IT-ASSISTED OPTIMISATION OF FUEL CONSUMPTION IN AIR TRANSPORT

Aviation continues to be an essential means of transport for passengers and cargo. In recent years, the COVID-19 pandemic led to a collapse. In 2022 Europe was back up to around 85% of 2019 levels (EASA, 2022). In 2021 van der Sman et al. predicted an recovery to 2019 levels in 2024 (van der Sman et al., 2021). However, fuel savings and emissions reduction have become increasingly important in recent years. As part of a PhD thesis, possibilities for reducing fuel consumption by reducing the final reserve fuel were investigated. A smaller amount of tanked fuel required leads to a reduction in the transported (fuel) weight and, thus, a reduction in overall fuel consumption. This is because fuel consumption for a given route depends, among other factors, on the aircraft's weight. The more an aircraft weighs, the higher the fuel consumption. To keep fuel consumption as low as possible, carrying only the minimum weight required for the route in question is the most economical. Carrying more or even unnecessary weight increases the amount of fuel required and consumed in flight. The overarching research aims to explore


INTRODUCTION
In 2015, around 3.5 billion passengers already used air transport for business and tourism purposes. Despite a downturn in 2020 and 2021, aviation is expected to recover to pre-pandemic levels. The high aviation traffic volume is associated with an enormous demand for aviation fuel and associated high emissions. Lee et al. provide an overview of CO2 and other related emissions and impacts of aviation on the climate (Lee et al., 2009), likewise Fleming and Ziegler (Fleming and Ziegler) and Filippone (Filippone, 2008) -to name just a few examples.
Over the past 30 years, damages resulting from climaterelated weather events increased by a factor of twenty. In 2017 the weather-related damages amounted to $ 330 billion 2017, making it the most costly year on record (van der Sman et al., 2021). Some observed effects of climate change, which also affect the aviation sector (van der Sman et al., 2021), are Temperature changes, changes in precipitation and humidity, different wind patterns, different storm patterns, and sea level rise. This is an increase of around 6.4 % compared to 2014 (ICAO, 2016).
For 2037, an IATA forecast predicts the number of air travellers reaching 8.2 billion (IATA, 2018). The industry is facing significant challenges at the same time. Emissions from aviation, domestically and internationally, account for about 2% of total global CO2 emissions (ICAO, 2014). The UK Civil Aviation Authority's Airspace Change Masterplan states that "without significant changes to the system, increased congestion, vectoring and arrival holding will lead to a further degradation in environmental efficiency as traffic levels grow, with average per flight CO2 emissions expected to rise by between 8% and 12% by 2030 compared to current levels" (Beevor and Alexander, 2022).
Reducing the effects of global warming due to emissions has become a goal. As a result, reducing emissions has become an important issue. Commercial aviation has already developed and implemented many techniques to reduce fuel consumption for economy and efficiency. On the operator side, these are primarily operational improvements, such as reducing the weight of onboard equipment or using a fixed ground power supply instead of the aircraft's auxiliary power unit on the ground. Airlines are searching for fuel-efficient routes or flight profiles most of the time. Airlines, airports and air navigation service providers take measures to reduce noise and pollution in their daily operations (IATA, 2019a). Effects on new aircraft generations introduced in recent years can be seen in Table 1 by IATA (IATA, 2019b).

SAFETY MANAGEMENT
Rules and regulations in aviation are drawn up for safety. Figure 1 (Shappell and Wiegmann, 2000) illustrates how the Swiss Cheese model helps to understand the interplay of different factors in accident causation. Several layers of defence are built into the aviation system to protect against variations, e.g. in human performance or decision-making, at all levels. But each layer typically has vulnerabilities, represented by the holes in the slices of "Swiss cheese" (ICAO, 2018).
Regulations, training and technology are some barriers (or slices) to preventing accidents. Safety management seeks to proactively mitigate safety risks before they result in aviation accidents and incidents (ICAO, 2018).
Figure 1: "Swiss cheese" model of human error causation Safety management is one of the pillars to enable aviation safety and is subject to change and development. Namely, the performance-based approach to safety offers improvements as it focuses on achieving the desired outcome and not just on whether or not the regulation is complied with (ICAO, 2018). However, the theoretically possible level of safety is not always achieved. Scott A. Snook's theory, see Figure 2 (ICAO, 2018), is used to understand how the performance of a system deviates from its original design.

