Smart Manufacturing with Smart Technologies – A Review
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Abstract
The application of smart technologies like the Internet of Things (IoT), Cloud Computing (CC), Cyber Physical Systems (CPS), Big Data (BD), and Artificial Intelligence (AI) in production is known as "smart manufacturing" (SM). This article examines how SM changed as a result of the advancement of these technologies. This review summarises the development of each technology before explaining how SM made these technologies possible. The final topic is the future improvements for Industry 4.0. With the purpose of elucidating next-generation smart manufacturing, this review will make an effort to respond to these questions, i.e., present date of resources in manufacturing and the difficulties associated with using smart technology in manufacturing.
(Manuscript received: 1st November 2022 | Accepted: 27 July 2023 | Published: 30 September 2023)
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References
Borangiu, T., Trentesaux, D., Thomas, A., Leitão, P., & Barata, J. (2019). Digital transformation of manufacturing through cloud services and resource virtualization. Computers in Industry, 108, 150-162.
Wang, B., Tao, F., Fang, X., Liu, C., Liu, Y., & Freiheit, T. (2021). Smart manufacturing and intelligent manufacturing: A comparative review. Engineering, 7(6), 738-757.
Gokhale, P., Bhat, O., & Bhat, S. (2018). Introduction to IOT. International Advanced Research Journal in Science, Engineering and Technology, 5(1), 41-44.
Tao, F., Qi, Q., Liu, A., & Kusiak, A. (2018). Data-driven smart manufacturing. Journal of Manufacturing Systems, 48, 157-169.
Giutini, R., & Gaudette, K. (2003). Remanufacturing: The next great opportunity for boosting US productivity. Business Horizons, 46(6), 41-48.
Mourtzis, D., & Vlachou, E. (2018). A cloud-based cyber-physical system for adaptive shop-floor scheduling and condition-based maintenance. Journal of manufacturing systems, 47, 179-198.
Hoffmann, M. W., Wildermuth, S., Gitzel, R., Boyaci, A., Gebhardt, J., Kaul, H., ... & Tornede, T. (2020). Integration of novel sensors and machine learning for predictive maintenance in medium voltage switchgear to enable the energy and mobility revolutions. Sensors, 20(7), 2099.
Nagy, J., Oláh, J., Erdei, E., Máté, D., & Popp, J. (2018). The role and impact of Industry 4.0 and the internet of things on the business strategy of the value chain—the case of Hungary. Sustainability, 10(10), 3491.
Khan, I. H., & Javaid, M. (2022). Role of Internet of Things (IoT) in adoption of Industry 4.0. Journal of Industrial Integration and Management, 7(04), 515-533.
Gunes, V., Peter, S., Givargis, T., & Vahid, F. (2014). A survey on concepts, applications, and challenges in cyber-physical systems. KSII Transactions on Internet and Information Systems (TIIS), 8(12), 4242-4268.
Barari, A., de Sales Guerra Tsuzuki, M., Cohen, Y., & Macchi, M. (2021). Intelligent manufacturing systems towards industry 4.0 era. Journal of Intelligent Manufacturing, 32, 1793-1796.
Li, C., Chen, Y., & Shang, Y. (2021). A review of industrial big data for decision making in intelligent manufacturing. Engineering Science and Technology, an International Journal. Volume 29, May 2022, 101021.
Belhadi, A., Zkik, K., Cherrafi, A., & Sha'ri, M. Y. (2019). Understanding big data analytics for manufacturing processes: insights from literature review and multiple case studies. Computers & Industrial Engineering, 137, 106099.
Ghosh, A., Chakraborty, D., & Law, A. (2018). Artificial intelligence in Internet of things. CAAI Transactions on Intelligence Technology, 3(4), 208-218.
Bahrin, M. A. K., Othman, M. F., Azli, N. H. N., & Talib, M. F. (2016). Industry 4.0: A review on industrial automation and robotic. Jurnal teknologi, 78(6-13).
Radanliev, P., De Roure, D., Van Kleek, M., Santos, O., & Ani, U. (2021). Artificial intelligence in cyber physical systems. AI & society, 36, 783-796.
Fantini, P., Pinzone, M., & Taisch, M. (2020). Placing the operator at the centre of Industry 4.0 design: Modelling and assessing human activities within cyber-physical systems. Computers & Industrial Engineering, 139, 105058.
Kaur, M., Sandhu, M., Mohan, N., & Sandhu, P. S. (2011). RFID technology principles, advantages, limitations & its applications. International Journal of Computer and Electrical Engineering, 3(1), 151.
Zhong, R. Y., Dai, Q. Y., Qu, T., Hu, G. J., & Huang, G. Q. (2013). RFID-enabled real-time manufacturing execution system for mass-customization production. Robotics and Computer-Integrated Manufacturing, 29(2), 283-292.
