Thesis Author: Samuel Kember
Academic Supervisor: Guodong Shi
Industry Supervisor: Marcus Valastro
This thesis was conducted over a six-month industry placement at Corehesion Services Pty Ltd.
Corehesion is an Australian-born software as a service (SaaS) company specialising in creating bespoke solutions for heavy industry to ensure safety compliance and improve efficiency. Its software platform has primarily been used within the mining industry, with current projects aimed at expanding services into energy production and global shipping industries. These projects will continue to build on Corehesion’s expertise in delivering safety and cost-efficiency solutions in heavy industry through software that is purpose-built around clients’ requirements.
Asset management and maintenance are essential components of business operations aimed at enhancing cost efficiency and safety [73]. Jung et al. states that the primary aim of this process is to “reduce the risk of equipment failure, extend equipment life, and minimise unplanned outages” [54, p.3391]. This thesis will focus on expanding Corehesion’s current service offerings to mining operations by developing a more efficient framework for inspecting truck tyres during normal operations and replacing the current antiquated methodology. The end goal of this project is to increase the operational lifespan of truck tyres by providing operators with more current and timely information about tyre conditions enabling preventative measures to be taken thereby significantly reducing operational costs for mines. This will be achieved by capturing more data from maintenance operations, providing operators with a practical framework to view the data on a timely basis, and laying the groundwork for integrating a market-ready artificial intelligence (AI) driven Computer Vision (CV) tool to aid decision-making.
