Ebook: Air Transport and Operations

This paper gives a summary of a thesis project conducted at KLM Royal Dutch Airlines Engineering and Maintenance. The research focuses on redesigning maintenance processes to increase the delivery performance of the A-check from a lean perspective. A theoretical framework is formulated based on the combination of lean thinking, six sigma and the theory of constraints. The A-check maintenance processes are analyzed from the gate (on-blocks) back to the gate (off-blocks). The chain of processes is analyzed with regard to the five lean principles. Through this analysis three improvement areas are identified namely buffer reduction, improved position management and reduction of interference between the (re)arranging process and the engine-run process. The processes are redesigned such that a future state is developed with improved customer value through increased delivery performance. Based on a reduction in waste and increased utilization of the primary constraint the delivery performance of the A-check is estimated to increase with 92%. The future state is designed in two phases namely an immediate solution which requires no significant investments and can be implemented right away and an ultimate solution.

This paper is meant to give guidelines on how to perform supply base rationalization at KLM Engineering & Maintenance. A methodology is written to help KLM Engineering & Maintenance to outsource the management of expendables to first tier suppliers. The desired level of outsourcing is determined by using the essentiality model of expendables. The essentiality of expendables identifies the strategic importance of the activity, which determines the preferred level of outsourcing. Outsourcing the management of expendables will create a leaner supply base. By using the essentiality model it is found that 35% of the expendables can be outsourced using some degree of hierarchical steering, 48% can be outsourcing using market steering and 17% do not need to be outsourced.

In this paper we investigate how the KLM E&M WBBM Unit can improve the accuracy of non-routine tasks man-hours forecasts for the Wide-Body C-checks, per specific check visit and maintenance organization. Following a contingent approach, a database was set-up and three econometric forecasting methods are compared with the judgmental method currently used by the unit: linear regression analysis, artificial neural network and nearest neighbour analysis. Higher accuracy was obtained from the econometric methods when cross-validated, which proves that it is indeed possible to have a model to forecast non-routine maintenance work more accurately than judgmental methods.

Amsterdam Schiphol Airport uses Continuous Descent Approaches during night time operations only, due to reduced runway capacity caused by unpredictable individual aircraft behavior. The Three-Degree Decelerating Approach (TDDA) has been developed to increase predictability and runway capacity by switching the separation task from Air Traffic Control to the pilot on board the aircraft. The research described in this paper identifies the factors that influence the control space of aircraft performing a TDDA in a real-life application. Control space is defined as the difference between the maximum and minimum duration to perform the TDDA. Using different control strategies, a fast approach or slow approach can be flown. A fast-time simulation tool was built to perform simulations with different aircraft types, initial weights, wind speeds and directions. The simulations show that the influence of wind direction depends on aircraft aerodynamic characteristics, which in turn depend on the drag characteristics of the aircraft and aircraft weight. Furthermore, the results can be used to determine whether a TDDA can be executed using different aircraft, different route properties and under different wind conditions.

Previous research introduced the solution space as a workload metric for air traffic controller merging tasks. The solution space Diagram is a mapping of intruding aircraft trajectories to the velocity/heading plane in the form of conflict zones and safe areas. Choosing a velocity vector in either one will provide an unsafe or a safe solution, respectively. In this paper an improved, dynamic solution space will be tested for correlations with air traffic controller workload. An experiment has been conducted where subjects were required to line up all aircraft in a sector towards a certain waypoint, while continuously rating their workload. High correlations were found between several solution space parameters and the subjective workload.

Aviation accident statistics provide essential information about the development of safety of air transport. They provide insight into the progress made by air transport industry and may indicate possible safety bottlenecks. Based on these insights, the aviation industry can set their strategy and priorities right. Important accident statistics are accident rate, trend and uncertainties based on recorded accident data. One established approach in jointly estimating rate and trend from accident statistics is to perform a regression analysis. However, the uncertainty is not estimated. Another established approach is not to bother about the trend, and just estimate rate and uncertainty for each year separately. This leads to rapid variations in year to year estimates. This paper overcomes the limitation of the established approaches by developing a Bayesian estimation approach for the joint estimation of accident rate, trend and uncertainty. Using worldwide statistical data on aviation accident and flights, it is demonstrated that the novel developed approach works well. Subsequently the novel approach is used to show that there is statistically significant evidence that since 2003 ground related accident rate tends to overtake lead from air related accident rate.

