Solving a New Mixed-Model Assembly LineSequencing Problem in a MTO Environment
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.
[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.
[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.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:57092", author = "N. Manavizadeh and M. Hosseini and M. Rabbani", title = "Solving a New Mixed-Model Assembly LineSequencing Problem in a MTO Environment", 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", volume = "5", number = "9", pages = "1828-10", }