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SIPS: An Application of Hierarchical Knowledge Clustering to Process Planning

Published

Author(s)

D Nau, M M. Gray

Abstract

This paper describes SIPS, an AI system which selects machining operations for the creation of metal parts. SIPS is a successor to SIPP, which was described at a previous ASME conference. Whereas SIPP was intended purely as a prototype, SIPS is intended to be at the core of a useable process planning system. SIPS uses knowledge-based reasoning techniques to make process plans completely from scratch,using only the specification of the part of be produced and knowledge about the intrinsic capabilities of each manufacturing operation. SIPS incorporates a knowledge representation language written in Lisp, a best-first Branch and Bound strategy for finding process plans of least possible cost and a new knowledge representation technique called hierarchical knowledge clustering.
Proceedings Title
Proceedings of the Symposium on Integrated and Intelligent Manufacturing ASME Winter Annual Meeting
Conference Location
, USA

Keywords

SIP, AI, ASME, process planning, knowledge-based reasoning techniques

Citation

Nau, D. and Gray, M. (1986), SIPS: An Application of Hierarchical Knowledge Clustering to Process Planning, Proceedings of the Symposium on Integrated and Intelligent Manufacturing ASME Winter Annual Meeting, , USA (Accessed July 27, 2024)

Issues

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Created February 28, 1986, Updated October 12, 2021