conventional manufacturing into a smart industrial city19Transformation of Conventional Industrial City
Global Industrial City Innovation Network
Manufacturing
Innovation

Conventional
Industrial City

GlobalCollaboration

NSmartUrbanization

TransformedIndustrial City

Global 4IR Model CityFostering
New Industry20

Transformation of manufacturing industrial city
Transform to a sustainable and smart industrial city
Global Innovation
Network Build a Platform
Innovation
Manufacturing Sector• Energy• Petro-Chemical• Shipbuilding• Automotive• E&E• Consumer Goods• Steel Mills• Equipment Fab• Farm Equipment• Textile•••

Business ModelProductProduction

Smart CityTechnology••

IoT, AI, Big Data
Robotics, CPS, Added Materials

Servitization••

P maintenance
Circular Economy

Skills & Employment••

New
ManufacClusterCity• Sustainable City• Education, Diversity& Job Growth• Global Ecosystem• Integrated Value Chain• Quality of Life
Work-life balance

Education, Reskill
Quality of Work

Sustainable Production•••Efficient Energy
Renewable
Sustainable Society21

Concluding Remarks• Digital Transformation has to take place in Process, Productand Business Model• While companies recognize opportunities of I4.0, many do
not know where and how to start.
• Evaluation tool to provide a common level ofunderstanding and where to start and how to implement
across all industries is recommended
Invite to join the International collaboration community
to transform manufacturing oriented city into a smart city.
dongsupk@unist.ac.kr
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