Smart Manufacturing Analytics Using Industrial Internet of Things
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DOI:
https://doi.org/10.67228/30715725/IJIARE-2022PII4Y7DPublished 09-05-2022
Smart Manufacturing, Industrial Internet of Things (Iiot), Industry 4.0, Manufacturing Analytics, Artificial Intelligence, Machine Learning, Predictive Maintenance, Cyber-Physical Systems, Edge Computing, Industrial Automation Issue
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ArticlesHow to Cite
[1]I. P. K, “Smart Manufacturing Analytics Using Industrial Internet of Things”, IJIARE, vol. 5, no. 2, pp. 01–16, Sep. 2022, doi: 10.67228/30715725/IJIARE-2022PII4Y7D.Abstract
Smart manufacturing analytics (sma) is a key component of industry 4.0 that combines the industrial internet of things (iiot), artificial intelligence (ai), machine learning (ml), cloud and edge computing, and big data analytics to improve manufacturing processes. It continuously collects and analyzes real-time data from sensors, machines, robots, and production systems to support intelligent decision-making.sma enables predictive maintenance, fault detection, quality control, energy optimization, and production forecasting, leading to higher productivity, reduced downtime, improved product quality, and lower operational costs. By integrating iiot with advanced analytics, smart manufacturing analytics supports the development of intelligent, autonomous, and sustainable manufacturing systems for the next generation of smart factories.
References
[1] L. Monostori, “AI and machine learning techniques for managing complexity, changes and uncertainties in manufacturing,” Engineering, vol. 7, no. 6, pp. 745–755, Jun. 2021.
[2] Y. Lu and X. Xu, “Cloud-based manufacturing equipment and big data analytics for smart manufacturing,” Robotics and Computer-Integrated Manufacturing, vol. 68, Art. no. 102083, Apr. 2021.
[3] M. Javaid, A. Haleem, R. P. Singh, and R. Suman, “Industrial Internet of Things (IIoT) applications for smart manufacturing: A review,” Journal of Industrial Information Integration, vol. 25, Art. no. 100240, Jan. 2022.
[4] S. Wang, J. Wan, D. Li, and C. Zhang, “Implementing Smart Factory of Industry 4.0: An outlook,” International Journal of Distributed Sensor Networks, vol. 18, no. 2, pp. 1–14, 2022.
[5] A. Kusiak, “Smart manufacturing using artificial intelligence and digital twins,” Journal of Manufacturing Systems, vol. 64, pp. 275–285, Jul. 2022.
[6] H. Lasi, P. Fettke, H. G. Kemper, T. Feld, and M. Hoffmann, “Industry 4.0 and intelligent manufacturing technologies: Recent advances and future perspectives,” IEEE Access, vol. 10, pp. 104312–104329, 2022.
[7] Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787–2805.
[8] Da Xu, L., He, W., & Li, S. (2014). Internet of Things in industries: A survey. IEEE Transactions on Industrial Informatics, 10(4), 2233–2243.
[9] Lee, J., Bagheri, B., & Kao, H. A. (2015). A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters, 3, 18–23.
[10] Wang, S., Wan, J., Li, D., & Zhang, C. (2016). Implementing smart factory of Industry 4.0: An outlook. International Journal of Distributed Sensor Networks, 12(1), 1–10.
[11] Lade, P., Ghosh, R., & Srinivasan, S. (2017). Manufacturing analytics and Industrial Internet of Things. IEEE Intelligent Systems, 32(3), 74–79.
[12] Tao, F., Qi, Q., Liu, A., & Kusiak, A. (2018). Data-driven smart manufacturing. Journal of Manufacturing Systems, 48, 157–169.
[13] Yang, H., Kumara, S., Bukkapatnam, S. T. S., & Tsung, F. (2019). The Internet of Things for smart manufacturing: A review. IISE Transactions, 51(11), 1190–1216.
[14] Ghahramani, M., Qiao, Y., Zhou, M. C., Hagan, A. O., & Sweeney, J. (2020). AI-based modeling and data-driven evaluation for smart manufacturing processes. IEEE/CAA Journal of Automatica Sinica, 7(4), 1026–1037.
[15] Lu, Y., Witherell, P., & Jones, A. (2020). Standard connections for IIoT empowered smart manufacturing. Manufacturing Letters, 26, 10–15.
[16] Kusiak, A. (2020). Convergence of engineering and data science: A foundation for smart manufacturing. International Journal of Production Research, 58(9), 2946–2960.
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How to Cite
[1]I. P. K, “Smart Manufacturing Analytics Using Industrial Internet of Things”, IJIARE, vol. 5, no. 2, pp. 01–16, Sep. 2022, doi: 10.67228/30715725/IJIARE-2022PII4Y7D.
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