In this paper literature study and consults of experts have been combined to answer the following research question: “Could a biometric passenger process at Schiphol Airport smoothen the passenger-flow without compromising the safety of air transport?” The research indicates that the use of biometrics in the passenger process could significantly smoothen the passenger-flow at Schiphol Airport, by strongly reducing the waiting lines. Safety won't be compromised but improved by the introduction of biometrics in the passenger process, since the automatical biometrical readings are much more accurate than readings done by security personnel. Furthermore, recent developments have made it possible to use biometrics on large scale without privacy issues, namely by storing biometric-identifiers instead of the actual biometric.

Agent-based dynamic risk modelling supports the design of future air traffic operations by risk analysis methods that account for the performance variability of the interacting operators and systems and the resulting emergence of safety occurrences. The paper shows the application of this modelling approach for a future A-SMGCS level 3 supported taxiing into position and hold operation. It provides preliminary risk results, which are obtained by Monte Carlo simulations of a dynamic risk model and by an evaluation of the risk uncertainty using feedback of operational experts.

Priority rules are often considered to be a promising method how to reduce number of maneuvering aircraft in the envisioned new (distributed) ATM separation modes. In the presented paper, we discuss priority rules that have been so far used, developed and suggested for the autonomous aircraft concept. The objective is to consider their advantages and drawbacks as well as factors that should be reflected in the definition of such rules for self separation operations in the future ATM. The relation between the priority rules on one side and applied conflict resolution strategy and information sharing process on the other side is also described. The paper concludes by a suggestion how to overcome the drawbacks of the existing priority rules through a combination of several operational elements.

The CleanEra project is initialed by the Faculty of Aerospace Engineering at Delft University of Technology. Significant reduction of noise impact on communities around airports is considered as one of the major targets of the project. In this paper, an optimization study is carried out in order to find global optimal trajectories for arriving passenger aircraft, in which the number of awakenings is selected as the objective function. Interval-related optimization algorithms are developed to solve such a highly nonlinear dynamic optimization problem. What differs from conventional optimization algorithms is that intervals rather than real numbers are evaluated in the entire course of optimization. Interval analysis is introduced as the core of such optimization algorithms and a flowchart is presented to show how the algorithms operate when solving practical optimization problems. A noise model, a population distribution model and a sleep disturbance model are connected to demonstrate the feasibility of the developed optimization tool for the considered airspace and aircraft. The result of an example shows that the tool is able to reduce the number of awakenings compared with that from a three-degree decelerating approach.

The prediction of the behavior of complex systems remains a costly and time consuming activity due to their data intensive nature. Such dynamic systems do not always lend themselves to a quantitative behavioral analysis. An impact analysis is a novel qualitative approach aimed at determining how a system element deviates from a pre-defined “normal” operational mode due to a change in the operation of another element existing within the same architecture, or due to an interaction with an external environmental condition. This qualitatively determines the elements in the system that would be affected by a modification, and can aid in system development by identifying relationships and interdependencies prior to implementation. An agent based modeling approach is used to create the analysis tool for determining impact within the system. The paper presents an agent based impact analysis applied to a sample United Kingdom Air Traffic Management system as a means of validating the model and approach. The analysis data is validated against data collected from the real world ATM system. The results from the test case vindicated the assumptions made and also identified a number of areas for further development. The capability of impact analyses and the potential for application to complex architectures appears promising based on the results.

The design of modern aerospace systems is commonly an exercise in creating and working with complex systems. This complexity stems from a combination of the complexity of the system itself, the interaction with environment that it operates in and often the organization which is creating the system. Historically, this complexity has been seen as a source of risk and uncertainty, especially with respect to future the future performance and utility of the system. Consequently actions were taken to minimize the downside risk, and especially eliminate what were considered significant failure modes. This risk minimization encompasses both technical and programmatic aspects. As a response the behavior of the program becomes inherently ‘stiff’ and is less likely to evolve to meet changes in the environment. Consequently it may actually be more likely that the program will fail suddenly and late in its development. One possible theory that helps to describe these behaviors and may unlock some of this information is Catastrophe Theory. When combined with a utility approach, specifically a Value-Driven approach this has the option to help organize the concept exploration and decision making phases of design.

