Document Type : Original Article

Authors

Department of Industrial Engineering, Islamic Azad university, Tabriz Branch.

Abstract

The Cellular Manufacturing System (CMS) is one of the most efficient systems for production environments with high volume and product variety which takes advantage of group technology. In the cellular production system, similar parts called part families are assigned to a production cell having similar production methods, and the needed machines are dedicated to cells. Determining part families and allocating the necessary machines to the production cell is known as the Cell Formation Problem (CFP) which is known as an NP-Hard problem. Safaei and Tavakkoli-Moghaddam (2009a) proposed a model that is widely used in literature which suffers some killer weaknesses highly affecting subsequent researches. In this paper, the mentioned model is modified and revised to fix these major issues.  Besides, due to the NP-Hard nature of the problem, a meta-heuristic algorithm based on Gray Wolf Optimization (GWO) approach is also developed for solving the revised model on the sample examples and the results are compared. Simulation results indicated that the proposed method can reduce the total cost of the manufacturing system by 3% in comparison with the base model. Furthermore, simulation results of five sample problems indicate the better performance of the proposed method comparing with Lingo and PSO.

Keywords

Aghajani, A., Kazemi, M., Rezaeian, J. (2010).” Designing a Dynamic Cellular Manufacturing Model with Considering Alternative Routing”, 3rd International Conference of Iranian Operations Research Society, Amirkabir University, Tehran, Iran.
Ahi, A., Aryanezhad, M.B., Ashtiani, B., Makui, A. (2009). “A novel approach to determine cell formation, intracellular machine layout and cell layout in the CMS problem based on TOPSIS method”, Computers & Operations research, 36(5), 1478-1496.
Almonacid, B. (2019). Resolve the cell formation problem in a set of three manufacturing cells (No. e27692v1). PeerJ Preprints.
‌Ardakani, A., Barzinpour, F., Tavakkoli-Moghaddam, R. (2012). “Developing the PSO algorithm for solving the integrated production planning and dynamic cellular manufacturing model”, Industrial Engineering Journal (in Persian), 46, 77-89.
Ayough, A., Khorshidvand, B. (2019). “Designing a manufacturing cell system by assigning workforce”. Journal of Industrial Engineering and Management, 12(1), 13-26.
Bajestani, M.A., Rabbani, M., Rahimi-Vahed, A.R., Baharian-Khoshkhou, G. (2009). “A multi-objective scatter search for a dynamic cell formation problem”, Computers & Operations research, 36(3), 777-794.
Ballakur A., Steudel, H.J. (1987). “A within Cell Utilization Based Heuristic for Designing Cellular Manufacturing Systems”, International Journal of Production Research, 25(5), 639-655.
Dehnavi-Arani, S., Sadegheih, A., Mehrjerdi, Y.Z. and Honarvar, M. (2020). “A new bi-objective integrated dynamic cell formation and AGVs’ dwell point location problem on the inter-cell unidirectional single loop”, Soft Computing, 24(21), 6021-16042.
Deljoo, V., Mirzapour Al-e-hashem, S.M.J., Deljoo, F., Aryanezhad, M.B. (2010). “Using genetic algorithm to solve dynamic cell formation problem”, Applied Mathematical Modelling, 34, 1078-1092.
Dmytryshyn, T., Ismail, M., & Rashwan, O. (2018, November). A novel modeling approach for solving the cell formation problem. In ASME International Mechanical Engineering Congress and Exposition (Vol. 52019, p. V002T02A074). American Society of Mechanical Engineers.
Doulabi, S.H., Hojabri, H., Davoudpour, H., Seyed-Alagheband, S.A., Jaafari, A. (2009). “Two-phase approach for solving cell-formation problem in cell manufacturing”, In Proceedings of the world congress on engineering and computer science, Vol II, October 20–22, San Francisco.
Golmohammadi, A. M., Honarvar, M., Hosseini-Nasab, H., & Tavakkoli-Moghaddam, R. (2020). A bi-objective optimization model for a dynamic cell formation integrated with machine and cell layouts in a fuzzy environment. Fuzzy Information and Engineering, 12(2), 204-222.
