LAUSR

Abstract In the last decade, traditional industrial and market features were replaced by emerging factors, such as the variable market demand, the need for flexibility, the shorter product life cycles and the mass personalisation, which drastically modified the production environment, pressing industrial companies to embrace and implement new types of production paradigms. Reconfigurable Manufacturing Systems (RMSs) rose as effective systems able to meet the current challenges rapidly changing their hardware, i.e. physical, and software, i.e. logical, structures to address changes in market needs. The manufacturing environment is usually characterised by dynamic cells, i.e. Reconfigurable Machine Cells (RMCs), including intelligent machines called Reconfigurable Machine Tools (RMTs). Such machines consist of fixed parts, i.e. basic modules, and dynamic parts, i.e. auxiliary modules, which allow performing different tasks, i.e. operations. This paper aims at proposing an optimisation linear programming model for the dynamic management of RMSs best balancing the RMTs reconfiguration, considering the auxiliary modules availability, i.e. the efforts to install and disassemble the auxiliary modules on/from the machines, and the part flows among the RMTs. The application to an operative case study widens the model discussion and a multi-scenario analysis concludes the study analysing how the overall system performances change varying the available auxiliary modules. Globally, results show the joint presence of multiple parts on the same RMT in each period allow concluding about the key role of the auxiliary modules to create useful and flexible structures suitable for multiple part processing.