Abstract
Simultaneous optimization of interrelated manufacturing processes viz. part sequencing and operation sequencing is required for the efficient allocation of production resources. Present paper addresses this problem with an integrated approach for Single Stage Multifunctional Machining System (SSMS), and identifies the best part sequence available in the part-mix. A mathematical model has been formulated to minimize the broad objectives of set-up cost and time simultaneously. The proposed approach has more realistic attributes as fixture related intricacies are also taken into account for model formulation. It has been solved by a new variant of particle swarm optimization (PSO) algorithm and named as Chaos embedded Taguchi particle swarm optimization (CE-TPSO) that draws its traits from chaotic systems, statistical design of experiments and time varying acceleration coefficients (TVAC). A simulated case study has been adopted from the literature and effectiveness of the proposed algorithm is proved. The results obtained with different variants of its own are compared along with the basic PSO and Genetic Algorithm (GA) to reveal the superiority of the proposed algorithm.
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Aihara K., Takabe T., Toyoda M. (1990) Chaotic neural network. Physics Letters A, 144: 333–340
Bachlaus M., Shukla N., Tiwari M.K., Shankar R. (2006) Optimization of system reliability using chaos embedded self organising hierarrchical particle swarm optimization. Proceedings of the Institution of Mechanical Engineers, Journal of Risk and Reliability, 220(2): 77–91
Bachlaus M., Tiwari M.K., Shankar R. (2008) Sequencing of parts on single-stage multifunctional systems using a chaos-embedded simulated annealing algorithm. International Journal of Production Research 46(12): 3387–3413
Caponetto R., Fortuna L., Fazzino S., Xibilia M.G. (2003) Chaotic sequences to improve the performance of evolutionary algorithm. IEEE Transactions on Evolutionary Computation 7(3): 289–304
Chan F.T.S., Chung S.H. (2005) Multicriterion genetic optimization for due date assigned distribution network problems. Decision Support Systems: Special Issue on Collaborative Work and Knowledge Management in Electronic Business, 39: 661–675
Chan F.T.S., Chung S.H., Chan L.Y., Finke G., Tiwari M.K. (2006) Solving distributed FMS scheduling problems subject to maintenance: Genetic algorithms approach. Robotics and Computer-Integrated Manufacturing 22: 493–504
Chan F.T.S., Chung S.H., Choy K.L. (2006) Optimization of order fulfillment in distribution network problems. Journal of Intelligent Manufacturing, 17(3): 307–319
Chan F.T.S., Wong T.C., Chan L.Y. (2005) Genetic algorithm-based approach to machine assignment problem. International Journal of Production Research, 43(22): 2451–2472
Chan F.T.S., Wong T.C., Chan L.Y. (2006) Flexible job-shop scheduling problem under resource constraints. International Journal of Production Research, 44(11): 2071–2089
Chan F.T.S., Wong T.C., Chan L.Y. (2008) Lot streaming for product assembly in job shop environment. International Journal of Robotics and Computer Integrated Manufacturing, 24(3): 321–331
Chandra P., Li S., Stan M. (1993) Jobs and tool sequencing in an automated manufacturing environment. International Journal of Production Research, 31(12): 2911–2925
Chang T.C., Tsai F.C., ke J.H. (2006) Data mining and taguchi method combination applied to the selection of discharge factors and the best interactive factor combination under multiple quality properties. International journal of Advance and Manufacturing Technology, 31: 164–174
Chen L., Aihara K. (1999) Global searching ability of chaotic neural networks. IEEE Transactions Circuit System I, 46: 974–993
Crama Y., Kolen A.W.J., Oerlemans A.G., Spieksma F.C.R. (1994) Minimizing the number of tool switches on a flexible manufacturing systems. International Journal of Flexible Manufacturing Systems, 6(1): 33–54
Crama Y., Oerlemans A.G. (1994) A column approach to job grouping for flexible manufacturing systems. European Journal of operational Research, 78: 58–80
Gray A.E., Seidmann A., Stecke K.E. (1992) synthesis of decision models for tool management for tool management in automated manufacturing. Management Science, 39(5): 549–567
Hertz A., Laporte G., Mittaz M., Stecke K.E. (1998) Heuristics for minimizing tool switches when scheduling part types on a flexible machine. IIE Transactions, 30(8): 689–694
Karen I., Yildiz A.R., Kaya N., Ozturk N., Ozturk F. (2006) Hybrid approach for genetic algorithm and Taguchi’s method based design optimization in the automotive industry. International Journal of Production Research, 44(15): 4897–4914
Kennedy J., Eberhart R. (1995) Particle swarm optimization. Proceedings—IEEE International Conference on Neural Network, 4: 1942–1948
