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ÜRETİM ENDÜSTRİSİNİ DÖNÜŞTÜREN TEKNOLOJİ TRENDLERİNE GENEL BİR BAKIŞ

Yıl 2023, Cilt: 33 Sayı: 3, 1339 - 1354, 26.09.2023

Yunus Emre Gür Koray Gündüz

https://doi.org/10.18069/firatsbed.1297867

Öz

Bilgi ve iletişim teknolojisi hızla gelişmekte ve bulut bilişim, Nesnelerin İnterneti, büyük veri analitiği ve yapay zekâ gibi birçok yıkıcı teknoloji ortaya çıkmaktadır. Bu teknolojiler üretim endüstrisine nüfuz etmekte ve endüstriyel üretimin dördüncü aşamasının (yani Endüstri 4.0) gelişini belirleyen siber-fiziksel sistemler (CPS) aracılığıyla fiziksel ve sanal dünyaların kaynaşmasını sağlamaktadır. CPS’nin üretim ortamlarında yaygın olarak uygulanması, üretim sistemlerini giderek daha akıllı hale getirmektedir. Endüstri 4.0’ın üretim endüstrisinde uygulanmasına ilişkin araştırmaları ilerletmek için bu çalışmada, ilk olarak, Endüstri 4.0 için kavramsal bir çerçeve sunulmuştur. İkinci olarak, bu çerçevede sunulan ön uç teknolojiler ile ilgili örnek senaryolar açıklanmıştır. Buna ek olarak, Endüstri 4.0 temel teknolojileri ve bunların Endüstri 4.0 akıllı üretim sistemlerine yönelik olası uygulamaları gözden geçirilmiştir. Son olarak, zorluklar ve gelecek perspektifleri belirlenmiş ve tartışılmıştır.

Anahtar Kelimeler

Endüstri 4.0 Akıllı Üretim Sistemleri Nesnelerin İnterneti Siber-Fiziksel Sistemler Büyük Veri Analitiği

Kaynakça

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  • Belhadi, A., Zkik, K., Cherrafi, A., and Sha'ri, M. Y. (2019). Understanding Big Data Analytics for Manufacturing Processes: İnsights From Literature Review and Multiple Case Studies. Computers & Industrial Engineering, 137, 106099.
  • Ben-Daya, M., Hassini, E., and Bahroun, Z. (2019). Internet of Things and Supply Chain Management: A Literature Review. International Journal of Production Research, 57(15–16), 4719–4742.
  • Bibby, L., and B. Dehe. (2018). Defining and Assessing Industry 4.0 Maturity Levels–Case of the Defence Sector. Production Planning & Control, 29 (12), 1030–1043. doi:10.1080/09537287.2018.1503355.
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  • Choi, S., Kim, B. H. and Do Noh, S. (2015). A Diagnosis and Evaluation Method for Strategic Planning and Systematic Design of A Virtual Factory in Smart Manufacturing Systems. Int. J. Precis. Eng. Manuf., 16(6), 1107–1115,
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An Overview Of Technology Trends That Are Transforming The Manufacturing Industry

Yıl 2023, Cilt: 33 Sayı: 3, 1339 - 1354, 26.09.2023

Yunus Emre Gür Koray Gündüz

https://doi.org/10.18069/firatsbed.1297867

Öz

Information and communication technology is developing rapidly and many disruptive technologies such as cloud computing, Internet of Things, big data analytics and artificial intelligence are emerging. These technologies permeate the manufacturing industry and enable the fusion of the physical and virtual worlds through cyber-physical systems (CPS), which marks the advent of the fourth stage of industrial production (i.e. Industry 4.0). The widespread application of CPS in production environments is making production systems increasingly intelligent. In order to advance research on the application of Industry 4.0 in the manufacturing industry, firstly, a conceptual framework for Industry 4.0 is presented in this study. Secondly, sample scenarios related to front-end technologies presented in this framework are explained. In addition, Industry 4.0 core technologies and their possible applications for Industry 4.0 smart manufacturing systems are reviewed. Finally, challenges and future perspectives are identified and discussed.

Anahtar Kelimeler

Industry 4.0 Intelligent Manufacturing Systems Internet of Things Cyber-Physical Systems Big Data Analytics.

