The broad sector of mechanical machining is essential and dominant in manufacturing and is characterized by unpredictable market changes in terms of demand. In such scenario, Flexible Manufacturing Systems (FMSs) allow manufacturing companies to remain highly competitive on the market. In FMSs, parts to be machined are mounted on multi-fixturing devices, called pallets, depending on product demand and product mix. Pallets are assembled at a loading/unloading station (LUS), moved by an automatic transporter from/to general-purpose machine centers where they are machined. The number of pallet configurations, i.e. pallet mounting clamping systems/jigs and products, present at the same time into a FMS can be considerable. As a consequence, LUSs could substantially influence FMS performance in terms of final throughput because of 4 critical operations at LUS: pallet configurations are assembled, dissembled and checked before and after the machining.
Very hard for humans. Although the pallet preparation task is always assigned to skilled operators, human can easily make errors during the pallet configuration because of the demanding cognitive task due to the large variability of part types and reconfigurable processes. Specifically, the limited or absent automation (e.g. ICT support, assistive technologies) in a context characterized by hundreds of elements to be assembled, tens of assembly operations and tools may lead to assembly relevant errors in terms of mismatching part types, wrong positioning on the pallet, and wrong mounting of the clamping systems. These errors may represent substantial economic losses in terms of damages in the machine tools or cutting tools and scraped parts (e.g. not in tolerance). On top of that, the operator workload may be significantly hard in terms of ergonomics.
Very hard for robots. Adopting full robot automation has not been yet achieved. The assembly/ disassembly is characterized from one side by many simple and repetitive operations, where the humans are acting as “robots”, and from other side by many bottlenecks where the human adaptability and dexterity is unique, e.g. for the insertion of screws in narrowed clearances. Furthermore, a complete automation of the process would require significant high investment and long-time return-of-investment, thus, affordable only for few industries.
PIROS solution: collaborative as-needed robotics. Derived from the analysis of the problem by the end-user and the development team, the optimal solution for standard LUS layout and framework is a safe robot co-worker and information management tools, able to support a fast setup of new batches (i.e. easy programming) and the online redefinition of tasks (i.e. the possibility to exchange operations between human and robot). This requirement-driven solution, however, will be designed to outstand the popular scientific and technological objectives of the robotic co-worker. An essential feature of the solution, in fact, must be the global speed of execution: the robot must almost keep the pace with skilled operators that are not keen to wait for operations that they may judge worthy to take over, in spite of the ergonomics or the loss of assistance.