Disassembly scheduling, one of the important operational problems in disassembly systems, can be generally defined as the problem of determining the quantity and timing of the end-of-use/life products while satisfying the demand of their parts over a planning horizon. This paper presents a literature review on this planning problem in disassembly systems. First, the basic form of the problem is defined with a mathematical formulation. To characterize the differences between assembly and disassembly processes, the effects of the divergence property are also explained with respect to the zero inventory property, indispensable surplus inventory, and mathematical representation. Then, we review the existing research articles on the basic problem and its generalizations. A systematic scheme for classifying problems is also suggested. Finally, we suggest several future research directions.
Remanufacturing, one of the most advanced product recovery options, processes used or end-of-life products with disassembly, reprocessing, and reassembly operations in such a way that their qualities are as good as new. This paper focuses on production planning in remanufacturing systems over a given planning horizon with discrete time periods. The main decisions are: (a) the number of used or end-of-life products to be disassembled and disposed; (b) the number of parts or components to be reprocessed, disposed, and newly purchased; and (c) the number of products to be reassembled. The objective is to maximize the total profit, i.e. the difference between the sales revenue and the relevant costs. In particular, set-up costs and times are explicitly considered since set-ups are significant in remanufacturing systems. As an extension of the existing literatures on production planning in remanufacturing systems, a generic mixed integer programming model is suggested that incorporates the detailed processes of the remanufacturing process. Then, owing to the complexity of the problem, two types of heuristics based on the linear programming technique are developed. To show the performances of the heuristics, computational experiments were done on some test instances, and the results are reported.
This paper considers the problem of selecting and sequencing operations in process planning for the objective of minimizing the sum of operation processing costs and machine, set-up and tool change costs. The main constraint is the precedence relations among operations. To represent the precedence relations and alternative operations, a tree-structured precedence graph is suggested. Based on the graph, the entire problem is decomposed into two subproblems: operation selection and operation sequencing. Then, three iterative algorithms are suggested that solve the two subproblems iteratively until optimal and nearoptimal solutions are obtained. The algorithms are illustrated using an example part, and to show the performances of the algorithms, computational experiments were done on randomly generated test problems. The results show that the algorithms suggested work well for the test problems.
IntroductionComputer-aided process planning (CAPP) is an approach that uses computers to generate a process plan that contains the route, operations, operation parameters, machines, set-ups and tools required for producing a part. Although process planning activities are different according to different industries and shops, they involve several or all of the following (Chang 1990): (1) selection of machining operations;(2) sequencing of machining operations; (3) selection of cutting tools; (4) selection of machine tools; (5) determining set-up requirements; (6) calculations of cutting parameters; (7) tool path planning and generation of NC part programs; and (8) design of jigs and fixtures. There are a number of previous research articles on the above process planning activities. For surveys on these subjects, see Ham and Lu (1988), Alting and Zhang (1989), ElMaraghy et al. (1993) and Kiritsis (1995).Among the various activities in process planning, this paper focuses on the operation selection and sequencing problems. That is, the problem considered in this paper is to select operations among alternatives as well as to determine the sequence of the selected operations so that the resulting solution satisfies the precedence constraints among operations. The objective is to minimize the sum of operation processing costs and machine, set-up and tool change costs. The operation selection and sequencing are needed to consider at the same time since better solutions can be obtained over the extended solution space. However, the two problems, especially
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