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Türkiye'deki Üniversitelerin Endüstri 4.0 Farkındalığı Üzerine Bir Çalışma

Year 2021, Volume: 01 Issue: 02, 35 - 50, 31.12.2021

Betül Soyöz Bahar Özyörük

Abstract

2011 yılında Almanya'da ortaya çıkan Endüstri 4.0, ülkelerin ilgisini çekti. 2011 yılından bu yana, çeşitli ülkelerdeki şirketler ve araştırmacılar, Endüstri 4.0'ın avantajlarını, dezavantajlarını, ülkelerine katkılarını ve geçiş aşamalarını anlamak için araştırmalar yapmaktadırlar. Bu çalışmada, akademik dünyadaki Endüstri 4.0 farkındalığı araştırılmıştır. Araştırma kapsamında bir online anket hazırlanmıştır. Üniversitelerin mühendislik fakültelerinde bulunan bölümlerin akademik personeline ve işletme bölümünde bulunan akademik personele çevrimiçi anket platformu yoluyla sorular gönderilmiştir.. Çalışmanın uygulandığı bölümlerdeki akademisyenlerin farkındalıkları yüksek olmakla birlikte, Endüstri 4.0 alanındaki çalışmaları çok azdır.

Keywords

endüstri 4.0 anket analizi vaka çalışması Endüstri 4.0'ın bileşenleri

References

  • [1] Fang, F. (2016). Atomic and close-to-atomic scale manufacturing - A trend in manufacturing development. Frontiers of Mechanical Engineering, 11, 4, 325-327.
  • [2] Macdougall, W. (2014). Industrie 4.0: Smart manufacturing for the future, Technical report of Germany Trade and Invest.
  • [3] Firat, O.Z. and Umit Firat, S. (2017). Endüstri 4.0 Yolculuğunda Trendler Ve Robotlar. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 46, 2, 211-223.
  • [4] Kolberg, D. and Zühlke, D. (2015). Lean Automation Enabled by Industry 4.0 Technologies. IFAC- PapersOnline, 48, 3, 1870-1875.
  • [5] Hazen, B.T., Skipper, J.B., Ezell, J.D. and Boone, C.A. (2016). Big Data And Predictive Analytics for Supply Chain Sustainability: A Theory-Driven Research Agenda. Computer and Industrial Engineering, 101, 592–598.
  • [6] Rozados, I. V. and Tjahjono, B. (2014). Big Data Analytics in Supply Chain Management: Trends and Related Research. 6th International Conference on Operations and Supply Chain Management, 1-13.
  • [7] Leveling, J., Edelbrock, M. and Otto, B. (2014). Big Data Analytics for Supply Chain Management. The IEEE International Conference on Industrial Engineering and Engineering Management, 918-922.
  • [8] Tuncel, S., Candan, Z. and Satir, A. (2018). Mobilya Endüstrinde Gelecek Vizyonu Endüstri 4.0. İleri Teknoloji Bilimleri Dergisi, 152-158.
  • [9] Bhargava, B. and Ranchal, R. (2013). Secure Information Sharing in Digital Supply Chains. 3rd IEEE International Advance Computing Conference, 1636-1630.
  • [10] Issa, A., Hatiboglu, B., Bildstein, A. and Bauernhansl, T. (2018). Industry 4.0 Roadmap: Framework For Digital Transformation Based On The Concepts Of Capability Maturity And Alignment. Procedia CIRP, 72, 973-978.
  • [11] Kocak, A. and Diyadin, A. (2018). Sanayi 4.0 Geçiş Süreçlerinde Kritik Başarı Faktörlerinin Dematel Yöntemi ile Değerlendirilmesi. Ege Academic Review, 181, 107-120
  • [12] Buyukozkan, G. and Gocer, F. (2018), “Digital Supply Chain: Literature Review and a Proposed Framework For Future Research”, Computers in Industry, 157-177.
  • [13] Buyukozkan, G. and Goçer, F. (2017a). An Extention of ARAS Methodology Based On Interval Valued Intuitionistic Fuzzy Group Decision Making For Digital Supply Chain. 2017 IEEE Int. Conf. Fuzzy Syst., 1-6.
  • [14] Buyukozkan, G. and Goçer, F. (2017b). An Extension of MOORA Approach for Group Decision Making Based on Interval Valued Intuitionistic Fuzzy Numbers In Digital Supply Chain. 2017 Jt. 17th World Congr. Int. Fuzzy Syst. Assoc. 9th Int. Conf., 1-6.
  • [15] Tsai, W.H. and Lu, Y. H. (2018). A Framework of Production Planning and Control with Carbon Tax under Industry 4.0. Sustainability Journal, 10(9), 1-24.
  • [16] Schumacher, A., Erol, S. and Sihn, W. (2016). A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises. Procedia CIRP, 52, 161-166.
  • [17] Oztemel, E. and Gursev, S. (2018). Türkiye’de Lojistik Yönetiminde Endüstri 4.0 Etkileri ve Yatırım İmkanlarına Bakış Üzerine Anket Uygulaması. Marmara Fen Bilimleri Dergisi, 2, 157-168.
  • [18] Hamzeh, R., Zhong, R., Xu, X. W., Kajáti, E. and Zolotova I. (2018). A Technology Selection Framework For Manufacturing Companies in The Context Of Industry 4.0. 2018 World Symposium on Digital Intelligence for Systems and Machines, 268-276.
  • [19] Dalenogarea, L. S.,Beniteza, G. B.,Ayalab, N. F., Franka,A. G. (2018). The Expected Contribution of Industry 4.0 Technologies for Industrial Performance. International Journal of Production Economics, 204, 383-394.
  • [20] Mittal, S., Khan, M.A., Romero, D., Wuest, T. (2018). A critical review of smart manufacturing & Industry 4.0 maturity models: Implications for small and medium-sized enterprises (SMEs). Journal of Manufacturing Systems, 49, 194-214.
  • [21] Frank, A. G., Dalenogare, L. S., Ayala, N. F. (2019). Industry 4.0 Technologies: Implementation Patterns in Manufacturing Companies. International Journal of Production Economics, 210, 15-26.
  • [22] Dutta, G., Kumar, R., Sindhwani, R., Singh, R. K. (2020). Digital Transformation Priorities of India’s Discrete Manufacturing SMEs – A Conceptual Study in Perspective of Industry 4.0. Competitiveness Review: An International Business Journal 30 (3), 289-314.
  • [23] Ozyoruk B. and Soyoz B. (2019). Endüstri Mühendisliği Öğrencilerinin Endüstri 4.0 Farkindalığı Üzerine Bir Çalışma. Middle East International Conference On Multidisciplinary Studies, 1, 401-409.
  • [24] Alcin, S. (2016). Üretim için yeni bir izlek: sanayi 4.0, Journal of Life Economics, 8, 19-30.
  • [25] Cekici, V. (2013). Müşteri Şikayet Değerlendirme Süreçleri İçin Kavramsal Bir Model ve Simülasyon Optimizasyon Yöntemi ile Değerlendirilmesi. Doktoral thesis, Cukurova University, Adana.

