Maximizing fuel efficiency is as important for airlines as ever. Fuel represents a significant portion of an air carrier’s operating costs but the spotlight now is also on cutting consumption due to environmental pressures.
Commercial aviation contributes about 2% of global carbon emissions, according to the International Air Transport Association (IATA). Beginning in 2020 there is a target to introduce a cap on emissions in the industry and by 2050, the goal is to reduce emissions by 50%.
The concept of better fuel consumption has positive implications across an airline, for instance leading to greater operational efficiencies and better overall reliability for the carrier. The technology inherent in modern aircraft is conducive to better consumption; the introduction of composite materials, more efficient engine designs and aerodynamic airframes are among the characteristics of new generation (or ‘new-gen’) aircraft that contribute. As outgoing, classic aircraft models retire to make way for new-gen aircraft, an organic increase in overall efficiency is occurring for operators. This is before considering the benefits of connectivity and big data, due to the vast amount of sensor-supplied information that these aircraft can transmit.
Fuel efficiencies can be gained by new technology and while these will not have the same saving as more efficient routes or climb profiles, they can contribute appreciable savings. “For example, new generation aircraft will provide sensors for the potable water tank: they have no interest for traditional flight data management (FDM), which is focused on safety, but these have a clear benefit for fuel efficiency,” Alexandre Feray, CEO and founder at Openairlines says. “Putting the right amount of potable water in an aircraft based on the route is a way to optimize its weight and efficiency.”
To meet the global targets in place, more needs to be done. Not all aircraft flying today are new technology, and aside from intelligent aircraft systems, an operator can digitize operations and create fuel savings that have a positive impact on bottom lines and the environment.
Several factors affect an aircraft’s fuel consumption in flight; taxi time, flight path and altitude, head/tail wind and weight are a few. Some of these are weather dependent, so better weather information can create benefits, as can stringent route management.
Management of fixed and variable costs is crucial. Variable costs are the most complex to predict, normalize and manage. An example of a fixed cost could be crew salaries, or maintenance power-by-the-hour (PbH) contracts. Meanwhile, the lead example of variable cost is fuel. This can vary by aircraft type, airport and fuel provider available at each location.
The two broad categories relating to fuel management, cost and operational, each comes with its own set of variables. Software products that focus on each approach exist. These products not only digests the big data offered by aircraft, analyze and compare with historical data and provide operators with the tools required to determine fuel initiatives. “For instance, a short haul carrier will find more benefits in the climb/descent phases because they are more frequent, while a long-haul carrier will want to better optimize their trajectory and cruise profiles because of their duration,” says Feray.
Ultimately, software must provide flight and operational crew with digestible information that consider industry best practices, safety, and intelligent information to enable efficient decision making.
“Considering fuel consumption for an airline relates not only to all phases of flights (taxi, climb, cruise, and descent) but also activities that are not directly related to flight operations such as dispatch, maintenance, ground activity, commercial activity and even legal aspects such as European Union Emissions Trading System (EU ETS) or CORSIA (Carbon Offsetting and Reduction Scheme for International Aviation),” explains Feray. “Factor in the threat of climate change on the industry, fuel efficiency at an airline must be a team effort where every department can contribute to a safe and efficient fuel culture.”
In order to fully utilize big data for this effort, communication between operations and flight crew is key. This is achieved primarily via an electronic flight bag (EFB). Software that is digesting data for fuel decision making should therefore interface with this via applications.
Data can originate from many different sources – and is also shared between several departments and third party providers within an airline (all often using different systems) complicates data sharing. “At the heart of the problem when instilling fuel efficient practices is data,” agrees Michael Charalambous VP commercial operations at FuelPlus Group. Data is fragmented and complex as it comes from different sources. “First an airline needs data to flow in – structured and unstructured and manual. To allow automation and data accuracy, software needs to cleanse data, check it for accuracy, and present the airline the best data to use,” adds Charalambous.
Software therefore needs to be able to do this for a variety of different data formats, and essentially unify it into a single format that can be interpreted by the end user whether it is flight crew, operations, accounting or third-party providers.
Transavia France is example of an airline focused on implementing operational processes that improve fuel efficiency. Part of the Air France-KLM group, it operates a fleet of 737-800 aircraft. The single aircraft fleet makes roll-out of new operating procedures easier.
In 2016 Transavia was the launch customer for Safety Line’s OptiClimb software. Its primary focus is achieving better fuel consumption in the ‘climb’ phase of flight, which is analyzed and achieved via the program. This is the area Transavia achieves its greatest savings. Combined with five industry best practices developed from data analysis with Openairlines, further savings are also achieved.
