Industry 4.0 from a technology adoption perspective

113 Pages·2017·6.8 MB·English

DEGREE PROJECT IN MECHANICAL ENGINEERING,
SECOND CYCLE, 30 CREDITS
STOCKHOLM, SWEDEN 2018
Industry 4.0 from a
technology adoption
perspective
A case study at Sandvik Coromant
EMIL WINBERG
JESPER AHRÉN
KTH ROYAL INSTITUTE OF TECHNOLOGY
SCHOOL OF INDUSTRIAL ENGINEERING AND MANAGEMENT
T R I T
HE OYAL NSTITUTE OF ECHNOLOGY

MASTER THESIS IN INDUSTRIAL PRODUCTION

Industry 4.0 from a technology adoption perspective

A case study at Sandvik Coromant

Authors: Commissioner:
Jesper Ahrén Sandvik Coromant

Emil Winberg
Academic Supervisors:
Anna Jerbrant

Abdullah Alhusin Alkhdur

June 13, 2018

Master of Science Thesis
KTH Industrial Engineering and Management
Industrial Production
SE-100 44 STOCKHOLM
Examensarbete Industriell Produktion 2018

Industry 4.0 ur ett teknikadoptionsperspektiv
En fallstudie på Sandvik Coromant

Jesper Ahrén
Emil Winberg
Godkänt Examinator Handledare
2018-06-13 Lihui Wang Abdullah Alhusin Alkhdur
Uppdragsgivare Kontaktperson
Sandvik Coromant Michael A Sköld

Sammanfattning
Produktionsindustrin står just nu inför den fjärde industrirevolutionen där en ökad grad av
anslutning och datastyrd produktion har möjligheten att skapa självoptimerande fabriker där
maskiner och system kommunicerar automatiskt i realtid. Införandet av ny teknik kan skapa stora
förändringar men även konkurrensfördelar för organisationer, vilket även är fallet för Industri 4.0.

Syftet med studien var att identifiera vilka faktorer som påverkar införandet av Industri 4.0 hos
tillverkande företag och hur problem inom automatiserad cellproduktion kan reduceras genom att
introducera Industri 4.0 koncept. Studien utfördes som en fallstudie hos Sandvik Coromant där
interna observationer och intervjuer utfördes. Dessutom intervjuades fem externa organisationer
verksamma inom industriell digitalisering.

Studien visade att det finns olika faktorer som påverkar införandet av Industri 4.0, kategoriserade
i tekniska, organisatoriska och marknadsmässiga faktorer. För de tekniska faktorerna har
småskaliga applikationer, ökad transparens genom anslutning av enheter och en ökad integration
av olika informationssystem en positiv effekt på införandet av industri 4.0. För att möjliggöra
införandet i organisatoriska sammanhang måste produktionsorganisationer skaffa digitala
kompetenser, integrera sin IT-organisation i sin produktion samt förändra sin kultur och inställning
till Industri 4.0. Dessutom är standardisering, skapande av digitala ekosystem och IT-säkerhet de
viktigaste marknadsaspekterna som påverkar införandet av Industri 4.0.

Hos Sandvik Coromant har elva problem identifierats som kan reduceras med införandet av
koncept från Industri 4.0. Studien föreslår att anslutning, visualisering och dataanalys används för
att reducera dessa problem.

Nyckelord: Adoption av teknik, Industri 4.0, CPS, IoT, Automatiserade produktionsceller
I (IV)
Master of Science Thesis Industrial Production 2018

Industry 4.0 from a technology adoption
perspective
A case study at Sandvik Coromant

Jesper Ahrén
Emil Winberg
Approved Examiner Supervisor
2018-06-13 Lihui Wang Abdullah Alhusin Alkhdur
Commissioner Contact person
Sandvik Coromant Michael A Sköld

Abstract
The fourth industrial revolution is emerging, where connection and data driven production has the
potential to create self-optimizing factories, in which machines and systems can communicate in
real-time. However, adopting new technologies can impose big changes but also create competitive
advantages for organisations, which is certainly the case of Industry 4.0.

