Optimisation des chaînes d’approvisionnement en boucle fermée dans un contexte d’économie circulaire à l’ère de l’Industrie 4.0

Abstract

The Circular Economy is a new conception of the economy responding to the problem of the exhaustion of natural resources. To remain economically competitive and meet the new ecological expectations of consumers, closed-loop supply chains (CLSC) are a concrete solution for the manufacturing industry with the reuse of end-of-life products (EOL) and the recycling of raw materials. However, CLSCs are difficult to implement because of the difficulty of optimally recovering EOL products given the uncertainties that exist about their condition after use. These uncertainties complicate the management of CLSCs by preventing effective flow planning. Industry 4.0 technologies such as the Internet of Things (IoT) can reduce them with the collection of data on its degradation condition throughout the product lifecycle. The choice of recovery treatment for the product and its components would then be facilitated and no inspection steps would be required. Recovered EOL products could also be optimally selected. This work proposes a CLSC model that optimizes flows to maximize the profit generated by the reuse of EOL products from a manufacturing company using IoT. A linear programming model on LINGO considering several modular products will be used to study the impact of such a CLSC. The main contribution of this research is to show the potential benefits of setting up a CLSC whose recovery and choice of processing of EOL products are directed by the IoT. Thus, in the case where remanufactured products would represent 40% of the total demand, an increase in profit of nearly 48% can be achieved thanks to the CLSC model presented. This work also shows the compatibility between economic interests and a more responsible consumption of natural resources, less exploited due to the recovery of EOL products.

Date	5 Jan 2021
Original language	French
Awarding Institution	École de technologie supérieure
Supervisor	Lucas Hof (Supervisor) & Jean-Pierre Kenné (Co-supervisor)