Data is becoming the new currency of IoT and analytics in the Maintenance, Repair and Overhaul (MRO) of modern aircraft.
By John Blyler, Founder – JB Systems
The explosive growth of data from connected Internet-of-Things (IOT) devices will ultimately be a major revenue generator in the avionics space – among many others. This article looks at one type of data – engine data – and how it will enhance the Maintenance, Repair, and Overhaul (MRO) of fleet aircrafts.
Modern aircraft use a variety of different engines for flight. The one common factor among all these engines is incorporation of a large quantities of sensors, instrumentation and electronics for aircraft control and maintenance.
Today, the average number of sensors monitoring the health of aircraft engines is about 250 devices per engine. These devices provide a snapshot of data at any one time. But with the availability of inexpensive and “smart” sensors, that snapshot is turning into a continuous stream of data. The challenge is how to quickly analyze the higher volume of increasingly more accurate data. The same data challenges – although at a lesser level of volume – is also happening on the In-Flight Entertainment (IFE) commercial side of the aviation industry. (That will be a topic for another story.)
Modern aircraft engine monitoring systems are quickly growing from several hundred to several thousand sensors. For example, the Bombardier C Series jetliner carries a Pratt & Whitney’s Geared Turbo Fan (GTF) engine, which is fitted with over 5,000 sensors that generate up to 10 GB of data per second. Thus, a single twin-engine aircraft with an average flight time of 12-hours from Los Angeles to New York and back again can produce up to 864 TB of data for that flight. If that number is expanded to include the typical number of commercial flights in the sky over the US on a given day (~28,000) times an entire year, then the amount of date is closer to 8,830,000,000 TB (see Figure 1).
It’s not just the sheer volume of data that’s available to the commercial flight industry but the value of that data. Such data, as within other industrial businesses, has more potential revenue value than other types of data currently generated via social media on the consumer internet (Figure 2).
For the engine data to be of value, it must first be captured and then processed into useful information. Capturing the data is often the easy part. For example, modern geared turbofan engines come equipped with sensors that can potentially capture 5,000 parameters, or 10 gigabytes of data every second. The types of parameters that will be measured include temperature, air and liquid pressure, rotational speed and vibration – among many other things. The real challenge is deciding how much initial processing to perform locally near the sensors and how much to send to the cloud for more intensive calculations. The cloud architecture will be part of the ground-based infrastructure capable of storing, processing and analyzing enormous amounts of data every years – measured in tens of petabytes to zettabytes of information.
Is it worth gathering all this data? Do we have the algorithms and know-how to process this raw data into useful information? The answers are (mostly) yes. This value of the potential information has already been demonstrated. For example, the GTF engine already uses such data along with artificial intelligence to predict the demands of the engine in terms of thrust levels during flight. As a result, GTF engines are demonstrating a reduction in fuel consumption by 10% to 15%, alongside impressive performance improvements in engine noise and emissions.
In addition to increasing the efficiency of engine and aircraft performance, analyzing big data real-time can help in the early detection of potential aircraft maintenance issues and even failures, e.g., component cracks in the engine. (see “Sensor System for Crack Initiation and Crack Growth Monitoring in Aeroengine Components,” by A. Kumar ; A. Nayak)
The IOT movement goes beyond improving aircraft engine performance and maintenance to include almost every other aircraft subsystem. Consider the avionic communication subsystem, which traditionally transfered data up to a maximum of 12.5 KB/s up to more modern Boeing 787s and Airbus A350s Ethernet-based aircraft data networks that achieve rates up to 12.5MB/s.
Higher network data rates makes it quicker and easier to transmit information via avionics systems within the aircraft and to the maintenance teams on the ground. This can include updates about current flying conditions and any faults that have occurred during the flight.
The importance of IOT data systems in the in-flight entertainment and connectivity (IFEC) systems are equally impressive. It has been predicted that by 2030, 90 percent of all aircraft will have some sort of connectivity. The new in-flight experience is being shaped by high-tech electronics like HD screens and touchscreens, as well as by low-tech advances like seats that accommodate tablets.
The reason why commercial air transport CEOs and product development managers care about Maintenance, Repair, and Overhaul (MRO), is that current demand for these costs is about $64B, with Asia equivalent to North America and Europe in market size.
By 2025, the global MRO market is expected to reach $96B at a growth of 4.1% per annum. While the engine and component MRO markets remain the largest segments, the strongest growth will occur in the modifications market (e.g., interiors and connectivity). Conversely, airframe markets MRO will slow to improved efficiencies and increased check intervals due to the introduction of new fleets. [Ref: IFC Analyst Forecast in 2016, MRO Market Update & Industry Trends Presented by: Jonathan M. Berger, VP, ICF]
The Internet of Things (IOT) will have a significant impact in reducing costs by making the MRO industry more proactive than reactive. Smart, sensor-based platforms connected to the aircraft, cloud and ground stations will be a catalyst to eliminate unscheduled maintenance. This will be accomplished by joining analytics with an ever increasing number of factors to improve the business decision making process. These “other” factors might include weather and road closures that could potentially slow down a truck delivering needed parts to high-level traffic flow analysis. The real-time inputs from all of these factors will lead to improved algorithms that enhance machined-learned models for MRO.
An integral part of a successful application of the IOT is handling of big data. For example, one of the critical business aspects of MRO is the aftermarket pricing of parts. A precise history of an aircraft and its components would help in determining the valuation of parts. The IOT will help to enable this history by providing the as-delivered and as-maintained data. Of course, all of these benefits require the capability to analyze large amounts of data quickly and efficiently from the aircraft engines, control systems and frame. This is why some have referred to data as the new currency of IoT and analytics.
Originally appeared in Reliability-Maintainability-Supportability (RMS) Journal, Jun 2018