Design of manufacturing systems for product variety using cluster and statistical analysis

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The scope of this research program is the optimization of manufacturing systems to support product variety and sustainability. To stay competitive in the market, original manufacturers (OM) need to satisfy customers with more product options and meet the environmental regulations and societal expectations. In this context, while formal optimization models have been widely used in system design, they often face the challenges of model and computational complexity (e.g., high number of integer variables and convergence issues). Instead of employing optimization methods, this research will investigate and develop clustering and statistical techniques for the design of manufacturing systems. The novelty is to develop a bottom-up approach to address complex structural decisions systematically with the target of better performance on solution convergence and computing time, as well as comparable optimality performance with metaheuristic algorithms.