Hong-Seok Kim discusses the transition from analog to digital technologies and the implications of digitalization. Digitalization generates large amounts of data that can be easily stored, duplicated, and edited using digital tools. This has led to transformations in research, industry, business, and society through infrastructure changes, new methodologies, and shifts in thinking. Korea has actively pursued digital technologies since the 1990s. The presentation outlines strategies for manufacturing innovation through the development of smart factories that utilize technologies like the Internet of Things, cyber-physical systems, and big data analytics.

1. August 15th, 2016
Hong-Seok Kim <hskim@kitech.re.kr>
Research Institute of Sustainable Manufacturing System
Korea Institute of Industrial Technology
( 韩 国 生 产 技 术 硏 究 院 淸 净 生 产 系 统 硏 究 所 所 长 金 弘 锡 )

2. (在数码科技显著变化)

3.  Analog vs. Digital
 digitus (Latin: finger, toe) → digit (= numerals, 0~9; counting with fingers?) → digital
 (Continuous) Quantities → (Discrete) Numbers, representing a physical quantity
 Digital, a metaphor (隐喻)
 Completely different concept from the original meaning
AnalogDigital
Digit + al
数码/數碼수마,
数字/數字,
計數(型)
Abstraction
模拟/模擬모의,
类似/類似유사,
仿真/仿眞방진,
相似(形)상사(형)
Physical World
3

4.  Digital-ization generates data
 Unified storing methods & media
 Analog: different methods & media for physical quantities
 Easy to duplicate, erase, and edit
 Possible to replicate infinite times without loss and deformation
 Software, tool to deal with these data according to the applications (digital tool)
 “Humans are omnipotent in the digital world with ‘tools’ implemented in software.”
 Computer as a ‘Tool Platform’ …
< The main function of computers is changing… >
Computing Search Social
4

5.  Technology advancement leads to social & cultural transformation
 Huge amounts of data (digitized quantities) generated in all fields and digital tools
 Transformations in academic research, technology and industry, and the
business environment
 Infrastructure, methodologies, framework (the framework of thinking) …
 CAD/CAM, simulation, digital communication, Internet banking … commonly used since the 1990’s
 Korea actively responded to the digital paradigm shift 21 years ago
 “We were late in industry, but let’s go ahead in information!”*
 This campaign leads to a great success in IT manufacturing (so far).
* The Chosun Ilbo (朝鲜日报; March 5, 1995) http://biz.chosun.com/site/data/html_dir/2014/06/16/2014061602283.html
5

6. * Ref.: http://content.time.com/time/interactive/0,31813,2048601,00.html
6

7. 1. Big Data
 Very large-scale data beyond the acceptable limits of size, collection and
management of the processing software which has been conventionally used;
(mostly) unstructured data
 Implicit meaning of ‘Big Data’ Analytics
2. (Cloud) Computing
 Innovations in computing power
 Cloud service, GPU (Nvidia), TPU (Google) …
3. Connectivity
 The world becomes hyper-connected
7

8.  Data generate double every 2 years
 2.8ZB (2012) → 40ZB (2020, 5.2TB / person)*
 Note: giga (109 [~230]) < tera (1012) < peta (1015) < exa (1018) < zetta (1021, giga × tera) < yotta
(1024)…
 World population: 1B (1804) → 2B (1927) → 3B (1960) → 4B (1974) → 5B (1987.7.11) → 6B
(1999.10.12) → 7B (2011.10.31) → ~ 7.43B (2016.6.26) → 8.42B (2030) → 9.96B (2060)
8
* Ref.: http://www.emc.com/collateral/analyst-reports/idc-the-digital-universe-in-2020.pdf ;
http://mirian.kisti.re.kr/futuremonitor/view.jsp?record_no=235704 ; http://www.worldometers.info/kr/

9.  Cloud computing / cloud services available
 Worldwide public cloud service market, $ 47.4B [~315B Yuan] (IDC, 2013)
 GPUGraphics Processing Unit shipment, 12.4M (JPR, 4Q/2014)
 Enabling Big Data processing and complex algorithms which have been
previously impossible to realize
 Deep Learning …
 IT giants show it possible!
 Google, Facebook, Microsoft, Amazon, etc.
9

