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Production planning of perishable products in an unreliable manufacturing system

  • Seyedpedram Pishvaeian

Student thesis: Master's thesisMaster in Engineering: Systems Engineering

Abstract

The current study tries to provide an optimal solution to the problem of production planning of perishable products in a failure-prone manufacturing system. The system under study has consisted of a single manufacturing machine producing one type of product, in which the machine is subject to random failures and repairs and the products are perishable. Even though the customer demand must be satisfied, shortages are allowed. Products are no longer usable after a certain course of time and must be discarded from the inventories on hand after their expiration. The objective of this study is to propose optimal control policies minimizing the total cost imposed on the system, including holding, shortage, and perishability costs. The decision and state variables for this model are the production rate and stock level of finished perishable products, respectively. A simulation-based approach in combination with the experimental design and the response surface methodology provides us with the opportunity to obtain the optimal values for the parameters under study. Through these models, three major scenarios to study the behavior of the system will be scrutinized. First, the situation in which both customer demand rate, and products’ lifetime are constant and predetermined will be studied. For the second case, it is assumed that products may perish at different times; however, the demand rate follows an unvarying pattern. In the last case, the randomness will be added to customer demand rate, while the products’ shelf life remains unchanged and constant. It has been suggested that in all cases, the proposed policies are valid, verified by the extensive sensitivity analyses performed and work well.
Date8 Jun 2021
Original languageAmerican English
Awarding Institution
  • École de technologie supérieure
SupervisorAli Gharbi (Supervisor) & Mustapha Ouhimmou (Co-supervisor)

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