Using Mine Truck On-Board Data as a Decision Making Tool for Mine Road Maintenance Management

Abstract

The management of unpaved mine road networks on large surface mines rarely results in optimal road maintenance strategies and minimised total road-user costs. This is ascribed mostly to the complex and dynamic combination of variable road networks and loading and discharge points. In a dynamic mining environment - typically those mines in which production is managed by a centralised truck dispatch system – there is no guarantee that a particular road maintenance intervention will contribute significantly to reducing total road-user costs or increasing productivity.Most surface mines rely on an integrated truck on-board diagnostic data collation, communication and GPS-asset location system as a real-time fleet management tool. By extending this system to monitor specific truck performance data, a road defect type and location can be recognised from the truck’s dynamic response. This paper presents the development of the analytical procedure used as a basis for evaluating the truck on-board data to establish maintenance priorities amongst a network of mine roads. Following an introduction to the system architecture, the results of field trials are analysed and the results discussed in the light of defect density and traffic volume as the primary variables in an approach to prioritising road maintenance. The paper concludes that by combining truck dynamic response data with the existing mine communication and asset management systems, road maintenance can be managed on a near real-time basis, thereby generating the maximum improvement in service and reduction in total road-user costs.