Airport categorizations offer a basis to derive representative scenarios for air traffic related simulation purposes. A methodology for an application specific airport categorization was developed as presented in this paper. Existing categorizations were identified to insufficiently reflect operational characteristics of airports and mostly to omit quantitative statements, which are a crucial simulation input. The presented approach shows a way to enhance an existing baseline categorization using application specific airport similarity parameters. A set of typical airports for each category can be specified by analyzing air traffic schedule data. Clustering techniques, the core element of the methodology, are applied to identify outliers, which are subsequently removed. The remaining group of airports is used to calculate the boundaries of the analyzed category as well as the representative scenario parameter values. The proposed approach is presented step by step for one category and the exemplary application in noise trading scheme simulations. Additional results for use in airport capacity analysis are provided. The presented approach offers the possibility to derive traffic scenarios that represent the characteristics of a multitude of airports within one category. In general a different set of similarity parameters can lead to different category boundaries and representative values. The results are application driven, as proven by the examples.

Like in many other sectors, also airports have the ambition “to become sustainable”. However, by stating this goal, airports still don't know what it exactly is that they aspire. By broadness of the definition of sustainability in the absolute sense, this ambition would better be converted to “to become more sustainable”. This way, a goal can be defined that is attainable. Adecs Airinfra has developed a method to help airports become efficiently more sustainable. An airport can follow the steps in this method to become a more sustainable airport.

The method consists of seven steps, where first of all the airport needs to define its vision on sustainability. This vision can depend for example on (local) legislation, the airport's corporate responsibility or issues at local communities. There are many aspects to cover: noise, air quality, CO₂ emission, energy use, safety, water, and of course costs and revenues. This method covers the environmental aspects of sustainability, since these aspects are most visible at airports. The social and economical aspects are considered boundary conditions for the method.

Based upon the vision, the airport continues to define sustainability by making it measurable by defining key performance indicators and boundaries of the airport and the airport's responsibilities. There may be more than just one key performance indicator. When key performance indicators are defined, the current sustainability status, or sustainability footprint, of the airport will be measured. From the footprint the airport can start to create a strategy to improve sustainability. The strategy consists of targets and a planning to implement solutions. The solutions are determined by evaluating the footprint, and the effectiveness of the solutions. This includes cost effectiveness. The next step is implementation of solutions. When starting the implementation, the airport will also need a plan to monitor if the implementation of the solutions is on track. The monitoring is not only used to determine whether the improvements are in line with expectations, they are also used to determine if implementation costs are in line with expectations. By continuous monitoring the strategy and implementation, the airport will reach its sustainability targets.

Since it assists them to get beyond their natural home market, airlines are competing to get the highest share from transit passenger traffic. Airlines keep focusing on their geographical advantage on certain regions in terms of attracting maximum number of transit passengers. By employing Cost of Available Seat per Kilometer (CASK) parameter as the reference point, this study assesses the geographical attraction of existing and promising hubs in Europe, Middle East and Northern Africa. For the sake of this study, seven cities that are claimed to be existing and freshly emerging hubs are chosen to compete in terms of cost effectiveness. The nominees are determined as London, Paris, Frankfurt, Dubai, Istanbul, Cairo and Madrid. Over a sample of 4,080 distinct Origin and Destination (O&D) pairs which is a well demonstration of the overall transit market of the regions of interest, a model comparing the relative superiorities of those candidate cities over another are outlined. The model evaluates geographical distance and the associated cost of this distance that is computed through the base CASK function. The raw results without the attribution of O&D's total traffic standings showed that Cairo, Istanbul and Dubai performed the three best hub candidates respectively. In absolute numbers, Cairo is advantaged more over six other candidate cities. On the other hand, when the size of the O&D's are weighted, the best performing cities are founded as Istanbul, Frankfurt and Cairo respectively. In this case, Istanbul is determined to be the most efficient hub for the majority of the transit passengers.

