Industry 4.0 from the MIS Perspective

by Sevinc Gülseçen (Volume editor) Zerrin Ayvaz Reis (Volume editor) Murat Gezer (Volume editor) Çiğdem Erol (Volume editor)
Edited Collection 350 Pages


Nowadays, an end-to-end industrial transformation called Industry 4.0 sets new goals for manufacturing and impacts on business outcomes. With some of its characteristic elements such as IoT (Internet of Things), digital twin simulation models, advanced robots, big data analytics, and virtual/augmented reality, Industry 4.0 is «de facto» going further. The book aims to provide relevant theoretical frameworks and the latest empirical research findings in the area of Management Information Systems (MIS) with the scope of Industry 4.0. The strategic role of Industry 4.0 in the distributed business environment and the necessity to protect and properly utilize its key elements at different levels of organizations as well as in society are discussed.

Table Of Content

  • Cover
  • Title
  • Copyright
  • About the author
  • About the book
  • This eBook can be cited
  • Preface
  • Contents
  • List of Contributors
  • A Roadmap for Turkey’s Industry 4.0 Transformation Based on Germany’s Strategy (İdil Atasu / Meltem Özturan / Birgül Kutlu)
  • Development of a Central Controlled Automation Project on the IoT Platform (Ahmet Gürkan Yüksek / Halil Arslan / Gülşah Çifçi / M. Lemi Elyakan)
  • A Scientometrics Study on Internet of Things (IoT) (Fatma Seray Demirkan / Sona Mardikyan / Bertan Badur)
  • Secure Management Model for Scada Systems (Çağrı Doğu / Tuncay Ercan)
  • How a Workforce for Industry 4.0 Era? Labor 4.0 (Türksel Kaya Bensghir / Ufuk Türen / Yücel Yılmaz)
  • Design of Intelligent Direction Systems via Multi-Criteria Decision Making (Emre Karagöz / Vahap Tecim)
  • The Technical Challenges of Cloud Computing as a Leading Trend in Business (Ahmet Cihat Baktir / Bilgin Metin)
  • Industry 4.0 and Key Technologies: A Review (Abide Coşkun Setirek / Aysun Bozanta)
  • Current Research Topics in Industry 4.0 and an Analysis of Prominent Frameworks (Kerem Kayabay / Mehmet Ali Akyol / Mert Onuralp Gökalp / Altan Koçyiğit / P. Erhan Eren)
  • Designing of Manufacturing Process with Mobile-Based Smart Systems (Ceyda Ünal / Cihan Çılgın / Vahap Tecim)
  • Readiness of MIS Undergraduate Programs in Turkish Universities to Industry 4.0 (M. Hanefi Calp / Ahmet Doğan / Aslıhan Tüfekci / Türksel Kaya Bensghir)
  • Industry 4.0 Revolution in Clothing and Apparel Factories: Apparel 4.0 (Ebru Gökalp / Mert Onuralp Gökalp / P. Erhan Eren)
  • Issues Regarding Deployment of IPv6 and Business Model Canvas for IPv6 (Mehmet N. Aydın / Ebru Dilan)
  • Big Problem in Health 4.0: Access and Protection of Electronic Health Records (Şebnem Akal)
  • Industry 4.0 and Turkey: A Chance or a Thread? (Tuğba Koç / Alptekin Erkollar / Birgit Oberer)
  • The Rising Fundamental Skills of IT Field in Industry 4.0 Age (Sevinç Gülseçen / Doğan Aydın)
  • Vehicle Sales Prediction Using Neural Fuzzy Logic Method in Industry 4.0 (Umut Kaya / Atınç Yılmaz / Kadir Keskin)
  • The Next Industrial Revolution: Industry 5.0 and Discussions on Industry 4.0 (Kadir Alpaslan Demir / Halil Cicibaş)
  • Industry 4.0 as High Technology and Evaluation of Turkey (Uğur Keleş / Zümrüt Ecevit Satı)
  • Augmented Reality 4.0: Opportunities and Challenges for Smart Factories (Gülay Ekren / Birgit Oberer / Alptekin Erkollar)
  • Toward A Maturity Model for Industry 4.0: A Systematic Literature Review (Umut Şener / Ebru Gökalp / P. Erhan Eren)
  • Toward Industry 4.0: Challenges of ERP Systems for SMEs (Gülay Ekren / Alptekin Erkollar / Birgit Oberer)
  • Big Data on Cloud for Telecommunications Industry (Abdulkadir Hızıroğlu / Dilan Özcan Kalfa / Ourania)
  • Challenges and Opportunities of Logistics 4.0: Reflections from Industry 4.0 (Zümrüt Ecevit Satı)
  • Index

