Using neural networks for process planning

Samuel H. Huang, Hong Chao Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Process planning has been recognized as an interface between computer-aided design and computer-aided manufacturing. Since the late 1960s, computer techniques have been used to automate process planning activities. AI-based techniques are designed for capturing, representing, organizing, and utilizing knowledge by computers, and are extremely useful for automated process planning. To date, most of the AI-based approaches used in automated process planning are some variations of knowledge-based expert systems. Due to their knowledge acquisition bottleneck, expert systems are not sufficient in solving process planning problems. Fortunately, AI has developed other techniques that are useful for knowledge acquisition, e.g., neural networks. Neural networks have several advantages over expert systems that are desired in today's manufacturing practice. However, very few neural network applications in process planning have been reported. We present this paper in order to stimulate the research on using neural networks for process planning. This paper also identifies the problems with neural networks and suggests some possible solutions, which will provide some guidelines for research and implementation.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsShuzi Yang, Ji Zhou, Cheng-Gang Li
Number of pages12
StatePublished - 1995
EventInternational Conference on Intelligent Manufacturing - Wuhan, China
Duration: Jun 14 1995Jun 17 1995

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


ConferenceInternational Conference on Intelligent Manufacturing
CityWuhan, China


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