Fleet reliability, energy efficiency and emissions control are top objectives in mining operations and all of these have a common origin in engine degradation. AMOP and Ai-RElia-BDt, two products of IOPTIA, enable integration of physic and chemical properties of fuel, lubricant and cooling fluids, which are originators of most of abnormal engine degradation mechanisms.
Traditional Condition Based Maintenance (CBM) or Health Monitoring Systems (HMS) take into consideration limited and discreet readings of values of some parameters of these fluids, in addition to engine parameters, to assess failure probability. This approach drives corrective action when the degradation process has already taken place and a failure in imminent.
On the other hand, when physic and chemical parameters of mentioned fluids are monitored in real time and this data is incorporated into a Big Data matrix for AI analysis, it is possible to monitor deviations on key parameters, which can be corrected on time to mitigate engine degradation much earlier.
With Ai-RElia-BDt Predictions of engine degradation is possible, well in advance before failures are imminent.
More over, Ai-RElia-BDt allows real time monitoring and visualizing of parameters which have strong correlations with engine degradation. This is key to identify prescriptive actions to mitigate engine degradation. This lead to less fuel consumption, less emissions and better availability over the entire fleet.
Machinery Monitoring Centres are quick and simple to implement at a very limited cost, thanks to IOPTIA web based solutions.