Mean Time Between Failure (MTBF) is a closely monitored key performance indicator for mining operations. MTBF is the sum of lengths of the operational periods divided by the number of observed failures. In other words, it measures the mean time, in hours, from when a piece of equipment becomes available after a maintenance stoppage until it is unavailable due to the next maintenance stoppage.
Of course, fewer unplanned breakdowns will improve MTBF and one of the most effective ways to prevent breakdowns is to employ predictive technologies to find and fix emerging issues. The dilemma is that stopping the machine to troubleshoot will trigger a maintenance event and reduce the MTBF.
It’s a Catch-22. If you stop a machine and inspect it every time condition monitoring triggers a critical alert, the MTBF will be abysmal. But, if you don’t perform the right corrective actions at the right time, you can have equipment breakdowns and end up with high costs, poor availability and increased Mean Time To Repair (MTTR).
The secret is in making effective decisions about when to stop machines to troubleshoot and when to keep them running.
For example, in one month a mining operation running a fleet of 8 shovels, 35 trucks, 15 dozers and typical support equipment has 140 oil samples rated as “Critical” by their lab and 65 “Critical” onboard sensor events. If the maintenance team stops equipment to investigate all of these issues, their MTBF will be cut in half–but if they don’t investigate and address the real issues with enough urgency, equipment will fail and costs will go up.
To get it right, this mine uses Trakka, a sophisticated condition management system with predictive analytics, supported by experienced maintenance professionals to proactively decide when to intervene. Of the 205 Critical condition monitoring events, only 4 were determined to need intervention before a scheduled downtime for the equipment. 143 events were determined to be non-issues, and the remaining 61 were scheduled for inspection and troubleshooting at the next scheduled PM.
Maximizing MTBF without impacting MTTR, cost and availability requires an effective condition management system that includes highly capable software, reliable comparative data, and deep maintenance expertise. The decisions regarding when to perform interventions based on condition information happen on a daily basis, and making the right decisions at the right time will positively impact the heavily scrutinized MTBF metric. Make sure you pay attention to your condition management system to maximize your MTBF.
By Steve Bradbury, COO of DINGO
