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© Fraunhofer IAO, IAT Universität Stuttgart

F1

Industry 4.0 – an Economy based on the Internet of Things

Prof. Dr.-Ing. Prof. e. h. Wilhelm Bauer Fraunhofer Institute for Industrial Engineering IAO, Stuttgart, Germany


F2

Fraunhofer IAO and University of Stuttgart IAT Applied and basic research for our customers´ benefit

Director: Prof. Dr.-Ing. Wilhelm Bauer

Budget: 34.3 million euros therefrom 35% are generated from industry contracts

Staff: 600 employees

Departments:

− Corporate development and work design

− Service and human resource management

− Engineering systems

− Information and communication technology

− Technology and innovation management

− Mobility and urban systems engineering

www.iao.fraunhofer.de www.iat.uni-stuttgart.de

Data from 2015, including IAT, University of Stuttgart


F3

Business Models 4.0 Human-Mach.-Interaction

Research topics of IAO and IAT

Knowledge Work 4.0

Industry 4.0

Smart Services City of the Future

Mobility Innovations

Smart Data Systems

Technology and Innovation Management Change Management


F4

»There is nothing permanent

except change.«

Heraklit, ca. 500 v. Chr.


F5

Digital Transformation

Industry 4.0

Internet of Services

The wind of change Digitalization changes economy and society dramatically


F6

Digitalization: The driving forces of the trend

Networking Internet of

Everything

Cloud

Sensors

Wireless and Mobile

Examples Social Networks

Industry 4.0

Connected Devices/Cars

Smart Home/Smart City/Smart Grids

Smart Mobility/Smart Services

Bildquelle: Werner Sobek


F7

Internet of everything Living and working within the »system of systems«

Internet of People 106-108

Internet of Services 104-106

Internet of Things 107-109

PAST: IPv4-Standard: 4,3 billion IP-addresses = 8,4 IP-addresses per square kilometre earth´s surface

FUTURE: IPv6-Standard 340 sextillion IP-addresses = 667 quadrillion IP-addresses per square millimetre earth´s surface


F8

Data Based Machines Autonomics

Simulation

Big Data Analytics

Bio-Informatics (extreme learning machines)

Self learning algorithms

Sensor data intelligence

Examples Automated driving

Self learning robots

Light weight construction robots

Speech/face recognition

Lab-on-Chip

Drones

Swarm intelligence: 500 robots form a »screw-wrench«

Automated air cargo: Drones prototypes delivery

Man-Machine-Cooperation: Robot-assistents capture factories

Digitalization: The driving forces of the trend


F9

Business Behaviour − Open Innovation − Fast Collaboration − Co-Working − Bikesharing/Carsharing − Crowd Innovation and Work

Economics − Digitalised business

models − Platform solutions − Sustainability − Globalised added value − Sharing economy

Business models as central driving force for future development


F10

Digital business models New rules for competitiveness

Charakteristics of digital business models:

Everything as a service

Strong growth after lock-in-effect

Zero marginal costs

Profits (cumulated)

Quantity/ Customers

Lock-in-effect

Digital business models

Traditional business models

»Scale without mass.«

»The winner takes it all.«


F11

Risks for the old economy New digital competitors are challenging the traditional industries

European industry

today

New competitors

Potential loss of value creation volume 1

2 Potential loss of customer contact points

Pressure to European value propostition

Share of value creation

Val

ue

crea

tio

n p

rop

osi

tio

n


F12

Investment in Uber with pilot project for city logistics

Google: selected investments and projects Internet companies discover growth potentials within the industrial sector

Acquisition of robot firms and test of auto-mated manufacturing lines

Development of drones (Titan Aerospace) and

balloons for transmitting radio signals

Development and test of automated driving Real-time navigation with Google Maps

Acquisition of Nest, a producer of

intelligent thermostats

Smart contact lens to monitor blood

glucose levels auto-matically

Investment in 23andme and Calicio


F13

Bosch: forcing digital business models and solutions Traditional industrial companies positioning within the Connected World

