The mining industry relies considerably on its heavy machinery to work in extreme conditions for extended periods of time before maintenance is required. Whether it is a large Liebherr T 282B haul truck carrying 400 short ton loads or a 637G Caterpillar wheel tractor-scraper, the machines will need to operate at full capacity for extended periods of time before maintenance is required.

Maintenance on heavy machinery requires sensor technology much greater than what most of us know with our personal cars. Heavy haul machines require real-time data streaming from their complex diesel-electric engines and subsystems. A breakdown of a key hauling truck could mean potentially millions in lost revenues. Mining reliability analysts have traditionally had to make educated guesses on past maintenance when best to pull a machine out of operation to do routine maintenance. If a machine does breakdown, the company will need to be sure that they have the appropriate parts on-hand or rapid turnaround on parts that must be ordered. Due to the complexity of these heavy machines, it is also critical that mining companies closely monitor the skill of the operators and their hours of operations.

Use Case Many of the newer heavy machine models come equipped with networks of interconnected sensors. Operators can use Augmate Connect to log all data captured from each of the sensors and associate them with policies where applicable. Using data modeling, an operator can begin to identify potential negative correlations arising from heat, vibration, sound frequency, and over capacity. Using these data models, the operator will also be able to better predict the most common parts needed to have on-hand. When extreme conditions are unavoidable and a newly identified problems are discovered, Augmate Connects predictive maintenance module will proactively notify the parts ordering department and schedule the appropriate technician. Operator fatigue or inexperience are significant factors that can lead to damaging heavy machines. Augmate Connect allows a reliability analyst to set policies based on operator inputs. For instance, a policy can be created for a specific heavy machine and an operator classification. A simplistic policy for the operation of the Leibherr T 282B may require that the operator has at least 10 years of experience driving haul trucks of 300 short ton loads or higher and a governance rule that limits him to eight hours operation.