Araştırma Makalesi
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Yeni Gelişmeler ve Sektörlerin Yeni Trendlerine İlişkin Endüstri 4.0 Yaklaşımı

Yıl 2021, Sayı: 28, 228 - 240, 30.11.2021
https://doi.org/10.31590/ejosat.996172

Öz

Bu araştırmanın amacı, Endüstri 4.0'ın temel ilkelerini, avantajlarını, literatür taramasını ve etkin uygulama tekniklerini değerlendirmektir. Böylece özellikle üretim sistemi ve teknolojisine ilişkin büyük veriler içeren endüstrilerdeki son gelişmeleri göstermektedir. Sanayileşme, çok çeşitli modern otomatik sistemler, veri alışverişleri ve üretim teknolojileri için kapsamlı bir terimdir. Bu terim, nesnelerin interneti, çevrimiçi hizmetler ve siber-fiziksel sistemlerden oluşan bir idealler dizisidir. Bu araştırma, endüstriye 4.0'ın evrimini, teknik ilerlemelerini ve faydalarını incelemekte, bu yapılandırmaya ve endüstrideki kullanımına bir arka plan oluşturmaktadır. Ayrıca çalışma, endüstrideki uygulamaları ve başarılı işletmeleri etkileyen temel bileşenleri vurgulamaktadır., endüstri 4.0 modeli için ürün, süreç ve iş gelişmeleri açısından organizasyonel yeniliklerin gerekli olduğunun altı çizilmiştir. Endüstri 4.0 modelinin uygulanabilmesi için birçok sektörde önemli ölçüde yenilik yapılması gerekmektedir. Ürün, süreç, iş ve operasyonel terimlerde inovasyon-yenilik, ek değer yaratan çeşitliliği ifade eder. Bu amaçla, çalışmada endüstri 4.0 ve inovasyon fikirleri açıklanmakta, terimsel kavramlarla birlikte endüstri 4.0 merceğinden inovasyon incelemesi yapılmaktadır. Bu araştırma, işletmeler için sanayi ortamında endüstri 4.0 kapsamında gelişmeleri yansıtmaktadır. Araştırma ayrıca, şirketin üretim sistemine bağlı olarak endüstri 4.0 teknolojisinin uygulama ve imalat-üretiminin iyileştirme aşamalarını içermektedir. Çalışmada, bir beyaz eşya imalat firmasının endüstri 4.0 teknolojisi ile yaptığı uygulama, operasyon yönetimi ve iş beklentilerin analizine yönelik üretim sisteminin girdi ve çıktı bileşenlerine göre bu imalat işletmesinin üretim performansı ve etkinliği değerlendirilmiştir.

Kaynakça

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Industry 4.0 Perception Regarding to New Developments and New Trends of Industries

Yıl 2021, Sayı: 28, 228 - 240, 30.11.2021
https://doi.org/10.31590/ejosat.996172

Öz

The purpose of this research is to assess the core principles of Industry 4.0, its advantages, literature review, and effective implementation techniques. Searching for published publications may demonstrate recent developments of industries with big data of production system and technology. Industrialization is a catch-all term for a wide range of modern automated systems, data exchanges, and manufacturing technologies. This revolution is a set of ideals comprised of the internet of things, online services, and cyber-physical systems. While the Industry 4.0 model represents a revolution in every aspect, it also delivers numerous breakthroughs, transformations, and adjustments. This research examines the evolution, technical advances, and benefits of Industrial 4.0, gives a brief background to this configuration and its use in industry implementations, and emphasizes the key components influencing successfully businesses. Furthermore, it is underlined those organizational innovations are required for the industry 4.0 revolution in terms of product, process, and business advancements. As a result, a significant deal of innovation is necessary in many sectors before the industry 4.0 model can be implemented. In product, process, business, and operational terms, innovation refers to variety that creates additional value. To that end, the ideas of Industry 4.0 and innovation are described briefly, followed by an examination of innovation through the lens of Industrial 4.0, with illustrations and concepts provided. It is abundantly clear through publications that are being searched those sectors and industries are making use of big data in the production environment and information. This research reflects on the developments of framework-structure in the enviroment of industry for the business-companies. The research also contains the aspect-application of the industry 4.0 technology depending on manufacturing system and improvement phases of manufacturing-production of the company. The application via Industry 4.0 technology of a white goods manufacturing company was evaluated on behalf of manufacturing performance and effectiveness of this manufacturing enterprise according to inputs and outputs components of manufacturing system for the analysis in terms of operation management and the business expectation.

