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Communication Dans Un Congrès Année : 2016

K-means clustering based method for production flow management facing rework disturbances

Résumé

Manufacturing companies that suffer from a high rework rate on their production have mostly problems with their production scheduling flow, too. Author's previous work have highlighted a panel of Key Performance Indicators (KPI) and their interactions. A simulation model has been made to obtain a cartography representing the evolution of the amount of delayed products depending of two indicators highlighting four areas useful to decision making. The main goal of this work is to propose an automated approach to determine these areas and the relating production flow management decisions. The determination of these areas is performed by using clustering approach, when the production flow management rules associated to each area are determined by performing experimental design. This work refers to a bigger project that tries to develop a production flow monitoring and control system based on the Product Driven System (PDS).
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Dates et versions

hal-01415418 , version 1 (13-12-2016)

Identifiants

  • HAL Id : hal-01415418 , version 1

Citer

Emmanuel Zimmermann, Melanie Noyel, Philippe Thomas, Hind Bril, André Thomas. K-means clustering based method for production flow management facing rework disturbances. International Conference on Information Systems, Logistics and Supply Chain, ILS’16, Jun 2016, Bordeaux, France. ⟨hal-01415418⟩
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