Paradigms for knowledge-based systems in industrial engineering

Abstract When developing expert systems, expertise lies not only in formulating the knowledge to be put into the knowledge base, but also in deciding upon the knowledge representation and inference mechanism most suited to the application. Six detailed knowledge bases demonstrate the application of various AI-based systems to industrial engineering problems. They illustrate a number of approaches: expert systems, which are based upon practical experience; decision systems, which derive from modelling skills; and situation-action systems, which rely on production process design skills. The six paradigms presented describe a logical expert system for selecting material handling equipment; a multi-valued expert system for selecting a dispatching rule for automatic guided vehicles; a profile matching expert system for selecting project management software; a confidence building expert system for selecting a machine feeder; a tandem decision system for developing a production schedule; and a situation-action system for controlling job allocation in a flexible manufacturing cell. The relationships between these various paradigms and the characteristics of problems to which they can be applied are categorized by the nature of the expert and his expertise; the features of the environment; the decision or decisions to be taken; and the manner in which AI-system performance can be evaluated. A knowledge base is proposed for determining which architecture is most appropriate for a given application.

[1]  Charles J. Malmborg,et al.  A prototype expert system for industrial truck type selection , 1987 .

[2]  David Ben-Arieh,et al.  Knowledge Based Control System for Automated Production and Assembly , 1985 .

[3]  J. Hatvany,et al.  Matching Al Tools to Engineering Requirements , 1987 .

[4]  James A. Reggia,et al.  A Comparative Analysis of Methods for Expert Systems , 1986, Int. J. Man Mach. Stud..

[5]  Richard A. Wysk,et al.  Intelligent Control of Flexible Manufacturing Systems , 1991 .

[6]  Richard A. Wysk,et al.  An Analysis Of Control Strategies For An Automated Storage/Retrieval System , 1987 .

[7]  Bing Liu,et al.  Scheduling via reinforcement , 1988, Artif. Intell. Eng..

[8]  Donald A. Waterman,et al.  A Guide to Expert Systems , 1986 .

[9]  Peter Mertens,et al.  Expert systems in production management: An assessment , 1986 .

[10]  Pius J. Egbelu,et al.  Characterization of automatic guided vehicle dispatching rules , 1984 .

[11]  Claude Le Pape,et al.  SONIA: A knowledge-based scheduling system , 1988, Artif. Intell. Eng..

[12]  Duc Truong Pham,et al.  Expert systems in mechanical and manufacturing engineering , 1988 .

[13]  Pietro Laface,et al.  A Rule-Based System to Schedule Production , 1986, Computer.

[14]  Andrew Kusiak,et al.  Designing expert systems for scheduling automated manufacturing , 1987 .

[15]  Heimo H. Adelsberger,et al.  Expert systems in production scheduling , 1987 .

[16]  David H. Marks,et al.  Intelligent use of Constraints for Activity Scheduling , 1986 .

[17]  Bartholomew O. Nnaji.  Computer-aided design, selection, and evaluation of robots , 1986 .

[18]  Andrew Kusiak.  Knowledge-Based Systems in Manufacturing , 1989 .

[19]  Pius J. Egbelu.  Pull versus push strategy for automated guided vehicle load movement in a batch manufacturing system , 1987 .

[20]  Andrew Kusiak,et al.  Artificial Intelligence And Operations Research In Flexible Manufacturing Systems , 1987 .

[21]  Lawrence Bodin,et al.  Microcomputer-based vehicle routing and scheduling software , 1986, Comput. Oper. Res..

[22]  Matthew J. Liberatore,et al.  Microcomputer systems for manufacturing planning and control , 1986, Comput. Oper. Res..

[23]  Farrokh Mistree,et al.  Rule-Based Post Solution Analysis of Decision Support Problems: Some Preliminary Results , 1986 .

[24]  Rivka Oxman,et al.  Architectural knowledge structures as “design shells”: a knowledge-based view of design systems and CAAD education , 1990 .

[25]  James MacGregor Apple.  Plant Layout and Materials Handling , 1977 .

[26]  Tao Li,et al.  CODAR: General purpose design tool for rule-based engineering expert systems , 1987, Artif. Intell. Eng..

[27]  Edward A. Wasil,et al.  Project management using a microcomputer , 1986, Comput. Oper. Res..

[28]  Soundar Kumara,et al.  Expert systems in industrial engineering , 1986 .

[29]  Efraim Turban,et al.  Integrating Expert Systems and Decision Support Systems , 1986, MIS Q..

[30]  Hirokazu Ihara,et al.  An Experimental Comparison of Knowledge Representation Schemes , 1984, AI Mag..