Solving a New Mixed-Model Assembly LineSequencing Problem in a MTO Environment
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Solving a New Mixed-Model Assembly LineSequencing Problem in a MTO Environment

Authors: N. Manavizadeh, M. Hosseini, M. Rabbani

Abstract:

In the last decades to supply the various and different demands of clients, a lot of manufacturers trend to use the mixedmodel assembly line (MMAL) in their production lines, since this policy make possible to assemble various and different models of the equivalent goods on the same line with the MTO approach. In this article, we determine the sequence of (MMAL) line, with applying the kitting approach and planning of rest time for general workers to reduce the wastages, increase the workers effectiveness and apply the sector of lean production approach. This Multi-objective sequencing problem solved in small size with GAMS22.2 and PSO meta heuristic in 10 test problems and compare their results together and conclude that their results are very similar together, next we determine the important factors in computing the cost, which improving them cost reduced. Since this problem, is NPhard in large size, we use the particle swarm optimization (PSO) meta-heuristic for solving it. In large size we define some test problems to survey it-s performance and determine the important factors in calculating the cost, that by change or improved them production in minimum cost will be possible.

Keywords: Mixed-Model Assembly Line, particle swarmoptimization, Multi-objective sequencing problem, MTO system, kitto-assembly, rest time

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1070087

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References:


[1] P. Fattahi , M. Salehi," Sequencing the mixed-model assembly line to minimize the total utility and idle costs with variable launching interval ". Int J Adv Manuf Technol, vol.12, 2009.
[2] I. Sabuncuoglu, E.Erel, ArdaAlp, "Ant colony optimization for the single model U-type assembly line balancing problem ".Int .J.Production Economics, vol. 14, 2008.
[3] S.M. Mirghorbani, M. Rabbani., R. Tavakkoli-Moghaddam, and A. Rahimi-Vahed,"A Multi-Objective Particle Swarm for a Mixed-Model Assembly Line Sequencing", Engineering Optimization, vol.11, 2007, pp. 997-1012.
[4] J. Kyu Yoo, Y.Shimizu and Rei Hino". A sequencing problem for mixed-model assembly line with the aid of relief-ma" ,JSME International Journal, vol. 6, 2005.
[5] G. Celano, A.Costa, S. Ficheraa, G. Perrone, "Human factor policy testing in the sequencing of manual mixed model assembly lines ". Computers & Operations Research, vol. 31 2004, pp. 39-59.
[6] S.M.J .Mirzapour Al-e-Hashem and M.B . Aryanezhad, "An Efficient Method to Solve a Mixed-model Assembly Line Sequencing Problem Considering a Sub-line ".World Applied Sciences Journal, vol. 6, 2009, pp. 168-181.
[7] O. carlsson, B. Hensvold, "kitting in a high verification assembly line-a case study at caterpillar BCP-E ".2007 :95.
[8] A. Scholl, R. Klein, W. Domschke," Pattern based vocabulary building for effectively sequencing mixed-model assembly lines ".Journal of Heuristics, vol. 4, 1998, pp. 359-381.
[9] R.Tavakkoli-moghadam, A.R.Rahimi-Vahed, "multi-criteria sequencing problem for a mixed -model assembly line in a jit production system ". Applied Mathematics and Computation, vol. 181, 2006, pp. 1471-1481.
[10] S. Kim, B. Jeong, "Product sequencing problem in Mixed-Model Assembly Line to minimize unfinished works ".Computers & Industrial Engineering, vol. 53, 2007, pp. 206-214.
[11] J.Miltenburg, G .Sinnamon, "Scheduling mixed model multi-level justin- time production systems." International Journal of Production Research, vol. 27, 1989, pp.1487-1509.
[12] J. Kennedy, RC. Eberhart, "Particle swarm optimization", in conf. Rec.1995 IEEE international conference on neural networks, Piscataway, NJ, pp. 1942-1948.
[13] Y. Shi, RC .Eberhart," A modified particle swarm optimizer", in conf. Rec. 1998 IEEE international conference on evolutionary computation. IEEE Press, Piscataway, NJ, pp. 69-73.
[14] RC. Eberhart, Y. Shi, "Comparing inertia weights and constriction factors in particle swarm optimization". In 2000 IEEE congress evolutionary computation, San Diego, CA, pp. 84-88.
[15] M .Clerc, J. Kennedy," The particle swarm: explosion, stability and convergence in a multi-dimensional complex space" .in 2002 IEEE Trans Evol Comput, vol. 6, pp. 58-73.
[16] M. Ahmadieh Khanesar, (July 2009). "A Novel Binary Particle Swarm Optimization", in 2009 conf. 15th Mediterranean conference on control & automation.