← 10 | 11 →

List of Contributors

Şebnem Akal

Marmara University, İstanbul, Turkey, sebnemakal@marmara.edu.tr

Musab Talha Akpınar


Mehmet Ali Akyol

Middle East Technical University, Ankara, Turkey, aliakyol@metu.edu.tr

Ourania Areta


Halil Arslan

Cumhuriyet University, Sivas, Turkey, harslan@cumhuriyet.edu.tr

İdil Atasu

Bogazici University, İstanbul, Turkey, idil.atasu@boun.edu.tr,

Doğan Aydın

Bahcesehir University, İstanbul, Turkey, dogan.aydin@vs.bau.edu.tr

Mehmet N. Aydin

Kadir Has University, Istanbul, Turkey, mehmet.aydin@khas.edu.tr

Bertan Badur

Boğaziçi University, İstanbul, Turkey, badur@boun.edu.tr

Ahmet Cihat Baktir

Bogazici University, Istanbul, Turkey, cihat.baktir@boun.edu.tr

Dr. Türksel Kaya Bensghir

Todaie, Ankara, Turkey, tbensghir@gmail.com

Aysun Bozanta

Boğaziçi University, İstanbul, Turkey, aysun.bozanta@boun.edu.tr

M. Hanefi Calp

Karadeniz Technical University, Trabzon, Turkey, hcalp25@hotmail.com

Gülşah Çifçi

Erciyes University, Kayseri, Turkey, gulsahhcifci@gmail.com

Cihan Çılgın

Dokuz Eylül University, İzmir, Turkey, cihan.cilgin@deu.edu.tr

Halil Cicibaş

Middle East Technical University, Ankara, Turkey, halil.cicibas@metu.edu.tr

Abide Coşkun Setirek

Boğaziçi University, İstanbul, Turkey, abide.coskunr@boun.edu.tr

Kadir Alpaslan Demir ← 11 | 12 →

Turkish Naval Research Center Command, Istanbul, Turkey, kadiralpaslandemir@gmail.com

Fatma Seray Demirkan

Boğaziçi University, İstanbul, Turkey, seray.demirkan@boun.edu.tr

Ebru Dilan

Kadir Has University, Istanbul, Turkey, ebru.dilan@khas.edu.tr

Ahmet Doğan

Osmaniye Korkut Ata University, Osmaniye, Turkey, ahmetdogan@osmaniye.edu.tr

Çağrı Doğu

Energy Holding A.S., Kavacik Meydani, Energy Plaza Kat: 8, 34805, Beykoz, Istanbul, Turkey

