Aviation Predictive Maintenance Solution

Forge’s Predictive Modeling applies machine learning to historical data to make predictions about future outcomes, such as machine failures, quality degradation, or when service will be required. Predictive Scoring anticipates future outcomes and offers the ability to make relevant outcome-based predictions based on data within ThingWorx. Confidence Models provide a range of uncertainty for a given prediction to better facilitate automated processes and enhance human decision-making. Forge’ solution will not only provide a state-of-the-art predictive maintenance capability, but it will also integrate with the wider sustainment engineering ecosystem that creates a true “decision support system” that enables modeling and simulation of scenarios to plan for a combat readiness within varying budgetary conditions, as well as other “what if?” scenarios, such as surges in op-tempo, causal factors, changes in parameters etc. This solution will enable the DAF to make strategic decisions on the F-22 in a way that maximizes the operational readiness. By adding Augmented Reality maintenance processes to complex maintenance tasks, the ability to follow an AR checklist when looking at a machine, along with the use of voice interaction to register inspection results, makes inspection and diagnosis faster. During the repair process, technicians see precisely what they need when they need it – without having to take their hands off the machine and reach for a manual. This has positive implications for health and safety because it keeps the technician’s focus on the equipment. The AR software can walk them through the correct sequence of maintenance steps, ensuring that they interact with the equipment safely. It is especially useful when dealing with heavy equipment, which could be dangerous when mishandled. AR headsets could also identify any potential health hazards linked to the equipment as the technician performs the work.