Human Resources Requirements for Industry 4.0

Prof. Dr. Dr.-Ing. Yilmaz Uygun

Jacobs University Bremen (Germany)

Massachusetts Institute of Technology (USA)

September 4, 2018

WHAT IS INDUSTRY 4.0

2

Industry 1.0“Mechanization”

Industry 2.0“Electrification”

Industry 3.0“Automation”

Industry 4.0“Autonomization”

1800 1900 1970 today

Mechanical production equipment with water and steam

power

Mass production with division of labor and

electrical energy

Automation of production with

electronics and IT

Cyber physical production based on the internet of things

& services

t

based on [Wahlster 2014; Bosch 2015]

1784 first mechanical loom

1870 first conveyor belt

1969 first programmable logic controller

(PLC)

…

The Fourth Industrial Revolution: Industry 4.0

Internet of Things Cyber Physical Systems

Industrial Internet Embedded Systems

Industry 4.0

Smart Factory

Result

Infrastructural requirement Technical requirement

Key Terms & Relations

Opportunities by Industry 4.0

Smart Product Smart Process Smart After Sales Service

Asset information management

Predictive maintenance

Adaptive & transparent logistics

Anticipatory quality management

One-piece flow

Digital product memory

Integrated compliance Service cross-selling

Fraud-secure warranty management

Targeted recall management

Service-enabled products

based on [5]

Consistent and autonomous data exchange

Collaborative product development

General R&D Strategies

New centralized systems and

platforms for data consistency

(e.g. SMLC)

New decentralized systems through

distributed self-control(e.g. FhG IML)

Decentralized control through direct

communication of materials with

machines (e.g. DFKI)

centralized decentralized

Degree of centrality of control

New

dev

elo

pm

ent

Fur

ther

dev

elo

pm

ent

Dev

elo

pm

ent

ap

pro

ach

Centralized control through autonomous

identification of materials (e.g. SAP)

Pictures[SAP 2014] [DFKI 2014] [SMLC 2014] [IML 2015]

R&D Focus

R&D Focus

Innovation Type

Degree of Centrality of

Control

Driving Force

IT-based Machinery-based

disruptive incremental

centralized decentralized

Large companies Consortia

IMPLICATIONS ON HUMAN LABOR

8

Nature of Jobs

9

Managing Others

Applying Expertise

Stakeholder Interactions

Unpredictable Physical Work

Predictable Physical Work

Data Collection

Data Processing

Threatened Jobs

Case Study: Purchasing 4.0

Based on: Uygun & Ilie (2017)

Strategic Purchasing Operational Purchasing

Innovation-based Purchasing

Transactional Purchasing

Strategic & Framework Contracts

Automatic Orders

human-basedw/ more sophisticated qualification profile

machine-basedw/ new ICT

Identification system

dep req

internal algorithm

new requirement

decision:

“send it to department A”

Case Study: Managing Requirements Changes

Anticipation of customer requirements changes

Feedback to customerImpact analysis &

re-negotiation needs

Qualification & Skill Set Requirements

Digital & Interpersonal Competencies

Acquiring Necessary Skill Set

Recommendations15

• Teach broader skill set• Train cross-functionally

and interdisciplinarily• Train job-specific

capabilities• Offer soft skill trainings• Foster innovation &

entrepreneurial spirit

• Retrain/upgrade current employees

• Adopt New Work and Organization Models

• Recruit for Industry 4.0• Engage in Strategic

Workforce Planning

• Offer consortium-based financial support and funds

• Improve coordination between stakeholders

• Promoting successful implementation

Universities Enterprises State

Conclusion

§ Knowledge is the most fundamental resource in modern society; and the most important process is learning

§ Digital and emotional intelligence are key

Critiq

ue

Bo

tto

m L

ine

Outlook

• How much intelligence are thing supposed to have in order not to loose overall human control?

• Is total data security possible against the backdrop of recent data breaches?

• How long will it take to reach fully autonomous systems?