Figure 2: Concept of practical drift
The drift is a consequence of daily practice and is referred to as practical drift. Audits, observations and safety performance indicator (SPI) monitoring, as safety assurance activities, can help uncover activities that practically drift (ICAO, 2018). As Figure 3 (ICAO, 2018) shows, aviation is moving within a field of tension. Too little action in safety can lead to accidents, while too much can lead to financial bankruptcy. The relationship between the costs of a safety measure and the benefits can be examined, for example, with the "Total Judgement-value" method (Dietrich, 2016).
Here, it can be determined how the costs are in relation to the increase in safety for the respective reference group.
Due to changes in Regulation (EU) No. 965/2012, which has been applied since the fall of 2022, there was an adjustment in the fuel requirements. These were previously regulated in CAT.OP.MPA.150, among others, will be referred to in CAT.OP in the future.MPA.180 and the following sections (EASA, 2020b). Operators demonstrating specific capabilities can use a basic scheme with variations or an individual fuel scheme.

Figure 3: Concept of a safety space
This is intended for operators who can demonstrate a defined safety level, thus reflecting the move towards performance-based regulations (EASA, 2020b). Data supporting the intended deviation is required to implement the individual fuel scheme. The Annex to Opinion No. 02/2020 already contains preliminary information on the draft Acceptable Means of Compliance (AMC) and Guidance Manual (GM) and information to be considered for the performance-based deviation. A non-exhaustive list of safety performance indicators (SPI) that can be used to measure safety performance are: • flights with 100 % consumption of the contingency fuel; • flights with a percentage consumption of the contingency fuel (e.g. 85 %), as agreed by the operator and the competent authority; • difference between planned and actual trip fuel; • landings with less than the final reserve fuel (FRF) remaining; • flights landing with less than minutes of fuel remaining (e.g. 45 minutes), as agreed by the operator and the competent authority; declarations; • in-flight replanning to the planned destination due to fuel shortage, including committing to land at the destination by cancelling the planned destination alternate; • diversion to an en-route alternate (ERA) aerodrome to protect the FRF; • diversion to the destination alternate aerodrome; and • any other indicator with the potential to demonstrate the suitability or unsuitability of the alternate aerodrome and fuel planning policy (EASA, 2020a).
As can be seen from these indicators, airlines wishing to have an individual fuel scheme approved by a competent authority are required to gather a significant amount of data and information on fuel consumption. The collection, monitoring and storage of these indicators is a challenge An example of a practical implementation follows below.

FUEL REDUCTION OPTIONS
Airbus has recently launched an initiative regarding sustainability, which can be found on its Worldwide Instructor News homepage (Airbus S.A.S., 2023). Part 1 of the series published there deals with flight planning and again emphasises the possibilities of saving fuel by reducing weight.  Table 2 shows the potential savings if the weight for a flight segment is reduced by 100 kg. Assumed were a loading of 80 per cent and a maximum range sector.
This paper focus researching and evaluating how to reduce the fuel carried by aircraft and, therefore, the total fuel requirement for a given flight under consideration of the necessary IT Data for the performance-based approach. This research aims to demonstrate, based on today's regulations in the field of aircraft certification and operation, that such a high level of safety has been achieved that it is possible, using a performance-based approach, to define a set of measures and circumstances that make it possible to reduce some of the fuel carried, and thus the weight and resulting emissions, almost immediately. Therefore, tracking, recording and evaluating vast amounts of Information is required -mainly to fulfil safety performance indicators.
The potential therein will be highlighted below using examples. The planning for two flights is adjusted so fuel is planned for five minutes less flight time. This is done using current flight, weather and aircraft data. Two flights are considered to highlight the potential for fuel savings: Hong Kong to Cincinnati and Hong Kong to Leipzig. Figure 4 and Figure 5 show these flights, planned with actual data and information as if they were carried out -but were not carried out. Table 3 and Table 4 present an excerpt from the operational flight plan, fuel planning, and mass and loading. Table 3 shows the comparison of fuel planning for a flight from Hong Kong to Leipzig.

