Prof. Dr. Steffen Kinkel 1

Industry 4.0 application and

reshoring of manufacturing –

evidence, limitations & policy implications

Prof. Dr. Steffen Kinkel

Karlsruhe University of Applied Sciences

Institute for Learning and Innovation in Networks (ILIN)

MAKERS Workshop “Industry 4.0 – Implications for an

EU industrial policy”, Brussels, January 25th 2018

MAKERS - Smart Manufacturing for EU growth and

prosperity is a project funded by the Horizon 2020-

MSCA- RISE - Grant agreement number 691192.

Prof. Dr. Steffen Kinkel 2

Content

Industry 4.0 and local value chains

Trends in manufacturing backshoring

Industry 4.0 enabling technologies and correlation with backshoring

Key competences for Industry 4.0

Conclusions for Industrial and Innovation Policy

Prof. Dr. Steffen Kinkel 3

Rise of local value chains and

Industry 4.0?

Transnationally highly fragmented value chains are typical for today's global

economy, in particular for high-tech products (Brennan et al., 2015).

E.g. iPhone: Designed and commercialised in the US

Assembled in China, “Made in the world”

But also disadvantages and risks of global supply chains show up:

(e.g. Handfield, 1994; Holweg at al., 2011; Nassimbeni, 2006)

Long lead-times, low flexibility, instability in supply chains

Unsatisfactory quality standards of foreign suppliers

Cultural differences and communication problems

Rising labour costs

Increasing awareness for the back-/reshoring of manufacturing

Industry 4.0 / Smart Factory enables efficient and agile production systems

Potentials to support back-/reshoring?

Potentials to restore manufacturing and local value chains in EU countries?

Prof. Dr. Steffen Kinkel 4

Offshoring stays on

lowest level since

mid 90s

Backshoring stable

(slightly upwards);

for every 3rd

offshoring company

there is one

backshoring

Around 500 German

manufacturing

companies per year

perform backshoring

German evidence: Manufacturing

offshoring and backshoring over time

17%

26%

27%

19%

25%

19%

12%11% 11%

15%

9%

8% 9%4%

6% 6%

4%3% 3%

2%3%

2% 3%2%

3%

1995(n = 1.305)

1997(n = 1.329)

1999(n = 1.442)

2001(n = 1.258)

2003(n = 1.134)

2006(n = 1.011,n = 1.663)

2009(n = 817,

n = 1.484)

2012(n = 820,

(n = 1.594)

2015(n = 571,

(n = 1.282)

Share

of com

panie

s (

in %

)

Jahr

German Manufacturing Survey 1995-2015, Fraunhofer ISI

Metal and electrical industry

Whole manufacturing industry

Offshoring in the two years before ...

Reshoring in the two years before ...

Prof. Dr. Steffen Kinkel 5

Issues: Different points in time, different economic conditions,

different phases in the „offshoring and backshoring lifecycle”

“Adjusted” shares of backshoring

companies in European countries

CountryShare of companies

active in reshoring

Time-frame

(years covered)

“Adjusted” share of companies active

in reshoring over a 2 years period

Sweden 27,0% 6 9,0%

Ireland 13,0% 3 8,7%

Belgium 9,5% 3 6,3%

Slovakia 9,0% 3 6,0%

France 14,0% 5 5,6%

Denmark 13,0% 6 4,3%

Finland 13,0% 6 4,3%

DACH 4,0% 2 4,0%

Portugal 6,0% 3 4,0%

Netherlands 6,0% 3 4,0%

Selected European countries

(EMS survey)4,0% 2 4,0%

UK 13,0% 8 3,3%

Germany 3,0% 2 3,0%

Estonia 3,5% 3 2,3%

Lithuania 2,0% 3 1,3%

Bulgaria 2,0% 3 1,3%

Romania 1,0% 3 0,7%

Source: Kinkel et al. (2017): Measuring reshoring

trends in the EU and the US, Deliverable 4.1 of the

MAKERS project, Karlsruhe

Prof. Dr. Steffen Kinkel 6

56%59%

43%

52%53%

68%

33%28%

31%25%

32%

27%21%

20%

15%13%

11%6%

33%

6%11%

5%

5%0%2%

0%13%

19%

0% 10% 20% 30% 40% 50% 60% 70%

Flexibility, Ability to deliver (2015)(2012)(2009)

Quality (2015)(2012)(2009)

Capacity utilisation (2015)(2012)(2009)

Transport costs (2015)(2012)(2009)

Coordination (2015)(2012)(2009)

Infrastructure (2015)(2012)(2009)

Labour costs (2015)(2012)(2009)

Loss of know-how (2015)(2012)(2009)

Proximity to R&D at home (2015)(2012)(2009)

Availability of skilled workers (2015)(2012)(2009)

Source: German Manufacturing Survey 2015, Fraunhofer ISI

Main motives for backshoring of

manufacturing activities (German evidence)