Those five best practices include: engine-out taxi-in, NADP (noise abatement departure procedure), CDA (constant descent approach); minimum extra fuel; and the use, where possible, of idle reverse. These are implemented when air traffic control (ATC) allows.
Transavia has been able to refine its fuel initiatives, due to the further analysis of its operational data. While 2016 commenced trials, in 2018 the operator gained approval to integrate its climb efficiency program as part of standard operational procedure (SOP).
Transavia also explored more frequent engine washes, as clean engines operate more efficiently. The logistics surrounding carrying out engine washes across an entire fleet every six weeks proves difficult. “[It] is cost prohibitive, and operationally complex to move aircraft across airports in between movements,” explains Emmanuel Cachia, head of flight operations at Transavia France.
Going forward, Transavia aims to implement its best practices via its EFB, so that pilots can assess the right moment to apply each practice before the flight. “By determining this we can assess the right time to feed data to the pilot,” says Cachia.
On average Cachia estimates that Transavia saves up to 120Kg of fuel per flight, depending on ATC constraints. The application rate is about 60% due to this. When adopted,about 75kg is related to savings in the climb, while the remaining 45kg is attributed to the implementation of fuel practices. During summer season the average saving was about 90kg.
OptiFlight is developed from Safety Line’s inaugural OptiClimb module. Rolled out at Transavia in 2016, OptiClimb’s primary purpose was to enable airlines to determine, based on the individual characteristics of each aircraft within its fleet, the best climb profile for a flight depending on the conditions of the day and the weight of each aircraft.
A picture of the aircraft, and its performance is built from historical data provided by the airline and analyzed by OptiClimb. It has evolved to become OptiFlight, a software suite that builds on additional profiles in a single flight, extending to cruise profile for instance. “OptiFlight’s recommendations allow pilots to perform a more efficient climb and descent, and use more efficient speeds, direct routes and flight levels based on historical data,” explains Francois Chazelle, COO at Safety Line.
“We initially started with OptiClimb as climb offers the most potential for fuel,” he continues. “It is also the most complex phase, with many parameters changing at the same time, which is why we approach it with machine learning performance models for each tail.” OptiFlight machine learning performance models are based on 25 flight parameters related to aircraft performance, stress, temperature, and angle of attack among others. Data is collated every second of flight. “The models allow to predict the fuel that will be consumed for different speed and altitude combinations among up to tens of thousands of scenarios taking into account forecasted winds and temperatures on each calculated trajectory,” adds Chazelle.
OptiFlight uses a combination of machine learning performance models for each tail number and a 4D weather forecast to optimize all flight phases thanks to customised recommendations for each flight. OptiFlight modules include OptiClimb (customised climb speeds); OptiSpeed (mach adjustments for time/fuel trade-offs); OptiDirect (inflight shortcuts based on historical tracks); OptiLevel (flight level recommendations) and OptiDescent (descent profile and related speeds).
Today, four airlines use OptiFlight including Transavia France, Transavia Netherlands, Air Austral and Sky Airline. Trials have been launched with a further 30 airlines. According to Chazelle, partner airlines include domestic, long haul, LCC and legacy, narrowbody and widebody, passenger and cargo operators. The software must be customizable for a wealth of mission types and lengths.
“Pilots receive customized flight optimization recommendations for each flight on their iPads, either as additional information in their Electronic Flight Folder, or through the eWAS weather application,” explains Chazelle. “eWAS is popular with pilots, as weather considerations are an integral part of the flight.”
While OptiClimb provides operators with fuel savings of 5-6%, savings in other flight phases are more opportunistic. For instance, in the cruise phase a saving of 1% is expected. “These are more dependent on obtaining clearances from ATC,” says Chazelle.
For new customers the first step is to build the machine learning performance models for each tail, using historical flight data. Safety Line suggests providing one year of historical data to account for seasonal variations. “This can be achieved for a fleet within a couple of weeks. We will also need to receive all OFPs and integrate with whichever distribution channels the airline is using to send briefings to their pilots.
“A one- to two-month trial can be performed across a fleet, in order to achieve enough flights to be able to statistically validate the level of savings the airline can achieve,” adds Chazelle. Aircraft data is either fed to OptiFlight via quick access recorder (QAR) data extracted manually, or via connectivity depending on operator setup. If an aircraft interface device (AID) is present for instance, weight and position data can auto-update. The machine learning performance models are updated as new flight data becomes available.
