Communications - Scientific Letters of the University of Zilina 2015, 17(3):78-82 | DOI: 10.26552/com.C.2015.3.78-82

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

Peter Bubenik1, Filip Horak1, Viktor Hancinsky1
1 Department of Industrial Engineering, Faculty of Mechanical Engineering University of Zilina, Slovakia

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.

Keywords: data mining; production planning; knowledge acquisition; genetic algorithm

Published: August 31, 2015  Show citation

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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. doi: 10.26552/com.C.2015.3.78-82
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    References

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