Modeling modular design for sustainable manufacturing: A fuzzy grouping genetic algorithm approach

Green modular design is one of the most effective techniques for promoting sustainable manufacturing. A good green modular design calls for a good choice of combinations of components and modules of a design, aimed at maximizing design fitness, while minimizing the product cost and potential environmental damage by the product when in use. It was realized that it is important to build manufacturing sustainability into the whole life cycle of a product (or process), which takes into account the ultimate potential impact of the product on the economic, environmental, and the social performance of the product/process. However, in a fuzzy environment, most of the necessary design information is not precisely known at the planning or design stage. Moreover, the combinatorial problem is computationally challenging, demanding more efficient and effective optimization methods. In this paper, a multiple criteria grouping approach was suggested for evaluating possible modular designs. This chapter proposed a modeling approach for modular design based on fuzzy grouping genetic algorithm. The proposed modular design approach is promising, especially when the design factors and the criteria for evaluation, such as design fitness, cost fitness, green fitness, and other relevant information, are not precisely known at the design stage. Fuzzy evaluation techniques are used to express the imprecise information for evaluating the fitness of potential solutions in the iterative genetic algorithm. Furthermore, the algorithm uses fuzzy-based control techniques to dynamically adapt genetic parameters of the algorithm on real time.