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Digitally-enhanced lubricant evaluation scheme for hot stamping applications

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Title: Digitally-enhanced lubricant evaluation scheme for hot stamping applications
Authors: Yang, X
Liu, H
Dhawan, S
Politis, D
Zhang, J
Dini, D
Hu, L
Gharbi, M
Wang, L
Item Type: Journal Article
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 lubricants, which requires a coherent research agenda involving the merging of tribological knowledge, manufacturing and data science. 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, 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 mechanism-based accurate theoretical modelling, enabling the development of data-centric lubricant limit diagrams and intuitive and quantitative evaluation of the lubricant performance.
Issue Date: 30-Sep-2022
Date of Acceptance: 21-Sep-2022
URI: http://hdl.handle.net/10044/1/100153
DOI: 10.1038/s41467-022-33532-1
ISSN: 2041-1723
Publisher: Nature Research
Journal / Book Title: Nature Communications
Volume: 13
Copyright Statement: © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/N025954/1
Publication Status: Published
Article Number: ARTN 5748
Appears in Collections:Mechanical Engineering
Faculty of Natural Sciences

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