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Teams across Boeing are collaborating with US Army Futures Command in developing predictive digital maintenance solutions to support and improve helicopter fleet readiness. John Chicoli, Director of US Army Services for Boeing Global Services, told MON “We have demonstrated capabilities and sensors that offer improved failure detection for electrical and drive components and oil systems. Some of our early warning signals have shown to be effective more than 100 flight-hours in advance, and support near real-time condition indicator calculations and messaging, available in-flight to pilots and on the ground for maintainers.”

Boeing has also developed Remaining Useful Life (RUL) prediction models for several helicopters, designed to extend RUL forecasts and support a variety of components including the drive system, generators, electrical/electronic and electro-mechanical components. In addition, Boeing “continues to develop and mature effective and affordable advanced maintenance solutions for current and future platforms.”

Chicoli offered one imperative to pursue predictive maintenance, pointing out it provides the flexibility to anticipate events and plan actions at all levels of operation, which improves readiness and reduces logistics footprint. “Readiness is supported by reduced downtime due to maintenance and logistic delays, reduced inspections and scheduled maintenance, extending component life, and extending the maintenance free operating period.”

The Boeing team reports other significant returns on investment from these activities. On helicopters with vibration monitoring and data collection capabilities, Boeing has successfully implemented condition-based maintenance algorithms into post-flight ground stations and onboard systems, to alert crews and maintenance personnel to impending failures. “By providing predicted degradation alerts, operators and maintainers can take appropriate corrective actions and schedule maintenance activities when they are needed,” Chicoli added.

Further, through data science and pattern recognition analysis, Boeing analytics efforts have produced algorithms to indicate degradation or failure of dynamic components in rotor heads, engines, drive trains and avionics. “System monitoring and post-operations analysis have shown customer savings in excess of $50 million in life-cycle costs in a single year through reduction in maintenance man-hours, part requirements and operating costs for test flights,” Chicoli explained, going on to provide his perspective on how predictive maintenance for military aviation might evolve over the next 12-24 months. As a baseline, Boeing’s current focus is on partnering with the Army and other military services to ensure the data-driven decisions are available to the maintainers, supply chain managers and aviation decision makers. “Observing that raw data by itself without understanding it is not helpful, so it’s about displaying it in a fashion that facilitates informed decisions […] We see predictive maintenance data becoming automated and feeding into the supply chain and other systems that bring an integrated approach to aircraft maintenance. More reliance on cloud storage and mobile devices is another way to have the right data available at the right time. Ultimately, it reduces the burden on the maintainer.”

Linking predictive maintenance to the broader operational domain, Chicoli concluded that Boeing’s customers must be ready to defend against threats from land, air, sea, space and cyber. “This will require rapid and efficient – and in some cases AI-enabled – coordination between aircrews, ground crews, maintainers, aircraft, vehicles and other systems across the Joint All Domain Operational (JADO) environment. As an original equipment manufacturer, we can leverage our expertise and the depth and breadth of our global enterprise to offer a holistic and strategic view of aviation operations under JADO.”

Marty Kauchak

Predictive maintenance promises fleet managers significant maintenance and operational cost savings. (Photo: Boeing)

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