Optimization On Component Allocation Between Placement Machines In A SMT Assembly Line

Printed circuit board (PCB) is the circuit board on which a number of electronic are located at predefined positions and wired through electrical connections. PCB assembly is to assemble electronic components on the circuit board to make them connected with each other. By 2005, China has become the second largest PCB assembly place following Japan. However, the PCB assembly industry in China has only 20 years history since 1980. PCB is assembled by surface mount manufacturing system. This system is an advanced manufacturing system, which has characteristics of surface mount technology (SMT), flexible manufacturing systems and computer integrated manufacturing system. PCB assembly is under high-mix and low-volume production environment, which must offer high product variety and satisfy the dynamic product demand. Its objective is to maximize the output with the lowest cost and smallest defect rate in the shortest possible time. This trend emphasizes the importance of optimizing the SMT assembly processes.This paper first introduces the main equipment of the SMT assembly line, focusing on high-speed and multi-function placement machines. Secondly, the basic principle and the realization technology of the genetic algorithms is introduced. Then the classification of SMT optimization problem is proposed, and the problem studied by this paper is on the second lever, i.e. the component allocation between placement machines in a SMT assembly line. The objective of the component allocation is to minimize the maximum workload of the table, which consists of both placement time and nozzle change time. A MIP model is proposed , then a genetic algorithm is developed and implemented on real life problems. The comparison experiments with both lower bound and built-in software show that the proposed model and algorithm are more efficient.