PADME - Process Automation for Discrete Manufacturing Excellence
The main idea of the project is to investigate and demonstrate how the digitalized and proven systems and technologies of the Process Industry, like CPAS, can be used in DM to improve competitiveness and drive growth.
ABB AB, Control Technologies, ABB Corporate Research, ABB Robotics, Level Twentyone Management, Sandvik Mining and Construction Tools AB, Scania, SICS Swedish ICT - the Swedish institute of computer science, Toyota Material Handling and Westermo R&D AB.
Project manager at MDH
Several signs indicate a shift of global industry towards customized Low Volume High Mix (LVHM) manufacturing closer to customers and skilled workforce. Customized LVHM manufacturing requires increased flexibility. Flexibility and performance of a manufacturing process is, however, negatively affected by incorrect, late, contradictory, and/or inadequate information, as well as operators or machines not being able to benefit from available information. Countermeasures to problems in Discrete Manufacturing (DM) are typically based on events that have occurred, e.g. a machine downtime, incomplete order data, or material shortage, all leading to lower productivity. Action is based on “corrective information”. The process industry has, on the other hand, successfully and for a long time, used digital systems like Collaborative Process Automation Systems (CPAS) to continuously control and monitor processes, enabling countermeasures before a production stop occurs. Actions is based on “preventive information”. The main idea of the project is to investigate and demonstrate how the digitalized and proven systems and technologies of the Process Industry, like CPAS, can be used in DM to improve competitiveness and drive growth. Such improvements are expected in safety, quality, cycle time, cost, and productivity. It would also be investigated how CPAS in DM can improve the sustainability of a production system, e.g. if the modularity of CPAS can improve scalability and redesign of the production system.