Showing papers by "Jean-Pierre Kenné published in 2016"

Machinability study of recycled aluminum cans and machining chips

Abstract: More and more, the recycling and recovery of many materials are becoming economically and ecologically viable. This is particularly true of aluminum alloys. While the mechanical properties and the field performance of recycled alloys are increasingly well documented, the same cannot be said of their machinability. This article presents the results of a comparative experimental study on the machinability of two recycled foundry aluminum alloys: one from aluminum can covers and another from chips produced during machining. A full factorial design of experiments was used to study the influence of lubrication and machining parameters on surface roughness (Ra and Rt) and chip morphology when turning the two recycled aluminum alloys. The results were analyzed using Pareto analysis and analysis of variance (ANOVA), after which roughness prediction models were proposed. The results show a clear difference in the machinability of the two alloys, suggesting the need for a separation of the aluminum alloys used during recovery.

Optimizing production while reducing machinery lockout/tagout circumvention possibilities

Abstract: Purpose – The optimization of production imposes a review of facility maintenance policies. Accidents during maintenance activities are frequent, sometimes fatal and often associated with deficient or absent machinery lockout/tagout. Lockout/tagout is often circumvented in order to avoid what may be viewed as unnecessary delays and increased production costs. To reduce the dangers inherent in such practice, the purpose of this paper is to propose a production strategy that provides for machinery lockout/tagout while maximizing manufacturing system availability and minimizing costs. Design/methodology/approach – The joint optimization problem of production planning, maintenance and safety planning is formulated and studied using a stochastic optimal control methodology. Hamilton-Jacobi-Bellman equations are developed and studied numerically using the Kushner approach based on finite difference approximation and an iterative policy improvement technique. Findings – The analysis leads to a solution that sugg...

Production Planning of a Failure-Prone Manufacturing System under Different Setup Scenarios

Abstract: This paper presents a control problem for the optimization of the production and setup activities of an industrial system operating in an uncertain environment. This system is subject to random disturbances (breakdowns and repairs). These disturbances can engender stock shortages. The considered industrial system represents a well-known production context in industry and consists of a machine producing two types of products. In order to switch production from one product type to another, a time factor and a reconfiguration cost for the machine are associated with the setup activities. The parts production rates and the setup strategies are the decision variables which influence the inventory and the capacity of the system. The objective of the study is to find the production and setup policies which minimize the setup and inventory costs, as well as those associated with shortages. A modeling approach based on stochastic optimal control theory and a numerical algorithm used to solve the obtained optimality conditions are presented. The contribution of the paper, for industrial systems not studied in the literature, is illustrated through a numerical example and a comparative study.

Production control of a deteriorated remanufacturing system within an open-reverse supply chain

Abstract: Reverse supply chain management is a significant issue for sustainable economy, product recovery and green thinking. In a closed loop reverse supply chain, used products are generally returned to original producers. But in an open loop reverse supply chain, used products are not returned to original producers, outsider firms recover them. This paper focuses on an open-loop reverse supply chain (OLRSC), which includes a single centralized collection point of returned products, a single remanufacturing machine (RM) and a single distribution center. The RM produces parts, and upon a breakdown, either an imperfect repair is undertaken or is replaced with a new identical one. The objective of the control problem is to find the production rate and the repair/replacement policy that minimize total incurred costs over an infinite planning horizon. This paper proposes a stochastic dynamic programming formulation of the problem and derives the optimal policies numerically. A numerical example is included and sensitivity analyses with respect to the system parameters are examined to illustrate the importance and effectiveness of the proposed methodology.