Figure 4: Flight information Hong Kong -Leipzig
Since the current approved planning is used, a value of 5 minutes of extra fuel was included as additional fuel for comparison. The alternate and final reserve values shown in Table 3 do not correspond to those that would result from an actual reduction. The 700 kg / 5 minutes in the right column only affects trip and contingency fuel, but not alternate and final reserve fuel. With an absolute fuel reduction, these values would also be lower, leading to a more significant reduction in trip and contingency fuel. Therefore, the resulting delta, in this case, an additional consumption of 257 kg, is lower than an actual saving in the reduction case. But the trend and thus a rough figure for evaluation is evident. The average additional consumption for this route is 21.34 kg/flight hour, i.e. this would be the savings potential.   The two flights examined above result in approximately 1 000 kg difference at the take-off. Figure 5 shows route optimisation options. These are presented to the crew during the planning process. As can be seen, the route already contains potential for shortcuts. These possibilities are statistically recorded and are considered in flight planning -by providing them as information to the crew in the IT application.

DATA COLLECTION -REPORTING SYSTEM
One significant change within the European airline operational rules through Regulation (EU) 2021/1296 was the introduction of fuel schemes. Operators who can demonstrate an equivalent level of safety may be approved to use a basic with variations or individual fuel scheme, as regulated in AMC1 CAT.OP.MPA.180. This reflects the move towards performance-based regulations (EASA, 2020b). Data supporting the intended application is required to support the implementation of such advanced fuel schemes. An Annex to Opinion No. 02/2020 already contained preliminary information on AMC and GM to be considered for the performance-based approach. GM2 CAT.OP.MPA.180 now shows a non-exhaustive list of safety performance indicators (SPI) that can be used to measure safety performance.
To shed light on the number of data and the challenges, examine real flight data of a worldwide operating European airline where chosen. Therefore, data from a roughly 5-year (4 years and ten months) period, from March 2016 to the end of December 2020, of a cargo airline was provided. The utilized aircraft are Boeing B777-200 in a freighter version. It has a maximum takeoff mass of around 347 800 kg, a maximum landing mass of 260 800 kg and a dry operating weight of around 141 600 kg. That explains a maximum resultant revenue payload capability of roughly 103 metric tons. Maximum fuel capacity for that version ~ 144 000 kg.
The operated network contains large airports, together with regional airports. The network destinations are a mix of short, medium and long-haul flights.
The data was provided in different reports. The following standard components of data analysis were done: -Pre-processing -accounting for outliers, missing values and smoothing data, -Summary -calculating basic statistics to describe the general position, scale and shape of the data, -Visualisation -plotting data to identify patterns and trends.
The data were analysed to obtain information for other evaluation purposes-two ways of analysing fuel information. In the first step, available and valuable data and information from the airline reporting system are evaluated, together with background information on limitations. In the second step, a detailed evaluation is done for some unique routings based on information gathered in the first step. The evaluation was conducted with the help of Excel and MATLAB. For advantages and possibilities of MATLAB, compare, e.g. Saivenkatesh et al. (Saivenkatesh et al., 2020).
The evaluation and the consequences are not the focus of this paper, but the focus is on the amount of data and the processing of the information to meet the performance-based approach.  (ICAO, 2015).
As shown above, GM2 CAT.OP.MPA.180 of Regulation (EU) No 965/2012 also contains similar parameters. ICAO Doc 9976 emphasises the special evaluation for respective city pairs. As seen from this SPI list, various information must be collected and stored for each flight. As mentioned, various reports are used for this purpose, two of which are presented by example.
As shown below, a large amount of information and data is simultaneously created, collected and stored during each flight. Filtering the necessary information while making data efficiently available for future flights is a challenge that can only be met with the support of appropriate software.

Fuel Analyzer App Data
The Fuel Analyzer App Data report contains data represented to the flight crews on the electronic flight back (EFB) application for fuel planning information. It is possible to choose a Flight number / City-Pair and get multiple information ( As described above, the Fuel Analyzer App is an application that is available to the crews and obtains the data from a system behind it. This data basis is presented in the next step.

