Abstract

The mining industry is undergoing a digital transformation across the entire mining value chain from Exploration all the way to Reclamation.  These new technologies are changing the way mines operate bringing improved operational efficiencies while also lowering costs. Mobile and fixed plant equipment maintenance presents one of the largest components of operational expenditure within the mining industry, stemming from the fact that as a rule, most operators tend towards the application of preventative maintenance regimes that OEMs design for the equipment they sell. Regardless of whether it’s mobile or stationary equipment it is delivered from the manufacturer with a detailed schedule of maintenance. These schedules stipulate at what cadence to inspect, test and service specific components and when they should be repaired or replaced throughout the equipment’s useful life. These historical methods for performing maintenance do not create any measurable value for the consumers and do not factor in any other operating conditions that could potentially impact the overall availability of the asset. 

Mining companies need to look at a more proactive approach to equipment maintenance across all their assets, a method that improves reliability and is optimized to their specific work environments and processes. The ability to utilize asset sensor data to proactively monitor equipment for imminent and future failures is something that adds immediate value to a maintenance program. Predictive and prescriptive analytics utilizing machine learning and artificial intelligence provide a new strategic approach to how companies manage their maintenance programs.  These solutions allow for companies to plan around predicted downtime rather than having to reactively work through them.  The costs associated with unplanned downtime result in lost revenue and profits for the organization but can also have human and environmental costs as well.  When there is advance warning of a failure, teams have more time to look at more options for correction which allows the opportunity to mitigate the negative impacts while also reducing related costs. Taking it a step further the prescriptive maintenance programs provide potential solutions to the customer which again increases the efficiency of the team and allows more time to prepare for the downtime.

In this discussion we will look at the successful implementation of a Prescriptive Maintenance Solution at Evolution Mining’s Mungari operation in Western Australia, where they have seen immediate financial and operational successes due to improved asset availability.  In early 2020 Paul Robbins, Group Head for Asset Effectiveness Evolution Mining, started looking at data enabled business improvements surrounding technology that would improve their asset performance and productivity. Starting out with a small number of assets being monitored the team saw immediate value and began to scale. Working with Maintenance operations and subject matter experts Paul and the team were able to put a tangible value of what a specific unplanned downtime event from failure would have cost the company, realizing significant cost savings right away.  This Prescriptive Maintenance program allows the mine to operate more efficient, profitable, and with fewer safety and environmental risks while quickly showing its ROI.