Optimization of automated high-speed modular placement machines using knowledge-based systems

This paper introduces an optimizer for a new family of modular, multistatio n, walking beam, high-speed chip mounters. The objective is to optimize the machines in a manner that would streamline the use of nozzles and part fee der mechanisms and at the same time increase throughput. The optimization o f these machines is a large NP-complete problem, and therefore, a heuristic search method is needed to solve the problem in reasonable time. Four know ledge-based systems are introduced to solve this problem. These systems wer e designed to emulate human experts, who have optimized these types of mach ines manually. Benchmarks were performed for 18 industrial test cases, The results show that overall, the knowledge-based systems outperformed softwar e supplied by the vendor of the machine in both feeder slot savings and thr oughput. This performance represents a key improvement, and a prototype sys tem has been implemented in our industrial partner's factory.