Our Reliability Digital Twin (RDT) analytics extracts valuable information from reliability event data. The RDT analyzes reliability event data, such as replacement and repair dates, collected in maintenance, repair, & operations (MRO) for the assets. The RDT Analytics Engine provides unique functionality for multi-level analysis of the MRO data for asset fleet.

Reliability Digital Twin (RDT) is trained on reliability event data, such as replacement and repair dates, collected in maintenance, repair, & operations (MRO) for the IIoT assets. The RDT analytics have been proven in Air Force applications. The data on reliability events (failures, part replacements, repairs) are analyzed with methods that are largely independent of the application. As a result, our analytics can be used in many vertical applications. The data-driven modeling facilitates the discovery of trends and causes of substandard reliability performance and the identification of remedial actions. In the sustainment of military aircraft, the reliability event data has been available for a few years. The Industrial IoT enables collection and analysis of the reliability event data in many other up and coming applications.

The baseline reliability models that are currently used in many industries describe the part reliability through a single parameter, Mean Time Between Failures (MTBF). Mitek’s Predictive Analytics for Asset Fleet Reliability connect individual histories of parts and systems in a unified multi-level model of fleet reliability that scales up the MTBF model. Our Predictive Analytics account for the time-varying reliability parameters across the fleet and with usage time