10.  Getting more connected, the
Internet becomes the Brain
 IT giants’ Connected businesses
 Platform-based businesses, ecosystem
 Open their resources (source code, tools,
framework, etc.) to developers to create
and raise an ecosystem
 It’s not the age to earn money with
framework and tools!
 Creating new value by collecting data
from a big number of connected people
and connected things
10
…?
Jeffrey M. Stibel,
Wired for Thought: How the Brain
Is Shaping the Future of the
Internet
이영기 역, 구글 이후의 세계

11.  What are they doing with Big Data?
 Big Data → (through DAData Analytics & AIArtificial Intelligence) → Knowledge system
 Human experiences (and domain knowledge) encoded in data → Knowledge in the digital world
 This knowledge is replicable infinitely and losslessly!
 Making money by the intelligent services & contents based on knowledge
 Advent of the ‘AI Age’
 Openness and collaboration are the important virtues.
11
< Sonny & VIKIVirtual Interactive Kinesthetic Interface in the movie, “I, Robot” >

12.  IT moves to AI
 Google
 ‘DeepMind’ (Jan. 2014), open ‘TensorFlow’ (May 2015), ‘AlphaGO’ (March. 2016)
 Baidu: AI research center in Silicon Valley, Andrew Ng signing (May 2014)
 Facebook: FAIRFacebook AI Research, open ‘Torch’ (Jan. 2015)
 Apple: ‘VocalIQ’ (voice), ‘Perceptio’ (smartphones) (Sep. 2015)
 Microsoft
 Windows 10 is available in voice recognition personal assistant apply ‘Cortana’
 Amazon: ‘Alexa’ and Alexa Skills Kit
12

13.  We already live in a smart world
 Smart …?
 Important to transform Big Data into Smart Data
 Finding patterns from (big) data through data analytics based on the domain knowledge
(experiences of the experts)
 Smart phone, Smart home, Smart car …
 Getting connected, aware of users’ situations & intentions, working autonomously
 Smart factories …?
Smart Factory
Smart Car
Smart Home
Smart Phone
13

14. (韩国制造业的创新3.0)

15. 製造業
革新 3.0Strategic Moves for Manufacturing Innovation
15
National Strategic Plan for Advanced Manufacturing
Advanced Manufacturing Program
USA
High Tech Strategy 2020
Industry 4.0 (’13.4)
Germany
Factories of the Future 2020
EU
Industry Revitalization Plan
Japan
China Manufacturing 2025
China

16. 製造業
革新 3.0Implications of MI* Strategies
16
4th Industrial
Revolution
Experiences of IT & Internet Business → Manufacturing
로봇산업 중심
제조혁신
Germany
System
Vendor-driven
U.S.A.
Personalized
Product-driven
Japan
Robotics
Industry-driven
* Manufacturing Innovation

17. 製造業
革新 3.0State of Korea’s Manufacturing Industry
17
Mfg. Company Size & Automation Level
Rank 2010 2013 2018
1 China China China
2 India Germany India
3 Korea USA Brazil
4 USA India Germany
5 Brazil Korea USA
6 Japan Taiwan Korea
Mfg. Competitiveness

18. 製造業
革新 3.0Needs of Manufacturing Innovation Strategy
18
*
Rank 2011 2012 2013
1 Korea Korea Denmark
2 Sweden Denmark Korea
3 Denmark Sweden Korea
4 Iceland Iceland Iceland
5 Finland Netherland UK
6 Netherland Norway Netherland
High
Manufacturing
Share
High
ICT Level
Bases of
Mfg. Innovation
in Korea
* Ref.: Institut der deutschen Wirtschaft, IWD, Ausgabe 2, 2012;
Manufacturing, value added (% of GDP), http://data.worldbank.org/indicator/NV.IND.MANF.ZS

19. 製造業
革新 3.0“Manufacturing Innovation 3.0”
19
Industrial Society Information Society Hyper-Connected Society
IT Focused
Smart Mfg.
(Mfg. + ICT)
(1980~) (2000~)
Manufacturing
Innovation 3.0
(2014~)
Paradigm
Competitive
Field
Internet
Computer
Cyber-Physical Space
Physical Production System Computer (Cyber) Production System Cyber-Physical Production System
Production
System
IoT
Smart Device
Manufacturing
Focused
Industrialization Informatization Smartization

