A methodology for the identification of waste-minimizing scheduling problems - Mines Saint-Étienne
Article Dans Une Revue Journal of Cleaner Production Année : 2020

A methodology for the identification of waste-minimizing scheduling problems

Résumé

Sustainability in manufacturing operations has become the subject of increasing attention in the recent years. At the operational level, knowledge about material and energy flows circulating in the production system provides information regarding costs, efficiency and environmental impact, as well as opportunities for improvements. Several methods have been proposed for flow assessment and flow cartography, but work combining production scheduling and flow assessment remains scarce. To address this issue, we propose comprehensive guidelines in order to identify waste reduction opportunities and integrate them in a scheduling problem. This work combines sustainable production principles with environmental and material flow assessment to promote waste prevention at the operational level of production, by identifying the main waste-generating activities that can be improved through scheduling. From a decision-maker's point of view, more informed choices can be made regarding the production scheduling and the opportunities for operational improvement. From a research perspective, a framework for the identification and integration of waste-minimizing opportunities in scheduling problems is proposed. Four steps permit the product system definition, flow inventory, economic and environmental impact assessment and scheduling problem identification. An application to a hub-cap production system serves to highlight the benefits of this methodology, showing that hazardous waste generation could be reduced by 10% using adequate scheduling.
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emse-02345594 , version 1 (21-07-2022)

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Corentin Le Hesran, Anne-Laure Ladier, Valerie Botta-Genoulaz, Valérie Laforest. A methodology for the identification of waste-minimizing scheduling problems. Journal of Cleaner Production, 2020, pp.119023. ⟨10.1016/j.jclepro.2019.119023⟩. ⟨emse-02345594⟩
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