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MRO and Big Data
Author: Benjamin Walther, CEO, and Marc Borkowsky, Business Analyst, aviationexpertsSubscribe
MRO and Big Data
Adding value to your bottom line, say Benjamin Walther, CEO, and Marc Borkowsky, Business Analyst, at aviationexperts, can be achieved through predictive maintenance
Predicting the future
To begin with let us travel to Southern California and take a look at a story worth talking about. Have you ever seen the movie ‘Minority Report’, in which criminals are being arrested before they actually commit a crime? While the movie calls it ‘Precrime’, real world equivalent system is called ‘PredPol’ and stands for predictive policing. As of today, Los Angeles is no longer known only for the rich and the famous including their Hollywood movies. PredPol is a pilot program between the Los Angeles Police Department (LAPD) and the University of California. With a mathematical algorithm initially used to predict earthquake aftershocks, PredPol is able to predict areas with elevated crime risks. But before we go on and approach the core of these thoughts, we need to clarify what we mean when we talk about big data and predictive analytics.
Data: collecting it and applying it
Big data describes data that is too large, complex, and dynamic for any conventional data tool to capture, store, manage, and analyze. The masses of data available today are further characterized by reference to the three V’s: volume, velocity, and variety. While volume describes the unbelievably huge amounts of data generated, velocity and variety stand for the increasing rate at which data in highly diversified formats is flowing. To cut a long story short: we have access to huge amounts of data in all kinds of formats that is too massive to handle.
Predictive analytics on the other hand can be seen as the discipline in which sophisticated software is used to analyze huge data sets. The results cannot be denied: new insights can be generated by identifying and analyzing hidden patterns just as in the case of PredPol. Huge data sets from the last 80 years, including 13 million arrests let the company identify previously unseen patterns from which to extract new and apposite insights; LAPD officers are provided with mission maps that show boxes of 500 square feet in which crimes are most likely to occur within the next twelve hours. Having tested the new system in the L.A. Foothill division, statistics revealed a 12% decline in property crime as well as a decrease in burglary by 26%. In short, predictive analytics enables users to forecast trends and developments more precisely, cloud-based, and in (near) real-time.
Who in the aviation industry is already using it?
There are already many great examples out there, but Etihad may be one of the airlines to currently use big data to its fullest and broadest known advantage. By analyzing the massive amount of passenger-related data the airline generates throughout its many processes, Etihad is able to add new destinations which suit their target customers while delivering the best available seat/price combination. In addition, the airline uses an analytics tool which is able to analyze the vast amount of data derived from aircraft sensors. Now Etihad can monitor its complete fleet in real-time, manage and predict maintenance events, reduce fuel consumption, and shorten turn-around times at airports.
These proactive steps will help the airline to provide much greater reliability for their global operations, resulting in fewer delays and disruptions. To even further increase the passenger experience, mobile solutions are used by crew members who are now able to access any passenger data ‘on-the-fly’ in order to be more responsive towards individual customer needs. Only time will tell how great the advantages for Etihad will really be in the long run; yet we are confident that great success stories from airlines using big data will continue to spread across the sector.
MRO applications, preventative maintenance
As well as in these operational areas, big data also provides huge opportunities for companies offering maintenance, repair, and overhaul services for aircraft. In times of tight flight schedules, lowest possible ground times, disruption-sensitive passengers, and strong consumer rights (e.g. EU regulations), carriers are more than ever in need of MRO services that are both cost and time efficient. Every unforeseen maintenance event means that a carrier loses real dollars… and fast. Hence, a few aerospace manufacturers have already come up with the idea of using the big data technology to analyze available data and get more insights as to when exactly a part or the whole aircraft will need maintenance or repairs.
According to the technology company Hewlett Packard, a Boeing 737 creates around 20 terabytes of information per engine every hour. With an average flight time of 16 hours a day and 365 days in a year, a twin-engine Boeing 737 creates an annual 233,600 terabytes only with its engines. Multiply this by all the small and large aircraft currently flying around the world and… well this really is big data.
Yet, despite the massive amount of data potentially available for analysis to predict real maintenance needs, today’s aviation industry still uses fixed maintenance schedules which are, in turn, being implemented into regular flight schedules. MRO service providers organize their operations – including the planning of staff, hangars, and spare parts, among other things – based on these rigid maintenance schedules.
Consequences of not planning ahead
Now, the practice of preventive maintenance just described above, which is commonly used throughout the industry, confronts us with several important issues. First, in case of unforeseen maintenance needs MRO providers are challenged due to the lack of available hangar space and technicians on duty. Second, MRO providers are either understocked, which entails delays in case a needed part is not in stock, or they are overstocked with parts that may not be needed resulting in unnecessary tying up of capital.
The carrier, in return, is faced with an inoperable aircraft, a case for which it was not able to make alternative plans. This means a major disruption of the operational flight schedule leading to stranded passengers who are entitled to costly rebooking, accommodation, vouchers, and applicable compensation. Even worse, and more enduring, is the resulting reputational damage to the airline and its image with regards to punctuality, reliability, and safety.
