A particle swarm optimization approach to optimize component placement in printed circuit board assembly
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ORIGINAL ARTICLE
A particle swarm optimization approach to optimize component placement in printed circuit board assembly Yee-Ming Chen & Chun-Ta Lin
Received: 18 January 2006 / Accepted: 28 August 2006 / Published online: 25 November 2006 # Springer-Verlag London Limited 2006
Abstract The particle swarm optimization (PSO) approach has been successfully applied in continuous problems in practice. However, its application on the combinatorial search space is relatively new. The component assignment/ sequencing problem in printed circuit board (PCB) has been verified as NP-hard (non-deterministic polynomial time). This paper presents an adaptive particle swarm optimization (APSO) approach to optimize the sequence of component placements on a PCB and the assignment of component types to feeders simultaneously for a pick-andplace machine with multiple heads. The objective of the problem is to minimize the total traveling distance (the traveling time) and the total change time of head nozzle. The APSO proposed in the paper incorporates three heuristics, namely, head assignment algorithm, reel grouping optimization and adaptive particle swarm optimization. Compared with the results obtained by other research, the performance of APSO is not worse than the performance of genetic algorithms (GA) in terms of the distance traveled by the placement head.
Y.-M. Chen : C.-T. Lin Department of Industrial Engineering and Management of Yuan Ze University, 135, Far-east Rd., Chung-li, Taoyuan, Taiwan, Republic of China C.-T. Lin (*) Department of Information Management of Yu-Da College of Business, 168, Hsueh-fu Rd., Tan-wen Village, Chao-chiao Township, Miao-li, Taiwan, Republic of China e-mail: [email protected]
Keywords Particle swarm optimization (PSO) . Printed circuit board (PCB) . Component assignment/sequencing problem in PCB
1 Introduction Enormous growth in demand for customer, commercial and industrial computer and other electronic devices has made printed circuit board (PCB) assembly a fast growing market. As the variety of products in need of PCBs grows, the circuit board manufacturing industry relies more and more upon highly automated production processes including the numerically controlled machines for the placement of surface mount technology (SMT) components on the circuit board. The expense of the automated production equipment motivates PCB manufacturers to plan for the optimal assembly process that either minimizes the total production cost or maximizes the profit. The overall PCB assembly time depends on two decision problems: (1) assignment of reels to slots on feeder racks; and (2) sequencing of pick-and-place (PAP) movements [1]. These two problems are combinatorial optimization problems, which are known to be NP-hard and discrete type [2]. Leipala and Nevalainen formulated component pick-andplace sequencing as a 3-dimensional asymmetric traveling salesman problem (TSP) and reel assignment as a quadratic assignment problem [3]. Although assignment/ sequencing problems are highly interrelated, it is diff
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