Flexibility and coordination have

become more important

Quality abroad still an issue

Labour costs and availability of

skilled personnel abroad have lost

in importance

Additional important reasons from

other research: “Made in” reputation

effect, total costs of sourcing

Prof. Dr. Steffen Kinkel 7

Industry 4.0 enabling technologies

application levels – long ways to go

37%

15%

5%

23%

26%

19%

6%

20%

21%

37%

34%

30%

16%

29%

55%

27%

0% 10% 20% 30% 40% 50% 60%

1-49 employees

50-249 employees

250+ employees

All companies

Level 3 Level 2 Level 1 Level 0

Based on three

technology fields:

(1) Digital management

systems, (2) Wireless

human-machine comm.,

(3) CPS-based operations

Levels = number of fields

in which companies have

implementations

Large firms much more

active than small firms

Source: Kinkel, S. and Jäger, A. (2017): Auslandsverlagerungen, Rückverlagerungen

und Digitalisierungsverhalten in der deutschen Industrie. Trends und Auswirkungen

für den Produktionsstandort Deutschland, Karlsruhe

Prof. Dr. Steffen Kinkel 8

Correlations of Industry 4.0

and backshoring

Significant positive correlation between the use

of Industry 4.0 enabling technologies and the

backshoring propensity of German

(also Austrian and Swiss) manufacturing companies

“Advanced users” (level 3) of Industry 4.0 enabling

technologies display on average a 10-times higher

backshoring propensity than "non-users" (level 0)

Two arguments:

Use of I4.0 enabling technologies facilitate increased

automation and productivity of the German factory

site, making labour arbitrage of low-cost countries (LCC)

less appealing and economies of scale more important

Even more important: Use of I4.0 enabling technologies

facilitate increased flexibility and efficient production

of individualized solutions, providing incentives for

firms to keep/reshore production close to their European

customers ( local value chains).

Cox & Snell: 0,055 Nagelkerkes: 0,230Regression

coefficient B Sig.

Step 1 Ln #employees ,072 ,673

sec99_other manufacturing -,038 ,974

sec24_metal & metal components -,093 ,938

sec26_Data processing equipment,

electronic and optical products

,691 ,561

sec27_electrical equipment ,439 ,724

sec28_machinery & equipment -1,023 ,415

medium batch size ,329 ,593

large batch size -,152 ,850

medium complex products -,383 ,532

complex products -,248 ,730

supplier company -1,485 ,004

main competition factor: price/cost ,574 ,310

Ln import quota of inputs -,143 ,468

Ln export quota of inputs 1,101 ,004

Ln share of unskilled workers ,137 ,439

I40-enabling-use-til-2013_level1 1,884 ,095

I40-enabling-use-til-2013_level2 1,932 ,076

I40-enabling-use-til-2013_level2 2,618 ,016

Constant -8,946 ,000

Source: Kinkel, S. and Jäger, A. (2017): Auslandsverlagerungen, Rückverlagerungen

und Digitalisierungsverhalten in der deutschen Industrie. Trends und Auswirkungen

für den Produktionsstandort Deutschland, Karlsruhe

Prof. Dr. Steffen Kinkel 9

Technical key competences:

Software development of modular applications (apps) and IT-based platforms

Integration with the programming of machine and plant controls

IT security and user-oriented IT design

Non-technical competences:

Comprehensive understanding of customer problems and business models

Analysis of complex data and making sense as “smart data”

Interdisciplinary cooperation, particularly between engineers and IT specialists

Agile development approach, early experimentation and testing, positive culture of

error: "be brave and fail fast“

Key competences for the

digital integration

Source: Kinkel et al. (2016): Digital-vernetztes Denken in der Produktion.

Studie für die IMPULS-Stiftung des VDMA, Karlsruhe, November 2016

Prof. Dr. Steffen Kinkel 10

Conclusions for Industrial and

Innovation Policy

The advantages of cost-based offshoring to LCC have clearly diminished, however

offshoring intensity is still higher than backshoring intensity

Positive correlation between the adoption of I4.0 enabling technologies and backshoring

limited with respect to jobs directly created at the home base, as “new production” is

more automated

Indirect effects through local purchase of equipment and infrastructure as well as

local sourcing of inputs and services

What policy can do

Support regional clusters and local value chains

Support local demand for innovative and more sustainable solutions (e.g. public

procurement, “Made in” local value chains)

Support development and adoption (!) of smart and agile production systems (e.g.

Industry 4.0, flexible and individualized manufacturing, additive manufacturing)

Support development of smart, data-driven services and business models for B2B

Support education, qualification and competence development of skilled personnel,

limit bottlenecks

Prof. Dr. Steffen Kinkel 11

Prof. Dr. Steffen Kinkel

ILIN Institute for Learning and Innovation in Networks

(www.ilin.eu)

Karlsruhe University of Applied Sciences

steffen.kinkel@hs-karlsruhe.de

Questions?