The purpose of the study was to identify what main factors that affects the adoption of Industry
4.0 for production organisations and how problems in automated production cells could be
reduced by introducing Industry 4.0 concepts. The study was performed as a case study at Sandvik
Coromant, where observations and interviews were conducted. In addition, five external
organisations specialized in industrial digitalization were interviewed.

The study found that there are various factors affecting the adoption of Industry 4.0 categorized
into technological, organisational and external/environmental factors. In terms of technology,
small scale applications, increased transparency through connection and an increased integration
of information systems have positive effect on the adoption of Industry 4.0. In organisational
context, production organisations must acquire digital competence, integrate their IT organisation
into their production and change the culture and attitude towards the adoption of Industry 4.0.
Furthermore, standardization, creation of ecosystem and IT security are the main
external/environmental aspects which affect Industry 4.0 adoption.

At Sandvik Coromant, eleven problems were identified which has the potential to be reduced by
implementing concepts of Industry 4.0. The study proposes use of connectivity, visualization, data
analysis to reduce these problems.

Key-words: Technology adoption, Industry 4.0, CPS, IoT, Automated production cells
I I (IV)
Foreword
This study was conducted as a master thesis at the Royal Institute of Technology in the spring of
2018 and comprises of 30 academic credits. The case study was performed at Sandvik Coromant
in Gimo.

The report has been published in two identical copies, one published by the Department of
Industrial Economics and Management, and one published by the Department of Production
Engineering.
Acknowledgements
A special thanks and gratitude towards our commissioner Sandvik Coromant and in particular our
supervisors, Michael A Sköld and Simon Åkerblad. Their experience and enthusiastic support has
guided us in the right direction and truly improved the quality of the study.

We would also like to thank our academic supervisors at the Royal Institute of Technology, Anna
Jerbrant, for her patient support and many encouraging discussions, as well as Abdullah Alhusin
Alkhdur, for providing valuable input and criticism reviewing our work.

Furthermore, this thesis would not have been possible without the contribution of all interviewees.
Therefore, we would like to thank the operators at Sandvik Coromant in Gimo, employees at
Sandvik Coromant and the external interviewees who willingly contributed with their time and
experience.

Lastly, we would like to thank our families and friends for their support and understanding
throughout the research process.

The Royal Institute of Technology
Stockholm, June 2018

_________________ _________________
Jesper Ahrén Emil Winberg

I I I (IV)
Abbreviation

AI Artificial Intelligence
BMBF Bundesministerium für Bildung und Forschung (German federal ministry of
education)
CAD Computer-Aided Design
CAM Computer Aided Manufacturing
CODE Center of Digital Excellence
CPS Cyber-Physical System
CPPS Cyber-Physical Production System
CNC Computer Numerical Control
CMM Coordinate-Measuring Machine
ERP Enterprise Resource Planning
GH Gimo Hårda (The production unit for cutting inserts in Gimo)
GV Gimo Verktyg (The production unit for tools in Gimo)
GVP Gimo Verktyg Produktion (Gimo tool production)
H2H Human to Human communication
HMI Human Machine Interaction
IoT Internet of Things
KPIs Key Performance Indicators
M2H Machine to Human communication
M2M Machine to machine communication
MES Manufacturing Execution System
MRP Material Requirements Planning
PLC Programmable Logic Controller
SMS Sandvik machining solutions
TAM Technology-Acceptance Model
TOE Technology-Organisation-Environment framework
UX User Experience
VP Visual Planning
VR Virtual Reality

