A logic representation of manufacturing control

Authors:
William I. Bullers;Shimon Y. Nof;Andrew B. Whinston
Affiliations:
Krannert School of Management, Purdue University, West Lafayette, IN;School of Industrial Engineering, Purdue University, West Lafayette, IN;Krannert School of Management and Computer Science Dept., Purdue University, West Lafayette, IN
Venue:
IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 1
Year:
1979

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A Machine-Oriented Logic Based on the Resolution Principle

Journal of the ACM (JACM)
Problem-Solving Methods in Artificial Intelligence

Problem-Solving Methods in Artificial Intelligence

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Abstract

This paper explores some of the typical problems in manufacturing systems planning and control, particularly those pertinent to automatic operation, and describes how artificial intelligence methods can be applied. We demonstrate how predicate logic and theorem-proving techniques using resolution can be used in a manufacturing environment. Assertions of fact and axioms representing the knowledge required are given in an underlying data base. Illustrative examples demonstrate how user problems, such as assignment of Jobs to machines when conflicts occur, can be handled by a decision support system in the framework of resolution in a problem-reduction approach.