Optimal Control Policy of Unreliable Production Systems Generating Greenhouse Gas Emission

Jean-Pierre Kenné (), Ali Gharbi, Armel Leonel Kuegoua Takengny and Morad Assid
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Jean-Pierre Kenné: Mechanical Engineering Department, École de Technologie Supérieure, Production System Design and Control Laboratory, University of Quebec, 1100 Notre-Dame West, Montreal, QC H3C 1K3, Canada
Ali Gharbi: Systems Engineering Department, École de Technologie Supérieure, Production System Design and Control Laboratory, University of Quebec, 1100 Notre-Dame West, Montreal, QC H3C 1K3, Canada
Armel Leonel Kuegoua Takengny: Mechanical Engineering Department, École de Technologie Supérieure, Production System Design and Control Laboratory, University of Quebec, 1100 Notre-Dame West, Montreal, QC H3C 1K3, Canada
Morad Assid: Systems Engineering Department, École de Technologie Supérieure, Production System Design and Control Laboratory, University of Quebec, 1100 Notre-Dame West, Montreal, QC H3C 1K3, Canada

Sustainability, 2024, vol. 16, issue 13, 1-20

Abstract: The current paper addresses the production planning problem of unreliable manufacturing systems generating greenhouse gas (GHG) emissions, producing a single product type in a dynamic and stochastic context. This work aims to develop a control policy that minimizes the sum of backlog, inventory, and emission costs. To achieve this goal, the stochastic optimal control theory is used to develop the optimality conditions solved by numerical techniques to establish the control policy structure. Sensitivity analyses are provided to depict and validate the obtained structure of the production policy characterized by multiple thresholds, which regulate the production rate with the emission and inventory levels. Furthermore, the performance of the developed optimal control policy is compared with the most pertinent ones identified in the literature. The developed optimal control policy outperformed those in the literature by significantly reducing the total cost incurred by these policies. Finally, the developed control policy is implemented to equip the manager of the considered manufacturing system with a practical and robust decision-support tool.

Keywords: manufacturing systems; environmental constraints; stochastic process; dynamic programming; numerical methods; optimal control policy (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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