Yasar University, Dep. of Comp. Eng., Izmir, Turkey, cdogu@enerjeo.com

Gülay Ekren

Sinop University, Sinop, Turkey, gekren@sinop.edu.tr

M. Lemi Elyakan

Cumhuriyet University, Sivas, Turkey, mlelyakan@gmail.com

Tuncay Ercan

Yasar University, Dep. of Comp. Eng., Izmir, Turkey, tuncay.ercan@yasar.edu.tr

Alptekin Erkollar

Sakarya University, Sakarya, Turkey, erkollar@sakarya.edu.tr

P. Erhan Eren

Middle East Technical University, Ankara, Turkey, ereren@metu.edu.tr

Ebru Gökalp

METU, Ankara, Turkey, egokalp@metu.edu.tr

Mert Onuralp Gökalp

Middle East Technical University, Ankara, Turkey, gmert@metu.edu.tr

Sevinç Gülseçen

Istanbul University, İstanbul, Turkey, gulsecen@istanbul.edu.tr

Abdulkadir Hızıroğlu


Dilan Özcan Kalfa


Emre Karagöz

Dokuz Eylül University, İzmir, Turkey, emre.karagoz@deu.edu.tr

Umut Kaya

Kavram Vocational High School, İstanbul, Turkey, umut.kaya@kavram.edu.tr

Kerem Kayabay

Middle East Technical University, Ankara, Turkey, kayabay@metu.edu.tr ← 12 | 13 →

Ugur Keles

Istanbul University, İstanbul, Turkey, ugur.keles@ogr.iu.edu.tr

Kadir Keskin

Kavram Vocational High School, İstanbul, Turkey, kadir.keskin@kavram.edu.tr

Tuğba Koç

Sakarya University, Sakarya, Turkey, tcekici@sakarya.edu.tr

Altan Koçyiğit

Middle East Technical University, Ankara, Turkey, kocyigit@metu.edu.tr

Birgul Kutlu

Bogazici University, İstanbul, Turkey, birgul.kutlu@boun.edu.tr

Sona Mardikyan

Boğaziçi University, İstanbul, Turkey, mardikya@boun.edu.tr

Bilgin Metin

Bogazici University, Istanbul, Turkey, bilgin.metin@boun.edu.tr

Birgit Oberer

Sakarya University, Sakarya, Turkey, oberer@sakarya.edu.tr

Meltem Ozturan

Bogazici University, İstanbul, Turkey, ozturanm@boun.edu.tr,

Zümrüt Ecevit Satı

Istanbul University, İstanbul, Turkey, zsati@istanbul.edu.tr

Umut Şener

METU, Ankara, Turkey, sumut@metu.edu.tr

Vahap Tecim

Dokuz Eylül University, İzmir, Turkey, vahap.tecim@deu.edu.tr

Aslıhan Tüfekci

Gazi University, Ankara, Turkey, asli@gazi.edu.tr

Dr. Ufuk Türen

Turkish Military Academy, Ankara, Turkey, uturen2011@gmail.com

Ceyda Ünal

Dokuz Eylül University, İzmir, Turkey, ceyda.unal@deu.edu.tr

Atınç Yılmaz

Beykent University, İstanbul, Turkey, atincyilmaz@beykent.edu.tr

Dr. Yücel Yılmaz

Marmara University, İstanbul, Turkey, yucelyilmaz@marmara.edu.tr

Ahmet Gürkan Yüksek

Cumhuriyet University, Sivas, Turkey, agyuksek@cumhuriyet.edu.tr ← 13 | 14 →

← 14 | 15 →

İdil Atasu*, Meltem Özturan and Birgül Kutlu

A Roadmap for Turkey’s Industry 4.0 Transformation Based on Germany’s Strategy

1.  Introduction

Since the end of the 18th century, the world has gone through three distinct industrial revolutions triggered by technology. The first one was around 1784 following the introduction of water-/steam-powered mechanical manufacturing facilities. The second one was following the introduction of electrically powered mass production based on the division of labor in the 1870s. The third one started in the early 1970s and has since continued to the present, which involved the employment of electronics and information technology (IT) in order to achieve increased automation of manufacturing processes. The machines have since then taken over most of the manual labor and some of the brainwork (Kagermann, Helbig, Hellinger & Wahlster, 2013). Thus, whereas up until and including the second industrial revolution the production was labor intensive, with the third industrial revolution a shift has begun toward capital-intensive production. When we look at the previous industrial revolutions, the commonality among them is that they have been ignited by technology improvements that have appeared through mechanization, electricity and IT.