OptiFlight recommendations are issued to the pilot as part of the briefing package and can also be illustrated on their iPad screens in the eWAS weather application. “Wind and temperature forecasts are usually quite accurate over a period of 12 hours,” explains Chazelle. “Only on longer flights will there be a benefit to update the forecasts in the final phase.”
SkyBreathe is a fuel efficiency software, developed by Openairlines. It is designed to digest the data generated during flight, condense into reports that enable operators and to determine best fuel saving practices. “For a large airline, that represents hundreds of gigabytes, sometimes even terabytes each day,” says Feray of Openairlines. “The most important data we use are from Flight Data Recorders (FDR) and Flight Plans (OFP). We may also integrate ACARS messages, loadsheets with weight and balance information or fuel prices.
“Combined with weather data, SkyBreathe can therefore compute the savings of each flight by taking into account the exact flight conditions and performance models,” explains Feray.
The software records 100+ parameters (including engine and weather) on each second of flight to reconstitute the flight profile. Once processed, it can generate more than a thousand KPIs and 4D views that can be analyzed by route, airport, aircraft or weather.
This fuel efficiency solution enables airlines to reduce fuel consumption and CO2 emissions from 2 to 5%, and an ROI within a couple of months. According to Feray, new customers to Openairlines must provide a minimum of one-month of historical data to establish machine learning algorithms. “Often we process a full year or more,” says Feray.
SkyBreathe comprises an a rtificial intelligence (AI) engine with algorithms that automatically analyses flight data and assesses operational efficiency improvements. “The solution integrates multiple sources of data in a single database and computes achieved and potential savings for the flight conditions,” explains Feray. “These include weather, flight path, air traffic control, and payload to produce fuel metrics.”
Pilots can visualise flights in 3D and get an individual debrief on each fuel-saving best practice via a mobile app called MyFuelCoach which can be implemented. “The recommendations may include the preparation of the aircraft – we calculate the impact of a clean engine for example,” continues Feray. “It may also include the preparation of the flight: choice of routes depending on the weather and traffic, or congestion based on time of day, etc. Last it may concern the execution of the flight, for instance it can advocate where a continuous descent is possible, the use or not of the thrust reversers, the configuration of the wings, or shut-down an engine during taxi,” elaborates Feray.
Norwegian is one customer of SkyBreathe. The airline has recently disclosed that by implementing measures such as single-engine taxi to gate, green approaches using a steady glide path from cruise altitude to landing and using the brakes instead of reverse thrust after landing, it has saved 3,700 tonnes of fuel per year, and reduced CO2 emission by 11,600 tonnes per month.
Airlines utilizing fuel efficiency software and initiatives not only see consumption and emission improvements but better operational performance. “This includes on-time performance (OTP) and improved ground activity,” elaborates Feray.
One add-on module to SkyBreathe is Advanced Trajectory, designed to enhance route efficiencies. “The most efficient route is one of the fuel-saving best practices that has most potential,” says Feray. “Flight planning software has traditionally been good at doing that, but their computations are based on a theoretical assumption of aircraft performance, without any other constraints than those that are in the procedures.”
Feray goes on to explain that applications using big data add a real-world observation, built on millions of real-life flights. “These flights and their routes might experience delays, holdings or vertical restrictions that are not in the procedures, or on the contrary they might benefit from frequent directs or visual approaches. It provides a map that understands historical and real-time traffic on each route,” he adds.
Cost Management and Efficiencies
Before big data realised opportunities for airlines to learn more about aircraft, operators had a rather un-dynamic and rigid view of operating costs. When one considers the wealth of factors that influence fuel burn during a flight, it is clear that because the slightest thing can change this figure, there is no one ‘cost per hour’ to attribute to an aircraft type.
There is plenty of opportunity for error considering the complexity of an airline’s operations. Errors can impact margin and therefore indirectly affect fuel efficiency.
FuelPlus assists airlines to increase efficiency and achieve compliance. The software focuses on automating cost management and reducing the potential for human error (that is, via manual input of costs onto an invoicing system for example).
“While airlines are investing billions in new aircraft to ensure they are able to reduce the impact of fuel on the environment and bottom line, it doesn’t automatically mean that it is maximising the savings potential that they provide,” says Charalambous of FuelPlus Group. “Efficient fuel cost management processes can therefore enhance these savings.”
