Abstract
A central aspect of surface mount technology (SMT) systems is the assembly of printed circuit boards (PCBs) which requires the resolution of many optimization problems. One of these problems arises when assembling many types of PCBs on a single machine. In this case, the main goal becomes the minimization of the setup times. That is, the time required to modify the feeder rack in order to have all components needed by the next type of PCB to be assembled. Achieving such a minimization goal will provide the system with improved productivity and flexibility capabilities. In order to minimize the setup time, we propose a genetic algorithm that uses a group-based representation with a series of specialized genetic operators. A set of 90 instances is proposed as a test bed for the single machine many-types of PCB problem. The proposed algorithm accomplishes the best known result for a benchmark instance of the problem and outperforms, in terms of assembly time, a well known heuristic on the set of proposed instances.
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References
Crama Y, Spieksma AOF (1994) Production planning in automated manufacturing. Springer, Berlin
Das S (1996) The measurement of flexibility in manufacturing systems. Int J Flex Manuf Syst 8:67–93
ElMaraghy HA (2006) Flexible and reconfigurable manufacturing systems paradigms. Int J Flex Manuf Syst 17:261–276
Lambert S, Abdulnor G, Drolet J, Cyr B (2006) Flexbility analysis of a surface mount technology electronic assembly plant: an integrated model using simulation. Int J Flex Manuf Syst 17:151–167
Garcia-Najera A, Brizuela CA (2005) PCB assembly: an efficient genetic algorithm for slot assignment and component pick and place sequence problems. In: Proceedings of the 2005 IEEE Congress on Evolutionary Computation, vol. 2, pp. 1485–1491
Bellman R (1991) Intelligent heuristic for fms scheduling using grouping. J Intell Manuf 2:387395
Smed J, Johnsson M, Puranen M, Leipälä T, Nevalainen O (1998) Job grouping in surface mounted component printing. Tech. Rep. 196. Turku Centre for Computer Science
Ammons JC, Carlyle M, Crammer LL, DePuy G, Ellis K, McGinnis LF, Tovey CA, Xu H (1997) Component allocation to balance workload in printed circuit card assembly systems. IIE Transcations 26:265–275
Crama Y, Flippo OE, van de Klundert J, Spieksma FCR (1997) The assembly of printed circuit boards: a case with multiple machines and multiple board types. Eur J Oper Res 98(3):457–472
Leon VJ, Peters BA (1998) A comparison of setup strategies for printed circuit board assembly. Comput Ind Eng 34(1):219–234
Balakrishnan A, Vanderbeck F (1999) A tactical planning model for mixed-model electronics assembly operations. Oper Res 47(3):395–409
Salonen K, Johnsson M, Smed J, Johtela T, Nevalainen O (2000) A comparison of group and minimum setup strategies in PCB assembly. In: Proceedings of Group Technology/Cellular Manufacturing World Symposium, vol. 1, pp 95–100
Crama Y, van de Klundert J, Spieksma FCR (2002) Production planning problems in printed circuit boards assembly. Discret Appl Math 123(1-3):339–361
Narayanaswami R, Iyengar V (2004) Setup reduction in printed circuit board assembly by efficient sequencing. Int J Adv Manuf Technol 26(3):276–284
Jeong IJ (2006) An entropy based group setup strategy for pcb assembly. In: 2006 International Conference on Computational Science and Its Applications. Springer, Berlin, pp 698–707
Ashayeri J, Selen W (2007) A planning and scheduling model for onsertion in printed circuit board assembly. Eur J Oper Res 183(2):909–925
Leu MC, Wong H, Ji Z (1993) Planning of component placement/insertion sequence and feeder setup in PCB assembly using genetic algorithm. Trans ASME 115:424–432
Ong N, Khoo LP (1999) Genetic algorithm approach in PCB assembly. Integr Manuf Syst 10(5):256–265
Ho W, Ji P (2005) A genetic algorithm to optimise the component placement process in PCB assembly. Int J Adv Manuf Technol 26(11):1397–1401
Godinho Filho M, Barco C, Tavares Neto R (2014) Using genetic algorithms to solve scheduling problems on flexible manufacturing systems (fms): a literature survey, classification and analysis. Flex Serv Manuf J 26(3):408–431. doi:10.1007/s10696-012-9143-6
Rubin PA, Ragatz GL (1995) Scheduling in a sequence dependent setup environment with genetic search. Comput Oper Res 22(1):85–99. doi:10.1016/0305-0548(93)E0021-K. Genetic Algorithms
Bigras LP, Gamache M, Savard G (2008) The time-dependent traveling salesman problem and single machine scheduling problems with sequence dependent setup times. Discret Optim 5(4):685–699. doi:10.1016/j.disopt.2008.04.001. http://www.sciencedirect.com/science/article/pii/S1572528608000339
Tan K, Narasimhan R (1997) Minimizing tardiness on a single processor with sequencedependent setup times: a simulated annealing approach. Omega 25(6):619–634. doi:10.1016/S0305-0483(97)00024-8