Hafezalkotob, A., Tehranizadeh, M., Sarani Rad, F., Sayadi, M. (2015). “An Improved DPSO Algorithm for Cell Formation Problem”, Journal of Industrial and Systems Engineering, 8(2), 30-53.
Hamza, S., & Jehad, A. (2019). “Heuristic Method for Solving Cell Formation Problem in Cellular Manufacturing System Based on Hamming Distance”, The Iraqi Journal for Mechanical and Materials Engineering, 19(1), 75-90. 
Karim, R., Biswas, S.K. (2015). “A literature review on cell formation problem in a batch-oriented production system”, International Journal of scientific research and management, 3(2), 2187-2192.
Kheirkhah, A., Ghajari, A. (2018). “A three-phase heuristic approach to solve an integrated cell formation and production planning problem”, Uncertain Supply Chain Management, 6(2), 213-228.
Kiaa, F., Khaksar-Haghanib, A., Javadian, N., Tavakkoli-Moghaddam, R. (2014). “Solving a multi-floor layout design model of a dynamic cellular manufacturing system by an efficient genetic algorithm”, Journal of Manufacturing Systems, 33, 218–232.
Kia, R., Baboli, A., Javadian, N., Tavakkoli-Moghaddam, R., Kazemi, M., Khorrami, J. (2012). “Solving a group layout design model of a dynamic cellular manufacturing system with alternative process routings, lot splitting and flexible reconfiguration by simulated annealing”, Computers & Operations research, 39(11), 2642-2658.
Kioon, S.A., Bulgak, A. A., Bektas, T. (2009). “Integrated cellular manufacturing systems design with production planning and dynamic system reconfiguration”, European Journal of Operations Research, 192(2), 414-428.
Mahdavi, I., Aalaei, A., Paydar, M.M., Solimanpur, M. (2010). “Designing a mathematical model for dynamic cellular manufacturing systems considering production planning and worker assignment”, Computers and Mathematics with Applications, 60(4), 1010-1025.
Mirjalili, S., Mirjalili S.M., Lewis, A. (2014). “Grey Wolf Optimizer”, Advances in Engineering Software, 69, 46-61.
Nagaraj, G., Arunachalam, M., Vinayagar, K. (2020). “Enhancing performance of cell formation problem using hybrid efficient swarm optimization”, Soft Computing, 24, 16679–16690.
‌Noktehdan, A., Karimi, B., Husseinzadeh Kashan, A. (2009). “A differential evolution algorithm for the manufacturing cell formation problem using group-based operators”, Expert System with Applications, 37(7), 4822-4829.
Rafiee, M. Rabbani, H. Rafiei, H., Rahimi-Vahed, A. (2011). “A new approach towards integrated cell formation and inventory lot sizing in an unreliable cellular manufacturing system”, Applied Mathematical Modelling, 32, 1810-1819.
Rafiee, H, Ghodsi, R. (2012). “A bi-objective mathematical model toward dynamic cell formation considering labor utilization”, Applied Mathematical Modelling, APM 8939.
Rajesh, K.V.D, Abidali, M.D., Chalapathi, P.V. (2018). “Voids Based Approach for Solving Cell Formation Problems”, MaterialsToday: Proceedings, Vol. 5, Issue 13, part 3, pp. 27185-27192.
Saeedi, S., Solimanpur, M., Mahdavi, I., Javadian, N. (2010). “Heuristic Approaches for Cell Formation in Cellular Manufacturing”, Journal of Software Engineering & Applications, 3, 674-682.
Saeedi, S., Solimanpur, M., Mahdavi, I., Javadian, N. (2014). “A multi-objective genetic algorithm for solving cell formation problem using a fuzzy goal programming approach”, International Journal of Advanced Manufacturing Technology, 70, 1635-1652.
Safaei, N., Tavakkoli-Moghaddam, R. (2009a). “Integrated multi-period cell formation and subcontracting production planning in dynamic cellular manufacturing systems”, International Journal of Production Economics, 120(2), 301-314.
Safaei, N., Tavakkoli-Moghaddam, R. (2009b). “Integrated multi-period cell formation and subcontracting production planning in dynamic cellular manufacturing”, International Journal of Production Economics, 120(2), 301-314.
Solimanpur, M, Saeedi, S., Mahdavi, I. (2010). “Solving cell formation problem in cellular manufacturing using ant-colony-based optimization”, International Journal of Advanced Manufacturing Technology, 50(9-12), 1135-1144.
Zhu, Y., & Li, S. (2018). Simultaneous Hierarchical Clustering for Cell Formation Problems with Production Information. Mathematical Problems in Engineering, 2018.