Fuzzy Multi-objective Modelling for Dynamic Production Planning and Scheduling in Reconfigurable Robotic Systems: an Industry 4.0 case study

The design and configuration process in a reconfigurable robot is a very complex task, often constituting an obstacle for the use of these robots categories in industry. More and more also to build online production planning and control (PPC) systems, able to synchronize mechatronics tasks involved in the configura-tion and re-configuration processes is an open complex issue in scientific literature an in industry. To design and implement a such system could make more easy the choice of a reconfigurable system to commercial monolithic solutions proposed by a robots catalogue of a specific robot manufacturer. By a computational perspec-tive this problem is particular interesting to solve. In this paper a representation of the uncertainty present in this robotic system is modelled with fuzzy variables and parameters [1 - 5], while the control feedback present in different time horizon re-quests fast algorithm in planning and scheduling phases in a scheme of combinato-rial explosions sub problems with continuous changing of features (variables and parameters before considered) during the synchronization of macro robotic tasks and macro tasks made of operations taken in consideration in production planning and scheduling, with the main goal to build a system adaptable in an "online" way during the execution of robotic tasks. For achieving this aim a Fuzzy Multi-Objective modelling is used and several heuristic techniques are compared [6 - 9].