Frana PM, Mendes A, Moscato P (2001) A memetic algorithm for the total tardiness single machine scheduling problem. Eur J Oper Res 132(1):224–242. doi:10.1016/S0377-2217(00)00140-5
Gupta SR, Smith JS (2006) Algorithms for single machine total tardiness scheduling with sequence dependent setups. Eur J Oper Res 175(2):722–739. doi:10.1016/j.ejor.2005.05.018
Liao CJ, Juan HC (2007) An ant colony optimization for single-machine tardiness scheduling with sequence-dependent setups. Comput Oper Res 34(7):1899–1909. doi:10.1016/j.cor.2005.07.020
Gagne C, Price W, Gravel M (2002) Comparing an aco algorithm with other heuristics for the single machine scheduling problem with sequence-dependent setups. J Oper Res Soc 53:895–906
Gagne C, Price W, Gravel M (2005) Using metaheuristic compromise programming for the solution of multiple objective scheduling problems. J Oper Res Soc 56:687–698
Armentano VA, Mazzini R (2000) A genetic algorithm for scheduling on a single machine with set-up times and due dates. Prod Plan Control 11(7):713–720. doi:10.1080/095372800432188
Siud A, Gravel M, Gagne C New crossover operator for the single machine scheduling problem with sequencedependent setup times. In: Proceedings of GEM09 The 2009 International Conference on Genetic and Evolutionary Methods, pp 79–84
Siud A, Gravel M, Gagne C (2010) Constraint-based scheduling in a genetic algorithm for the single machine scheduling problem with sequence-dependent setup times. In: Proceedings of the IEEE CEC International Conference on Evolutionary Computation, pp 137–145
van Laarhoven PJM, Zijm WHM (1993) Production preparation and numerical control in PCB assembly. Int J Flex Manuf Syst 5(3):187–207
Salonen K, Smed J, Johnsson M, Nevalainen O (2003) Job grouping with minimum setup in PCB assembly. In: Proceedings of Group Technology/Cellular Manufacturing World Symposium, vol. 1, pp 221–225
Garey MR, Johnson DS (1999) Computers and intractability: A guide to the theory of NP-completeness. Freeman, San Francisco
Papadimitriou CH, Steiglitz K (1998) Combinatorial optimization: Algorithms and complexity. Dover, New York
Maimon O, Braha D (1998) A genetic algorithm approach to scheduling pcbs on a single machine. Int J Prod Res 36(3):761–784
Hardas CS, Doolen TL, Jensen DH (2008) Development of a genetic algorithm for component placement sequence optimization in printed circuit board assembly. Comput Ind Eng 55(1):165–182
Ho W, Ji P (2009) An integrated scheduling problem of pcb components on sequential pick-and-place machines: mathematical models and heuristic solutions. Expert Syst Appl 36(3):7002–7010
Neammanee P, Reodecha M (2009) A memetic algorithmbased heuristic for a scheduling problem in printed circuit board assembly. Comput Ind Eng 56(1):294–305
Dikos A, Nelson PC, Tirpak TM, Wang W (1997) Optimization of high-mix printed circuit card assembly using genetic algorithms. Ann Oper Res 75(1):303–324
Wang W, Nelson PC, Tirpak TM (1999) Optimization of high-speed multi-station SMT placement machines using evolutionary algorithms. IEEE Trans Electron Packag Manuf 22(2):137–146
Ho W, Ji P (2003) Component scheduling for chip shooter machines: a hybrid genetic algorithm approach. Comput Oper Res 30(14):2175–2189
Ho W, Ji P (2006) A genetic algorithm approach to optimising component placement and retrieval sequence for chip shooter machines. Int J Adv Manuf Technol 28:556–560
Chyu CC, Chang WS (2008) A genetic-based algorithm for the operational sequence of a high speed chip placement machine. Int J Adv Manuf Technol 36(9):918–926
Lee W, Lee S, Lee B, Lee Y (2000) A genetic optimization approach to operation of a multi-head surface mounting machine. IEICE Trans Fundam Electron Commun Comput Sci E83-A(9):1748–1756
Jeevan K, Parthiban A, Seetharamu KN, Azid IA, Quadir GA (2002) Optimization of PCB component placement using genetic algorithms. J Electron Manuf 11(1):69–79
Gyorfi JS, haur Wu C (2008) An efficient algorithm for placement sequence and feeder assignment problems with multiple placement-nozzles and independent link evaluation. IEEE Trans Syst Man Cybern : Part A 38(2):437–442
Falkenauer E (1996) A hybrid grouping genetic algorithm for bin packing. J Heuristics 2:5–30
Gen M, Cheng R (2000) Genetic algorithms and engineering optimization. Wiley, New York
Salonen K, Smed J, Johnsson M, Nevalainen O (2006) Grouping and sequencing pcb assembly jobs with minimum feeder setups. Robot Comput Integr Manuf 22(4):297–305
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García-Nájera, A., Brizuela, C.A. & Martínez-Pérez, I.M. An efficient genetic algorithm for setup time minimization in PCB assembly. Int J Adv Manuf Technol 77, 973–989 (2015). https://doi.org/10.1007/s00170-014-6510-3
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DOI: https://doi.org/10.1007/s00170-014-6510-3