Excerpt of the Fuel Analyzer App Data
During the flight planning, the crew used the collected and provided information, for example, for a flight from Hong Kong to Leipzig. Table 4 contains excerpts of the information; the following list contains the information for the crew. The information in Tables 4 and 5 is cut off  behind the data contained in the original table,   As can be seen, the crew can choose between the similar and the equal conditions.  In total, an 18 by 15 matrix entry is created for each flight analysis. This relates to the connection for a city pair which shows the amount of information. With 20 aircraft flying between 2 and four sectors a day, you can see the large amount of data that is being collected.

Fuel Analyzer App Reference List
In another report, additional information is stored for each flight. The manual evaluation and monitoring of this data, 24 hours a day throughout the year, is no longer possible.
In the meantime, commercial providers offer the possibility of using off-the-shelf software to give crews in the air and dispatchers on the ground the comprehensive possibility of planning and executing flights with a uniform programme. In particular, the possibility of almost immediate communication between the crew on board and the ground crew makes it possible to react to unforeseen events.
The connection between aircraft in-flight and dispatch personnel on the ground becomes increasingly important (SITA, 2023b).
During the coming three years, airlines will continue to drive investments in emerging technologies. The top four priorities remain the same, as airlines focus on data management to enhance their business models and operational efficiencies through technologies such as business intelligence software (74%), data exchange technologies (82%), artificial intelligence (76%), and Radio Frequency Identification (RFID) tracking (80%). Two areas look set for significant growth in the future, despite showing low implementation at the present moment. Airlines have doubled R&D plans for Near Field Communications (57%) and 'augmented/virtual reality tech'(42%) suggesting they have the potential to become areas of focus in years to come (SITA, 2023a).

CONCLUSION
Operational regulations in aviation are adapted to take account of the reliability of aircraft, better avionics and possibilities out of it, and technical developments in-flight monitoring and communication with the crews on board. The collection and processing of large amounts of data, using appropriate IT hardware and software, allow the definition and control of safety performance indicators and move away from prescriptive regulations towards performance-based approaches.
Operators with appropriate safety levels can apply more tailored provisions. This requires the demonstration of the safety level. This is achieved by defining specific safety performance indicators (SPIs), compliance with which is then continuously monitored and evaluated during operation. This requires the collection and evaluation of correspondingly large amounts of data. This is only possible using appropriate IT applications. The example above shows the amount of data that accumulates during flight operations. Recording, processing and saving pose a challenge in this respect.
Implementing the latest technologies for flight planning operations offers advantages. Improved process management, decision-making and profitability are possible through modern IT systems. This can reduce the amount of fuel used, thus reducing emissions and costs. At the same time, flight availability can be increased and regulatory compliance granted.
If the operator makes the necessary effort, he can apply a basic with a variation or individual fuel scheme. This, in turn, enables operational advantages, plus saves fuel and thus emissions.
The use of artificial intelligence is one of the challenges but also one of the options that can help companies meet the numerous regulatory requirements. In some cases, companies are taking the first steps in this area (Travelnews, 2023), but further research is necessary.

AUTHOR BIOGRAPHIES
ANDREAS WALTER was born in Görlitz, Germany and started his career as a cadet in the German Air Force in 1997. As a young officer, he completed his studies in aerospace engineering at the University of the German Armed Forces in Munich. He then served as a technical officer in the German Air Force for seven years, dealing with all technical aspects of aviation. During this time, he studied business administration alongside his job at the FernUniversität in Hagen. After his military career, he moved to the German Civil Aviation Administration. Within the framework of a broad education, he got to know all the facets of aviation and eventually became an air operations inspector. He obtained the authorisation to fly various Airbus aircraft within the scope of commercial aviation, up to the authorisation as an instructor. His experience in supervisory work, his commercial and technical background provided the impetus and motivation to write a thesis in the field of fuel consumption. With the aim of combining his extensive and almost unique technical, organisational and operational experience, he is currently working on his PhD thesis at the Tor Vergata University of Rome and TH Wildau. His e-mail address is: walter.andreas@students.uniroma2.eu.