I V (IV)
Table of Contents
1 INTRODUCTION ....................................................................................................... 1
1.1 BACKGROUND ........................................................................................................................................... 1
1.2 PROBLEM FORMULATION ........................................................................................................................ 2
1.3 PURPOSE ..................................................................................................................................................... 3
1.4 RESEARCH QUESTIONS ............................................................................................................................ 3
1.5 DELIMITATIONS ........................................................................................................................................ 3
1.6 EXPECTED CONTRIBUTION .................................................................................................................... 4
1.7 DISPOSITION ............................................................................................................................................. 4
2 METHODOLOGY ....................................................................................................... 5
2.1 RESEARCH APPROACH ............................................................................................................................. 5
2.2 RESEARCH DESIGN ................................................................................................................................... 6
2.3 DATA GATHERING METHODS ................................................................................................................ 7
2.4 DATA ANALYSIS ..................................................................................................................................... 11
2.5 RESEARCH QUALITY .............................................................................................................................. 12
3 LITERATURE STUDY ............................................................................................. 14
3.1 INTRODUCTION TO INDUSTRY 4.0 ..................................................................................................... 14
3.2 CONCEPTS OF INDUSTRY 4.0 ............................................................................................................... 18
3.3 RISKS AND REQUIREMENTS WITH INDUSTRY 4.0 ............................................................................ 23
4 THEORETICAL FRAMING .................................................................................... 26
4.1 TECHNOLOGY ADOPTION IN ORGANISATIONS ............................................................................... 26
4.2 TECHNOLOGY ACCEPTANCE IN THE CONTEXT OF INDUSTRY 4.0 .............................................. 30
5 SANDVIK COROMANT ........................................................................................... 31
5.1 COMPANY OVERVIEW ........................................................................................................................... 31
5.2 GIMO VERKTYG .................................................................................................................................... 32
5.3 AUTOMATED PRODUCTION CELLS ..................................................................................................... 33
6 RESULTS AND ANALYSIS ...................................................................................... 44
6.1 PROBLEMS IN AUTOMATED PRODUCTION CELLS ............................................................................ 44
6.2 TECHNOLOGICAL FACTORS AFFECTING INDUSTRY 4.0 ADOPTION ............................................ 58
6.3 ORGANISATIONAL FACTORS AFFECTING INDUSTRY 4.0 ADOPTION ........................................... 68
6.4 ENVIRONMENTAL FACTORS AFFECTING INDUSTRY 4.0 ADOPTION ........................................... 77
6.5 ALIGNMENT BETWEEN PROBLEMS AND FACTORS AFFECTING ADOPTION ............................... 83
7 CONCLUSION .......................................................................................................... 85
7.1 ANSWERING THE RESEARCH QUESTIONS ......................................................................................... 85
7.2 SUSTAINABILITY IMPLICATIONS ......................................................................................................... 88
7.3 FUTURE WORK ....................................................................................................................................... 89
LIST OF REFERENCES .................................................................................................. 91
APPENDIX ........................................................................................................................ 96
Table of Figures
FIGURE 1. RESEARCH APPROACH. .............................................................................................................................. 5
FIGURE 2. PROJECT ACTIVITIES AND TIMELINE. ......................................................................................................... 6
FIGURE 3. LITERATURE STUDY STRUCTURE. ............................................................................................................. 14
FIGURE 4. THE FOURTH INDUSTRIAL REVOLUTIONS (ROSER, 2015). ........................................................................ 15
FIGURE 5. DEFINITION OF INDUSTRY 4.0 (LEAP AUSTRALIA, 2017). ....................................................................... 15
FIGURE 6. CPS FRAMEWORK (LEE, ET AL., 2015). .................................................................................................... 17
FIGURE 7. MAIN INDUSTRY 4.0 CONCEPTS. .............................................................................................................. 18
FIGURE 8. STAGES OF A BUSINESS ECOSYSTEM (CITED FROM JAMES F. MOORE (1993)). .......................................... 29
FIGURE 9. SANDVIK GROUP: ORGANISATIONAL STRUCTURE. .................................................................................. 32
FIGURE 10. MILLING, TURNING AND DRILLING TOOLS. ........................................................................................... 32
FIGURE 11. GV FACTORY LAYOUT. .......................................................................................................................... 33
FIGURE 12. CONCEPTUAL VIEW OF AN AUTOMATED PRODUCTION CELL. ................................................................ 34
FIGURE 13. WORK PROCEDURE STEPS. ..................................................................................................................... 34
FIGURE 14. OVERVIEW OF AN AUTOMATED PRODUCTION CELL. ............................................................................. 39
FIGURE 15. AUTOMATED PRODUCTION CELL, INCLUDING: (1) WAGONS, (2) PALETTES, (3) ROBOT, (4) CNC AND (5)
FIXTURE SHELF. .............................................................................................................................................. 40
FIGURE 16. CELL MANAGER SOFTWARE HOME PAGE. ............................................................................................... 41
FIGURE 17. CELL MANAGER SOFTWARE VIEW FOR ORDER MANAGEMENT. .............................................................. 42

