Global competition, increased customization of products, shorter product lifecycles and delivery times require more agility from manufacturing companies. In contrast to conventional manufacturing systems, the new paradigm of Reconfigurable Manufacturing Systems (RMS) aim to achieve agility by adapting itself to changing market conditions, using its reconfiguration capabilities. Since RMS are evolving systems, the justification techniques should include features that incorporate the aspect of reconfiguration and the strategic benefits of reconfigurability. The purpose of this thesis is to show that lifecycle evaluation of RMS that considers both economic and strategic objectives results in providing cost-effective, easy to manage and responsive manufacturing system configurations throughout the system’s lifecycle.

In order to prove this thesis, a multi-criteria decision making approach has been followed. First, a lifecycle cost model has been developed representing the various activities in RMS. The cost model incorporates in-house production and outsourcing, machine acquisition and disposal costs, operational costs, and reconfiguration cost and duration. Second, a structural manufacturing system complexity metric has been developed. The complexity metric provides insight into the system components and structure, and assist in selecting a less complex system at the early design stages. Third, a manufacturing system responsiveness metric has been developed in order to assess the configurations’ ability to respond to the changes in demand mix within each period of the lifecycle. These objectives are then incorporated in a fuzzy multiple objective optimization tool in order to incorporate the decision maker’s preferences into the model.

The proposed methodology has been applied to a case study where various demand scenarios have been used in order to determine the suitable RMS configurations over the planning horizon. In addition, an equivalent Flexible Manufacturing System (FMS) configuration has been generated under the same conditions in order to compare FMS and RMS investments.

The main contribution of this work is to enhance the investment evaluation of manufacturing systems by incorporating strategic along with economic objectives within a lifecycle analysis framework. A decision support tool for planning RMS configurations and their justification has been developed. It can also be used for the comparison of FMS and RMS.