Research Article
Year 2015,
Volume: 7 Issue: 2, 34 - 42, 15.06.2015
Abstract
In this study, variation of the task times, and precedence relation effects are investigated to evaluate the line performance. A new solution procedure based on queueing networks and constraint programming is proposed to model and solve the Assembly Line Balancing Problem (ALBP). Station utilization, total average number of jobs and smoothness index are used as performance measures. Bowl effect, inverted bowl effect and variability imbalance which are seen in balanced lines are examined by using proposed procedure. Also effects of the variability on the line performance are reviewed. Literature data sets are utilized to assess the effectiveness of the procedure.
References
- [1] A. Scholl, Balancing and Sequencing Assembly Lines. 2nd Edition, Physica, Heidelberg, 1999. [2] P.N. Rao, “A generalization of the 'bowl phenomenon' in series production systems”, International Journal of Production Research., vol. 14(4), pp. 437-443, 1976. [3] F.S. Hillier and C.K. So, “The Effect of the Coefficient of Variation of Operation Times on the Allocation of Storage Space in Production Line Systems”, IIE Transactions, vol. 23(2), pp. 198-206, 1991. [4] B. Das, A. Garcia-Diaz, A.C. MacDonald, K.K. Ghoshal, “A computer simulation approach to evaluating bowl versus inverted bowl assembly line arrangement with variable operation times”, The International Journal of Advanced Manufacturing Technology,vol. 51, pp. 15–24, 2010. [5] M.E. Salveson, “The assembly line balancing problem”, Journal of Industrial Engineering, vol. 6, pp. 18–25, 1955. [6] E. Erel, , S.C. Sarin, “A survey of the assembly line balancing procedures”, Production Planning & Control, vol. 9(5), pp. 414-434, 1998. [7] A. Scholl, C. Becker, “State-of-the-art exact and heuristic solution procedures for simple assembly line balancing”, European Journal of Operational Research, vol. 168(3), pp. 666-693, 2006. [8] C.Becker, A. Scholl, “A survey on problems and methods in generalized assembly line balancing”, European Journal of Operational Research, vol. 168(3), pp. 694-715, 2006. [9] C.L. Moodie, H.H. Young, “A heuristic method of assembly line balancing for assumptions of constant or variable work element times”, Journal of Industrial Engineering, vol. 16, pp 23–29, 1965. [10] J.F. Kottas, H.S. Lau, “A stochastic line balancing procedure”, International Journal of Production Research, vol. 19, pp. 177–193, 1981. [11] F. N. Silverman, J. C. Carter, “A cost-based methodology for stochastic line balancing with intermittent line stoppages”, Management Science, vol. 32(4), pp. 455-463, 1986. [12] S. C. Sarin, E. Erel, E. M. Dar-El, “A methodology for solving singlemodel, stochastic assembly line balancing problem”, Omega, vol. 27, pp. 525-535, 1999. [13] Z. Xiaobo, D. Xu, H. Zhang, Q.M. He, “Modeling and analysis of a supply–assembly–store chain”, European Journal of Operational Research, vol. 176(1), pp. 275-294, 2007. [14] Q.G. Sun, Y.D. Li, “Study on Stochastic Mixed-Model Assembly Line”, Proceeding of the International Conference on Mechanic Automation and Control Engineering (MACE), Wuhan, China, June 26-28, pp 3446 – 3449, 2010. [15] K. Ağpak, H. Gökçen, “A chance-constrained approach to stochastic line balancing problem”, European Journal of Operational Research, vol. 180(3), pp. 1098-1115, 2007. [16] U. Özcan, T. Kellegöz, B. Toklu, “A genetic algorithm for the stochastic mixed-model U-line balancing and sequencing problem”, International Journal of Production Research, vol. 49(6), pp. 1605-1626, 2011. [17] B. Cakir, F. Altiparmak, B. Dengiz, “Multi-objective optimization of a stochastic assembly line balancing: A hybrid simulated annealing algorithm”, Computers & Industrial Engineering, vol. 60(3), pp. 376-384, 2011. [18] P. R. McMullen, P. Tarasewich, “Using Ant Techniques to Solve the Assembly Line”, IIE Transactions, vol. 35(7), pp 605-617, 2003. [19] U. Özcan, “Balancing stochastic two-sided assembly lines: A