The Art and Science of Cell Production System Design: A Literature Review

Authors

  • Elend Mirzaei Faculty Member of Academic Center for Education, Culture and Research (ACECR), Tabriz, Iran

Keywords:

Cell Production System, Manufacturing Design, Group Technology

Abstract

This literature review, The Art and Science of Cell Production System Design: A Literature Review, provides a comprehensive examination of the principles, methodologies, and advancements in the design of cell production systems (CPS) within manufacturing environments. A cell production system is a flexible, efficient approach that organizes production processes into cells based on product families, allowing for increased efficiency, reduced lead times, and improved product quality. This review synthesizes research from multiple disciplines, including industrial engineering, operations management, and manufacturing technology, to offer insights into the key components and challenges of CPS design. The paper explores various strategies, such as group technology, layout optimization, and automation, that influence cell design, highlighting the benefits of improved workflow, worker collaboration, and adaptability to demand changes. It also examines the role of technological advancements, including robotics and AI, in modernizing cell production systems. The review identifies gaps in current literature, such as the need for more empirical studies and the integration of sustainability factors in CPS design. Ultimately, this study provides valuable knowledge for practitioners and researchers seeking to optimize manufacturing processes and achieve operational excellence through cell production systems.

References

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Askin, R. G. (2013). Contributions to the design and analysis of cellular manufacturing systems. International Journal of Production Research, 51(23-24), 6778-6787.

Nouri, H. A., Leman, Z., Moghadam, H. P., & Sulaiman, R. (2014). Literature review on machine reliability in cellular manufacturing system. Am J Appl Sci, 11(12), 1964-1968.

Wu, L., Zhao, Y., Feng, Y., Niu, B., & Xu, X. (2021). Minimizing makespan of stochastic customer orders in cellular manufacturing systems with parallel machines.Computers & Operations Research,125, 105101.

Zhao, Y., Xu, X., & Li, H. (2018). Minimizing expected cycle time of stochastic customer orders through bounded multi-fidelity simulations. IEEE Transactions on Automation Science and Engineering, 15(4), 1797-1809.

Nasiri, M. M., & Naseri, F. (2019). Metaheuristic algorithms for the generalised cell formation problem considering machine reliability. International Journal of Process Management and Benchmarking, 9(4), 469-484.

Zhao, Y., Xu, X., Li, H., & Liu, Y. (2018). Stochastic customer order scheduling with setup times to minimize expected cycle time. International Journal of Production Research, 56(7), 2684-2706.

Chen, J., Wang, M., Kong, X. T., Huang, G. Q., Dai, Q., & Shi, G. (2019). Manufacturing synchronization in a hybrid flowshop with dynamic order arrivals. Journal of Intelligent Manufacturing, 30(7), 2659-2668.

Aalaei, A., Kayvanfar, V., & Davoudpour, H. (2019). Integrating multi-dynamic virtual cellular manufacturing systems into multi-market allocation and production planning. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 233(2), 643-664.

Xue, G., & Offodile, O. F. (2020). Integrated optimization of dynamic cell formation and hierarchical production planning problems. Computers & Industrial Engineering, 139, 106155.

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Published

2023-12-19

How to Cite

The Art and Science of Cell Production System Design: A Literature Review. (2023). International Journal of Political Sciences and Economics, 2(4), 4-7. https://ijmri.de/index.php/ijpse/article/view/47

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