Our Reliability Digital Twin (RDT) analytics has been proven in aerospace applications. The algorithms, data, and software can be used for many other applications. The main prerequisite is the ability to collect the asset management data such as repairs and replacement information combined with the asset serial number. In the sustainment of military aircraft, the reliability event data has been collected for over a decade. The Industrial IoT enables collection of the reliability event data in many other applications.
In one project Mitek Analytics collaborated with Lockheed Martin in development of enterprise RDT software for US Air Force fleet reliability analytics. The software analyses usage and event data of repairable parts and systems. The predictive analytics have been demonstrated for the usage and maintenance actions for repairable Line Replaceable Unit (LRU) components of a fleet of aircraft over ten years of operation.
The RDT Predictive Analytics in the Air Force project process event and usage information available in current Air Force systems. They include data preprocessing and cleansing logic necessary to addresses bad data records that would otherwise distort the analysis.
The RDT Prescriptive Analytics deliver value by using the predictive models to identify bad actors and offending factors at both system and component level that contribute disproportionally to system failures. This allows targeting the maintenance and significantly reducing the number of unnecessary actions leading to cost savings and increased system availability.
The RDT Prescriptive Analytics attribute root cause of substandard performance to specific factors that include the following: subpopulation of parts, subpopulations of systems hosting those parts, maintenance actions, and usage patterns. The Prescriptive Analytics can include self-organizing logistics that increase aircraft availability, reduce unscheduled maintenance, and optimize the logistics chain to generate cost avoidance benefits.
The RDT Analytics are largely agnostic to the application. As an additional example, they can be used for electric power systems assets: generating equipment, transmission equipment, substation equipment, and distribution systems.