Table of Tables
TABLE 1. DISPOSITION OF THE REPORT WITH DESCRIPTIONS TO EACH CHAPTER. ...................................................... 4
TABLE 2. KEYWORDS USED FOR OBTAINING LITERATURE. .......................................................................................... 7
TABLE 3. INTERVIEWS WITH PRODUCTION STAFF. ...................................................................................................... 9
TABLE 4. INTERVIEWS WITH NON-OPERATIVE EMPLOYEES AT SANDVIK COROMANT. ............................................. 10
TABLE 5. INTERVIEWS WITH EXTERNAL ORGANISATIONS. ....................................................................................... 10
TABLE 6. SUMMARY OF PROBLEMS IN AUTOMATED PRODUCTION CELLS. ................................................................. 57
1 INTRODUCTION
1 Introduction
In this chapter, the background of the research is presented, followed by the problem formulation, purpose and research
questions. Finally, limitations, expected contribution as well as report disposition is presented.
1.1 Background
Introduction of new technologies can enable competitive advantages for the organisations which
manages to adopt these technologies, but it can also create big changes in the market and the way
businesses is managed. This includes changes in both internal operations and customer offerings,
consequently pressuring companies to adopt to these new technologies (Lanzolla & Suarez, 2012).
Companies that fails to adopt new emerging technologies may be overtaken by more successful
competitors. Tornatzky & Fleischer (1990) found that technological adoption is affected by more
than just the technology itself, and that an organisation should consider other aspects as well
(Baker, 2011). To describe technological adoption in organisations, Tornatzky & Fleischer (1990)
created the Technology-Organisation-Environmental Framework which acknowledges that
technology adoption needs to consider not only the technological context itself, but also the
organisational and environmental context (Baker, 2011). In the case when a new technology is
intended to be used by actors within an organisation, it is not sufficient for the organisation to only
adopt the technology. Lanzolla & Suarez (2012) suggest that organisations also must make sure
that the adopted technologies are accepted by the intended users. If not, organisations can risk
making unnecessary efforts and investments in technologies that will eventually be perceived as
redundant by its indented users (Lanzolla & Suarez, 2012). To enable technology acceptance, the
Technology acceptance model (TAM model) can be used to explain how technologies are accepted
by users. It states that acceptance is dependent on two main characteristics: perceived usefulness and
perceived ease of use (Davis, 1989).

The production industry has historically faced many introductions of technology, the most
important are categorized into the four industrial revolutions. These revolutions have enabled
technological advancements and industrialization in many countries, leading up to today’s
production systems (Liao, et al., 2017). The first industrial revolution started in the later part of the
18th century with the introduction of machines and mechanical production. In the beginning of
the 20th century, the second industrial revolution took place and introduced the production line
and electrical powered mass production. The third industrial revolution, which is still ongoing,
started in the 1970s and includes the application of information technology and electronics in
production system to increase the level of production automation. The next industrial revolution,
Industry 4.0, is highly driven by internet, digitalisation and technology to enable a far smarter and
connected industrial era (Kagermann, et al., 2013). While the fourth industrial have not yet been
fully executed, it is still expected to create significant change in existing industries and organisations.
Many countries have developed strategic initiatives and allocated billions of euros to support the
digitalisation and transition towards Industry 4.0. This includes countries such as Germany, Japan,
US, UK, Singapore and Sweden (Swedish Government Office, 2017) as well as the European
Union (Liao, et al., 2017) to name a few.

