Digitally enhanced lubricant evaluation and improvement framework through developing digital characteristics (DC) for hot forging of aluminium alloys

The manufacturing sector is experiencing a never-before-seen surge in data generation, acquisition, and analytics. The promising potential of fundamental research following a data-driven approach may enable a more comprehensive understanding of forming operations and efficient optimisation of component quality. However, as a crucial component of metal forming operations, the investigation and insights from a data-centric perspective of hot forging processes is still absent. In the present study, the digital characteristics (DC) of the hot forging process was generated based on voluminous metadata extracted from experimentally verified FE simulations and localised sensors. Inherent and distinctive manufacturing nature throughout the life cycle of a hot-forged product have been revealed, spanning over the design, manufacturing, and application stages. The tribological DC was then extracted and analysed, and the data-guided interactive friction modelling was established to enable a digitally enhanced evaluation and improvement scheme of the lubricant product applied during the hot forging process. Significant potential has been demonstrated in implementing data-centric innovation techniques into traditional manufacturing paradigms to improve efficiency and process effectiveness.