Wear particles formation in cold rolling

Melkamu Awoke Mekicha

Research output: ThesisPhD Thesis - Research UT, graduation UT

15 Downloads (Pure)

Abstract

The surface cleanliness of a cold rolled sheet metal is a very important parameter for product performance in many sectors, such as automotive and packaging industries. Wear particles, generated during cold rolling, contaminate the surface and reduce the surface quality of a cold rolled sheet. Furthermore, wear particles can negatively influence downstream processes such as annealing, galvanizing and deep drawing. A detailed understanding of the microscale mechanisms at the roll-strip interface, relevant for wear particles generation, is crucial to enable control and predictability over the surface quality of a cold rolled metal sheet. This thesis focuses on developing a physically based multi-scale wear model for the prediction of wear particles generation formation in cold rolling processes operating in the boundary lubrication regime. This model development is underpinned by fundamental insights into the relevant interfacial mechanisms during cold strip rolling influencing wear particles generation. The wear model is developed through several steps involving modelling the roll-strip contact at the macroscale and modelling the microscale wear behavior of a single roll asperity sliding through a sheet metal. The wear model is validated by conducting cold rolling experiments with varying process parameters on a pilot scale rolling mill. Moreover, the influence of rolling parameters on wear particles formation was investigated in the rolling experiments. The developed wear model covers the main physical phenomena related to wear particle generation and it can be included in industrial rolling models as both a predictive and retrospective tool.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Twente
Supervisors/Advisors
  • de Rooij, Matthias B., Supervisor
  • Schipper, Dirk J., Supervisor
  • Matthews, David Thomas Allan, Co-Supervisor
Award date3 Mar 2021
Place of PublicationEnschede
Publisher
Print ISBNs978-90-365-5136-6
DOIs
Publication statusPublished - 3 Mar 2021

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