Development of a Maturity Scale for Mining Performance and Maintenance Analytics

Organisation: Vale – The University of Queensland
Start and Estimated Duration: From 01–January–2016 To 15 – December – 2018

Summary: Since the onset of the lump in commodity prices in mid-2012, the mining industry has sought to enhance productivity and lower labour and cost inputs significantly. Most companies have progressed through two to three waves of cost-cutting exercises, with the result that much of the low-hanging fruit has been plucked and further cost reduction demands the application of smarter, more targeted thinking. As a result, there is currently a great deal of interest in the implementation of data analytics to improve equipment performance and reduce maintenance downtime and costs. The potential exists for mining companies to contract expensive analytics programs only to be disillusioned by failing to create the magnitude of savings and performance gains promised. In response to these issues, Vale, in conjunction with the University of Queensland have identified the need to develop a maturity model, designed to be specific to the mining industry, to assess mining companies’ capabilities to use analytics to deliver performance improvements in the areas of equipment operations and maintenance. These areas have been selected as they are the current focus for many mining companies- to drive the optimisation of costs and returns. This project developed a framework, an approach and methodology as well as tools for assessing the maturity of analytics solutions employed by the Australian and Brazilian mining industry to enhance equipment performance and maintenance. A questionnaire will be developed and completed via telephone interviews with key personnel. Analysis of the collected information is expected to reveal a national picture of analytics take-up in the mining industry as well as the relative status of individual participant companies.