The coming industrial revolution, Industry 4.0, may offer an even more sophisticated production
industry through increased digitalisation and creating a better representation of the physical world
in the digital systems used in the production. Some characteristics of Industry 4.0 are that machines
and processes in the value chain can communicate and act independently, as well as make optimized
and proactive decisions (Kagermann, et al., 2013). For many production companies, Industry 4.0
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1 INTRODUCTION
has great potential in terms of reducing cost and improving efficiency. In a survey with 235
European manufacturers, 36 % believe that Industry 4.0 will increase efficiency between 11-20 %
in 5 years while 37 % expect the efficiency to increase with over 20 %. In the same survey, 35 %
of the production companies expect that Industry 4.0 will reduce cost with 11-20 % while 21 %
expect costs to be reduced by over 20 %. Some of the most promising areas of Industry 4.0 are
better control and planning of production processes, improved quality and increased flexibility by
enabling data analysis, information exchange and use of real-time data (Geissbauer, et al., 2014).
Clearly, adopting to Industry 4.0 have the possibility to enable huge advantages in terms of quality,
cost benefits, flexibility and product customization if adopted properly (Baheti & Gill, 2011;
MacDougall, 2014).

An enabler of Industry 4.0 is Internet of Things (IoT), which is a concept on the connection and
information sharing of objects such as machines, equipment, sensors and other objects
(Dorsemaine, et al., 2015). IoT in an industrial setting enables the connection of the physical and
digital world, integrating them even further and creating a Cyber-Physical System (CPS). CPS offers
the physical entities of a system to be represented in a virtual setting, where changes in the physical
system affect the virtual equivalent and conversely (Baheti & Gill, 2011). For production processes,
CPS enables the development of smart factory capabilities such as real-time & predictive control,
learning ability, self-optimization and decentralized decision making (MacDougall, 2014; Tantik &
Anderl, 2016; Pai, et al., 2018; Lu, 2017). The use of IoT and CPS in production creates vast amount
of data and information, which has the potential to be processed and analysed to provide insight
and decision support to humans in the organisation. The handling and analysis of big amount of
data is referred to as Big Data. However, to be able to bring the full potential of Big Data, new
capabilities may be required, and high quality of the data is essential (Yi, et al., 2014; Demchenko,
et al., 2013)

Even though Industry 4.0 may increase the usage of machines that can process information and
independently act upon it, thanks to smart communication and data analytics, humans is expected
to be a central part of the future production systems (Lu, 2017; Chen, et al., 2017). By designing
the production systems around individuals, strong human capabilities such as creativity and
flexibility can be enhanced, while the amount of monotonous and redundant tasks can be reduced.
Thus, data analysis and connectivity through IoT and CPS can be used to deliver information or
decision support to operators in the right way, at the right time and to the right person (Gorecky,
et al., 2014).

To summarize, in the context of Industry 4.0, IoT and CPS have the possibility to enable an
increased connectivity and information sharing. At the same time, data analysis enables this
information flow to be processed to provide insights and decision support. Finally, humans will
need to act on many of these insights and interact with machines and systems, which requires
human-machine interaction. These concepts, connection of the physical world, analysis of data and
human-machine interaction are the focus areas of Industry 4.0 in this report.
1.2 Problem formulation
While the benefits of Industry 4.0 are perceived as high, there are still many challenges to overcome.
Some of the biggest obstacles for adoption of Industry 4.0 in production are that specific benefits
are unclear and that initial investments are high. There is also a need for more qualified staff and
technology- and data/IT standardization (Geissbauer, et al., 2014). In a survey with 1,600
participating companies, only 15 % expressed that they are prepared to adopt smart technologies.
Furthermore, the ability to upgrade current facilities is a high influencing factor affecting
technology investments (Deloitte Insights, 2017).
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