Minicell-based manufacturing system is used in identifying best minicell designs. The existing method of minicell design generates best minicell designs by designing and scheduling minicells simultaneously. While in this research designing of minicells and scheduling of jobs in minicells is done separately. This research evaluates the effectiveness of hierarchical approach and compares with simultaneous method. Minicell designs with respect to average flow times and machine capacities and both are identified in a multi-stage flow shop environment. Rules for the extraction of good minicell designs in mass customization manufacturing systems are also established.

Minicells are small manufacturing cells dedicated to an option family and organized in a multi-stage configuration for mass customization manufacturing. Product variants, depending on the customization requirements of each customer, are routed through the minicells as necessary. For successful mass customization, customized products must be manufactured at low cost and with short turn around time. Effective scheduling of jobs to be processed in minicells is essential to quickly deliver customized products. In this research, a genetic algorithm based approach is developed to schedule jobs in a minicell configuration by considering it as a multi-stage flow shop. A new crossover strategy is used in the genetic algorithm to obtain a minimum flow time schedule.

Artificial neural networks, so far, have not been used for designing modular cells. Therefore, Self-organizing neural network (SONN) is used in the present research to design minicell-based manufacturing system. Two previously developed methods were studied and implemented using SONN model. Results obtained are compared with previous results to analyze the effectiveness of SONN in designing minicells. A new method is then developed with the objective to design minicells more effectively and efficiently. Results of all three methods are compared using machine-count and materialhandling as performance measuring criteria to find out the best method