We recently commenced a project to assist a client make sound data supported decisions around reducing expenditure in their oil sampling program.
Relialytics’ first equipment model assessment demonstrated that, on the final drives alone, over $12k per annum could potentially be saved on oil sampling costs on this vehicle type.
A 50% reduction.
This was achieved by utilising a combination of Text and Numerical Analytics and Data Visualisation, to very quickly (i.e. in our first day of analysis), identify initial savings in oil sampling for a single component type (final drives) on a small fleet of trucks (all of the same model).
Our review was conducted with the following philosophy i.e. an equipment type / component would be a candidate for an increase in sample intervals (e.g. from 500 to 1,000 hours) depending on the:
1. Severity of previous issues with the components
2. Rate at which these issues manifested
3. Stage of life at which the issues present themselves
4. Systemic or isolated nature of the issues
Our initial text analytics and data visualisation investigation showed that across approximately 17 years of oil sample data, very few problems had been experienced with the final drives. In fact, 30% of the samples had shown only minor issues, 70% showed no issues at all.
Over 17 years only 2 samples were considered severe enough to be considered “C” samples i.e. take action. These issues presented themselves at a slow rate i.e. progressively, were related to one truck (both left and right final drives) and in the early stages of the life of the components (suggesting breaking in of the components).
The rates of change of element levels in the oil, when compared to other vehicle analyses were very low providing significant confidence that sampling intervals could be increased.
potential savings in oil sampling per equipment unit / component type
years of CM data used to help justify these savings
component samples reviewed in detail, in a single day