Charalambous sees a repetition in the factors motivating airlines to investigate fuel management solutions. “Imagine an airline turning over ~$2B a year,” he says. “If 5% of this is profit that equates to roughly $100M, meaning $1.9B is costs. It is generally acknowledged that fuel is 30% of an airline’s cost. For this scenario that works out at $570M. On the face of it, a small error in fuel management, say 1-3%, seems minor but if you look at the figures it’s a significant portion of the profit,” continues Charalambous. Indeed, 1-3% error suggests $6M -18M, which can eat into almost 20% of the airline’s profit margin.
There is certainly plenty of opportunity for error to occur in a fuel management programme. For the airline with a $2B annual turnover, Charalambous adds that annually, the number of fuelling events an airline is invoiced for is significant. “An airline of this size can have 300k flights to 75 locations,” he continues. “It’ll require a supplier at each airport and might take on fuel at each turnaround. That means about 300K fuelling events and invoice lines.” Inadequate fuel management processes can lead to errors.
This is before one explores the logistics of an operator’s daily movements, across an entire fleet of aircraft. Charamlambous at FuelPlus explains that for each flight an airline needs to take into consideration several areas including planning fuel uplift; tender and negotiations with suppliers (whereby each supplier will have a different bid format) and payment. Different tender or bid formats can complicate the process to reconcile information in-house. The operator’s accounting department will need to match for each flight the specific invoice line with the amount uplifted, usually via a fuel ticket. According to Charalambous, this process done manually leads to up to 10% pricing errors.
The largest operating costs for an airline, in addition to fuel, is airport, navigation and ground operation fees. These are inherently difficult to monitor, because unlike fixed costs like pilot salaries, these will change depending on aircraft type, destination, handler or time of day.
The FuelPlus platform enables airlines to automate fuel, airport, navigation and ground operations costs by consolidating the fuel, flight and cost data into one centralised database. All teams (fuel planning, operations, procurement and finance/accounting) can access and manage the data, simplifying data sharing problems.
Automation is enabled in key areas, for instance planning processes, procurement, flight data capture and invoice verification tender. FuelPlus provides analytics, alerts and insights automatically via role-based dashboards and reports, allowing departments to understand all aspects of the fuel operation. “For instance, it can provide smart alerts,” explains Charalambous. “These can be location price alerts, triggered by contract parameters, or late tickets against SLA for invoices.”
Smart alerts utilize statistical data and machine learning/AI to set automated alerts on location prices and volumes. Rather than have to set a manual price or volume alert for each of the sample 75 locations, fuel management software that utilizes big data can notify if there is an anomaly in the price based on historical behaviours of that location.
“Airlines can therefore explore all the dimensions surrounding fuel costs and can add data from previously unconnected systems to see if there is any causality relationship between surging prices.”
Benefits of FuelPlus include faster and easier fuel planning; a transparent procurement process; automatic checking of invoices and fights against contract data; auto-checking of invoices against tickets, actual flight data and contracts, and better operational data for tankering, planning and forecasting. It also enables a more efficient procurement process, because it normalizes bids from suppliers and generates a single format contract that is easier to reconcile. “FuelPlus provides airlines the ability to use actual historical data on each location to understand volumes, station average prices, volume uplifts by period not just standard schedule sheet – more accurate data leads to better contract negation, capital allocation and inventory management,” adds Charalambous.
It also enables greater education when formulating operational decisions. “The provision of daily average location prices and tankering exceptions enables flight planning systems to make full use of tankering procedures,” continues Charalambous. “A tankering recommendation report supports flight crew to make use of price differences.”
Last, FuelPlus can interface with operational and EFB software so that the two elements can exchange information. “Most customers use the data to create strategies and make business decisions,” says Charalambous. “It can actually go both ways – depending on the airline they might choose to use the data available in the system by exporting it or use an analytics platform, like FuelPlus Analytics, to connect data from various sources.”
With the recent focus on reducing carbon emissions, in addition to creating savings, fuel software is deploying add-ons that help airlines comply with the industry mission to become greener. “FuelPlus has an Emissions module that safeguards the correct application of both EU ETS and CORSIA methodologies and provides automated checks, which means correct emissions monitoring is now provided,” explains Charalambous. “Tolerances are established in the FuelPlus Emissions module to help airlines cleanse data and highlight inconsistencies. Examples include tolerances for fuel burn-off, consumption, aircraft turnaround and taxi time.”
“Climate change is the biggest challenge of our time. Big data, artificial intelligence and machine learning opens new horizons in the aviation industry to play its part in a global effort to improve emissions,” Feray stresses. “Exploring advanced trajectory analysis or aircraft performance monitoring, a connected EFB app for in-flight real-time recommendations are some of the next steps in the industry,” he says. “The focus is now to develop a safe and efficient ATM system that takes care of the environment.”