Despite the downturn in the Aviation Industry that was apparent in 2009, the growth trend both in Egypt Air and Turkish Airlines is a demonstration of airlines' recent actualization of their potential in hub efficiency. Especially since 2005, Turkish Airlines is increasing its number of transit passengers by approximately 50% annually every year.

As multilateration systems have proved to be reliable and cost efficient alternatives to radar tracking, the authors attempted to design a multilateration surveillance solution for Aurel Vlaicu International Airport Bucharest, capable of accurate tracking of both aircraft and ground vehicles. Although the airport is not large, the number of ground vehicles is significant, and in order to be received by a classic multilateration receiver network, they need to be fitted with Mode S transponders. Also, the receiver network requires rather expensive digital clocks, for an adequate measurement of phase. In the stage of value engineering of the project, the authors managed to change significantly the system, as to become a truly low cost one. The idea keeps the hyperbolic positioning method, but based on frequency drift (similar to radar altimeter technology), and not on phase, as in a classic multilateration system. The ground vehicles require an inexpensive low-power transceiver, which is active regardless of the status of the vehicle: in use, turned off, parked etc. This feature (provided by an autonomous battery) is useful as a safety net against the risk of vehicle driver error or misconduct. Whereas pilots are generally trained and reliable, vehicle drivers need a tracking system out of their possibility of intervention. As for the position of the aircraft, the authors propose the use of an inexpensive ADS/B receiver. For the moment, this technology is not yet mature (some aircraft are not fitted with ADS/B, some are transmitting the position taken from the IRS as the only source, indicating inaccurate positions). In the future though, one can expect consistent progress of ADS/B technology, thus improving the practical value of this system. The system provides a simulated radar image on any PC, being easily accessible not only to the TWR and GND air traffic services, but also to the airport management, airport service providers, airport security, operators and other authorized parties. The authors trust that a low cost hyperbolic airport surveillance system could be an interesting alternative for many not so large airports, with occurrences of low visibility, with a modest investment budget.

The fare estimation model proposed in this paper was set up by analyzing the domestic United States air transportation market 2005 year database. A division analyses into seven different studies is presented. There exists substantial fare dispersion in the airline transportation industry for the full-service carrier market whilst very little dispersion can be found for the low-cost carrier market. Both airlines business models were also divided into four different markets. Major fare dispersion has been found for the routes dominated by full-service carriers without the presence of a low-cost carrier and the presence of low-cost carriers make full-service carriers low fares. Routes dominated by low-cost carriers without the presence of full-service carriers price routes with more dispersion than the routes fighting with full-service carriers.

The revenue management processes usually consist of four components: Forecasting, overbooking, seat inventory control and pricing ([McGill and van Ryzin, 1999]). In this test study at the Dutch low cost carrier transavia.com, a full subsidiary of Air France-KLM, a research is done to improve the forecasting component by testing demand forecasting methodologies with actual data some scheduled routes in a Matlab^TM environment. The new revenue management software has been used since August 2008 and has given new opportunities for the revenue controllers to optimize their flights. The forecasting possibilities are however not yet tested.

In a research study, multiple methods are tested with data of the carrier. The additive pickup method turns out to perform the best on several criteria, but a lot of adjustments need to be made in order to give a valuable forecast for the revenue controllers. Important is the dataset that is given as input for the forecast, but also the way fare classes are used within the low cost environment has to be dealt with. This paper suggests three modifications to the basic additive pickup and evaluates them eventually in a simulated environment for the revenue controllers.

Revenue management is one of the key strategic business aspects of airlines. In the airline industry, the use of mathematical revenue management models has become a standard due to their revenue enhancing effect. This paper discusses a simulation set-up with which the performance of a revenue management model can be compared to manual inventory control. Results showed that an in-house designed model can indeed improve revenues in a simulation environment compared to the experience-based manual inventory control.