chance-constrained, piecewise-linear, mixed integer program and a simulated annealing algorithm”, European Journal of Operational Research, vol. 205(1), pp. 81-97, 2010. [20] R.L. Carraway, “A dynamic programming approach to stochastic assembly line balancing”, Management Science, vol. 35(4), pp. 459-471, 1989. [21] G. Suresh, S. Sahu, “Stochastic assembly line balancing using simulated annealing”, International Journal of Production Research, vol. 32(8), pp. 1801-1810, 1994. [22] S. B. Liu, H. L. Ong, H. C. Huang, “A bidirectional heuristic for stochastic assembly line balancing Type II problem”, The International Journal of Advanced Manufacturing Technology, vol. 25(1-2), pp. 71-77, 2005. [23] K.R. Apt, Principles of Constraint Programming. Cambridge University Pres, 2003. [24] G.E. Khayat, A. Langevin, D. Riopel, “Integrated production and material handling scheduling using mathematical programming and constraint programming”, European Journal of Operational Research, vol. 175(3), pp. 1818-1832, 2006. [25] P.E. Hladik, H. Cambazard, A.M. Déplanche, N. Jussien, “Solving a real-time allocation problem with constraint programming”, Journal of Systems and Software, vol. 81(1), pp. 132-149, 2008. [26] L.J. Zeballos, “A constraint programming approach to tool allocation and production scheduling in flexible manufacturing systems”, Robotics and Computer-Integrated Manufacturing, vol. 26(6), pp. 725-743, 2010. [27] M. Trojet, F. H’Mida, P. Lopez, “Project scheduling under resource constraints: Application of the cumulative global constraint in a decision support framework”, Computers & Industrial Engineering, vol. 61(2), pp. 357-363, 2011. [28] H. Li, K. Womer, “Optimizing the supply chain configuration for make-to-order manufacturing”, European Journal of Operational Research, vol. 221(1), pp. 118-128, 2012. [29] D. Terekhov, M.K. Doğru, U. Özen, J.C. Beck, “Solving two-machine assembly scheduling problems with inventory constraints”, Computers & Industrial Engineering, vol. 63(1), pp. 120-134, 2012. [30] G. Latouche, M.F. Neuts, “Efficient algorithm solutions to exponential tandem queue with blocking”, SIAM J Algebra Disc Method, vol. 1(1), pp. 93–106, 1980. [31] E.H. Lipper, B. Sengupta, “Assembly-like queues with finite capacity: bounds, asymptotics and approximations”, Queueing systems: Theory and Applications, vol 1, pp. 67-83, 1986. [32] I. Duenyas, W.J. Hopp, “Estimating the throughput of an exponential CONWIP assembly system”, Queueing Systems, vol. 14, pp. 135-157, 1993. [33] A. Azaron, H. Katagiri, K. Kato, M. Sakawa, “Modelling complex assemblies as a queueing network for lead time control”, European Journal of Operational Research, vol. 174(1), pp. 150-168, 2006. [34] M. Manitz, “Queueing-model based analysis of assembly lines with finite buffers and general service times”, Computers & Operations Research, vol. 35(8), pp. 2520-2536, 2008. [35] R.R. Lazaro, C.J. Luis Perez, “Dynamic analysis of an automobile assembly line considering starving and blocking”, Robotics and Computer-Integrated Manufacturing, vol. 25(2), pp. 271-279, 2009. [36] J. Jackman, E. Johnson, “The Role of Queueing Network Models in Performance Evaluation of Manufacturing Systems”, The Journal of the Operational Research Society, vol. 44(8), pp. 797-807, 1993. [37] H.T. Papadopoulos, C. Heavey, “Queueing theory in manufacturing systems analysis and design: A classification of models for production and transfer lines”, European Journal of Operational Research, vol. 92, pp. 1-27, 1996. [38] M.K. Govil, M.C. Fu, “Queueing theory in manufacturing A survey”, Journal of Manufacturing Systems, vol. 18(3), pp. 214-240, 1999. [39] J.H. Patterson, J.J. Albracht, “Assembly-Line Balancing: Zero-One Programming with Fibonacci Search”, Operations Research, vol. 23(1), pp. 166-172, 1975. [40] R. Klein, A. Scholl, “Maximizing the Production Rate in Simple Assembly Line Balancing-A branch and bound procedure”, European Journal of Operational Research, vol. 91, pp. 367-385, 1996. [41] G. Bolch, S. Greiner, H. Meer, K.S. Trivedi, Queueing Networks and Markov Chains Modeling and Performance Evaluation with Computer Science Applications, John Wiley & Sons, New Jersey, 2006
