“This truck runs seven days a week, hauling material out of the mine,” said Tyler Andersen, condition monitoring supervisor of Wheeler Machinery.
What if you spent a couple million dollars for a new piece of equipment for your job site, and then have to pay a quarter-million dollars more because a small part had failed, causing a total engine failure? What if that scenario could have been avoided with a predictive diagnostics system?
This near-crisis situation was recently averted for a mining company in Nevada. The engine oil pressure on a Caterpillar 793C haul truck was dropping dramatically, which was causing a drastic increase in engine oil filter restriction. But without the diagnosis of the need for a pre-failure repair, there was no way to know that the problem was happening.
The 793C is a big truck; more than 44 ft. (13.4 m) long and 25 ft. (7.6 m) wide with a payload of 240 tons (217.7 t). Having this work horse out of service would have been costly for the company.
“This truck runs seven days a week, hauling material out of the mine,” said Tyler Andersen, condition monitoring supervisor of Wheeler Machinery. “It would have been a serious setback for the company if this truck was taken out of production by a catastrophic failure while hauling ore. One of the most costly repairs is an unscheduled major failure on a haul truck.”
The predictive diagnostic system in this case is called a condition monitoring analyst, which is attached to the truck. It sent an alert to the mine site supervisor who immediately shut down the truck.
A subsequent inspection by mechanics found a failed fuel injector, which was causing raw fuel to be dumped into the engine oil pan. That led to a big drop in the engine oil pressure, which then caused the oil filters to plug. If the truck had not been immediately shut down, there would have been a total engine failure resulting in a repair costing more than $257,000 dollars. Instead, the customer paid $1,239 to replace the fuel injector. The savings was more than $255,000.
The conditioning monitoring analyst technology was sold with the truck by Wheeler Machinery in Salt Lake City as part of the company’s effort to integrate and utilize more technology to create a “repairs before failure” situation for customers. “We want to add value to the products we sell and service,” said Leon Ernest, mine site supervisor of Wheeler Machinery.
“We believe that our customers appreciate things like the condition monitoring analyst, because it makes them productive and profitable and helps them avoid costly situations.”
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