Connected Energy

Connected X

Connected Industry Enabler

2015

5,5 Mrd. connected

people

2015

6,6 Mrd. connected

things

Bosch Software Innovations

Bosch Sensortec

ETAS/Escrypt

Bosch Connected Devices and Solutions

Bosch Start up Platform

User experience

Corporate research

IoT Lab St. Gallen

Connected Car

Connected Building

Source: Robert Bosch GmbH, 2015


F14

Risk volume for loosing value propositions Europe‘s risk potential is enormous

2015

Gro

th o

f IC

T p

ote

nti

al in

GVA

2025

Transformation related loss of GVA in Europe

Medtech, Elektro, Machinery, Energy

215 bn EUR GVA

Chemistry, Aero,Space

40 bn EUR GVA

Automotive, Logistics

350 bn EUR GVA

Wav

e 1

Wav

e 2

Wav

e 3

+ 17%

+ 10%

+ 5%

Disruptive to high impact

High to medium impact

Evolutionary to low impact

∆ ICT-share from 2015 to 2025

Potential loss until 2025

By missing the digital transformation Europe‘s loss of gross value added of 605 bn Euro is possible

Source: BDI/Roland Berger, 2015


F15

The digitalization of value creation is already on the way and will penetrate business, work and private life further on. New and disruptive business models occure.

Statement #1


F16

First weaving loom 1784

1. Industrial Revolution Mechanical production with water and steam power

2. Industrial Revolution Work-sharing mass production with electrical power

Ford assembly line Beginning 20th century

First programmable controller »Modicon 084« 1969

3. Industrial Revolution Electronics and IT for automation of production

4. Industrial Revolution Basis: Cyber-Physical Systems

End of 18th century Beginning 20th century Beginning 1970 today

Co

mp

lexi

ty

»Smart Factory«

Towards an Industry 4.0 Cooperation within social networks

Work instruction workers’ participation cooperation

Resources based on prediction consumption order related

Processes starr flexible adaptive in real-time


F17

Video: Industry 4.0 – Cyber-physical systems https://www.youtube.com/watch?v=HPRURtORnis


F18

Retail

Banks ICT & media

Leisure & travel

Insurances

Professional services

Gastronomy

Education

Real estate

Building industry

Government

Energy supply

Manufacturing

Agriculture

Health care

Transportation

Mining, oil, gas, chemical

industry

0

5

10

15

20

25

30

35

40

45

50

0 1 2 3 4 5

Disruption map by industries Numerous sectors facing dramatic challenges

Imp

act

on

bu

sin

ess

mo

del

s

Time response (in years)

SHORT FUZE – BIG BANG LONG FUZE – BIG BANG

SHORT FUZE – SMALL BANG LONG FUZE – SMALL BANG

Sources: Heads! and Deloitte Digital


F19

Towards smarter business Companies realise the need to change their business models

How strong will your business model

change by 2020? (Answers »fundamental« respectively »strong«)

60 % 50 % 34 % 28 % 28 % 20 % 20 % 34 %

IT und Elektronik

Gesamt Handel Auto- mobil Auto- mobile

Finance/ Insurance

Transport/ Logistics

Trade Overall IT/ Electronics

Energy Telecommunication/ Media

Source: KPMG-Study Survival of the smartest, 2014; % (n = 350)


F20

Economy 4.0 Big chances – lots of work to be done

Source: IHK-Unternehmensbarometer zur Digitalisierung, Januar 2015; Basis: Umfrage vom 27. November bis 4. Dezember 2014; N = 1.849 Unternehmen

Digital change is encompassing German economy in total

74% are expecting an expansion of innovation activities in order to fully exploit the possibilities of digitalization

How do companies estimate the status of digitalization in total? (%)

Is the increasing digitalization influencing business and working processes in your company?