A Study on Industry 4.0 Awareness of Universities in Turkey

Year 2021, Volume: 01 Issue: 02, 35 - 50, 31.12.2021

Betül Soyöz Bahar Özyörük

Abstract

Industry 4.0, which emerged in Germany in 2011, attracted the attention of countries. Since 2011, companies and researchers in various countries have conducted researches to understand the advantages, disadvantages, contributions to their countries, and transition stages of Industry 4.0. In this study, the awareness of Industry 4.0 in the academic world was investigated. An online survey was prepared within the scope of the research. Questions were sent to the academicians working in the departments of engineering faculties and business administration of universities via an online survey platform. Although the awareness of the academicians in the departments where the study was applied is high, their studies in the field of Industry 4.0 are very few.

Keywords

industry 4.0 survey analysis case study component of industry 4.0

References

  • [1] Fang, F. (2016). Atomic and close-to-atomic scale manufacturing - A trend in manufacturing development. Frontiers of Mechanical Engineering, 11, 4, 325-327.
  • [2] Macdougall, W. (2014). Industrie 4.0: Smart manufacturing for the future, Technical report of Germany Trade and Invest.
  • [3] Firat, O.Z. and Umit Firat, S. (2017). Endüstri 4.0 Yolculuğunda Trendler Ve Robotlar. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 46, 2, 211-223.
  • [4] Kolberg, D. and Zühlke, D. (2015). Lean Automation Enabled by Industry 4.0 Technologies. IFAC- PapersOnline, 48, 3, 1870-1875.
  • [5] Hazen, B.T., Skipper, J.B., Ezell, J.D. and Boone, C.A. (2016). Big Data And Predictive Analytics for Supply Chain Sustainability: A Theory-Driven Research Agenda. Computer and Industrial Engineering, 101, 592–598.
  • [6] Rozados, I. V. and Tjahjono, B. (2014). Big Data Analytics in Supply Chain Management: Trends and Related Research. 6th International Conference on Operations and Supply Chain Management, 1-13.
  • [7] Leveling, J., Edelbrock, M. and Otto, B. (2014). Big Data Analytics for Supply Chain Management. The IEEE International Conference on Industrial Engineering and Engineering Management, 918-922.
  • [8] Tuncel, S., Candan, Z. and Satir, A. (2018). Mobilya Endüstrinde Gelecek Vizyonu Endüstri 4.0. İleri Teknoloji Bilimleri Dergisi, 152-158.
  • [9] Bhargava, B. and Ranchal, R. (2013). Secure Information Sharing in Digital Supply Chains. 3rd IEEE International Advance Computing Conference, 1636-1630.
  • [10] Issa, A., Hatiboglu, B., Bildstein, A. and Bauernhansl, T. (2018). Industry 4.0 Roadmap: Framework For Digital Transformation Based On The Concepts Of Capability Maturity And Alignment. Procedia CIRP, 72, 973-978.
  • [11] Kocak, A. and Diyadin, A. (2018). Sanayi 4.0 Geçiş Süreçlerinde Kritik Başarı Faktörlerinin Dematel Yöntemi ile Değerlendirilmesi. Ege Academic Review, 181, 107-120
  • [12] Buyukozkan, G. and Gocer, F. (2018), “Digital Supply Chain: Literature Review and a Proposed Framework For Future Research”, Computers in Industry, 157-177.
  • [13] Buyukozkan, G. and Goçer, F. (2017a). An Extention of ARAS Methodology Based On Interval Valued Intuitionistic Fuzzy Group Decision Making For Digital Supply Chain. 2017 IEEE Int. Conf. Fuzzy Syst., 1-6.
