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TÜRKİYE’DE ENDÜSTRİ 4.0'IN BENİMSENMESİNİN ÖNÜNDEKİ ENGELLERİN YORUMLAYICI YAPISAL MODELLEME (ISM) VE MICMAC İLE ANALİZİ

Yıl 2024, Cilt: 7 Sayı: 1, 51 - 67, 19.07.2024
https://doi.org/10.46238/jobda.1215803

Öz

Günümüzde dijital teknolojiler ve Yapay Zeka ile önem kazanan Endüstri 4.0, üç boyutlu üretim de dahil olmak üzere kişiye özel üretimi mümkün kılarak maliyetleri düşürmektedir. Kalite arttmakta, müşteri memnuniyetini sağlanmakta ve çevre korumaktadır. Endüstri 4.0 iş sağlığı ve güvenliğinde de dönüşümü sağlayarak güvenlik yaklaşımlarını değiştirmektedir. Tüm bu olumlu avantajlarına rağmen, günümüzde halen Endüstri 4.0'ın uygulamalarının önünde engeller bulunmaktadır. Bu çalışma, Türkiye Cumhuriyeti’nde Endüstri 4.0'ın uygulanmasını zorlaştıracak potansiyel engelleri tespit etmeyi ve analiz etmeyi amaçlamıştır. Bu makalede, “Türkiye” kelimesi, Türkiye Cumhuriyeti anlamına gelmektedir. Kapsamlı literatür taramasının ardından sektör uzmanlarının görüşleri de alınarak engeller belirlenmiştir. Bu engeller üretim altyapısı, kurulum maliyeti, dijital veri koruması, güvenlik prosedürleri, veri kullanım zorlukları, ürünlerin belirsiz değerleri, kâr belirsizliği, deneyimli işgücü eksikliği, üretim kesintileri, değişime direnç, devlet desteği, makinelere artan bağımlılık, mevzuat ve hükümet politikası olarak tespit edilmiştir. Tanımlanan engeller arasında hiyerarşik bir yapı geliştirmek için yorumlayıcı yapısal modelleme (ISM) ve MICMAC analizi kullanılmıştır. Ayrıca, Türkiye’de Endüstri 4.0'a geçiş yapacak işletmeler için önerilerde bulunulmuştur.

Teşekkür

Çalışmamızın, değerlendirilmesini saygılarımızla arz ederiz.

Kaynakça

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  • Cherrafi, A., Elfezazi, S., Garza-Reyes, J. A., Benhida, K., & Mokhlis, A. (2017). Barriers in Green Lean implementation: a combined systematic literature review and interpretive structural modelling approach. Production Planning & Control, 28(10), 829-842.
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ANALYSIS OF THE BARRIERS TO INDUSTRY 4.0 ADOPTION IN THE REPUBLIC OF TURKEY WITH INTERPRETATIONAL STRUCTURAL MODELING (ISM) AND MICMAC

Yıl 2024, Cilt: 7 Sayı: 1, 51 - 67, 19.07.2024
https://doi.org/10.46238/jobda.1215803

Öz

Nowadays, Industry 4.0 has gained importance with digital technologies and Artificial Intelligence and reduces costs by enabling customized production, including three-dimensional production. It increases quality, ensures customer satisfaction and protects the environment. Industry 4.0 also transforms occupational health and safety, changing safety approaches. Despite all these positive advantages, there are still barriers in front of the applications of Industry 4.0. This study aimed to identify and analyze the potential barriers that will complicate the implementation of Industry 4.0 in the Republic of Türkiye. In this article, the word “Turkey” means the Republic of Turkey. After a comprehensive literature review, the opinions of industry experts were also taken and barriers were identified. These barriers were identified as production infrastructure, cost of installation, digital data protection, security procedures, data usage challenges, uncertain values of products, uncertainty of profit, lack of experienced workforce, production interruptions, resistance to change, government support, increased dependence on machinery, legislation and government policy. Interpretive structural modeling (ISM) and MICMAC analyzes were used to develop a hierarchical structure among the identified barriers. In addition, suggestions are made for businesses that will transition to Industry 4.0 in Turkey.