Dai, Q., Zhong, R., Huang, G. Q., Qu, T., Zhang, T., & Luo, T. Y. (2012). Radio frequency identification-enabled real-time manufacturing execution system: a case study in an automotive part manufacturer. International Journal of Computer Integrated Manufacturing, 25(1), 51-65.
Zhang, Y., Qu, T., Ho, O. K., & Huang, G. Q. (2011). Agent-based smart gateway for RFID-enabled real-time wireless manufacturing. International Journal of Production Research, 49(5), 1337-1352.
Zhang, Y., Huang, G. Q., Qu, T., & Sun, S. (2013). Real-time work-in-progress management for ubiquitous manufacturing environment. In Cloud Manufacturing (pp. 193-216). Springer, London.
Qu, T., Lei, S. P., Wang, Z. Z., Nie, D. X., Chen, X., & Huang, G. Q. (2016). IoT-based real-time production logistics synchronization system under smart cloud manufacturing. The International Journal of Advanced Manufacturing Technology, 84(1), 147-164.
Radziwon, A., Bilberg, A., Bogers, M., & Madsen, E. S. (2014). The smart factory: exploring adaptive and flexible manufacturing solutions. Procedia engineering, 69, 1184-1190.
Bi, Z., Da Xu, L., & Wang, C. (2014). Internet of things for enterprise systems of modern manufacturing. IEEE Transactions on industrial informatics, 10(2), 1537-1546..
Tsang, Y. P., Wu, C. H., Ip, W. H., & Shiau, W. L. (2021). Exploring the intellectual cores of the blockchain–Internet of Things (BIoT). Journal of Enterprise Information Management.
Wang, T., Guo, S., & Lee, C. G. (2014). Manufacturing task semantic modeling and description in cloud manufacturing system. The International Journal of Advanced Manufacturing Technology, 71(9), 2017-2031.
Garetti, M., & Taisch, M. (2012). Sustainable manufacturing: trends and research challenges. Production planning & control, 23(2-3), 83-104.
Tao, F., Cheng, Y., Da Xu, L., Zhang, L., & Li, B. H. (2014). CCIoT-CMfg: cloud computing and internet of things-based cloud manufacturing service system. IEEE Transactions on industrial informatics, 10(2), 1435-1442.
Cheng, Y., Tao, F., Zhao, D., & Zhang, L. (2017). Modeling of manufacturing service supply–demand matching hypernetwork in service-oriented manufacturing systems. Robotics and Computer-Integrated Manufacturing, 45, 59-72.
Boss, G., Malladi, P., Quan, D., Legregni, L., & Hall, H. (2007). Cloud computing. IBM white paper, 321, 224-231.
Cao, Q., Schniederjans, D. G., & Schniederjans, M. (2017). Establishing the use of cloud computing in supply chain management. Operations Management Research, 10(1), 47-63.
Bhardwaj, S., Jain, L., & Jain, S. (2010). Cloud computing: A study of infrastructure as a service (IAAS). International Journal of engineering and information Technology, 2(1), 60-63.
29. Ooi, K. B., Lee, V. H., Tan, G. W. H., Hew, T. S., & Hew, J. J. (2018). Cloud computing in manufacturing: The next industrial revolution in Malaysia? Expert Systems with Applications, 93, 376-394.
Wang, L., & Wang, X. V. (2018). Cloud-based cyber-physical systems in manufacturing (pp. 163-192). New York, NY, USA:: Springer International Publishing.
Li, Z., Barenji, A. V., & Huang, G. Q. (2018). Toward a blockchain cloud manufacturing system as a peer to peer distributed network platform. Robotics and computer-integrated manufacturing, 54, 133-144.
Cerquitelli, T., Pagliari, D. J., Calimera, A., Bottaccioli, L., Patti, E., Acquaviva, A., & Poncino, M. (2021). Manufacturing as a data-driven practice: methodologies, technologies, and tools. Proceedings of the IEEE, 109(4), 399-422.
Huang, L., Wu, C., & Wang, B. (2019). Challenges, opportunities and paradigm of applying big data to production safety management: From a theoretical perspective. Journal of Cleaner Production, 231, 592-599.
Cerquitelli, T., Pagliari, D. J., Calimera, A., Bottaccioli, L., Patti, E., Acquaviva, A., & Poncino, M. (2021). Manufacturing as a data-driven practice: methodologies, technologies, and tools. Proceedings of the IEEE, 109(4), 399-422.
Zhong, R. Y., Xu, X., Klotz, E., & Newman, S. T. (2017). Intelligent manufacturing in the context of industry 4.0: a review. Engineering, 3(5), 616-630.