Prof. Dr. Steffen Kinkel 12

Target and source countries of

manuf. offshoring and backshoring10%

49%51%

13%14%

16%

23%27%

7%

32%17%

9%

16%4%

14%

0%0%

9%

0%0%0%

13%0%

54%55%

40%

31%30%

27%

21%25%

16%

8%11%

10%

7%8%9%

2%2%

12%

2%2%3%

1%0%

-60% -50% -40% -30% -20% -10% 0% 10% 20% 30% 40% 50% 60%

EU 13 (2015)(2012)(2009)

China (2015)(2012)(2009)

Rest of Asia (2015)(2012)(2009)

EU 15 (2015)(2012)(2009)

North America (2015)(2012)(2009)

Rest of Eastern Europe (2015)(2012)(2009)

Latin America (2015)(2012)(2009)

Rest of World (2015)(2012)(2009)

Source countries of Reshoring(n = 36 (2015) | 32 (2012) | 46 (2009))

Target countries for Offshoring(n = 128 (2015) | 154 (2012) | 161 (2009))

Source: European Manufacturing Survey 2015, Fraunhofer ISI

Prof. Dr. Steffen Kinkel 13

Main motives for offshoring of

production activities

Main motives for

manufacturing relocations

Manufacturing

relocation mid

2004 to mid 2006

Manufacturing

relocation 2007 to

mid 2009

Manufacturing

relocation 2010 to

mid 2012

Manufacturing

relocation 2013 to

mid 2015

Trend

Labour costs 80 % 77 % 71 % 75%

Access to new markets 27 % 28 % 28 % 27%

Vicinity to key customers 21 % 29 % 26 % 29%

Vicinity to to relocated

production capacities n.a. 16 % 23 % 20%

Access to raw materials n.a. n.a. 15 % 12%

Import restrictions n.a. n.a. 11 % 9%

Lack of skilled workers n.a. 8 % 9 % 13% ()

Taxes, levies, subsidies 11% 12% 5% 11%

Following competition n.a. n.a. n.a. 10% n.a.

Prof. Dr. Steffen Kinkel 14

Use of Industry 4.0 enabling technologies

in German manufacturing industry

67%

11%

33%

19%

31%

30%

27%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Enterprise Resource Planning Systems (ERP)

Product Lifecycle Management Systems (PLM)

Digital visualization

Mobile devices for programming / operation of machines

Digital exchange of disposition data (SCM)

Techniques for automation and control of internal logistics

Real-time manufacturing execution system (MES)

Source: German Manufacturing Survey 2015, Fraunhofer ISI

Digital Management Systems

Wireless human-machine communication

CPS-related operations

Prof. Dr. Steffen Kinkel 15

Cox & Snell: 0,077 Nagelkerkes: 0,168Regression

coefficient B Sig.

Step 1 Ln #employees ,449 ,000

sec99_other manufacturing -,435 ,475

sec24_metal & metal components -,325 ,617

sec26_Data processing equipment,

electronic and optical products

-,291 ,706

sec27_electrical equipment 1,094 ,097

sec28_machinery & equipment ,159 ,808

medium batch size ,377 ,255

large batch size -,349 ,472

medium complex products ,039 ,917

complex products ,321 ,451

supplier company ,153 ,573

main competition factor: price/cost ,788 ,012

Ln import quota of inputs ,153 ,213

Ln export quota of inputs ,215 ,107

Ln share of unskilled workers ,121 ,271

I40-readyness-til-2013_level1 ,323 ,430

I40-readyness-til-2013_level2 ,463 ,223

I40-readyness-til-2013_level2 ,250 ,538

Constant -6,437 ,000

Logit model for offshoring

propensity of companies

Large firms are

more active in

offshoring

Companies with a

focused price/cost

leadership

strategy are more

active in offshoring

No effects of

Industry 4.0

readiness on

offshoring

propensity

Prof. Dr. Steffen Kinkel 16

Cox & Snell: 0,055 Nagelkerkes: 0,230Regression

coefficient B Sig.

Step 1 Ln #employees ,072 ,673

sec99_other manufacturing -,038 ,974

sec24_metal & metal components -,093 ,938

sec26_Data processing equipment,

electronic and optical products

,691 ,561

sec27_electrical equipment ,439 ,724

sec28_machinery & equipment -1,023 ,415

medium batch size ,329 ,593

large batch size -,152 ,850

medium complex products -,383 ,532

complex products -,248 ,730

supplier company -1,485 ,004

main competition factor: price/cost ,574 ,310

Ln import quota of inputs -,143 ,468

Ln export quota of inputs 1,101 ,004

Ln share of unskilled workers ,137 ,439

I40-enabling-use-til-2013_level1 1,884 ,095

I40-enabling-use-til-2013_level2 1,932 ,076

I40-enabling-use-til-2013_level2 2,618 ,016

Constant -8,946 ,000

Logit model for backshoring

propensity of companies

Company size no

factor for backsho-

ring propensity

Supplier companies

are more reluctant

to backshoring

Export-intensive

firms are more

active in back-

shoring, to shorten

their upstream

value chains

Positive effects of

use of Industry 4.0

enabling

technologies on

backshoring

propensity