Kaynakça

  • AbouRizk, S. (2010). Role of simulation in construction engineering and management. Journal of construction engineering and management, 136(10), 1140-1153.
  • Aggarwal, A., Gupta, S., & Ojha, M. K. (2019). Evaluation of key challenges to industry 4.0 in Indian context: a DEMATEL approach. In Advances in Industrial and Production Engineering (pp. 387-396). Springer, Singapore.
  • Azevedo, S. G., Sequeira, T., Santos, M., & Mendes, L. (2019). Biomass-related sustainability: A review of the literature and interpretive structural modeling. Energy, 171, 1107-1125.
  • Barreto, L., Amaral, A., & Pereira, T. (2017). Industry 4.0 implications in logistics: an overview. Procedia manufacturing, 13, 1245-1252.
  • Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of things and supply chain management: a literature review. International Journal of Production Research, 57(15-16), 4719-4742.
  • Braaksma, A. J., Klingenberg, W. W., & van Exel, P. P. (2011). A review of the use of asset information standards for collaboration in the process industry. Computers in industry, 62(3), 337-350.
  • Calabrese, A., Levialdi Ghiron, N., & Tiburzi, L. (2021). ‘Evolutions’ and ‘revolutions’ in manufacturers’ implementation of industry 4.0: a literature review, a multiple case study, and a conceptual framework. Production Planning & Control, 32(3), 213-227.
  • Chauhan, C., Singh, A., & Luthra, S. (2021). Barriers to industry 4.0 adoption and its performance implications: An empirical investigation of emerging economy. Journal of Cleaner Production, 285, 124809.
  • Cherrafi, A., Elfezazi, S., Garza-Reyes, J. A., Benhida, K., & Mokhlis, A. (2017). Barriers in Green Lean implementation: a combined systematic literature review and interpretive structural modelling approach. Production Planning & Control, 28(10), 829-842.
  • Cozmiuc, D., & Petrisor, I. (2018). Industrie 4.0 by siemens: steps made next. Journal of Cases on Information Technology (JCIT), 20(1), 31-45.
  • Cugno, M., Castagnoli, R., & Büchi, G. (2021). Openness to Industry 4.0 and performance: The impact of barriers and incentives. Technological Forecasting and Social Change, 168, 120756.
  • Dalenogare, L. S., Benitez, G. B., Ayala, N. F., & Frank, A. G. (2018). The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of production economics, 204, 383-394.
  • Dalmarco, G., & Barros, A. C. (2018). Adoption of Industry 4.0 technologies in supply chains. In Innovation and Supply Chain Management (pp. 303-319). Springer, Cham.
  • Elhusseiny, H. M., & Crispim, J. (2022). SMEs, Barriers and Opportunities on adopting Industry 4.0: A Review. Procedia Computer Science, 196, 864-871.
  • Errandonea, I., Beltrán, S., & Arrizabalaga, S. (2020). Digital Twin for maintenance: A literature review. Computers in Industry, 123, 103316.
  • Fathi, M., & Ghobakhloo, M. (2020). Enabling mass customization and manufacturing sustainability in industry 4.0 context: a novel heuristic algorithm for in-plant material supply optimization. Sustainability, 12(16), 6669.
  • Flatt, H., Schriegel, S., Jasperneite, J., Trsek, H., & Adamczyk, H. (2016, September). Analysis of the Cyber-Security of industry 4.0 technologies based on RAMI 4.0 and identification of requirements. In 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA) (pp. 1-4). IEEE.
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  • 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.
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Toplam 98 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Özgün Bilimsel Makaleler
Yazarlar

