Li-Liang Wan,*²*, Xiao Yang^1,2

¹ Metal Forming and Materials Modelling Group, Department of Mechanical Engineering,
Imperial College London, London SW7 2AZ, UK
²SmartForming Research Base, Imperial College London, LondonSW7 2AZ, UK

EXTENDED ABSTRACT: Digitally-enhanced technologies are set to transform every aspect of manufacturing. Networks of sensors that compute at the edge (streamlining information flow from devices and providing real-time local data analysis), and emerging Cloud Finite Element Analysis technologies yield data at unprecedented scales, both in terms of volume and precision, providing information on complex processes and systems that had previously been impractical. Cloud Finite Element Analysis technologies enable proactive data collection in a supply chain of； for example the metal forming industry, throughout the life cycle of a product or process, which presents revolutionary opportunities for the development and evaluation of digitally-enhanced products, which requires a coherent research agenda involving the merging of tribological knowledge, manufacturing and data science. Digital characteristics (DC) is proposed for characterising manufacturing technologies from the perspective of the metadata generated during the process. The DC is the visualisation of manufacturing metadata for a specific manufacturing process incorporating essential information spanning the design, manufacturing and application stages of manufactured products. In the present study, data obtained from a vast number of experimentally verified finite element simulation results is used for a metal forming process to develop a digitally-enhanced lubricant evaluation approach [1], by precisely representing the tribological boundary conditions at the workpiece/tooling interface, i.e., complex loading conditions of contact pressures, sliding speeds and temperatures. The presented approach combines the implementation of digital characteristics of the target forming process, data-guided lubricant testing and mechanism­based accurate theoretical modelling, enabling the development of data-centric lubricant limit diagrams and intuitive and quantitative evaluation of the lubricant performance.

Keywords: digital characteristics; digitally enhanced manufacturing; industry 4.0; lubricant limit diagram.

REFERENCES

[1] Yang, X., Liu, H., Dhawan, S., Politis, D. J., Zhang, J., Dini, D.,... & Wang, L., Nat Commun., 13, (2022) 5748