Even though these might be the consequences of a worst-case scenario, even the various minor irregularities arising due to unforeseen maintenance needs may well have far-ranging consequences. Most of today’s carriers try to minimize aircraft on ground times, which consequently results in tight flight schedules that are highly vulnerable to even small irregularities. Due to this vulnerability, even a small delay might expand to impact interdependent flights within a schedule and thus create some kind of snowball effect, possibly spreading over a major part of the complete schedule. For example, what about a soon-to-be breaking oven? Might this minor irregularity have the potential to disrupt the flight schedule? Again, the timely anticipation of even the smallest irregularity might help to counteract unnecessary effects which could have resulted in major disruptions.
But so much for possible impacts and consequences of unscheduled maintenance needs; again the question remains, what if these unforeseen maintenance events could be predicted and thus be accounted for beforehand? For one, more accurate predictions could lead to an optimization of two major cost drivers for MRO service providers: material and labor. By predicting previously unknown maintenance events, the planning ability, flexibility, and utilization of the staff can be increased while always having the exact number of required technicians on duty; in essence the business is able to optimize the marginal cost of labor.
With regards to spare parts and their storage, having a more accurate knowledge of maintenance needs allows MRO service providers to reduce overstocks because they know which parts will be needed, thus increasing parts availability; not needed parts only represent unnecessary capital tied up, which can be abolished. In addition, reducing overstocks means that less storage facilities are needed; so let us call this approach ‘lean inventories’.
Spinning off all these positive effects to the client-side, carriers are better able to keep their aircraft in the air as planned, resulting in reduced unscheduled ground-times and delays. This inevitably leads to a more reliable and stable flight schedule with fewer disruptions and thus creates a direct effect on the airline’s profitability.
Hence, by adapting predictive maintenance, MRO service providers are able to add real value to their bottom line through more efficient and effective operations. While lean inventory management, as we have called it above, increases cash-flow through the reduction of unnecessary capital tie up, additional maintenance capacity for prospective clients could be made available through a more accurate planning process, affecting the revenue side of the business.
Now these thoughts are only the tip of the iceberg; many more advantages and much more promise are hidden in the vast amount of data available to the aviation industry. Today’s decision-makers have to explore if and how Big Data and predictive analytics are able to deliver insights through which efficiencies, no matter in what form, can be improved. Engaging in an open dialogue to explore the possibilities that new technologies have to offer might be a great starting point.
In order to bring these thoughts down to numbers, let us play through the following scenario of hypothetical unforeseen maintenance events. On a flight from Berlin to San Francisco, the B747 experiences an engine failure due to a breakdown of a wearing part which forces the crew to a technical stop in New York. Having analyzed the affected engine, it becomes clear that it needs to be replaced completely. As a consequence, the technical stop affects around 450 passengers who will be arriving late at their destination (SFO). While current EU-regulation adjudges 600€ compensation to each passenger to be paid by the airline, additional costs are incurred for alternative transportation and applicable accommodation. In addition, the airline is faced with a costly procurement of an engine replacement including the necessity to repair the aircraft away from its technical base, which could all add up to an aircraft downtime of well over 24 hours. This scenario definitely costs a lot of money.
Here is another scenario to consider. During standard safety-check procedures just before the boarding of a flight from Izmir to Zurich, the captain identifies a malfunction in one of the engines due to the breakdown of a wearing part. As a result, the inoperative aircraft incurs a delay, which also affects all subsequent flights within its current rotation. The aftermath is clear: decreased utilization of the aircraft leading to revenue losses, angry passengers, disruption of the operational flight schedule and additional costs for applicable compensation, rebooking, and so forth.
Readers will get the picture and might already have figured out the hint we just gave a couple lines ago. By forecasting unscheduled maintenance events, airlines would be able to reduce to a minimum reserves of aircraft idling around on the apron; hence these reserved capacities could be made available for utilization in order to raise additional revenues.
Benjamin Walther is one of two CEOs of aviationexperts. As a recognized specialist for aviation IT and operations, he has delivered projects to airlines and airports around the globe, being an expert for the implementation and execution of long-term strategies. With his deep expertise, international project delivery experience, and his leadership personality, Benjamin exemplifies aviationexperts’ commitment to change the client’s business. Benjamin graduated in Business Information Systems from University of Applied Sciences in Frankfurt.
aviationexperts is an international technology and consulting company in the aviation industry. Since establishment in 2009, it has advised 16 customers in 10 countries. With a team of almost 20 consultants, the company generates annual revenues beyond 1 million Euros at sustainable profitability.
Top management has more than 15 years’ experience in managing airlines and airports around the globe. In addition, aviationexperts has a Supervisory Board of industry experienced top-level managers who contribute their expertise and business networks and ensure a high quality of service with the company’s basic principle of service delivery