Abstract
Process design of injection molding mainly involves the selection of molding machine, mold design, cost estimation, and the determination of injection molding parameters, which traditionally is performed by experienced engineers. Some researchers have attempted to automate the process design by using the simulation, process windows, expert systems, and the artificial neural network approach. In this paper, an artificial intelligence technique, case-based reasoning (CBR), is adopted to develop a case-based system for process design (CBSPD) of injection molding, which aims to derive a process solution for injection molding quickly and easily without relying on the experienced molding personnel. In the system, experience of the process design is represented in cases which are stored in the case library in a structural manner. After the input of the part, production and the quality information, 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 similarity analysis. Two types of adaptation, substitution and transformation, 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 for injection molding to be represented easily, but will facilitate a self-learning capability in the CBSPD.
Original language | English |
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Pages (from-to) | 40-50 |
Number of pages | 11 |
Journal | International Journal of Computer Applications in Technology |
Volume | 14 |
Issue number | 1-3 |
Publication status | Published - 1 Jan 2001 |
Keywords
- Case-based reasoning
- Injection molding
- Process design
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Computer Science Applications
- Computer Networks and Communications
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering
- Software
- Information Systems