Nowadays, what is capturing the industrial world is the advancement of the fourth industrial revolution, or Industry 4.0. The term was first used in Germany at the Hannover Fair in 2011 (Vogel-Heuser & Hess, 2016). In North America, similar ideas are gathered around the term “Industrial Internet”, which is used to refer to a broader concept than industrial production (Drath & Horch, 2014).

Manufacturing needs to shift from mass production to mass customization, and it needs to move toward lack of inventory and instead create “on demand” products close to the centers of demand. This would require optimizing the capital used, and the fourth industrial revolution is shaped around this idea (Dujin & Geissler, 2016). ← 15 | 16 →

The fourth industrial revolution has been occurring as a result of the incorporation of the Internet of Things (IoT) into the manufacturing environment (Kagermann, Helbig, Hellinger & Wahlster, 2013). The IoT is basically the connection of objects to the Internet instead of human beings. These objects exchange data through embedded sensors. The application of the IoT into the factory environment will be via cyber physical structures. A Cyber Physical Structure (CPS) is the interaction between humans and cyber physical systems. Since a CPS is made up of a physical and virtual, digital component, the interaction between the human and the CPS occurs by either manipulating the physical component directly or via a user interface where the virtual component is managed by humans (Gorecky, Schmit, Loskyll & Zuhlke, 2014). In a manufacturing environment, the CPS will comprise of smart machines, storage systems and other production facilities that would be capable of autonomously exchanging data, triggering actions in related objects and all of these smart objects define smart factories. Within this framework, smart objects or products know their own history, current status and all possible routes to reaching their target. They are also uniquely identifiable, which makes it possible to monitor their movements and states. Business processes within the factories are vertically linked to these manufacturing systems and horizontally connected to the business value networks that are managed starting from when an order is placed that continues until the end when the final product reaches the customer (Kagermann, Helbig, Hellinger & Wahlster, 2013). Thus, with the creation of the smart factories, there will begin a phase of cost-cutting in terms of capital, energy and personnel as well as more flexibility, reduced lead times and adaptation to customer requirements with small batch sizes (Heng, 2014).

Industry 4.0 will also address and is expected to solve some of the challenges of the world today, which include resource and energy efficiency, urban production and demographic change. That is because Industry 4.0 is expected to enable resource productivity and efficiency gains that will affect the entire value network (Kagermann, Helbig, Hellinger & Wahlster, 2013). Industry 4.0 overall is that term that describes the changes of the manufacturing and production industry landscape of the developed world (Brettel, Friederichsen, Keller & Rosenberg, 2014).

Unlike the previous industrial revolutions that were triggered from technological innovations, Industry 4.0 is a planned attempt for a revolution of production systems. Globalization has increased competition of companies producing in high-wage countries (Schuh, Klocke, Brecher & Schmitt, 2007). Cost advantages in production, especially that of labor cost, have caused relocation of ← 16 | 17 → production from high-wage countries to low-wage countries. Therefore, companies in low-wage countries are mainly focusing on mass production (economies of scale) and those in high-wage countries have to balance their production among mass production and producing customized products (economies of scope). In order to maintain a balance, the latter types of companies have to optimize their processes using capital-intensive tools and systems. Thus in the case of production economy there is a dilemma between economies of scale and scope. Since mass production requires standardized automation, it undermines flexibility that is attained through economies of scope. Another dilemma in production is the one between value orientation and planning orientation in the production planning process. The first comes with costly planning efforts and is beneficial in the long run while the latter focuses on maximizing value by efficient planning processes (Schuh et al., 2013). These two dilemmas make up the polylemma of production (Brecher et al., 2012). In Germany, The Cluster of Excellence “Integrative Production Technology for High-Wage Countries” of RWTH University focuses on resolving this polylemma through individualization, virtualization, hybridization and self-optimization. All of these four research areas have strong links to the topic of Industry 4.0 (Brettel, Friederichsen, Keller & Rosenberg, 2014). Germany has a special interest in the topic because according to German Chamber of Commerce and Industry, one in four German industrial companies have relocated to low-cost countries. However, relocation of production also results in relocation of R&D and services, and for high-wage countries, securing domestic production is a vital part of securing national wealth (Brecher et al., 2012).