Year 2015,
Volume: 7 Issue: 2, 34 - 42, 15.06.2015
Abstract
References
- [1] A. Scholl, Balancing and Sequencing Assembly Lines. 2nd Edition, Physica, Heidelberg, 1999. [2] P.N. Rao, “A generalization of the 'bowl phenomenon' in series production systems”, International Journal of Production Research., vol. 14(4), pp. 437-443, 1976. [3] F.S. Hillier and C.K. So, “The Effect of the Coefficient of Variation of Operation Times on the Allocation of Storage Space in Production Line Systems”, IIE Transactions, vol. 23(2), pp. 198-206, 1991. [4] B. Das, A. Garcia-Diaz, A.C. MacDonald, K.K. Ghoshal, “A computer simulation approach to evaluating bowl versus inverted bowl assembly line arrangement with variable operation times”, The International Journal of Advanced Manufacturing Technology,vol. 51, pp. 15–24, 2010. [5] M.E. Salveson, “The assembly line balancing problem”, Journal of Industrial Engineering, vol. 6, pp. 18–25, 1955. [6] E. Erel, , S.C. Sarin, “A survey of the assembly line balancing procedures”, Production Planning & Control, vol. 9(5), pp. 414-434, 1998. [7] A. Scholl, C. Becker, “State-of-the-art exact and heuristic solution procedures for simple assembly line balancing”, European Journal of Operational Research, vol. 168(3), pp. 666-693, 2006. [8] C.Becker, A. Scholl, “A survey on problems and methods in generalized assembly line balancing”, European Journal of Operational Research, vol. 168(3), pp. 694-715, 2006. [9] C.L. Moodie, H.H. Young, “A heuristic method of assembly line balancing for assumptions of constant or variable work element times”, Journal of Industrial Engineering, vol. 16, pp 23–29, 1965. [10] J.F. Kottas, H.S. Lau, “A stochastic line balancing procedure”, International Journal of Production Research, vol. 19, pp. 177–193, 1981. [11] F. N. Silverman, J. C. Carter, “A cost-based methodology for stochastic line balancing with intermittent line stoppages”, Management Science, vol. 32(4), pp. 455-463, 1986. [12] S. C. Sarin, E. Erel, E. M. Dar-El, “A methodology for solving singlemodel, stochastic assembly line balancing problem”, Omega, vol. 27, pp. 525-535, 1999. [13] Z. Xiaobo, D. Xu, H. Zhang, Q.M. He, “Modeling and analysis of a supply–assembly–store chain”, European Journal of Operational Research, vol. 176(1), pp. 275-294, 2007. [14] Q.G. Sun, Y.D. Li, “Study on Stochastic Mixed-Model Assembly Line”, Proceeding of the International Conference on Mechanic Automation and Control Engineering (MACE), Wuhan, China, June 26-28, pp 3446 – 3449, 2010. [15] K. Ağpak, H. Gökçen, “A chance-constrained approach to stochastic line balancing problem”, European Journal of Operational Research, vol. 180(3), pp. 1098-1115, 2007. [16] U. Özcan, T. Kellegöz, B. Toklu, “A genetic algorithm for the stochastic mixed-model U-line balancing and sequencing problem”, International Journal of Production Research, vol. 49(6), pp. 1605-1626, 2011. [17] B. Cakir, F. Altiparmak, B. Dengiz, “Multi-objective optimization of a stochastic assembly line balancing: A hybrid simulated annealing algorithm”, Computers & Industrial Engineering, vol. 60(3), pp. 376-384, 2011. [18] P. R. McMullen, P. Tarasewich, “Using Ant Techniques to Solve the Assembly Line”, IIE Transactions, vol. 35(7), pp 605-617, 2003. [19] U. Özcan, “Balancing stochastic two-sided assembly lines: A chance-constrained, piecewise-linear, mixed integer program and a simulated annealing algorithm”, European Journal of Operational Research, vol. 205(1), pp. 81-97, 2010. [20] R.L. Carraway, “A dynamic programming approach to stochastic assembly line balancing”, Management Science, vol. 35(4), pp. 459-471, 1989. [21] G. Suresh, S. Sahu, “Stochastic assembly line balancing using simulated annealing”, International Journal of Production Research, vol. 32(8), pp. 1801-1810, 