  • [14] Buyukozkan, G. and Goçer, F. (2017b). An Extension of MOORA Approach for Group Decision Making Based on Interval Valued Intuitionistic Fuzzy Numbers In Digital Supply Chain. 2017 Jt. 17th World Congr. Int. Fuzzy Syst. Assoc. 9th Int. Conf., 1-6.
  • [15] Tsai, W.H. and Lu, Y. H. (2018). A Framework of Production Planning and Control with Carbon Tax under Industry 4.0. Sustainability Journal, 10(9), 1-24.
  • [16] Schumacher, A., Erol, S. and Sihn, W. (2016). A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises. Procedia CIRP, 52, 161-166.
  • [17] Oztemel, E. and Gursev, S. (2018). Türkiye’de Lojistik Yönetiminde Endüstri 4.0 Etkileri ve Yatırım İmkanlarına Bakış Üzerine Anket Uygulaması. Marmara Fen Bilimleri Dergisi, 2, 157-168.
  • [18] Hamzeh, R., Zhong, R., Xu, X. W., Kajáti, E. and Zolotova I. (2018). A Technology Selection Framework For Manufacturing Companies in The Context Of Industry 4.0. 2018 World Symposium on Digital Intelligence for Systems and Machines, 268-276.
  • [19] Dalenogarea, L. S.,Beniteza, G. B.,Ayalab, N. F., Franka,A. G. (2018). The Expected Contribution of Industry 4.0 Technologies for Industrial Performance. International Journal of Production Economics, 204, 383-394.
  • [20] Mittal, S., Khan, M.A., Romero, D., Wuest, T. (2018). A critical review of smart manufacturing & Industry 4.0 maturity models: Implications for small and medium-sized enterprises (SMEs). Journal of Manufacturing Systems, 49, 194-214.
  • [21] Frank, A. G., Dalenogare, L. S., Ayala, N. F. (2019). Industry 4.0 Technologies: Implementation Patterns in Manufacturing Companies. International Journal of Production Economics, 210, 15-26.
  • [22] Dutta, G., Kumar, R., Sindhwani, R., Singh, R. K. (2020). Digital Transformation Priorities of India’s Discrete Manufacturing SMEs – A Conceptual Study in Perspective of Industry 4.0. Competitiveness Review: An International Business Journal 30 (3), 289-314.
  • [23] Ozyoruk B. and Soyoz B. (2019). Endüstri Mühendisliği Öğrencilerinin Endüstri 4.0 Farkindalığı Üzerine Bir Çalışma. Middle East International Conference On Multidisciplinary Studies, 1, 401-409.
  • [24] Alcin, S. (2016). Üretim için yeni bir izlek: sanayi 4.0, Journal of Life Economics, 8, 19-30.
  • [25] Cekici, V. (2013). Müşteri Şikayet Değerlendirme Süreçleri İçin Kavramsal Bir Model ve Simülasyon Optimizasyon Yöntemi ile Değerlendirilmesi. Doktoral thesis, Cukurova University, Adana.
There are 25 citations in total.

Details

Primary Language English
Subjects Industrial Engineering
Journal Section Reviews
Authors

Betül Soyöz 0000-0002-6450-9223

Bahar Özyörük 0000-0001-5434-6697

Publication Date December 31, 2021
Published in Issue Year 2021 Volume: 01 Issue: 02

Cite

IEEE B. Soyöz and B. Özyörük, “A Study on Industry 4.0 Awareness of Universities in Turkey”, Researcher, vol. 01, no. 02, pp. 35–50, 2021.
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The journal "Researcher: Social Sciences Studies" (RSSS), which started its publication life in 2013, continues its activities under the name of "Researcher" as of August 2020, under Ankara Bilim University.
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