Hybrid genetic algorithm to optimize drilling route for copper clad laminate for printed circuit board substrate

Abstract

With a high demand in electronic device, Printed Circuit Board (PCB) and Integrated Circuit (IC) processing is attractive market segment. Many companies invest money and talent in order to get leading position. One of steps in PCB process is holes making to mount components, this is called drilling. Generally, drilling can be done by Computer Numerical Control (CNC) and optimization of tool routing path operation in machining can lead to significant reduction in non-productive machining time. Because of mass production, many PCB are processed before they are cut apart. Thus, reducing movement path length among board also helps to reduce total processing time for amount of board. Recently, most of researches work on optimization for single of board. This thesis focuses on the development of the Hybrid Genetic Algorithm and Cuckoo Search algorithm for use in searching for the optimal tool routing path and then, proposes some methods to reduce waste of movement among boards.