İmalat atölyesi yerleşiminde bir karma düzenleme yaklaşımı

While the benefits of organizing machines in form of manufacturing cells are highly praised, certain industrials do not want a comprehensive transformation due to the possible changes that may occur, for example, in the parts? demands or routings. A hybrid manufacturing system that associates functional departments and machine cells may then appear much more attractive given that it would takes advantages of both. Nevertheless, the design of such systems is a much less researched issue compared to the effort spent to the efficient design of each mentioned organization separately. In this work, we suggest an approach that penalizes the allocation of parts that are less stable to manufacturing cells, and highly stable to functional departments. The abstract concept of part stability is associated with two part characteristics: routing similarity and demand variability. In order to determine the similarities between parts, sequence based similarity principles and alternative process routings are considered simultaneously. Meanwhile, demand variability is assumed to be related with the coefficient of variation. While such a discrimination of parts between manufacturing cells and functional departments is desired, the flow of materials in the planned cells should also be appropriate. Suitable machine investment is another issue to consider. Hence, the hybrid manufacturing system design problem is formulated as a constrained multiobjective optimization problem. Evolutionary algorithms present important features for the solution of this type of problems. Among them, a very efficient algorithm, which incorporates pareto dominance and elitism, namely SPEA2, is adapted. Both the proposed optimization model and the solution method are illustrated with an artificially generated example. Keywords : Hybrid Manufacturing Systems; Manufacturing Cells; Functional Layout; Multiobjective Optimization; Fuzzy Sets; Evolutionary Programming