Project number
16057
Organization
Caterpillar Inc.
Academic year
2016-2017
Downtime for repair is costly for a company that operates a large fleet of expensive vehicles. The goal of this project is to create a predictive wear model for the sponsor’s large mining trucks.
The model aims to predict the rate at which the wear plates lose volume, determining where the truck will wear and giving truck operators foresight into when repairs will be necessary. Experiments to determine rates of wear over the lifetime of a mining truck were designed after static testing in a lab, to examine the relationship between impinging and wearing materials, and dynamic testing at the sponsor’s Tucson Proving Grounds.
The designed system gives operators a customized assessment of repair schedules by allowing them to enter specific truck parameters, such as material mined, type of mining truck, capacity of the body, and shovel specifications.
The model aims to predict the rate at which the wear plates lose volume, determining where the truck will wear and giving truck operators foresight into when repairs will be necessary. Experiments to determine rates of wear over the lifetime of a mining truck were designed after static testing in a lab, to examine the relationship between impinging and wearing materials, and dynamic testing at the sponsor’s Tucson Proving Grounds.
The designed system gives operators a customized assessment of repair schedules by allowing them to enter specific truck parameters, such as material mined, type of mining truck, capacity of the body, and shovel specifications.