978-1-4799-6065-1/15/$31.00 ©2015 IEEE Reconfiguring manufacturing systems using an analytic hierarchy process with strategic and operational indicators Souhir BEN CHEIKH Sonia HAJRI-GABOUJ Saber DARMOUL LISI, INSAT, B.P. 676, Centre Urbain Nord, 1080, Tunis, Tunisia souhir.bencheikh@gmail.com LISI, INSAT, B.P. 676, Centre Urbain Nord, 1080, Tunis, Tunisia sonia.gabouj@insat.rnu.tn Industrial Engineering Department, King Saud University, P.O. Box 800, Riyadh, 11421, Saudi Arabia sdarmoul@ksu.edu.sa Abstract— In Reconfigurable Manufacturing Systems (RMS), decision makers often have to select one configuration among a set of available alternatives to meet new, unexpected and unpredictable changes disturbing production. A lot of research has been dedicated to evaluate configuration selection decisions using operational indicators based on performance. Unfortunately, the use of such indicators only may be relatively restrictive and can lead to choose an inefficient configuration. There is a need to include strategic indicators, which reflect both the capacity of the system to evolve and the real operating conditions of the workshop. In this paper, we consider both strategic and operational indicators when evaluating the reconfiguration decisions. We suggest a multi-criteria decision- making approach based on an Analytic Hierarchy Process (AHP) to assist decision makers in the selection process. Simulation results are provided to show the effectiveness of our approach. Keywords—Reconfigurable Manufacturing; multi criteria decision making; AHP; Strategic indicators; Operational indicators I. INTRODUCTION Nowadays, manufacturing companies have to deal with increasingly severe market conditions and highly changing environments. To stay competitive, these companies must possess more efficient, flexible, agile and responsive production systems that can be adapted rapidly and cost effectively [1]. Reconfigurable Manufacturing Systems (RMS) have emerged to address such challenging issues by offering rapid adaptation capabilities of both their capacity and functionality to overcome new situations [2]. However, the reorganization of such systems is a very difficult activity. It is essential for decision makers to rely on efficient tools that can help them in selecting, when needed, the configuration that best meets the requirements among a set of different available alternatives. To achieve this, it would be very useful to have indicators that could measure the competitiveness of the available configurations. A lot of research has been conducted on evaluating configuration selection decisions using operational indicators based on performance. Unfortunately, the use of such indicators only may be quite restrictive and can lead to a configuration that is not really efficient. There is a need to include strategic indicators that are related to the capacity of the system to evolve and which are close to the real operating conditions of the workshop. In this paper, we propose to capture the reconfiguration features as well as the dynamic behavior of the manufacturing system during reconfiguration. We consider both strategic and operational indicators when evaluating system configurations according to a multi-criteria outranking methodology. Thus, the selection of the most appropriate configuration is achieved with an Analytic Hierarchy Process (AHP), which is widely used in this context [3, 4, 6, 7, 8]. Therefore, the article is organized as follows. Section II provides an overview of related works. In section III, the decision-making process for configuration selection whilst considering strategic and operational indicators is presented. In section IV, a case study illustrates the benefits of the proposed approach. Section V concludes the article and suggests future research directions. II. LITERATURE REVIEW Multi-criteria decision-making techniques have been widely used to address problems in reconfigurable manufacturing. For some specific problems, a few research works consider reconfiguration related features as well as operational features when selecting a configuration among a set of available alternatives. The final priorities of alternatives are computed using additive formulas, like in the weighted sum model [10], the analytic hierarchy process (AHP) [3, 4, 7, 8], the Fuzzy AHP [6], ELECTRE [11] and PROMETHEE methods [5]. Reference [3] addresses the design stage of a manufacturing system, and suggests a multi-criteria reconfiguration approach to select one configuration among six available configurations. The authors consider strategic indicators related to reconfiguration features, such as scalability, convertibility, reliability and maintainability. Such a method is based on the assumption that all different production scenarios and technological evolution are known in advance and in an exact