Kaynakça

  • Abele, E. and Reinhart, G. (2011). Zukunft der Produktion, Carl Hanser Verlag GMBH & München
  • Adolph, S., Tisch, M. and Metternich, J. (2014). Challenges and approaches to competency development for future production. Educ. Altern. 12, 1001–1010.
  • Aheleroff, S., Xua , X., Lua, Y., Aristizabalb, M., Velásquez, J.P., Joab, B. and Valenciab, Y. (2020). IoT-enabled smart appliances under industry 4.0: A case study, Advanced Engineering Informatics, 43, 101043.
  • Amaral, A., Jorge, D. and Peças, P. (2019). Small Medium Enterprises And Industry 4.0: Current Models’ Ineptitude And The Proposal Of A Methodology To Successfully Implement Industry 4.0 In Small Medium Enterprises. Procedia Manufacturing, 41, 1103–1110. doi:10.1016/j.promfg.2019.10.039.
  • Alborzi, M. and Khanbabaei, M. (2016). Using data mining and neural networks techniques to propose a new hybrid customer behaviour analysis and credit scoring model in banking services based on a developed RFM analysis method. International Journal of Business Information Systems, 23(1), 1-22.
  • Bahrin, M.A.K., Othman, M.F., Azli, N.H.N. and Talib, M.F. (2016). Industry 4.0: a review on industrial automation and robotic, Jurnal Teknologi, 78, 6–13.
  • Bauer, W., Hämmerle, M., Schlund, S. and Vocke, C. (2015). Transforming to a hyper-connected society and economy – towards an “Industry 4.0.”. Procedia Manuf. 3, 417–424. https://doi.org/10.1016/j.promfg.2015.07.200.
  • Bravi, L. and Murmura, F. (2021). Industry 4.0 enabling technologies as a tool for the development of a competitive strategy in Italian manufacturing companies, Journal of Engineering and Technology Management. April-June 2021, 60, DOI: 10.1016/j.jengtecman.2021.101629.
  • Bruhn, M. and Hadwich, K. (2017). Dienstleistungen 4.0, Springer Fachmedien Wiesbaden, Wiesbaden, 2017.
  • Cedeño J.M.V., Papinniemi J., Hannola L., Donoghue I., 2018. Developing smart services by internet of things in manufacturing business. LogForum 14 (1), 59-71. http://dx.doi.org/10.17270/J.LOG.2018.268.
  • Culotta, A. and Cutler, J. (2016). Mining Brand Perceptions from Twitter Social Networks. Marketing Science, 35(3) ,343-362.
  • Chiarello, F., Trivelli, L., Bonaccorsi, A. and Fantoni, G. (2018). Extracting and mapping industry 4.0 technologies using wikipedia. Computers in Industry, 100, 244–257. doi:10.1016/j.compind.2018.04.006.
  • Dalenogare, L. S., Benitez, G. B., Ayala, N. F. and Frank, A. G. (2018). The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of Production Economics. doi:10.1016/j.ijpe.2018.08.019.
  • De Sousa Jabbour, A. B. L., Jabbour, C. J. C., Foropon, C., and Godinho Filho, M. (2018). When titans meet – Can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors. Technological Forecasting and Social Change, 132, 18–25. doi:10.1016/j.techfore.2018.01.017 .
  • Douaioui, K., Fri, M., Mabroukki, C. and Semma, E. A. (2018). The Interaction between Industry 4.0 and Smart Logistics: Concepts and Perspectives. 11th International Colloquium of Logistics and Supply Chain Management LOGISTIQUA 2018, (128-132). Morocco: IEEE. doi: 10.1109/LOGISTIQUA.2018.8428300.
  • Duysak, H., Ozkaya, U., & Yigit, E. (2021). Determination of the Amount of Grain in Silos with Deep Learning Methods Based on Radar Spectrogram Data. IEEE Transactions on Instrumentation and Measurement.
