Mining operations generally rely on load and haul fleets with different pieces of heavy equipment, most commonly haul trucks, carrying vast volumes of materials out of the pit to either a dump location or the mine’s stockpile for mineral processing.
The equipment in these fleets typically represent one of the most significant capital expenditures mines initially make. The cost to maintain these assets is a substantial portion of a mine’s ongoing operating expenditure. Today’s global haul truck fleet exceeds 40,000 machines representing billions of dollars in capital invested across the mining industry with an additional hundreds of millions of dollars in operating expenditure to keep these fleets running.
With a price tag of several million dollars or more per haul truck and operating expenditures typically running upwards of a million dollars per year per truck, it is vitally important for mining operations to maximize utilization of their fleets and therefore return on investment while also ensuring they are operated safely and within the boundaries of the manufacturer’s specifications.
Shortcomings of Preventative Maintenance
Traditional preventative maintenance guidelines and programs are often implemented by mining companies as suggested by the manufacturers. These are seen as prerequisites for ideal haul truck utilization. Standard preventative maintenance guidelines for trucks might include:
- Oil changes every 500 service hours
- Engine valve inspections every 3,000 service hours
- Fuel injector changes every 6,000 service hours
- Full service every 10,000 service hours
- Engine replacement every 20,000 service hours
But these programs can be extremely expensive to execute and don’t always ensure that optimal equipment utilization is achieved.
Preventative maintenance can also diminish utilization rates, or in some circumstances, create issues where none existed before. Similarly, following the manufacturers’ maintenance schedule does not always ensure that trucks won’t fail. This can lead to unplanned maintenance activities which at best can reduce plant productivity, at worst, can pose a safety risk to operators and other assets.
Prescriptive Maintenance and Preventative Maintenance as Simultaneous Solutions
Prescriptive maintenance goes an extra step beyond preventative maintenance by not only identifying potential issues but providing a specific remedy to address the problem.
One particular prescriptive maintenance solution, available from AspenTech, the market leader in AI and machine learning (ML), provides an opportunity for maintenance managers to introduce advanced, proprietary ML technology to inform decisions, detect potential issues early, optimize equipment use, decrease costs and lengthen the life of high CAPEX assets. The solution can also identify data patterns, specifically which patterns are demonstrating “normal behavior” within a given system based on historical data. Agents are placed in the system to monitor the equipment in real time, capturing all data from the system and when these agents detect behavior that falls outside the established norms, alerts are triggered for certain events that may lead to future failures. With an ability to mark specific warnings as acceptable—the solution provides very few false positives.
The AspenTech solution’s ease of deployment and scalability across assets are two more significant benefits for businesses.
As an example of this solution’s success, one of the world’s largest platinum producers has successfully scaled the solution to over 213 assets across 11 sites globally and is seeing material impact in their operations reliability and predictability by observing alerts that indicated given maintenance activities would be required to ensure equipment availability and uptime. The facility also realized safety and environmental benefits thanks to failure alerts triggering well in advance of severe problems occurring, which may have resulted in further secondary effects.
Another company deployed the AspenTech solution to assist with analysis of its haul network, machinery and engines to prevent engine failures. Using data from both normal behavior and exact failure patterns in archived engine lube oil samples, agents were created and rapidly scaled to nearly 600 engines in the field. Within just four months the ML algorithm detected 10 pending failures and prescribed corrective action with early advance warning, enabling the company to save millions in maintenance costs and avoid unplanned downtime resulting from equipment failure and associated lost revenues.
By gaining insights on when unplanned maintenance events occur, mining companies can make informed decisions to create maintenance schedules that are aligned with and complement preventative maintenance schedules rather than simply implementing the haul truck OEM’s suggested maintenance plan.
With the high commodity prices in the current market, mining companies are in an optimal position to take advantage of advanced and highly scalable technologies such as prescriptive maintenance to maintain wider margins and ensure they remain as competitive as possible in today’s extremely challenging business environment.
Watch this video to learn more about our prescriptive maintenance solution for the metals and mining industry.