All industries

Production

Trade

Construction

Information/Communication

Finance

Other services

Transportation

Hotel and restaurant industry

1 – digitally low developed 6 – digitally complete developed

All industries

Production Services

Construction Trade

Yes

No


F21

Potential value effect of Industry 4.0 for Western Europe Increase of ROCE in Western Europe from 18 % up to 28% until 2035 up to 420 Billion Euro*

* net profits and savings in capital employed would be the value effect of Industrie 4.0.

** adoption rate of 50% for Industrie 4.0 solutions until 2035.

*** The created jobs by new industrial activities bear little resemblance to old ones and are based on an entirely different business model.

Source: Roland Berger 2016

2035 2015

Number of employees in industry [m]**

25,0

1,1 1,9

6,7 26,4 8,3

Industrial productivity

(2.7 m) Lack of

competitiveness (2.7 m)

Investment in Industrie 4.0

solutions (2.9 m)

Relocation of activities leveraging

Industrie 4.0 business

model ***

Reinvest- ments in new

industrial products, equipment

***

Reinvest- ments in new services activities

***

Approx. 10 m jobs


F22

From value chains to value networks Automotive industries as an example

Supplier A Supplier B Customer Supplies parts Integrates components Uses products components, modules Controls customer contact

Demands components Effects market needs

From rigid value chains…

… to dynamic value network structures

OEM

Customer

ICT Platform

Supplier A

Mobility services

Balancing market demands

Delivers data/ services

Provides services

Delivers production techn.

Supplier B

Supplier C


F23

Current barriers within the transformation process Far beyond technology

64%: Lack of clarity concerning economic benefit

60%: Lack of experts and specialised knowledge

43%: Lack of technical requirements

40%: Lack of ability to change organisational structures

37%: Lock of norms and standards

29%: Employee representation

27%: Prevention of data relating to employees

27%: Age distribution within companies

25%: Prevention of data relating to companies Source: Ingenics AG/Fraunhofer IAO (Pre-Evaluation from survey to be released in 09/ 2016)


F24

Many initiatives in Europe are dealing with Industry 4.0


F25

How to deal with digitalisation

»We need to significantly increase the speed of our actions. The digitalisation must be a top issue in Germany and Europe. The Revolution itself out faster than many actors in politics and economics wanted to admit it.«

»German Chancellor Merkel reinforcing the need of intelligent usage of »Big Data« and Industry 4.0: Take chances – avoid risks!«

Günther Oettinger EU-Commissioner for Digital Economy and Society

Angela Merkel Chancellor of Germany


F26

Industry 4.0 raises high expectations. The public perception of the topic has gone beyond real solutions and implementations. Industry 4.0 is penetrating enterprises top-down and bottom-up.

Statement #2


F27

Human-machine-interaction Working hand in hand with specific competencies

Power

Repeatability

Precision

Persistence

Unique response patterns

Performance, multitasking

Creativity

Evaluation- and decision-making ability

Solution findings

Intuition

Emotion

Flexibility and adaptability

Social competency

…

Humas performing as senior experts, decision makers

and coordinators!


F28

1955 future

Tasks of production and knowledge workers merging more an more

Indirecte activities expanding above average to direct ones

Routine jobs as well as simple skilled work and processing replaced by machines

New forms of communication, cooperation and collaboration

Increase of leeways in decision-making and dispositive tasks

New qualification requirements: Digital competencies within all areas

Dominator Captain Conductor

today

Changing relation between humans and working world Technique, organisation and humans within a new triad


F29

Leadership

Employment

Organisation

Work objectives

Working tasks

Work equipment

Workspace

Qualification

FUTURE WORK

Human

Dimensions changing work in the context of digital transformation towards an Industry 4.0

Human-machine-collaboration

Flexibility of content and time

KapaflexCy

On-the-job

Mobile and connected work

Diversity in society

Individualised workplace

Flexible forms of employment

Mobile devices


F30

The use of mobile devices opens up new possibilities for the usage of current data in manufacturing

Yes

Partially

No

72.7%

19.0%

8.3%

Example: Networked work Tasks in logistics and troubleshooting using data glasses

Source: Fraunhofer IAO: Produktionsarbeit der Zukunft – Industrie 4.0; 2013


F31

Example: Human-Robot-Collaboration Defining »rules« for future partnership of work

High-power sensor technology:

− Identification of persons/components

− Robots with tactile sense

Safety fences drop out: Humans and robots working in the same area

Robots as working partner instead of a simple working tool:

Significant benefit for ergonomics and value added

Requirement of new methods of valuation for Human-Robot- Collaboration

New ways of interacting for operations and programming

Robots as workout partner?

