Modularity assessment in reconfigurable manufacturing system (RMS) design: an Archived Multi-Objective Simulated Annealing-based approach

  • Hichem Haddou BenderbalEmail author
  • Mohammed Dahane
  • Lyes Benyoucef


Enhancing productivity, reducing inaccuracy and avoiding time waste at changeover are considered major drivers in manufacturing system design. One of the emerging paradigms concerned with these characteristics is reconfigurable manufacturing systems (RMSs). The high responsiveness and performance efficiencies of RMS make it a convenient manufacturing paradigm for and flexible enabler of mass customization. The RMS offers customized flexibility and a variety of alternatives as features thanks to its reconfigurable machine tool (RMT). These machines represent a major component of RMS and are based on an adjustable, modular and reconfigurable structure. Hence, the system modularity is of great importance. This paper outlines a multi-objective approach to optimize the RMS design. Three objectives are considered: the maximization of the system modularity, the minimization of the system completion time and the minimization of the system cost. We developed a modularity-based multi-objective approach that uses an adapted version of the “Archived Multi-Objective Simulated Annealing” (AMOSA) method to solve the optimization problem by selecting from a set of candidate machines the most suitable ones. Implemented, the decision maker can use a multi-objective decision making tool based on the well-known “Technique for Order of Preference by Similarity to Ideal Solution” (TOPSIS) to choose the best solution in the Pareto front according to his preferences. We demonstrated the applicability of the proposed approach through an illustrative example and an analysis of the obtained numerical results.


Reconfigurable manufacturing systems System design Modularity index Performance metrics Process plan Machine selection AMOSA TOPSIS 


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Copyright information

© Springer-Verlag London Ltd. 2017

Authors and Affiliations

  • Hichem Haddou Benderbal
    • 1
    Email author
  • Mohammed Dahane
    • 1
  • Lyes Benyoucef
    • 2
  1. 1.LGIPM Research LaboratoryLorraine UniversityMetzFrance
  2. 2.LSIS-UMR 7296Aix-Marseille UniversityMarseilleFrance

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