Predictive Maintenance 2.0 - Using Analytics to Significantly Reduce Maintenance Costs

CIM Montreal 2015
Martin Provencher (IBM)
Mining companies are facing increasingly complex business challenges. As capital budgets shrink, return on investment (ROI) becomes more important. Ore prices often rise or fall dramatically without warning, increasing the pressure to maximize productivity and eliminate unplanned downtime. With cuts to operational and maintenance resource allocations, your organization may struggle to cost-effectively manage assets, carry out preventive maintenance work and proactively address quality issues. Deploying a Predictive Asset Maintenance solution can supply the insights needed in near real time to make faster, more informed decisions. Smarter maintenance of production equipment and vehicles can help get the most out of your budget and contribute to the bottom line by sustaining product quality. A predictive maintenance solution using data integration and analytics will help reduce operational costs, improve asset productivity and increase process efficiency.
Keywords: Maintenance, Real time, Data, Analytics, Smarter Mining, Predictive, Innovation, Costs
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