20. 製造業
革新 3.0Plans for “Manufacturing Innovation 3.0”
20
’12년도
이용기업
확대
‘Creative
Economy’
in Korea
Spread of Smart
Production
Build-up of
Innovation Infra
Creation of
New Industry
Activation of
Local Mfg. & Start-ups
 Spread of smart factory
 8 smart manufacturing technologies
 Software enhancement in manufacturing
 Investigation of advanced production facility

21. 製造業
革新 3.0Concept of ‘Smart Factory’ in Korea
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ShopFloor
Production&Planning
Control
Traditional Factory
Production Network
Smarter Objects
Component
Maker 1
Component
Maker 2
Module
Maker 1
Module
Maker 2
Internet of Services (IoS)
Internet of Things (IoT)
Manufacturing Big Data
Real-time
Connection (CPS)
Optimized
Production
Inventory
Control/
Logistics
MES Equipment
Maintenance
Quality
Analysis
Smart Factory
Based on production data
Better
Automation Level
* Ref.: DFKI(Deutsche Forschungszentrum für Künstliche Intelligenz), 德国人工智能研究中心; http://www.dfki.de/

22. 製造業
革新 3.0Steps of ‘Smart Factory’
22
Basic
Inter-
mediate-1
Inter-
mediate-2
Advanced
Barcodes &
RFIDs
IT technologies
(sensors & Internet)
IT technologies &
Embedded SWs
IoT & CPS
Stepwise Evolution of Smart Factory

23. 製造業
革新 3.0Spread of ‘Smart Factory’
23
2015 2017 2020
Stepwise spread of Smart Factory in Korea
3 Key Areas
① Direction Constructing/Promoting factory model
② Smartization Providing customized a smarter factory
③ Infrastructure Establishing certification/standard/security

24. 製造業
革新 3.0Strategies of spreading ‘Smart Factory’
24
Model Factory
Smartization within Value Chain
Certification ∙ Standard ∙ Security
(1) Single Factory (2) Factory-to-Factory (3) Factory-to-Customer
Certification Security
Industrial
Standard
Human
Resource
Training
Government: Infrastructure support Industry: Spread

25. 製造業
革新 3.08 Smart Manufacturing Technologies
25
Production
System
Innovation

26. 製造業
革新 3.08 Smart Manufacturing Technologies (cont.)
26
ICT
Convergence

27. 製造業
革新 3.0Hierarchy of (8) Technologies
27
Device
Network
Platform
Service
IoT
Smart
Sensor
3D Printing
CPS
Energy
Saving
Hologram
Big Data Cloud
Factory operation, control & intelligence
Flexible design & customization

28. 製造業
革新 3.0R&D Projects on ‘Smart Factory’
28
‘14 ‘15 ‘16 ‘17 ‘18 ‘19 ‘20
1st Stage
Distribution
2nd Stage
Distribution
3rd Stage
Distribution
Pilot Project of
Smart Factory
Advanced Technology
for Smart Factory
(1st Stage)
Advanced Technology
for Smart Factory
(2nd Stage)
Connected Smart Factory (CSF)
(1st Stage)
Connected Smart Factory (CSF)
(2nd Stage)
Smart Factory Level
(Advanced)
(Basic)

29. 製造業
革新 3.0Advanced Technology for ‘Smart Factory’
29
1st Stage :
Application
Platform
Device
Standardization
Technological Developments in Automation of Optimized Manufacturing
Process Design for the Customized Production & Flexible Manufacturing
The Development of Core Technologies of Quality Advancement based on the
Manufacturing Process Data
The Development of Operational Technologies for Smart Factory Applications
with the Manufacturing Big Data
Factory-Thing H/W & Open IIoT Smart Factory Platform Development for the
Manufacturing Industry
The Development of Data Collection/Process System for the Manufacturing &
Demonstration Model of Smart Factory
Common Industry Standard Development for Promoting/Spreading Smart
Factories
* Ministry of Trade, Industry and Energy, 2015

30. 製造業
革新 3.0Wrap-up
30
Current ICT Technologies
ICT Key Technologies
ICT Advanced Technologies
Real-time production
information
Partially connected
systems
Real-time production
control
Fully Integrated system
2014 ~ 2016 2017 ~ 2018 2019 ~ 2020
Basic production
information
Heterogeneous systems
Boosting
Manufacturing
Competitiveness &
Reforming Major
Industries
1st Stage 2nd Stage 3rd Stage

31. 製造業
革新 3.0
31
谢谢
© Hong-Seok Kim <QrioCty@Gmail.com>