By John Maggiore
Aviation Maintenance, like many other industries, has gone through a change over the last 20 years fueled by impact of digital technologies and transformation on business. Maintenance has seen some good gains in efficiency from the adoption of things like digital records, software maintenance planning and tracking systems, data warehousing, and affordable devices bringing relevant information directly to the hangar and line mechanic. Boeing already empowers more than 10,000 commercial and military aviation mechanics worldwide with applications accessible on mobile devices.
Digital transformation has brought access to an unprecedented amount of aircraft, airline and military-aviation operational data. Access to this data has opened up the potential for doing predictive maintenance – the capability to spot an emerging issue before it may impact schedule operations. Boeing was first to begin exploring this new capability in commercial and military aviation. More than 10 years ago, Boeing introduced Airplane Health Management (AHM), an application that includes predictive analytics, for use in commercial aviation. Since AHM was released, Boeing has continued to advance the analytics capabilities of the solution as well as introducing other analytics enabled applications throughout the aerospace spectrum, using insights gained from each aviation sector to create and enhance applications for all segments.
Predictive maintenance rests on two other analytics capabilities: descriptive – identifying that an event happened, and diagnostic – determination of why a situation occurred. These form the basis for predictive maintenance. Why is predictive maintenance now coming to the forefront? Two reasons: First, the maturity of the digital systems used in maintenance have led to the emergence of new more efficient group of analytics software tools that are easier and faster to use. Second, many operators have come to the same understanding that drove Boeing to create AHM years ago: Predictive maintenance lowers operational cost and increases airplane availability. For example, one Boeing customer airline recently said that AHM’s predictive analytics has helped avoid delays, minimize disruption or save money more than 1,000 times across the fleet.
In one instance, an AHM predictive alert identified the potential for a failure of an Integrated Drive Generator on a 777. Without this alert, the airline may have experienced a future flight delay or cancellation, resulting in a loss of customer satisfaction and higher operating costs. Because of the predictive alert, an inspection was ordered at the next routine maintenance period. During inspection, an issue was found and corrected, preventing the potential in-service disruption and, because of early detection, avoiding a more costly repair.
The Boeing V-22 Readiness Operations Center uses data analytics to interpret data from the aircraft to: develop conditioned-based maintenance capabilities to reduce costs, identify training opportunities for aircrew and maintenance personnel, and to improve part demand forecasting models to ensure operators have the right parts at the right time.
The next frontier for predictive maintenance in aviation will come with the ready access to full-flight data – all the detailed parameters captured throughout a flight. Full-flight data has traditionally been used for such operations as Flight Operations Quality Assurance (FOQA) and engine health management activities. Today, we are working with operators to unlock the full potential of this data to further expand predictive maintenance activities.
More data and more sophistication in the analytics methods will lead to a new level of meaningful predictive alerts. However, the goal is not to stop with predictive, but to expand further into prescriptive analytics. It takes a solid foundation, as Boeing has, in predictive maintenance to deliver meaningful prescriptive analytics solutions. Boeing uses prescriptive analytics to create algorithms using tools like machine learning, modeling, simulation, and expert systems to power applications that will help airlines evaluate and select the best response to a predictive alert. Boeing also is offering EFPAC, which helps operators manage engine maintenance. EFPAC allows operators to optimize engine maintenance and leases by evaluating multiple scenarios.
Another area fueling the continued digital transformation of maintenance is the need to maintain an accurate record of the maintenance and configuration of the airplane. Nowhere is this more important than in the leased aircraft market. Almost 40 percent of commercial airplanes are leased. Airplanes change hands about four times during the course of their life, and passing along highly accurate maintenance records for each aircraft is important – this has a direct impact on asset value and transition time between leases. Today, Boeing manages more than 500 million digital records through STREAM.
Predictive maintenance is becoming a huge imperative in the aviation industry, and Boeing AnalytX is continuing to advance the practice and provide people and groups with analytics tools to help them boost their individual and organization’s efficiency, economy, performance, and safety. The future is about more predictability, less surprises, and having the time to innovate, plan, and optimize rather than react to emerging situations.
If you want to learn more about Boeing AnalytX and how predictive maintenance can benefit your operation, speak with your Boeing account representative or visit boeing.com/analytx.