Kaynakça

  • Antrobus V, Burnett G, and Krehl C. (2017). Driver-Passenger Collaboration as a Basis for Human-Machine İnterface Design for Vehicle Navigation Systems. Ergonomics, 60(3): 321–332.
  • Arunachalam, D., Kumar, N., and Kawalek, J. P. (2018). Understanding Big Data Analytics Capabilities in Supply Chain Management: Unravelling the İssues, Challenges and İmplications for Practice. Transportation Research Part E: Logistics and Transportation Review, 114, 416-436.
  • Badarinath, R., and Prabhu, V. V. (2017). Advances in Internet Of Things (Iot) in Manufacturing. In Advances in Production Management Systems. The Path to Intelligent, Collaborative and Sustainable Manufacturing: IFIP WG 5.7 International Conference, APMS, Hamburg, Germany, September 3-7, Proceedings, Part I, 111-118.
  • Baheti R, and Gill H. (2011). Cyber-physical systems. In: Samad T, Annaswamy AM, Editors The İmpact of Control Technology: Overview, Success Stories and Research Challenges. New York: IEEE Control Systems Society, 161–166.
  • Baines, T., Ziaee Bigdeli, A., Bustinza, O. F., Shi, V. G., Baldwin, J., and Ridgway, K. (2017). Servitization: Revisiting the State-of-the-Art and Research Priorities. International Journal of Operations & Production Management, 37(2), 256-278.
  • Belhadi, A., Zkik, K., Cherrafi, A., and Sha'ri, M. Y. (2019). Understanding Big Data Analytics for Manufacturing Processes: İnsights From Literature Review and Multiple Case Studies. Computers & Industrial Engineering, 137, 106099.
  • Ben-Daya, M., Hassini, E., and Bahroun, Z. (2019). Internet of Things and Supply Chain Management: A Literature Review. International Journal of Production Research, 57(15–16), 4719–4742.
  • Bibby, L., and B. Dehe. (2018). Defining and Assessing Industry 4.0 Maturity Levels–Case of the Defence Sector. Production Planning & Control, 29 (12), 1030–1043. doi:10.1080/09537287.2018.1503355.
  • Bloom N, Garicano L, Sadun R, and Van Reenen J. (2014). The Distinct Effects of İnformation Technology and Communication Technology on Firm Organization. Manage Sci, 60(12), 2859–2885.
  • Bond, T. C. (1999). The Role of Performance Measurement in Continuous Improvement. International Journal of Operations & Production Management 19 (12), 1318–1334. doi:10.1108/01443579910294291.
  • Calabrese, A., M. Dora, N. Levialdi Ghiron, and L. Tiburzi. (2020). Industry’s 4.0 Transformation Process: How to Start, Where to Aim, What to Be Aware of. Production Planning & Control 32, 1–21.
  • Chiang, L., Lu, B., and Castillo, I. (2017). Big Data Analytics in Chemical Engineering. Annual Review of Chemical and Biomolecular Engineering, 8, 63-85.
  • Choi, S., Kim, B. H. and Do Noh, S. (2015). A Diagnosis and Evaluation Method for Strategic Planning and Systematic Design of A Virtual Factory in Smart Manufacturing Systems. Int. J. Precis. Eng. Manuf., 16(6), 1107–1115,
  • Colin, M., Galindo, R., and Hernández, O. (2015). Information and Communication Technology As A Key Strategy for Efficient Supply Chain Management in Manufacturing Smes. Procedia Computer Science, 55, 833–842.
  • Dalenogare, L. S., G. B. Benitez, N. F. Ayala, and A. G. Frank. (2018). The Expected Contribution of Industry 4.0 Technologies for Industrial Performance. International Journal of Production Economics, 204, 383–394. doi:10.1016/j.ijpe.2018.08.019.
  • Davis, J., Edgar, T., Graybill, R., Korambath, P., Schott, B., Swink, D., Wang, J. and Wetzel, J. (2015). Smart Manufacturing. Annual Review of Chemical and Biomolecular Engineering, 6, 141–160.
