A rule-based harmony search simulation-optimization approach for intelligent control of a robotic assembly cell

This paper proposes to use a rule-based simulation-optimization approach for the dynamic scheduling and control of a robotic assembly cell. The approach is useful in both hierarchic control structure and hybrid control structure where the decision is distributed among the robotic cell entities that are products and resources (robots). Particularly, the approach make use of scheduling/dispatching rules and a harmony search optimization process coupled to a discreet event model of the studied manufacturing system, modeled in the FlexSim simulation software. Target system consists of the Valenciennes´s AIP PRIMECA robotic assembly cell (France) that represents a hard declination of the flexible job shop scheduling problem. Obtained results validate the simulation model and the methodology but highlights a lack of efficiency of the adopted optimization process witch have to be addressed in future works.