The Application of Multidimensional Scaling for Recognising Similarities and Production Planning

  • Manfred Auch
Conference paper

Abstract

Multidimensional scaling is a method for representing objects as points in a space. The similarity between 2 objects is represented by the distance between these 2 points. Thus the similarities within a set of objects can be recognized. One further advantage of multidimensional scaling is that ordinal scale level is sufficient for collecting data i.e. the exact value of the Objects’ characteristics need not be known. The rank order is sufficient and this simplifies data collecting considerably. Thus multidimensional scaling proves itself to be widely superior to cluster analysis which has been used up to now for classifying and recognizing similarities. This is proved by practical examples where multidimensional scaling was used for recognizing families of parts in order to design cellular manufacturing systems, for creating groups of products when designing assembly areas, for grouping working places according to tasks and stress criteria when working out design recommendations etc.

Keywords

Drilling Allo Fami Novi 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. /1/.
    Bock, H. H.: Automatische Klassifikation. Theoretische und praktische Methoden zur Gruppierung und Strukturierung von Daten (Cluster-Analyse). Göttingen: Vandenhoeck & Ruprecht, 1974Google Scholar
  2. /2/.
    Borg, I.: Multidimensional Data Representation: When and Why. Ann Arbor, Mich.: Mathesis Press, 1981Google Scholar
  3. /3/.
    Borg, I.: Anwendungsorientierte Multidimensionale Skalierung. Springer-Verlag: Berlin, Heidelberg, 1981CrossRefGoogle Scholar
  4. /4/.
    Davison, M. L.: Multidimensional Scaling. New York: John Wiley & Sons, 1983Google Scholar
  5. /5/.
    Hartigan, J. A.: Clustering Algorithms. New York: John Wiley & Sons, 1975Google Scholar
  6. /6/.
    Schiffman, S. S.; Reynolds, M. L.; Young, F. W.: Introduction to Multidimensional Scaling. Theory, Methods and Applications. New York, London: Academic Press, 1981Google Scholar
  7. /7/.
    Scoltock, J.; Gallagher, C. C.: The Limitations of the Application of Cluster Analysis to Manufacturing Industrie. Proceedings of the 6th International Conference on Production Research. Edited by D. M. Zelenovic. Novi Sad, Yugoslavia, August 24–29, 1981, Vol. 1, p. 217–220Google Scholar
  8. /8/.
    Speith, G.; Göhing, U.: Be-triebsgruppenbildung zum überbetrieblichen Vergleich. Ein Beitrag für die Anwendung eines EDV-gestützten Verfahrens zur Gruppenbildung. FIR-Mittei- lungen 9 (1981) Nr. 41, S. 17–29Google Scholar
  9. /9/.
    Young, F. W.; Lewyckyj, R.: Alscal-4, User’s Guide, Chapes Hill, NC: Data Analysis and Theory Associates, 2nd ed., 1979Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1985

Authors and Affiliations

  • Manfred Auch
    • 1
  1. 1.Fraunhofer-Institut für Arbeitswirtschaft und Organisation (IAO)StuttgartDeutschland

Personalised recommendations