1994. [22] S. B. Liu, H. L. Ong, H. C. Huang, “A bidirectional heuristic for stochastic assembly line balancing Type II problem”, The International Journal of Advanced Manufacturing Technology, vol. 25(1-2), pp. 71-77, 2005. [23] K.R. Apt, Principles of Constraint Programming. Cambridge University Pres, 2003. [24] G.E. Khayat, A. Langevin, D. Riopel, “Integrated production and material handling scheduling using mathematical programming and constraint programming”, European Journal of Operational Research, vol. 175(3), pp. 1818-1832, 2006. [25] P.E. Hladik, H. Cambazard, A.M. Déplanche, N. Jussien, “Solving a real-time allocation problem with constraint programming”, Journal of Systems and Software, vol. 81(1), pp. 132-149, 2008. [26] L.J. Zeballos, “A constraint programming approach to tool allocation and production scheduling in flexible manufacturing systems”, Robotics and Computer-Integrated Manufacturing, vol. 26(6), pp. 725-743, 2010. [27] M. Trojet, F. H’Mida, P. Lopez, “Project scheduling under resource constraints: Application of the cumulative global constraint in a decision support framework”, Computers & Industrial Engineering, vol. 61(2), pp. 357-363, 2011. [28] H. Li, K. Womer, “Optimizing the supply chain configuration for make-to-order manufacturing”, European Journal of Operational Research, vol. 221(1), pp. 118-128, 2012. [29] D. Terekhov, M.K. Doğru, U. Özen, J.C. Beck, “Solving two-machine assembly scheduling problems with inventory constraints”, Computers & Industrial Engineering, vol. 63(1), pp. 120-134, 2012. [30] G. Latouche, M.F. Neuts, “Efficient algorithm solutions to exponential tandem queue with blocking”, SIAM J Algebra Disc Method, vol. 1(1), pp. 93–106, 1980. [31] E.H. Lipper, B. Sengupta, “Assembly-like queues with finite capacity: bounds, asymptotics and approximations”, Queueing systems: Theory and Applications, vol 1, pp. 67-83, 1986. [32] I. Duenyas, W.J. Hopp, “Estimating the throughput of an exponential CONWIP assembly system”, Queueing Systems, vol. 14, pp. 135-157, 1993. [33] A. Azaron, H. Katagiri, K. Kato, M. Sakawa, “Modelling complex assemblies as a queueing network for lead time control”, European Journal of Operational Research, vol. 174(1), pp. 150-168, 2006. [34] M. Manitz, “Queueing-model based analysis of assembly lines with finite buffers and general service times”, Computers & Operations Research, vol. 35(8), pp. 2520-2536, 2008. [35] R.R. Lazaro, C.J. Luis Perez, “Dynamic analysis of an automobile assembly line considering starving and blocking”, Robotics and Computer-Integrated Manufacturing, vol. 25(2), pp. 271-279, 2009. [36] J. Jackman, E. Johnson, “The Role of Queueing Network Models in Performance Evaluation of Manufacturing Systems”, The Journal of the Operational Research Society, vol. 44(8), pp. 797-807, 1993. [37] H.T. Papadopoulos, C. Heavey, “Queueing theory in manufacturing systems analysis and design: A classification of models for production and transfer lines”, European Journal of Operational Research, vol. 92, pp. 1-27, 1996. [38] M.K. Govil, M.C. Fu, “Queueing theory in manufacturing A survey”, Journal of Manufacturing Systems, vol. 18(3), pp. 214-240, 1999. [39] J.H. Patterson, J.J. Albracht, “Assembly-Line Balancing: Zero-One Programming with Fibonacci Search”, Operations Research, vol. 23(1), pp. 166-172, 1975. [40] R. Klein, A. Scholl, “Maximizing the Production Rate in Simple Assembly Line Balancing-A branch and bound procedure”, European Journal of Operational Research, vol. 91, pp. 367-385, 1996. [41] G. Bolch, S. Greiner, H. Meer, K.S. Trivedi, Queueing Networks and Markov Chains Modeling and Performance Evaluation with Computer Science Applications, John Wiley & Sons, New Jersey, 2006
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Details
| Journal Section | Articles |
|---|---|
| Authors | |
| Publication Date | June 15, 2015 |
| Submission Date | October 24, 2017 |
| Published in Issue | Year 2015 Volume: 7 Issue: 2 |
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