German firms create one-third of EU’s total value added (Heng, 2014) and Germany has significantly improved its return on capital employed over the last 15 years, despite a 9 % drop in employment. The value added of German industry has risen 80 % between 2000 and 2014 and the profits have risen 158 % during the period. The rate of use of production equipment rose from 85 % in 1998 to 95 % in 2014.

Thus, for Germany, a successful transformation of the manufacturing industry is of high importance as it contributes over 25 % of the Gross Domestic Product (GDP) and provides over seven million jobs as announced by Eurostat and the Federal Statistical Institute of Germany (as cited in Brettel, Friederichsen, Keller & Rosenberg, 2014, p. 37). Therefore, a strategic proposal for the implementation of Industry 4.0 was issued in 2013 after the collaboration of German government, industry and research institutions. In December 2013, Germany released the standardization roadmap, and German Industry 4.0 has become the ← 17 | 18 → national strategic plan to increase German global competitiveness by 2020 (Zhang, Peek, Pikas & Lee, 2016).

German Industry 4.0 uses certain strategies in its transformation to Industry 4.0 that can be listed as: attaining standardization and open standard reference systems, setting up models to manage the complex systems, providing a comprehensive broadband infrastructure, establishing security mechanisms, innovating the organization and design models, emphasizing training and continuous professional development and establishing sound rules and regulations to improve resource efficiency (Zhang, Peek, Pikas & Lee, 2016).

As a result of the transformation to Industry 4.0, German manufacturing sectors are expected to boost their productivity by 5–8 % or 90–150 billion Euros over the next ten years. Increased corporate demand in advanced technologies as well as demand for customized products is expected to add on additional revenues of 300 billion Euros and an increase employment by 6 %. In addition capital investment is expected to revert the cost advantage in production back to Germany by cutting the costs by 20 % (Numanoglu, Eynehan, Morkoc-Nikelay & Aksoy, 2016).

In comparison to the German economy, Turkish economy is the 17th largest economy in the world as of 2014. The 75 % urban population of Turkey supports its industrial manufacturing based economy (Tuncel, 2014). Until 2008, the EU’s share in Turkey’s exports was higher than 50 %. But after 2008, this share began declining, whereas the share of Middle East and North Africa began increasing. Given the demographic structures of EU with an aging population and Turkey with a young and active human capital stock, Turkey has been exporting labor-intensive products and importing capital-intensive products from the EU (Alpaslan, 2012).

In order to assess the manufacturing productivity in Turkey, manufacturing value added can be observed. Manufacturing value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. As of 2013, Turkey ranks 16th in current USDs in terms of manufacturing value added.

Biographical notes

Sevinc Gülseçen (Volume editor) Zerrin Ayvaz Reis (Volume editor) Murat Gezer (Volume editor) Çiğdem Erol (Volume editor)

Sevinç Gülseçen has her doctoral degree in artificial neural networks from the Faculty of Business, İstanbul University. Her primary teaching and research interests are system analysis and design, constructivist learning, e-learning, social informatics, and knowledge management. Zerrin Ayvaz Reis received her PhD degree from İstanbul University, Natural Sciences Institute, Department of Computer Sciences Engineering. Her research interests focus on UML methodology, software engineering, database management systems, e-learning, disadvantaged groups and social responsibility studies. Murat Gezer received his PhD degree from Istanbul University. His areas of interest include Linux, machine learning, artificial intelligence and image processing. Çiğdem Erol received her PhD degree from İstanbul University, Institute of Science. Her research interests focus on bioinformatics, microarray data analysis and data mining.


Title: Industry 4.0 from the MIS Perspective