Managing lumpy demand for aircraft spare parts

This paper deals with effective forecasting methods for typically lumpy demand for aircraft spare parts, and analyzes the behavior of forecasting techniques when dealing with lumpy demand. Twenty forecasting techniques are considered and tested and historical data from Alitalia are used to analyze and compare their performance. The results demonstrate that item lumpiness is the dominant parameter and show that demand forecasting for lumpy items is a complex problem; results from previous studies are not very accurate. The best approaches are found to be weighted moving averages, the Croston method, and exponentially weighted moving average models.     

Sources of intermittent demand for aircraft spare parts within airline operations

Owing to the sporadic nature of demand for aircraft maintenance repair parts, airline operators perceive difficulties in parts demand forecasting. In this paper we investigate the sources of demand lumpiness, as a function of flying hours, that may affect the parts demand rate. Experimental results of demand lumpiness, measured by the square coefficient of variation (CV²) and the average inter-demand interval (ADI), are examined and clarified through statistical analysis. The general linear model approach is used to explain the variation attributable to the various experimental factors and their interactions. Actual historical data for hard-time and condition-monitoring components from an airlines operator are used. This study shows that aircraft utilization rate can be a major source of lumpiness since it increases and decreases the square coefficient of variation and the average inter-demand interval respectively for the observed demand. This assumes a strictly linear relationship between demand and flying hours/landings.     

From passenger growth to aircraft movements

Airlines are able to deal with passenger growth by either increasing the frequency or the aircraft size, which may entail different numbers of aircraft movements. Forecasting the latter is necessary for evaluating technologies, approaching future emissions or anticipating capacity constraints. Purpose of this paper is to forecast a typical fleet mix and the growth of aircraft movements on flight segments worldwide based on an assumed passenger growth. The methodology is implemented in a model called Forecast of Aircraft Movements. Basic approach is the assignment of each flight segment worldwide to a distance, passenger number and aircraft category. For each combination of distance and passenger numbers a typical fleet mix is defined. The forecasted worldwide growth of passenger demand and the empirically determined fleet mix is applied to all segments in order to derive a future scenario. Assuming a certain seat load factor, the frequency growth can be deduced from the aircraft movements generated for all segments. The paper includes a forecast for aircraft movements in a future scenario based on real schedule and passenger data and gives a detailed overview of the methodology and results considering airlines' behaviour.     

Three-stage airline fleet planning model

One of the main factors affecting airline success is bringing supply and demand as closely together as possible. In order to achieve this goal, an airline needs to adopt an appropriate methodological approach for the fleet planning process. Selection of an aircraft for operating a defined route network is a key element which has a direct impact on the increase of an airline's profitability and on the reduction of an airline's costs. The objective of this paper is to develop a robust model for fleet planning that deals with both fleet size and fleet composition problems for airlines operating on short haul and medium haul routes. The three-stage model for fleet planning involves approximate fleet composition, fleet sizing and aircraft type selection based on fuzzy logic, heuristic and analytic approaches, and multi-criteria decision making, respectively. This model is exemplified with a hypothetical airline based at Belgrade Airport.     

An innovative method to optimize the maintenance policies in an aircraft: General framework and case study

Maintenance policies applied to aircrafts are governed by a mix of airworthiness authorities’ regulations and choices of suppliers and users. This allows airlines to use different strategies to minimize the total costs of maintenance. In this paper, a new approach that integrates the failure and reparation processes, such as modelling, optimization algorithms, and simulation methods, is proposed to define the best maintenance strategies for complex systems.A case study of an airline carrier is presented. In particular, several critical components for the A320 aircraft family are considered. The impact of the spare parts inventory management is discussed. Different preventive maintenance policies are tested and simulated. With the new policies, the average availability of the aircraft is satisfactory and the total annual cost is reduced to a value of approximately 20% in comparison with the previous policies adopted by the company.     

Aircraft replacement scheduling: A dynamic programming approach

This study developed a stochastic dynamic programming model to optimize airline decisions regarding purchasing, leasing, or disposing of aircraft over time. Grey topological models with Markov-chain were employed to forecast passenger traffic and capture the randomness of the demand. The results show that severe demand fluctuations would drive the airline to lease rather than to purchase its aircrafts. This would allow greater flexibility in fleet management and allows for matching short-term variations in the demand. The results of this study provide a useful reference for airlines in their replacement decision-making procedure by taking into consideration the fluctuations in the market demand and the status of the aircraft.     