  • Duxbury, T. (2012). Creativity: Linking Theory and Practice for Entrepreneurs. Technology Innovation Management Review, 2(8), 10-15.
  • Dima, A. (2021). Kfactory Short history of manufacturing: from Industry 1.0 to Industry 4.0, https://kfactory.eu/short-history-of-manufacturing-from-industry-1-0-to-industry-4-0/ (Access Date: 21.05.2021).
  • Enyoghasi, C. and Badurdeen, F. (2021). Industry 4.0 for sustainable manufacturing: Opportunities at the product, process, and system levels, Resources, Conservation and Recycling, doi: 10.1016/j.resconrec.2020.105362.
  • Ganzarain, J. and Errasti, N. (2016). Three stage maturity model in SME’s towards industry 4.0, J. Ind. Eng. Management. Gartner Group (2017). Advanced Technology Research Note 2017, https://www.gartner.com/technology/research/, (Access Date: 12.04.2021).
  • Gerbert, P., Lorenz, M., Russmann, M., Waldner, M., Justus, J., Engel, P., and Harnisch, M. (2015). Industry 4.0: The Future of Productivity and Growth in Manufacturing Industries. https://www.bcg.com/publications/2015/engineered_products_project_business_industry_4_future_productivity_growth_manufacturing_industries.aspx, (Access Date: 12.04.2021).
  • Ghazavi, E., and Lotfi, M. M. (2016). Formulation of customers’ shopping path in shelf space planning: A simulation-optimization approach. Expert Systems with Applications, 55, 243–254. doi:10.1016/j.eswa.2016.01.043.
  • Griva, A., Bardaki, C., Pramatari, K. and Papakiriakopoulos, D. (2018). Retail business analytics: Customer visit segmentation using market basket data. Expert Systems with Applications, 100, 1–16. doi:10.1016/j.eswa.2018.01.029.
  • Horváth, D. and Szabó, R. Z. (2019). Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities? Technological Forecasting and Social Change, 146, 119–132. doi:10.1016/j.techfore.2019.05.021.
  • Holubčík, M., Koman, G. and Soviar, J. (2021). Industry 4.0 in Logistics Operations, Transportation Research Procedia. 53, 282-288, DOI: 10.1016/j.trpro.2021.02.040.
  • Infineon. (2021). What you need to know about Big Data? https://www.infineon.com/cms/en/discoveries/big-data-basics/ (Access Date: 20.03.2021).
  • Innovation Cycle, https://www.crf.org/crf/contact-us/68-skirball-innovation-center-2/1549-innovation-cycle, (Access Date:21.05.2021).
  • Innovation Management, How do you Define Innovation and Make it Practical and Saleable to Senior Management? https://innovationmanagement.se/2008/01/07/how-do-you-define-innovation-and-make-it-practical-and-saleable-to-senior-management/ (Access Date: 14.06.2021).
  • Inkermann, D., Schneider, D., Martin, N. L., Lembeck, H., Zhang, J., and Thiede, S. (2019). A framework to classify Industry 4.0 technologies across production and product development. Procedia CIRP, 84, 973–978. doi:10.1016/j.procir.2019.04.218.
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  • Kurt, R. (2019). Industry 4.0 in Terms of Industrial Relations and Its Impacts on Labour Life. Procedia Computer Science, 158, 590–601. doi:10.1016/j.procs.2019.09.093.
  • Lasi, H., Fettke, P., Kemper, H.-G., Feld, T. and Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6(4), 239–242. doi:10.1007/s12599-014-0334-4.
  • Lee, I. and Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431–440. doi:10.1016/j.bushor.2015.03.008.
  • Lichblau, K., Sicht, V., Bertenrth, R., Blum, M., Bleider, M., Millack, A., Schmitt, K., Schmitz, E. and Schroeter, M. (2015). IMPULS - Industrie 4.0 Readiness, 0–77.
