Knowledge Representation Structures for the Evaluation of Production Planning and Control Systems

  • I. P. Tatsiopoulos
  • N. D. Mekras
Conference paper


This paper describes the knowledge representation of an expert system which helps solving the problem of evaluating software packages for production planning and control (PPC). It addresses this problem on the basis of the package’s functionalities and features as compared with the production management theory for the various types of production systems. A frame-based knowledge representation model is proposed whose objects and relations describe a typology of production systems and a generic PPC software package. A dual taxonomy of production systems is used based both on functional types and industrial sectors.

The above knowledge forms the knowledge base of an expert system that can help those who design Production Planning and Control (PPC) systems. This expert system gathers and processes the above knowledge and gives as inference results the functionalities and the module features of the software package that are required in the PPC system of a manufacturing firm.


Expert System Industrial Sector Production Management Prolog Language Expert System Technology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Burbidge, JL., A Production System Variable Connectante Model,Cranfield Institute of Technology, Cranfield, 1984.Google Scholar
  2. [2]
    Davis, G.B. and Olson, M.H., Management Information Systems, McGraw Hill,1985.Google Scholar
  3. [3]
    Doumeingts, G. et al, Knowledge-based System for the Design of Production Management Systems, in: J. Browne (Ed), Knowledge Based production Management Systems, Elsevier ( North-Holland ), IFIP, 1989.Google Scholar
  4. [4]
    Eloranta, E et al, ‘Model-based reasoning in manufacturing systems design’ in Browne, J (ed), Knowledge Based Production Management Systems, Fkevier/North - Holland, Amsterdam, Netherlands, 1989.Google Scholar
  5. [5]
    Foerster, H., Hoff, H. and Missen, E., Marktspiegel PPS-Systems auf dem Pruefstand, Verlag, Koeln, Germany, 1986.Google Scholar
  6. [6]
    Frost, R, A, Introduction to Knowledge Base Systems,William Collins and Sons, London, UK, 1986.Google Scholar
  7. [7]
    Gane, C. and Sarson, T., Structured Systems Analysis, Prentice-Hall, 1979.Google Scholar
  8. [8]
    Keller, R., Expert System Technology, Prentice-Hall, Englewood Cliffs, NJ, USA, 1987.Google Scholar
  9. [9]
    Kettner,H., J.Schmidt and HRGreim, Leitfaden der systematischen Fabrikplanung, Carl Hanser Verlag, Munchen, 1984.Google Scholar
  10. [10]
    Malpas, J., Prolog: A relational language and its applications, Prentice-Hal, Englewood Cliffs, NJ, USA, 1987.Google Scholar
  11. [11]
    Mensel, G. and J. Michel, Moeglichkeiten des Einsatzes wissenbasierter Systeme in der Fertigung, ZwF 80 11, pp. 495–500, 1985.Google Scholar
  12. [12]
    Schmenner, R.G., Production/Operations Management, SRA Chicago, 1981.Google Scholar
  13. [13]
    Schmitt, T.G., T. Klastorin and A. Shtub, Production classification system: concepts, models and strategies, pp.563–578, Int.J.Prod.Res., 1985.Google Scholar
  14. [14]
    Schneider, H.-J. and Karagiannis, D., ‘Intelligent Knowledge Bases of CAD Environments: The Hybrid System KANON’, NATO ASI Series, Vol.’ F49, pp 161–1%, Springer-Verlag, Berlin, 1988.Google Scholar
  15. [15]
    Schomburg, E., Entwicklung eines Betriebstypologischen Instrumentariums zur Systematischen Ermittlung der Anforderungen an EDV - Gestuetzte Productionsplanungs - und - Steuerungssysteme im Maschinenbau, Dissertation, TH Aachen, Germany, 1980.Google Scholar
  16. [16]
    Sepehri, M., ‘Newest manufacturing software packages offer modules which meet specialized needs’, Ind. Eng. Vol 28, pp 32–43, 1985.Google Scholar
  17. [17]
    Sheil, B., Thinking about artificial intelligence, Harvard Business Review, July-August 1987.Google Scholar
  18. [18]
    Speith, G. and U. Brief, BAPSY - ein Instrumentarium zur Beurteilung und Auswahl von Produktionsplanung - und steuerungs - Systemen, FIR mitteilungen, TH Aachen, Nr. 43 (Juni), 1982.Google Scholar
  19. [19]
    Tatsiopoulos, I., J (ed), Knowledge Based Production Management Systems, Elsevier/North - Holland, Amsterdam, Netherlands, 1989.Google Scholar
  20. [20]
    Tatsiopoulos, I.P., ‘Requirements analysis of production management software systems’, in Computer Integrated Manufacturing Systems, Vol 3, pp 207–215, Butterworth - Heineman Lid, 1990.Google Scholar
  21. [21]
    Tatsiopoulos, I.P. and Pappas IA., ‘Design of fault-tolerant production management systems for small and medium sized fes,in Eloranta, E (ed), Advances in production management systems, Elsevier/North - Holland, Amsterdam, Netherlands, 1990.Google Scholar
  22. [22]
    Weiskamp, K and Hengl, T., Artificial Intelligence Programming with Turbo Prolog, John Wiley and Sons, New York, USA, 1988.Google Scholar

Copyright information

© Springer-Verlag Wien 1991

Authors and Affiliations

  • I. P. Tatsiopoulos
    • 1
  • N. D. Mekras
    • 1
  1. 1.Dept. of Mechanical Engineering Sector of Industrial Management & O.R.National Technical University of AthensAthensGreece

Personalised recommendations