Adnan Karabulut 0000-0002-0643-098X

Mehmet Baran 0000-0001-6674-7308

Yayımlanma Tarihi 19 Temmuz 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 7 Sayı: 1

Kaynak Göster

APA Karabulut, A., & Baran, M. (2024). TÜRKİYE’DE ENDÜSTRİ 4.0’IN BENİMSENMESİNİN ÖNÜNDEKİ ENGELLERİN YORUMLAYICI YAPISAL MODELLEME (ISM) VE MICMAC İLE ANALİZİ. Journal of Business in The Digital Age, 7(1), 51-67. https://doi.org/10.46238/jobda.1215803
AMA Karabulut A, Baran M. TÜRKİYE’DE ENDÜSTRİ 4.0’IN BENİMSENMESİNİN ÖNÜNDEKİ ENGELLERİN YORUMLAYICI YAPISAL MODELLEME (ISM) VE MICMAC İLE ANALİZİ. JOBDA. Temmuz 2024;7(1):51-67. doi:10.46238/jobda.1215803
Chicago Karabulut, Adnan, ve Mehmet Baran. “TÜRKİYE’DE ENDÜSTRİ 4.0’IN BENİMSENMESİNİN ÖNÜNDEKİ ENGELLERİN YORUMLAYICI YAPISAL MODELLEME (ISM) VE MICMAC İLE ANALİZİ”. Journal of Business in The Digital Age 7, sy. 1 (Temmuz 2024): 51-67. https://doi.org/10.46238/jobda.1215803.
EndNote Karabulut A, Baran M (01 Temmuz 2024) TÜRKİYE’DE ENDÜSTRİ 4.0’IN BENİMSENMESİNİN ÖNÜNDEKİ ENGELLERİN YORUMLAYICI YAPISAL MODELLEME (ISM) VE MICMAC İLE ANALİZİ. Journal of Business in The Digital Age 7 1 51–67.
IEEE A. Karabulut ve M. Baran, “TÜRKİYE’DE ENDÜSTRİ 4.0’IN BENİMSENMESİNİN ÖNÜNDEKİ ENGELLERİN YORUMLAYICI YAPISAL MODELLEME (ISM) VE MICMAC İLE ANALİZİ”, JOBDA, c. 7, sy. 1, ss. 51–67, 2024, doi: 10.46238/jobda.1215803.
ISNAD Karabulut, Adnan - Baran, Mehmet. “TÜRKİYE’DE ENDÜSTRİ 4.0’IN BENİMSENMESİNİN ÖNÜNDEKİ ENGELLERİN YORUMLAYICI YAPISAL MODELLEME (ISM) VE MICMAC İLE ANALİZİ”. Journal of Business in The Digital Age 7/1 (Temmuz 2024), 51-67. https://doi.org/10.46238/jobda.1215803.
JAMA Karabulut A, Baran M. TÜRKİYE’DE ENDÜSTRİ 4.0’IN BENİMSENMESİNİN ÖNÜNDEKİ ENGELLERİN YORUMLAYICI YAPISAL MODELLEME (ISM) VE MICMAC İLE ANALİZİ. JOBDA. 2024;7:51–67.
MLA Karabulut, Adnan ve Mehmet Baran. “TÜRKİYE’DE ENDÜSTRİ 4.0’IN BENİMSENMESİNİN ÖNÜNDEKİ ENGELLERİN YORUMLAYICI YAPISAL MODELLEME (ISM) VE MICMAC İLE ANALİZİ”. Journal of Business in The Digital Age, c. 7, sy. 1, 2024, ss. 51-67, doi:10.46238/jobda.1215803.
Vancouver Karabulut A, Baran M. TÜRKİYE’DE ENDÜSTRİ 4.0’IN BENİMSENMESİNİN ÖNÜNDEKİ ENGELLERİN YORUMLAYICI YAPISAL MODELLEME (ISM) VE MICMAC İLE ANALİZİ. JOBDA. 2024;7(1):51-67.

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