Knowledge-Based Engineering (KBE) is a developing research field that studies technologies for capture and re-use product and process engineering knowledge to reduce time and cost of product development. KBE has held great promise since its inception, but evolution in the technologies and notions underlying KBE as well as significant challenges towards adoption have so far precluded its main-stream use. The main objective of this paper is to identify the conceptual foundations of KBE and focus on research issues within KBE, pointing out the challenges and pitfalls that currently prohibit a wider adoption of KBE while suggesting possible solutions and avenues for further research. In particular, the case-based ad hoc development of KBE and the ‘black-box’ nature of many KBE applications, subsequent difficulties with knowledge re-use, and insufficient quantification of the benefits of KBE are significant challenges towards a wider adoption of KBE. Methodological and technological advances address some of these issues, and propositions are made to further both qualitative and quantitative analysis and evaluation of KBE applications.

Air travel demand is increasing at a rate much higher than the annual economic growth. This growth has both very positive and negative effects. The increase of negative effects – such as the noise pollution and greenhouse gas emissions – might not cause problems because technologies are being developed that will compensate them. The starting point of this research is to discover whether this claim concerning the possibilities of the current aircraft technology developments is true. In other words: is the current development in aircraft technology capable to contribute to a sustainable development in the aviation sector by keeping current benefits, while mitigating the adverse effects? Existing research on this issue is mostly trend research, focussing at the average technology efficiency increase and transposing this to the future. In a context where multiple actors have to decide about what to do, this transposition is not enough. An aggregated number does not reveal the concrete options and causal relations behind it. This paper, therefore, introduces the open and explicit method of systems analysis to answer the question if (and if so, how) new aircraft technology can mitigate the adverse effects of an increasing air travel demand, while keeping the benefits. Applying the systems analysis, this paper concludes that current developments in aircraft technology are not enough to mitigate the adverse effects of growth. The combination of the efficiency improvement rate, the growth rate of the demand for air travel, and the long replacement times for older technology in our research do not proof to cancel each other out. We suggest to not only invest more into developing even better technologies, but to also search for non-technical solutions; unless we, as a society, decide that an increase in the negative consequences of aviation is less important than other (environmental) issues.

This papers aims (1) to provide a review of the (non-acoustic) social-psychological determinants of aircraft noise annoyance, (2) evaluate Schiphol's noise policy from a social-psychological perspective and (3) review a governance model that can effectively address non-acoustic factors in aircraft noise policy. It is concluded that the insights in the psychology of noise annoyance inform us that local actors in the relationship ‘airport-environment’ should have the means to adjust to each other's presence. However, presently aggregated claims (e.g. average energy-equivalent noise norms), which are ineffective in representing and regulating the social conflict between the airport and its environment, have become dominant in aircraft noise policy. Resultants of this policy are polarization, deficient local control, distrust and noise annoyance. The paper concludes with a review of a previously developed governance model, in which local actors are given room to formulate specific individual preferences and establish transactions between them. This model aims to enhance local control and provide a context of mutual trust in the relationship ‘airport-environment’. Within this context aircraft noise may not necessarily be reduced, but can become much less annoying.

One contributor for excessive flight delays is insufficient ground operation performance with excessive process durations. Further productivity is measured not only by the airline but also by the airport operator and the ground handling companies. Collaborating in the A-CDM with other partners, the aim is to understand process characteristics and to predict process duration for the exact Gate Occupancy Time needed for operational capacity planning. Within this paper focus is set on process variations within specific sub processes for different airports, depending on their network function. An introduction of an intermediate airport category beside hub and non-hub airport is given. We found significant dependencies of turnaround characteristics depending on airport classification, especially for loading process on hub airports.

This paper presents the result of a 6 month research project conducted at the Maintenance Control Center of KLM (Royal Dutch Airlines) Engineering & Maintenance (E&M). The research focuses on the development of a monitoring/forecast tool to anticipate days with a high risk of network disruption. A theoretical framework is formulated based on the combination of Lean and the effectiveness-efficiency trade-off. A model is developed to evaluate operational robustness: the ability of the airline operation to absorb disruptive events and ensure a punctual operation. For each of the parameters of the model an analysis is performed to determine its relation with operational robustness. Flexibility is shown to be a key determinant. The parameters are integrated into a monitoring/forecast tool with a 2 week time horizon. Through a monitoring phase the tool is shown to successfully forecast days with high and low risk. The monitoring phase points out that further calibration of the critical values of the tool is required. Based on the output of the tool and the findings of the analyses, ways to increase operational robustness are suggested.