In progressive die stamping processes, maintenance activities caused by tool damage, and wear represent economic losses for companies. An effective predictive maintenance strategy can only be implemented if maintenance data coming from the operations are correlated to specific process-related information. As a part of a more general data-based predictive maintenance strategy, the main causes of tool damage and wear in a progressive die stamping factory that produces automotive metal washers have been identified by means of FEA simulations. In this study, the progressive die stamping of a dented conical washer is simulated with Transvalor FORGE FEA software by implementing the process parameters used in a real case. In this study, two indicators called FEAwear and FEAdamage are proposed for prediction of die wear and damage for tools with high risk of failure. For validating the accuracy of the FEA simulations, dimension and geometry comparisons are performed between FEA and real washer, and then real and FEA maximum press force comparison is performed. In the end, FEA simulations demonstrated their accuracy in predicting the stamping force of the press and the final part quality, and proposed FEA damage and wear indicators accurately predicted the most critical tools and stations, as confirmed by the real maintenance data. Finally, the simulations also correctly detected potential damage zones of the tools.

Abstract. New paradigms based on Circular Economy (CE) principles are needed for boosting the ecological transition and improving the energy and material efficiency. In this paper, a novel remanufacturing process chain for End-of-Life (EoL) automotive panels is first presented. The core of the recycling strategy is the reshaping of curved EoL automotive sheets through flattening by means of a hydraulic press. Flattening experiments together with press power consumption measurements have been performed on thin steel parts. While the experimental procedure demonstrated the technical feasibility of flattening “small-scale” steel parts, a more complete analysis on environmental sustainability was required. For this purpose, a Life Cycle Assessment (LCA) of the remanufacturing process chain proposed was set up. The results of the study demonstrated that flattening is a viable solution for reshaping EoL automotive panels, and that, for one kg of reshaped steel, approximately 2.2 kg CO2 and 24 MJ could be saved.