APPENDIX

17

Innovation Fields

18

Service Innovation

Process Innovation

Organizational Innovation

physical intangible

prod

uct

pro

cessIn

no

vatio

n O

bje

ct

Tangibility

Product Innovation

based on [Kirner et al. 2009]

Determinants of Innovation

Novelty

Uncertainty

Complexity

Conflict Potential

+

+

+

[Vahs & Brem 2013; Thom 1980]

The higher the novelty,• the higher the uncertainty• the higher the conflict potential

The higher the complexity,• the higher the uncertainty• the higher the conflict potential

Arbeitsplätze in D

[BCG 2015a] [BCG 2015b]

INNOVATION ECOSYSTEM

21

Systems of Innovation22

• Universities• Private (for-profit)

organizations• Public authorities

(state)• Research &

Technology Organizations

• Venture Capital / Financial Organizations

• Laws• Rules• Regulations• Routines• Established

practices

• R&D provision• Competence building• Creating new markets• Articulating quality

requirements• Creating new

organizations• Networking• Creating/adjusting

institutions• Financing• Providing service

Organization Institutions Functions

Relations

Manufacturing Innovation Ecosystem: MA & USA

SMEs

OEMs Universities

Startups

AssociationsG

loba

l net

wor

ks

R&D networksInnovation sources

Strong knowledge flowWeak knowledge flow

R&

D n

etw

orks

23

Uygun & Reynolds (2016)

The Innovation Process24

[Trischler & vom Bruch 1999]

basic research application-oriented basic research

applied development

technicalprototyping

demonstration commercial prototyp

manufacturing/sales

Research & Technology Organizations

Demonstration Centers, Accelerators, Shared Facilities, etc.

Industrial R&D

Research & Development Commercialization

Res

ourc

es

Innovation Process

Research Universities & National Labs

Factors Hampering Innovation25

• Excessive perceived risk

• High costs• Lack of appropriate

sources of finance• Too long pay-off period

of innovation

• Insufficient innovation potential

• Lack of skilled personnel

• Lack of information on• technology• markets

• Innovation expenditure hard to control

• Resistance to change in the firm

• Deficiencies in the availability of external services

• Lack of opportunities for cooperation

• Lack of technological opportunity

• Lack of infrastructure• No urge due to prior

innovations• Weakness of property

rights• Legislation, norms,

regulations, standards, taxation

• Unresponsive customers

Economic Enterprise Others

Derived Vision of Smart Manufacturing 4.0

QC

1

1 1

2 3

1 Precise and rapid matchmaking

2 Remote Quality Control (CMM, 3D Scan, CT)

3 Custom Shipping (esp. P2P)

4 Ubiquitous Tracking & Tracing Goods Flow

Information Flow

4

based on [Berger 2013]

Autonomous Warehouse Systems

Conveyor Belt Systems

Autonomous Warehouse

Systems

Reconfiguration

Planning and Control

Customization

Demand Volatility

auto

nom

ous

man

ual

cent

raliz

ed

decen

tralized

Jobs28

[McKinsey 2016]

Fraunhofer´s Innovation Diffusion29

Innovation Power in 2013 [Fraunhofer 2014]

• 733 inventions and 603 patent applications => 2 patent applications per day• Licensing revenue: EUR 116M

Contract Research & Consortium-

based Projects

• Direct problem-solving

• Other major outreach initiatives (innovation centers, demonstration centers, etc.)

Fluctuation FhI – Industry

• Highly skilled workforce strengthens companies competitive position

• Forms an informal network of alumni: door opener for contract research and cosortium-based projects

University – FhI

• Students: hands-on training for students and supervision of students’ theses

• Graduates: opportunity to obtain a doctorate and simultaneously work application-orientedly

• Access to each other’s research results

• Access to each other’s facilities

• Adjunct faculty and guest speaker opportunities

Patents and Licenses

• Opportunity esp. for SMEs to take advantage of technologies not invented internally

Spinoffs

• Fraunhofer Venture w/ 130+ startups

Projects organize work at RTOs. They are generally funded in three ways, and for three broad purposes

30

Source: Adapted from the European Association of Research and Technology Organizations

PublicCore

CompetitivePublic and Private

Customer Revenues

Funding

Kno

wle

dge

Applied

Basic

Competence Building

TechnologyDevelopment

Diffusion, Dissemination,

Application

31

Innovation Power

Interpersonal Skills

Autonomous Warehouse Systems

MA Manufacturing Innovation Ecosystem: OEMs

33

Opportunities for Operating in MA

• Lack of skilled workers for technician-level work

• High operating costs (labor, energy, etc.)

