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The ARC Training Centre for
Transforming Maintenance through Data Science
Presentations

Conveyor belt wear forecasting through a Bayesian Hierarchical Modeling framework using functional data analysis and gamma processes.

ryan-leadbetter

UWA - Blakers Lecture Theatre( MATH:G18

Thursday 29 September 2022

Reliability engineers make critical decisions about when and how to maintain conveyor belts; decisions that can significantly impact the production of the mine. The engineers use thickness measurements across the belt's width to justify these decisions. However, the current approaches to forecast the wear of the conveyor belts are naive and throw away valuable information about the spacial wear characteristics of the conveyor. Ryan has developed a new method for forecasting belt wear that retains the wear profile's spacial structure and considers the wear rate's heterogeneity - caused by operation and ore body composition variations.

This presentation was delivered to an academic audience as part of Maths and stats Colloquium series at UWA.