Kim D.H., Shin S. (2006) Self-organization of decentralized swarm agent based on modified particle swarm algorithm. Journal of Intelligent and Robotic Systems, 46: 129–149
Kis T., Kiritsis D., Xiroouchakis P., Neuendorf K.P. (2000) A Petri net model for integrated process and job shop production planning. Journal of Intelligent Manufacturing, 11(2): 191–207
Koo P.H., Tanchoco J.M.A. (1999) Real-time operation and tool selection in single stage multifunctional machine systems. International Journal of Production Research, 37(5): 1023–1039
Koo P.H., Tanchoco J.M.A., Talavage J.J. (1998) Estimation of tool requirement in single-stage multimachine systems. International Journal of Production Research, 36(6): 1699–1713
Kusiak A. (1990) Optimal selection of machinable volumes. IEEE Transactions, 22(2): 151–162
Leung Y.W., Wang Y. (2001) An orthogonal genetic algorithm with quantization for global numerical optimization. IEEE Transactions on Evolutionary Computation, 5: 41–53
Levitine G., Ruubinovitz J. (1995) Algorithm for tool placement in an automatic tool change magazine. International Journal of Production Research, 33(2): 351–360
Lue P.H., Makiis V., Jardine A.K.S. (2001) Scheduling of the optimal tool replenishment time in a flexible manufacturing system. IEEE Transactions, 33(6): 487–495
Mati Y., Rezg N., Xie X. (2001) A taboo search approach for deadlock-free scheduling of automated manufacturing systems. Journal of Intelligent Manufacturing, 12(5–6): 535–552
Montgomery D.C. (1991) Design and analysis of experiments. Wiley, New York
Pandey M.K., Tiwari M.K., Zuo M.J. (2007) Interactive enhanced particle swarm optimization: A multiobjective reliability application. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 221: 177–191
Park S.H. (1996) Robust design and analysis for quality engineering. Chapman & Hall, London UK
Parker T.S., Chua L.O. (1989) Practical numerical algorithms for chaotic system. Springer-Verlag, Berlin, Germany
Peitgen H., Jurgens H., Saupe D. (1992) Chaos and fractals. Springer-Verlag, Berlin, Germany
Phadke M.S. (1989) Quality engineering using robust design. Prentice Hall, Englewood Cliffs, NJ
Ratnaweera A., Halgamuge S.K. (2004) Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients. IEEE Transactions on Evolutionary Computation, 8(3): 240–255
Sarma S.E., Wright P.K. (1996) Algorithms for the minimization of setups and tool changes in simply fixturable components of milling. Journal of Manufucturing Systems, 15(2): 95–111
Sinreich D., Nelkenbaum B.D. (2006) Determining production sequences for single-stage multifunctional machining systems based on the tradeoff between fixture cost, re-fixturing and tool replenishment. IIE Transactions, 38(10): 813–828
Sinriech D., Rubinovitz J., Milo D., Nakbily G. (2001) Sequencing, scheduling and tooling single stage multifunctional machines in a small batch environment. IIE Transactions 33(10): 897–911
Subramaniam V., Kumar A.S., Seow K.C. (2001) A multi-agent approach to fixture design. Journal of Intelligent Manufacturing, 12(1): 31–42
Tang C.S., Denardo E.V. (1988) Models arising from a flexible manufacturing machine, part1: minimization of the number of tool switches. Opera Research, 36: 767–777
Tsai, J.T., Chou, J.H., Liu, T.K. (2006). Tuning the Structure and parameters of a neural network by using hybrid taguchi-genetic algorithm. IEEE Transactions on Neural Networks, 17 (1).
Tsai J.T., Liu T.K., Chou J.H. (2004) Hybrid Taguchi genetic algorithm for global numerical optimization. IEEE Transactions on Evolutionary Computation, 8(4): 365–377
Tzur M., Altman A. (2004) Minimization of tool switching for a flexible manufacturing machine with slot assignment of different tool sizes. IIE Transactions, 36: 95–110
Venjara Y. (1996) Setup savings. Manufacturing Engineering, 117(1): 96–102
Webster S., Jog P.D., Gupta A. (1998) Genetic Algorithm for scheduling job families on a single machine with arbitrary earliness/ tardiness penalties and an unrestricted common due date. International Journal of Production Research, 36(9): 2543–2351
Yang L., Chen T. (2002) Application of chaos in genetic algorithms. Communication Theoretical Physics, 38: 168–72
Yuan X.H., Yuan Y.B., Zhang Y.C. (2002) A hybrid chaotic genetic algorithm for short-term hydro system scheduling. Mathematics and Computers in Simulation, 59: 319–327
Zhang F., Zhang Y.F., Nee A.Y.C. (1997) Using genetic algorithm in process planning for job shop machining. IEEE Transactions on Evolutionary Computation, 1(4): 278–289
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Kumar, V.V., Pandey, M.K., Tiwari, M.K. et al. Simultaneous optimization of parts and operations sequences in SSMS: a chaos embedded Taguchi particle swarm optimization approach. J Intell Manuf 21, 335–353 (2010). https://doi.org/10.1007/s10845-008-0175-4
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DOI: https://doi.org/10.1007/s10845-008-0175-4