  • Derler P, Lee EA, and Vincentelli AS. (2012). Modeling Cyber-Physical Systems. Proc IEEE, 100(1), 13–28. Dewar, R. D., and J. E. Dutton. (1986). The Adoption of Radical and Incremental Innovations: An Empirical Analysis. Management Science, 32 (11), 1422–1433. doi:10.1287/mnsc.32.11.1422.
  • E. Wallace and F. Riddick, (2013). Panel on Enabling Smart Manufacturing. State College, USA. Eardley, A., H. Shah, and A. Radman. (2008). A Model for Improving the Role of IT in BPR. Business Process Management Journal, 14(5), 629–653. doi:10.1108/14637150810903039.
  • El Kadiri, S., Grabot, B., Thoben, K. D., Hribernik, K., Emmanouilidis, C., Von Cieminski, G., and Kiritsis, D. (2016). Current Trends on ICT Technologies for Enterprise İnformation Systems. Computers in Industry, 79, 14-33.
  • Farooq MU, Waseem M, Mazhar S, Khairi A, and Kamal T. (2015). A Review on Internet of Things (IoT). Int J Comput Appl, 113(1), 1–7.
  • Ferdows, K. (2018). Keeping Up with Growing Complexity of Managing Global Operations. International Journal of Operations & Production Management, 38(2), 390–402. doi:10.1108/IJOPM-01-2017-0019.
  • Fernando, N., Loke, S. W., and Rahayu, W. (2013). Mobile Cloud Computing: A survey. Future Generation Computer Systems, 29(1), 84-106.
  • Fleischmann, M., Bloemhof-Ruwaard, J. M., Dekker, R., Van der Laan, E., Van Nunen, J. A., and Van Wassenhove, L. N. (1997). Quantitative Models for Reverse Logistics: A review. European Journal of Operational Research, 103(1), 1-17.
  • Frank, A. G., G. H. Mendes, N. F. Ayala, and A. Ghezzi. (2019). Servitization and Industry 4.0 Convergence in the Digital Transformation of Product Firms: A Business Model Innovation Perspective. Technological Forecasting and Social Change, 141, 341–351. doi:10. 1016/j.techfore.2019.01.014.
  • Frank, A. G., L. S. Dalenogare, and N. F. Ayala. (2019). Industry 4.0 Technologies: Implementation Patterns in Manufacturing Companies. International Journal of Production Economics, 210, 15–26. doi:10.1016/ j.ijpe.2019.01.004.
  • Ge, Z., Song, Z., Ding, S. X., and Huang, B. (2017). Data Mining and Analytics in the Process İndustry: The Role of Machine Learning. Ieee Access, 5, 20590-20616.
  • Gilchrist, A. (2016). Industry 4.0: The İndustrial İnternet of Things. Apress. New York.
  • Guo ZX, Ngai EWT, Yang C, and Liang X. (2015). An RFID-Based İntelligent Decision Support System Architecture for Production Monitoring and Scheduling İn A Distributed Manufacturing Environment. Int J Prod Econ, 159, 16–28.
  • He, Q. P., and Wang, J. (2018). Statistical Process Monitoring As A Big Data Analytics Tool for Smart Manufacturing. Journal of Process Control, 67, 35-43.
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  • Nguyen, T., Li, Z. H. O. U., Spiegler, V., Ieromonachou, P., and Lin, Y. (2018). Big Data Analytics in Supply Chain Management: A State-of-the-Art Literature Review. Computers & Operations Research, 98, 254–264.
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Toplam 83 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm İktisadi ve İdari Bilimler
Yazarlar

Yunus Emre Gür 0000-0001-6530-0598

Koray Gündüz 0000-0002-9734-3290

Yayımlanma Tarihi 26 Eylül 2023
Gönderilme Tarihi 16 Mayıs 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 33 Sayı: 3

Kaynak Göster

APA Gür, Y. E., & Gündüz, K. (2023). ÜRETİM ENDÜSTRİSİNİ DÖNÜŞTÜREN TEKNOLOJİ TRENDLERİNE GENEL BİR BAKIŞ. Fırat Üniversitesi Sosyal Bilimler Dergisi, 33(3), 1339-1354. https://doi.org/10.18069/firatsbed.1297867
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