Effect of reconfiguration costs on planning for capacity scalability in reconfigurable manufacturing systems

In a globally competitive market for products, manufacturers are faced with an increasing need to improve their flexibility, reliability, and responsiveness to meet the demands of their customers. Reconfigurable manufacturing systems (RMS) have become an important manufacturing paradigm, because they broadly encompass the ability to react efficiently to this environment by providing the exact capacity and functionality needed when needed. This paper studies how such new systems can manage their capacity scalability planning in a cost effective manner. An approach for modeling capacity scalability planning is proposed. The development of the model is based on set theory and the regeneration point theorem which is mapped to the reconfigurable manufacturing paradigm as the capacity scalability points of that system. The cost function of the model incorporates both the physical capacity cost based on capacity size and costs associated with the reconfiguration process which referred to as the scalability penalty cost and scalability effort cost. A dynamic programming (DP) approach is manipulated for the development of optimal capacity scalability plans. The effect of the reconfiguration costs on the capacity scalability planning horizon and overall cost is investigated. The results showed the relation between deciding on the optimal capacity scalability planning horizon and the different reconfiguration costs. Results also highlighted the fact that decreasing costs of reconfiguration will lead to cost effective implementation of reconfigurable manufacturing systems.