Predictive maintenance
The goal of predictive maintenance is to forecast potential failures or issues before they occur, allowing for maintenance to be scheduled at a convenient time, thereby minimizing downtime and reducing costs.
To accomplish this goal, we need to collect data from the component or ECU that is being monitored and then analyze the collected data by advanced analytics or ML algorithms to identify patterns, trends, or anomalies that indicate a developing failure. Models are then developed to predict future component or ECU failures based on historical data and real-time monitoring. Now, based on the insights gained from the analysis and predictive modeling, maintenance can be scheduled.
The same framework can be utilized during the development and testing phases of vehicle components to predict failures and improve design. This assists Original Equipment Manufacturers (OEMs) in preventing design failures in the field, thus reducing recalls.
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