A case-based system for process design of injection moulding

Process design of injection molding mainly involves the selection of moldin g machine. mold design, cost estimation. and the determination of injection molding parameters, which traditionally is performed by experienced engine ers. Some researchers have attempted to automate the process design by usin g the simulation, process windows, expert systems. and the artificial neura l network approach. In this paper, an artificial intelligence technique, ca se-based reasoning (CBR), is adopted to develop a case-based system for pro cess design (CBSPD) of injection molding, which aims to derive a process so lution for injection molding quickly and easily without relying on the expe rienced molding personnel. In the system. experience of th process design i s represented in cases which are stored in the case library in a structural manner. After the input of the part, production and the quality informatio n, the system searches for the proper cluster of cases and the closest case is then retrieved based on the pre-defined indexes and the two stages of s imilarity analysis. Two types of adaptation. substitution and transformatio n. have been introduced to adapt the closest case for the new problem. This approach will not only allow the fragile knowledge of the process design f or injection molding to be represented easily, but will facilitate a self-l earning capability in the CBSPD.