Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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Machine-Part Grouping with Alternative Process Plan - An algorithm based on the self-organizing neural networks -

대체공정이 있는 기계-부품 그룹의 형성 - 자기조직화 신경망을 이용한 해법 -

  • Received : 2016.08.22
  • Accepted : 2016.08.29
  • Published : 2016.09.30
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Abstract

The group formation problem of the machine and part is a critical issue in the planning stage of cellular manufacturing systems. The machine-part grouping with alternative process plans means to form machine-part groupings in which a part may be processed not only by a specific process but by many alternative processes. For this problem, this study presents an algorithm based on self organizing neural networks, so called SOM (Self Organizing feature Map). The SOM, a special type of neural networks is an intelligent tool for grouping machines and parts in group formation problem of the machine and part. SOM can learn from complex, multi-dimensional data and transform them into visually decipherable clusters. In the proposed algorithm, output layer in SOM network had been set as one-dimensional structure and the number of output node has been set sufficiently large in order to spread out the input vectors in the order of similarity. In the first stage of the proposed algorithm, SOM has been applied twice to form an initial machine-process group. In the second stage, grouping efficacy is considered to transform the initial machine-process group into a final machine-process group and a final machine-part group. The proposed algorithm was tested on well-known machine-part grouping problems with alternative process plans. The results of this computational study demonstrate the superiority of the proposed algorithm. The proposed algorithm can be easily applied to the group formation problem compared to other meta-heuristic based algorithms. In addition, it can be used to solve large-scale group formation problems.

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References

  1. Adenso-Dias, B., Lozano, S., Racero, J., and Guerrero, F., Machine cell formation in generalized group technology, Computers and Industrial Engineering, 2001, Vol. 41, No. 2, pp. 227-240. https://doi.org/10.1016/S0360-8352(01)00056-0
  2. Adil, G.K., Rajamani D., and Strong D., Cell Formation Considering Alternate Routeings, International Journal of Production Research, 1996, Vol. 34, No. 5, pp. 1361-1380. https://doi.org/10.1080/00207549608904970
  3. Goldengorin, B., Krushinsky, D., and Pardalos, P.M., Cell Formation in Industrial Engineering Theory, Algorithms and Experiments, Springer, 2013, pp. 1-23.
  4. Ham, I., Hitomi, K., and Yoshida, T., Group Technology : Production Methods in Manufacture, Kluwer-Nijhoff, Boston, MA, 1985.
  5. Jeon, Y.D. and Kang, M.K., A Self-Organizing Neural Networks Approach to Machine-Part Grouping in Cellular Manufacturing Systems, Journal of the Society of Korea Industrial and Systems Engineering, 1998, Vol. 21, No. 48, pp. 123-132.
  6. Jeon, Y.D. and Kang, M.K., Grouping of parts reflecting changes of manufacturing conditions : An algorithm based on the self-organizing neural networks, Journal of the Korean Institute of Plant Engineering, 1998, Vol. 3, No. 2, pp. 241-251.
  7. Kasilingam, R.G. and Lashkari, R.S., Cell Formation in the Presence of Alternate Process Plans in Flexible Manufacturing Systems, Production Planning and Control, 1991, Vol. 2, No. 2, pp. 135-141. https://doi.org/10.1080/09537289108919340
  8. Kohonen, T., Self-organized formation of topologically correct feature maps, Biological Cybernetics, 1982, Vol. 43, pp. 59-69. https://doi.org/10.1007/BF00337288
  9. Kumar, C.S. and Chandrasekharan, M.P., Grouping efficacy : A quantitative criterion for goodness of block diagonal forms of binary matrices in group technology, International Journal of Production Research, 1990, Vol. 28, No. 2, pp. 233-243. https://doi.org/10.1080/00207549008942706
  10. Kusiak, A. and Cho, M., Similarity coefficient algorithms for solving the group technology problem, International Journal of Production Research, 1992, Vol. 30, No. 11, pp. 2633-2646. https://doi.org/10.1080/00207549208948181
  11. Kusiak, A., Computational Intelligence in Design and Manufacturing, Wiley and Sons, 2000, pp. 294-346.
  12. Kusiak, A., The generalized group technology concept, International Journal of Production Research, 1987, Vol. 25, No. 4, pp. 561-569. https://doi.org/10.1080/00207548708919861
  13. Logendran, R., Ramakrishna, P., and Sriskandarajah, C., Tabu Search-Based Heuristics for Cellular Manufacturing Systems in the Presence of Alternative Process plans, International Journal of Production Research, 1994, Vol. 32, No. 2, pp. 273-297. https://doi.org/10.1080/00207549408956933
  14. Moon, Y.B. and Chi, S.C., Generalized Part Family Formation Using Neural Network Techniques, Journal of Manufacturing Systems, 1992, Vol. 11, No. 3, pp. 149-159. https://doi.org/10.1016/0278-6125(92)90001-V
  15. Nagi, R., Harhalakis, G., and Proth, J.M., Multiple Routeings and Capacity Considerations in Group Technology Applications, International Journal of Production Research, 1990, Vol. 28, No. 12, pp. 2243-2257.
  16. Sankaran, S. and Kasilingam, R.G., An Integrated Approach to Cell Formation and Part Routing in Group Technology Manufacturing Systems, Engineering Optimization, 1990, Vol. 16, No. 3, pp. 235-245. https://doi.org/10.1080/03052159008941175
  17. Sofianopoulou, S., Manufacturing cells design with Alternative Process Plans and/or replicate machines, International Journal of Production Research, 1999, Vol. 37, No. 3, pp. 707-720. https://doi.org/10.1080/002075499191742
  18. Won, Y.K. and Kim, S.H., Multiple Criteria Clustering Algorithm for Solving the Group Technology Problem with Multiple Process Routings, Computers and Industrial Engineering, 1997, Vol. 32, No. 1, pp. 207-220. https://doi.org/10.1016/S0360-8352(96)00209-4
  19. Wu, T.H., Chung, S.H., and Chang, C.C., Hybrid Simulated Annealing Algorithm with Mutation Operator to the Cell Formation Problem with Alternative Process Routings, Expert Systems with Applications, 2009, Vol. 32, No. 2, pp. 3652-3661.

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