A methodology for the identification of waste-minimizing scheduling problems

JOURNAL OF CLEANER PRODUCTION

卷:246

Article

Le Hesran, Corentin¹  Ladier, Anne-Laure¹  Botta-Genoulaz, Valerie¹  Laforest, Valerie² 

[1] Univ Lyon, INSA Lyon, DISP Lab EA 4570, F-69621 Villeurbanne, France

[2] Univ Lyon, CNRS, Mines St Etienne, UMR 5600 EVS,Inst Henri Fayol, F-42023 St Etienne, France

关键词: Waste minimization;    Flow control;    Environmental and cost assessment;    Scheduling;    Manufacturing;   

DOI  :  10.1016/j.jclepro.2019.119023

来源: Elsevier

【 摘 要 】

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. (C) 2019 Elsevier Ltd. All rights reserved.

【 授权许可】

Free