Improving Haul Truck Availability by Braking System Failure Prediction Using Advanced Data Analytics

Abstract

The aim of this article is introducing a haul truck availability improvement multi-objective computer model developed by using Artificial Intelligence Methods (AIMs) to complete predictive analytics for the haul trucks braking system. This model will be developed as an on-line service or a software package working with existing data collecting and analysing systems to predict serious and catastrophic failures in haul trucks’ braking system. This model makes a priority list for future maintenance activities to reduce unscheduled events, avoid catastrophic failures, and provide a platform for ongoing proactive maintenance. All recommendations created by the model will be filtered and sent to operators, supervisors and mine managers for making better decisions (See Figure 1).

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