Acquiring Knowledge Needed for Pull Production System Design through Data Mining Methods

  • Peter Bubenik
  • Filip Horak
  • Viktor Hancinsky
Keywords: data mining, production planning, knowledge acquisition, genetic algorithm

Abstract

Article deals with defining relationships for setting the optimal number of kanban cards in individual circuits of pull production systems, in order to minimize work in progress, while maximizing the number of completed orders in the observed time interval. To achieve this objective, data mining methods were used.

Author Biographies

Peter Bubenik

Department of Industrial Engineering, Faculty of Mechanical Engineering University of Zilina, Slovakia

Filip Horak

Department of Industrial Engineering, Faculty of Mechanical Engineering University of Zilina, Slovakia

Viktor Hancinsky

Department of Industrial Engineering, Faculty of Mechanical Engineering University of Zilina, Slovakia

Published
2015-08-31
How to Cite
Bubenik, P., Horak, F., & Hancinsky, V. (2015). Acquiring Knowledge Needed for Pull Production System Design through Data Mining Methods. Communications - Scientific Letters of the University of Zilina, 17(3), 78-82. Retrieved from http://journals.uniza.sk/index.php/communications/article/view/451
Issue
Vol 17 No 3 (2015)
Section
Articles