To generate the alert, your condition monitoring system assesses the bulldozer’s overall machine health and status, its oil sample results, its recent inspection data and an electronic copy of its full work order history. But that’s just the beginning.
The system then recommends when and how you should replace the part, incorporating weather data to suggest the optimal day to perform the necessary maintenance – identifying a window of time when rain is forecasted, since your projects are typically paused during precipitation.
In the background, the required part is automatically quoted, ordered and replaced—all in the matter of a few days, without jeopardizing the asset’s uptime or your project’s completion timeline.
Sound like life in the future? It’s not. It’s made possible by predictive technology that exists today. Let’s examine how.
Welcome to the next generation of equipment maintenance
The value of data in equipment maintenance cannot be understated. Without data-driven insights, maintenance processes are manual and difficult at best—at worst, they’re inefficient and costly in terms of time and money lost.
Traditionally, when parts break, someone at the dealership calls the customer, they go back and forth on how to proceed, the part is then manually quoted and ordered, and perhaps most importantly the machine is in the shop the entire time.