• Competition from other states (esp. New York)

Challenges

• Rapid-response, high quality and reliable suppliers

• A well-educated and highly skilled labor force (esp. in engineering)

• World-class universities

• Startups that drive innovation

OEMs use suppliers for rapid and on-time delivery => “time trumps costs”

OEMs are most important innovation driver in MA

OEMs in key industries draw on region’s capabilities differently

Sig

nif

ica

nc

e f

or

Ec

osy

ste

m

Consolidation of supply chain; emphasis on strategic suppliers and collaboration

34

• Relatively few collaborations between SMEs and Universities

• Weak linkages with startups

• Historically little focus on product and process innovations

• Lacking managerial expertise

• More strategic sourcing and long-term relationships with OEMs

• Supplying different industries and cross-clusters

• Rich institutional support in process improvement

MA Manufacturing Innovation Ecosystem: SMEs

Supplier SMEs enable New Product Introduction (NPI) & prototyping

Different types of SMEs supporting different types of innovation

SMEs fulfill high process performance (esp. quality, time, quantity, delivery)

Sig

nif

ica

nc

e f

or

Ec

osy

ste

m

Opportunities for Operating in MA

Challenges

Supplier SMEs are mainly commodity suppliers

35

SMEs and Characteristics for High Performance

• Price: yearly price reductions

• Quality Control: zero defects

• Rapid Response: 100% on-time delivery

• High Flexibility

• Accountability

• Concurrent Engineering due to product complexity

• Innovative components that

• add value to OEMs’ products

• support OEMs’ product innovation process

Current Small Suppliers (esp. commodity & bottleneck suppliers)

New Suppliers(Startup / Spin-off Suppliers)

Minimal Requirements • Standard Certifications (e.g., ISO, AS)• Lean (esp. cross-trained operators, Just-in-time, Kanban)• Technical skills (IT, CAD/CAM)• Culture of “Curiosity” and Continuous Improvement

36

MA Manufacturing Innovation Ecosystem: Universities

• Very strong (basic) research in MA

• Proven track record of University-OEM research

• Significant federal dollar inflow

• Recent regional collaborations around federal NMII RFPs

• Limited SME contact with universities

• Little to no research consortia that involve SMEs

• Hard for companies to navigate

• No regional technology roadmap guiding advanced manufacturing R&D strategy in the state

World-class basic and applied (bilateral) R&D research

Enabler of applied R&D through recent advanced mfg. centers (UMass Amherst, Lowell, Woods Hole) & affiliated Fraunhofer CentersS

ign

ific

ance

fo

r E

cosy

ste

m

Opportunities for Operating in MA

Challenges

37

MA Manufacturing Innovation Ecosystem: Startups

• Vibrant startup community in MA

• Robust ecosystem for early stage scale up

• Increasing focus on ways to better connect startups and OEMs (e.g. NECEC)

• Little systematic connection btw. startups and mfg. SMEs

• Financing and capability challenges for startups to scale up in MA/U.S.

Need for manufacturing capabilities (e.g. 80% of MIT‘s TLO companies)

Startups deliver innovative technology that add value to OEMs’ products

Significant manufacturing startups in MA; 15% (or 500) of all SBIR grantees in MA are engaged in manufacturing ($200M of $1.2B in grants over past 5 yrs)S

ign

ific

an

ce

for

Ec

osy

ste

m

37

Opportunities for Operating in MA

Challenges