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Using the knowledge base and fuzzy inference system to estimate the safety factor in calculating the number of the kanban cards

Author

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  • Farzad Firouzi Jahantigh
  • Ali Noroozian
  • Ali Daneshi

Abstract

There are many studies in the field of using fuzzy logic in estimating the logistic computational parameters. In most of these studies, the proposed model is too large and too complicated which contains a lot of parameters. These issues make the proposed models hard to use in many industries. In this article, the safety factor considered in kanban card calculations named kanban safety factor and its relationship with fuzzy theory are addressed. Since kanban safety factor is obtained using expert judgements, there is uncertainty in it. Therefore, a practical fuzzy method is introduced in this article to calculate kanban safety factor. The method is efficient due to its simple calculations and comprehensive due to its ability to consider all parameters that affect kanban safety factor. The new proposed fuzzy method is implemented in a warehouse of Iran Khodro Corporation of Iran which resulted in remarkable improvements.

Suggested Citation

  • Farzad Firouzi Jahantigh & Ali Noroozian & Ali Daneshi, 2018. "Using the knowledge base and fuzzy inference system to estimate the safety factor in calculating the number of the kanban cards," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 28(2), pages 275-287.
    • Handle: RePEc:ids:ijisen:v:28:y:2018:i:2:p:275-287
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    Cited by:

    1. Asefeh Hasani Goodarzi & Seyed Hessameddin Zegordi, 2020. "Vehicle routing problem in a kanban controlled supply chain system considering cross-docking strategy," Operational Research, Springer, vol. 20(4), pages 2397-2425, December.

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