  • MAGG4. (2018). Endüstri 4.0 Demek, İnovasyon Demektir. Genç Nesil, Güncel İçerikler: https://magg4.com/endustri-4-0-demek-inovasyon-demektir/, (Access Date:22.04.2021).
  • Marr, B. (2017). How BMW Uses Artificial Intelligence And Big Data To Design And Build Cars Of Tomorrow. Forbes: https://www.forbes.com/sites/bernardmarr/2017/08/01/how-bmw uses-artificial-intelligence-and-big-data-to-design-and-build-cars-oftomorrow/#3e36a06d2b91, (Access Date: 12.04.2021).
  • Morrar, R., Arman, H. and Mousa, S. (2017). The Fourth Industrial Revolution (Industry 4.0): A Social Innovation Perspective. Technology, Innovation Management Review, 7(11), 12-21.
  • Nakagawa, E. Y., Antonino, P.O., Schnicke, F.; Capilla, R.; Kuhn, T. and Liggesmeyer, P.(2021). Industry 4.0 reference architectures: State of the art and future trends, Computers & Industrial Engineering. June 2021, 156, 107241, doi: 10.1016/j.cie.2021.10724.
  • Niemeyer, C. L., Gehrke, I., Müller, K., Küsters, D. and Gries, T. (2020). Getting Small Medium Enterprises started on Industry 4.0 using retrofitting solutions. Procedia Manufacturing, 45, 208–214. doi:10.1016/j.promfg.2020.04.096.
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  • Vishal A. and Vinodh, S. (2021). Analysis of Industry 4.0 challenges using best worst method: A case study, Computers & Industrial Engineering. September 202, 159, DOI: 10.1016/j.cie.2021, 1074- 87.
  • Vyas, K. (2018). How the First and Second Industrial Revolutions Changed Our World. Interesting Engineering: https://interestingengineering.com/how-the-first-and-secondindustrial-revolutions-changed-our-world, (Access Date: 12.04.2021). What is Innovation?, https://innolytics-innovation.com/what-is-innovation/ (Access Date: 13.05.2021).
  • Weng, C. H. (2016). Identifying association rules of specific later-marketed products. Applied Soft Computing, 38, 518-529.
  • Xu, L. D., Xu, E. L. and Li, L. (2018). Industry 4.0: State of the Art and Future Trends. International Journal of Production Research, 56(8), 2941-2962. doi:10.1080/00207543.2018.1444806.
  • Yao, X., Zhou, J., Zhang, J. and Boer, C.R. (2017). From intelligent manufacturing to smart manufacturing for industry 4.0 driven by next generation artificial intelligence and further on. In: 2017 5th International Conference on Enterprise Systems, vols. 22-24. IEEE, Beijing, China. Sept. 2017.
  • Yu, Y., Zhang, J. Z., Cao, Y., and Kazancoglu, Y. (2021). Intelligent transformation of the manufacturing industry for Industry 4.0: Seizing financial benefits from supply chain relationship capital through enterprise green management, Technological Forecasting & Social Change. November 2021, 172, doi:10.1016/j.techfore.2021.120999.
  • Zheng, P., Chen, C.-H. and Shang, S. (2019). Towards an automatic engineering change management in smart product-service systems – A DSM-based learning approach. Advanced Engineering Informatics, 39, 203–213. doi:10.1016/j.aei.2019.01.002.
Toplam 67 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Ayşenur Erdil 0000-0002-6413-7482

Yayımlanma Tarihi 30 Kasım 2021
Yayımlandığı Sayı Yıl 2021 Sayı: 28

Kaynak Göster

APA Erdil, A. (2021). Industry 4.0 Perception Regarding to New Developments and New Trends of Industries. Avrupa Bilim Ve Teknoloji Dergisi(28), 228-240. https://doi.org/10.31590/ejosat.996172