Qu

elle: Fraun

ho

fer IAO

Source: BMW, 2015

Campaign BMW AG


F32

Physical assistance with human-robot-collaboration Robots are leaving their cages

Source: Volkswagen AG. 2015


F33

Video: human-robot-collaboration https://www.youtube.com/results?q=Universal+Robots+collaboration&sp=SADqAwA%253D

Source: Universal Robots, Fraunhofer IAO


F34

Example: Self-Organization Self-organized human resource allocation

Selbstorganisierte Kapazitätsflexibilität in Cyber-Physical-Systems

http://www.sap.com/index.epx

http://www.t-h.de/fileadmin/inhalt/Trebing_und_Himstedt/downloads/Logos/TH_Logos.zip

http://www.kaba.de/

http://www.beru.com/

http://www.flughafen-stuttgart.de/sys/index.php?lang=0

http://www.bruker.com/home_.html?&no_cache=1&L=1

http://www.introbest.de/


F35

Customer order: 50 gearboxes until Monday

I can work this Saturday

I am not available this Saturday

Extra-shift this Saturday

Capacity request

»Cockpit« für for capacity requests

Rules Engine who is able to, who is allowed to, who should, who wants to work

Example: Self-organization Self-organized human resource allocation


F36

Example: Optimised working conditions Activity-based lighting

Intensity, colour and direction of lighting are triggered due to context information

RFID cards load individual employees‘ lighting profile

RFID chip records presence of assembly dolly and triggers lighting of work station

Photo sensor records removal of last assembly part and triggers new lighting setting (spots for visual testing)

Work Tasks: Visual Testing Position: Only Work Station 2 lighted

Individual and Shift Parameters: - Older colleague working morning shift - Younger colleague working night shift


F37

85%: Willingness for lifelong learning

70%: More active participation in problem solving and process optimisation

69%: Stronger interdisciplinary thinking and acting

67%: Ability to permanently interact with machines and cyber-physical systems

63%: Higher knowledge of systems (over the whole process chain and its controls)

Source: Ingenics AG/Fraunhofer IAO (Pre-Evaluation from survey to be released in 09/ 2016; n=324)

Industry 4.0 – A revolution of work organisation?! Qualification and build-up of further competencies essential


F38

There will be significant impacts on work, work organization and qualification. It is a big challenge for the societies and for all companies to develop their people with the adequate qualifications.

Statement #3


F39

»It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most adaptable to change.«

Charles Darwin (1809 - 1882) English naturalist and geologist


F40

Prof. Dr.-Ing. Prof. e. h. Wilhelm Bauer Fraunhofer IAO Nobelstraße 12 70569 Stuttgart Tel: +49 711 970-2090 Fax: +49 711 970-2083 [email protected] http://www.iao.fraunhofer.de

Contact


F41

Industry 4.0 MIM 2016

Vortragsdatum: 28. Juni 2016

Vortragsort: Troyes (France)

Vortragszeitraum: 09:30 - 10:30 Uhr

Vortragsdauer: 60 Min.

Diskussion: keine

Veranstaltungsausrichtung: wissenschaftlich

Teilnehmeranzahl: >100 Teilnehmer

Documents

IT Fiction Meets Shop Floor Reality Industry 4.0 – an ...mim2016.utt.fr/Keynote_Bauer_Industry 4.0_MIM... · Internet companies discover growth potentials within the industrial