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Cormier G.,Alfaisal University | Rezg N.,CNRS Production Engineering and Mechanical Production Laboratory
Journal of Quality in Maintenance Engineering

Purpose: The purpose of this study is to gain some insights into the number of shortages resulting from two alternative demand allocation schemes between a contractor (machine M 1) and subcontractor (machine M 2), on the one hand, and from inventory accumulation, on the other hand. The shortages stem from random machine breakdowns, and each machine undergoes preventive maintenance. The motivation behind inventory accumulation is to allow demand to be fulfilled even when both machines are down. Design/methodology/ approach: The number of shortages stemming from all scenarios under consideration was established via computer simulation with the Arena © language. Findings: For demand allocation that remains unchanged for the duration of the planning horizon and constant reliability of M 1, it was found that, the less reliable M 2 is, the more biased in favour of M 1 will be the optimal demand allocation and the greater will be the number of shortages. Moreover, both dynamic demand reallocation over the planning horizon and inventory accumulation result in a substantial reduction in shortages. Research limitations/implications: The results are representative of the specific data, which were assumed in the simulation models. Nevertheless, this methodology is recommended for this type of analysis, as it is highly flexible and can take into account many practical considerations, which an analytical approach cannot. Practical implications - Within the context of unreliable production machines, the most important practical implication of this study is that the dynamic reallocation of demand between a contractor and subcontractor, along with inventory accumulation, both have the potential to yield important reductions in the number of shortages. Originality/value: The subject-matter of this paper was not previously reported in the literature. Furthermore, the insights gained as a result of this study can yield substantial benefits to companies in terms of improving their service levels as measured by reduced shortages. © Emerald Group Publishing Limited 1355-2511. Source

Schutz J.,CNRS Production Engineering and Mechanical Production Laboratory
IEEE International Conference on Industrial Engineering and Engineering Management

This paper deals with production and maintenance plans. Among a set of proposed requests, the production system must satisfy several of them. Each request is characterized by a profit, products quantity and delivery date. The choice of the requests to perform must allow to maximize net profit. To achieve this objective, preventive maintenance plans and optimal production rates associated with each request must be computed jointly. To solve this problem, a great deluge algorithm is used. A numerical example is also given to illustrate the proposed model. © 2014 IEEE. Source

Bouguerra S.,University of Tunis | Chelbi A.,University of Tunis | Rezg N.,CNRS Production Engineering and Mechanical Production Laboratory
International Journal of Production Economics

Numerous products are sold with a warranty period and the possibility of buying an extended warranty for a given additional cost. The buyer has then to decide to take the extended warranty or not when purchasing the product. We develop in this paper a mathematical model to study the opportunity provided by the extended warranty for the buyer as well as for the manufacturer. The total average cost incurred by each side during the product's life cycle is expressed in order to determine the maximum extra cost the consumer should pay and the minimum price at which the manufacturer should sell the extended warranty. This is done under different options in terms of maintenance strategies adopted during the product's lifecycle. © 2011 Elsevier B.V. All Rights Reserved. Source

Li J.,CNRS Production Engineering and Mechanical Production Laboratory | Sava A.,CNRS Production Engineering and Mechanical Production Laboratory | Xie X.,Ecole Nationale Superieure des Mines de Saint - Etienne CMP
2007 European Control Conference, ECC 2007

This paper deals with inventory cost optimization of a multi-stage production-distribution system subject to non analytical constraints. These kind of constraints need to be evaluated by simulation. Therefore, the method that we propose addresses problems where both the performance evaluation and the constraints are evaluated via a stochastic, discrete-event simulation. It is based on random search in a neighborhood structure called the most promising area. A special attention is given to optimizing the allocation of the simulation budget. We show that under some assumptions, the algorithm converges to a set of local optimal solutions with probability 1. This approach is applied to cost optimization of a production-distribution system subject to fill rate specifications. Numerical experiments show that this new method can efficiently solve the discrete optimization problem proposed in this paper. © 2007 EUCA. Source

Hajej Z.,CNRS Production Engineering and Mechanical Production Laboratory | Rezg N.,CNRS Production Engineering and Mechanical Production Laboratory | Gharbi A.,Ecole de Technologie Superieure of Montreal
International Journal of Advanced Manufacturing Technology

This paper proposes a new ecological joint production and maintenance policy, which considers an ecological aspect for a forecasting problem of unreliable manufacturing system subject to degradation. The manufacturing system is composed of a single machine producing one product type in order to satisfy a random demand under a given service level. On the other hand, the production system generates harmful emissions to the environment and may be sanctioned by an environmental tax. The objective of this paper is to propose an ecological production and maintenance policy (EPMP) optimization by calling a subcontracting in the context of a calling of tenders in order to satisfy the random demand and to decrease the carbon tax. In this context, we determine the economical production plan and the optimal maintenance strategy by defining a condition for the subcontracting cost in order to respect the EPMP optimization. To illustrate the highlight of the proposed policy, some numerical results are presented. © 2016 Springer-Verlag London Source

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