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International audienceThe purpose of this work is to efficiently design disassembly lines taking into account the uncertainty of task processing times. The main contribution of the paper is the development of a decision tool that allows decision-makers to choose the best disassembly alternative (process), for an End of Life product (EOL), and assign the corresponding disassembly tasks to the workstations of the line under precedence and cycle time constraints. Task times are assumed to be random variables with known normal probability distributions. The case of presence of hazardous parts is studied and cycle time constraints are to be jointly satisfied with at least a certain probability level, or service level, fixed by the decision-maker. An AND/OR graph is used to model the precedence relationships among tasks. The objective is to minimise the line cost composed of the workstation operation costs and additional costs of workstations handling hazardous parts of the EOL product. To deal with task time uncertainties, lower and upper-bounding schemes using second-order cone programming and approximations with convex piecewise linear functions are developed. The applicability of the proposed solution approach is shown by solving to optimality a set of disassembly problem instances (EOL industrial products) from the literature

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International audienceThe present work deals with the problem of stochastic disassembly line balancing and sequencing in the presence of hazardous parts of the End of Life (EOL) product. The case of partial disassembly process is considered. The objective is to design a production line with a maximum profit under uncertainty of task times which are assumed to be random variables with known probability distributions. Tasks of the best selected disassembly alternative are to be assigned to a sequence of workstations while satisfying precedence and cycle time constraints. To cope with uncertainties, an exact solution method based on integer programming and Monte Carlo sampling is developed. Results of experiments on problem instances are presented

a b s t r a c tA problem of profit oriented disassembly line design and balancing with possible partial disassembly and presence of hazardous parts is studied. The objective is to design a production line providing a maximal revenue with balanced workload. Task times are assumed to be random variables with known normal probability distributions. The cycle time constraints are to be jointly satisfied with at least a predetermined probability level. An AND/OR graph is used to model the precedence relationships among tasks. Several lower and upper-bounding schemes are developed using second order cone programming and convex piecewise linear approximation. To show the relevance and applicability of the proposed approach, a set of instances from the literature are solved to optimality.

A Stochastic Partial profit-oriented Disassembly Line Balancing Problem (SP-DLBP) in the presence of hazardous parts is considered. The goal is to assign disassembly tasks of the best selected disassembly alternative to a sequence of workstations while respecting precedence and cycle time constraints. An AND/OR graph is used to model the disassembly alternatives and the precedence relations among tasks. Task times are assumed independent random variables with known normal probability distributions. Cycle time constraints are to be satisfied with at least a certain probability level fixed by the decision maker. The objective is to maximize the profit produced by the line. It is computed as the difference between the positive revenue generated by retrieved parts and the line operation cost considered as negative revenue. The line cost includes the workstations operation costs as well as additional costs of workstations handling hazardous parts of End of Life (EOL) product. To deal with uncertainties, a Chance Constrained Programming formulation is developed.

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