Abstract
Group Technology (GT) is a manufacturing philosophy that explores similarities in product and process design. Starting from a binary machine-part matrix, the objective is to form clusters, made up of families of parts and machine cells aiming to minimize the number of voids and exceptional elements in the cells. Since this is a combinatorial problem, the proposed hybrid genetic algorithm (GA) finds good solutions with a partial greedy population that uses similarities with machines and with parts. A local search k-means based method can recreate cells with small movements among machine assignments. The proposed framework performance presents good results, most of them overcoming literature classic problems solutions, when considering the group effectiveness indicator. The results are presented and discussed.
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References
Carrie, A.S.: Numerical taxonomy applied to group technology and plant layout. Int. J. Prod. Res. 11(4), 399–416 (1973)
King, J.R.: Machine-component grouping in production flow analysis: an approach using a rank order clustering algorithm. Int. J. Prod. Res. 18(2), 213–232 (1980)
Chandrasekharan, M.P., Rajagopalan, R.: MODROC: an extension of rank order clustering for group technology. Int. J. Prod. Res. 24(5), 1221–1233 (1986)
Onwubolu, G.C., Mutingi, M.: A genetic algorithm approach to cellular manufacturing systems. Comput. Ind. Eng. 39(1–2), 125–144 (2001)
Rao, P.K.: A multi stage heuristic for manufacturing cell formation. Int. J. Res. Eng. Technol. 1163(45), 2308–2321 (2014)
Goldbarg, M.C., Luna, H.P.L.: Otimização Combinatória e Programação Linear: Modelos e Algoritmos. Elsevier, Rio de Janeiro (2005)
King, J.R., Nakornchai, V.: Machine-component group formation in group technology: review and extension. Int. J. Prod. Res. 20(2), 117–133 (1982)
Waghodekar, P.H., Sahu, S.: Machine-component cell formation in group technology: MACE. Int. J. Prod. Res. 22(6), 937–948 (1984)
Seifoddini, H.: Single linkage versus average linkage clustering in machine cells formation applications. Comput. Ind. Eng. 16(3), 419–426 (1989)
Kusiak, A., Cho, M.: Similarity coefficient algorithms for solving the group technology problem. Int. J. Prod. Res. 30(11), 2633–2646 (1992)
Kusiak, A., Chow, W.S.: Efficient solving of the group technology problem. J. Manuf. Syst. 6(2), 117–124 (1987)
Chandrasekharan, M.P., Rajagopalan, R.: GROUPABILITY: an analysis of the properties of binary data matrices for group technology. Int. J. Prod. Res. 27(6), 1035–1052 (1989)
Mccormick, W.T., Schweitzer, P.J., White, T.W.: Problem decomposition and data reorganization by a clustering technique. Oper. Res. 20(5), 993–1009 (1972)
Srinlvasan, G., Narendran, T.T., Mahadevan, B.: An assignment model for the part-families problem in group technology. Int. J. Prod. Res. 281(1), 145–152 (1990)
Mosier, C., Taube, L.: Weighted similarity measure heuristics for the group technology machine clustering problem. Omega 13(6), 577–579 (1985)
Ravi Kumar, K., Kusiak, A., Vannelli, A.: Grouping of parts and components in flexible manufacturing systems. Eur. J. Oper. Res. 24(3), 387–397 (1986)
Paydar, M.M., Saidi-Mehrabad, M.: A hybrid genetic-variable neighborhood search algorithm for the cell formation problem based on grouping efficacy. Comput. Oper. Res. 40(4), 980–990 (2013)
Kumar, K.R., Vannelli, A.: Strategic subcontracting for efficient disaggregated manufacturing. Int. J. Prod. Res. 25(12), 1715–1728 (1987)
Chandrasekharan, M.P., Rajagopalan, R.: Zodiac – an algorithm for concurrent formation of part-families and machine-cells. Int. J. Prod. Res. 25(6), 835–850 (1987)
Srinivasan, G., Narendran, T.T.: GRAFICS – a nonhierarchical clustering algorithm for group technology. Int. J. Prod. Res. 29(3), 463–478 (1991)
Srinivasan, G.: A clustering algorithm for machine cell formation in group technology using minimum spanning trees. Int. J. Prod. Res. 32(9), 2149–2158 (1994)
Cheng, C.H., Gupta, Y.P., Lee, W.H., Wong, K.F.: A TSP-based heuristic for forming machine groups and part families. Int. J. Prod. Res. 36(5), 1325–1337 (1991)
Laha, D., Hazarika, M.: A heuristic approach based on Euclidean distance matrix for the machine-part cell formation problem. Mater. Today. Proc. 4(2), 1442–1451 (2017)
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Branco, R.M., Rocha, C.R. (2020). Group Technology: Hybrid Genetic Algorithm with Greedy Formation and a Local Search Cluster Technique in the Solution of Manufacturing Cell Formation Problems. In: Anisic, Z., Lalic, B., Gracanin, D. (eds) Proceedings on 25th International Joint Conference on Industrial Engineering and Operations Management – IJCIEOM. IJCIEOM 2019. Lecture Notes on Multidisciplinary Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-43616-2_7
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