Grounded: Characterising the market exit of European low cost airlines

The aim of this paper is to undertake a comprehensive study of low cost carrier (LCC) market entry and exit in Europe between 1992 and 2012. In the 20 year period between 1992 and 2012, 43 LCCs have taken advantage of the progressive liberalisation of the European aviation market and commenced scheduled flight operations within the continent. Of these 43, only 10 remain operational, a failure rate of 77%. This paper contributes to extant literature on LCCs by examining the market entry, business practices, operating longevity and fate of failed operators to characterise European LCC market exit. Drawing on the findings of a detailed continental-wide study, the paper identifies that an airline's start-up date, the nature and size of its operation and the size and composition of its aircraft fleet are key factors which influence LCC success and failure. The implications for both European and emerging LCC markets are discussed.     

Cost adjustment for single item pooling models using a dynamic failure rate: A calculation for the aircraft industry

This paper presents an analytical model for cost estimation in a single-item, multi-hub (S-1,S) inventory policy-pooling model for high-value spare parts in the aviation industry. The model extends existing, static pooling models by implementing a dynamic failure rate, using a maintenance free operating period (MFOP) as a measurement technique to increase availability of aircraft components. The gained results through a dynamic failure rate show significant effects for a reduction of total costs of ownership and achieving a better operational stock planning, which is demonstrated in a numerical application.     

Cost adjustment for single item pooling models using a dynamic failure rate: A calculation for the aircraft industry

This paper presents an analytical model for cost estimation in a single-item, multi-hub (S-1,S) inventory policy-pooling model for high-value spare parts in the aviation industry. The model extends existing, static pooling models by implementing a dynamic failure rate, using a maintenance free operating period (MFOP) as a measurement technique to increase availability of aircraft components. The gained results through a dynamic failure rate show significant effects for a reduction of total costs of ownership and achieving a better operational stock planning, which is demonstrated in a numerical application.     

Drivers of long-haul air transport route development

An analysis of long-haul routes identifies trends and patterns underlying their development. Five distinct perspectives: geography, regulation, manufacturers, passengers and airlines are taken to investigate the drivers of long-haul route development. From the insights gained it is inferred that the demand for long-haul aircraft is a complex function thereof, whereby long-haul routes are operated between cities with strong business and social connections as influenced by the dynamics of change and underlying geography.     

Spare parts demand: Linking forecasting to equipment maintenance

Demand for spare parts is typically intermittent and forecasting the relevant requirements constitutes a very challenging exercise. Why is the demand for spare parts intermittent and how can we use models developed in maintenance research to forecast such demand? We attempt to answer these questions; we present a novel idea to forecast demand that relies upon the very sources of the demand generation process and we compare it with a well-known time-series method. We conclude that maintenance driven models are associated with a better performance under certain conditions. We also outline an inter-disciplinary agenda for further research in this area.     

The cost of abatement options to reduce carbon emissions from Australian international flights

In 2012, a total of 13.1 million tonnes of carbon dioxide were emitted by 14 airlines while transporting 72 per cent of international passengers into and out of Australia in 2012. With passenger and cargo traffic growing at between five to six per cent annually from 2013 to 2033, acquiring more fuel efficient aircraft to both renew the existing fleet and to service growth has the greatest potential in reducing emissions over the next 20 years. Our analysis shows that implementing carbon dioxide emissions abatement options such as installing light weight seats, iPad electronic flight bags, winglets, washing aircraft engines and reducing the number of engines used during taxiing, all offer net financial savings when considered over 20 years. Acquiring new fuel efficient aircraft has the biggest impact on emissions reduction. Low interest loans and longer loan repayment periods may incentivise airlines to acquire more fuel efficient aircraft to service traffic growth but other complimentary incentives and penalties are required to influence airlines to replace their current fleet with more fuel efficient aircraft.     

Grounded aircraft: An airfield operations perspective of the challenges of resuming flights post COVID

The global COVID pandemic, national lockdowns and unprecedented decline in passenger demand worldwide has led to airlines cancelling services, furloughing staff, applying for financial support and placing aircraft into temporary storage. However, with finite space available, and up to two-thirds of the world's total passenger fleet grounded for an indeterminate period of time, airlines have been forced to park their aircraft in unusual places, sometimes at airports they do not normally serve and in volumes never normally experienced. The aim of this paper is to investigate the extent of grounded aircraft at UK airports and explore the challenges, from an airfield operations perspective, of resuming flights post-COVID.     

An empirical analysis of airport capacity expansion

Theoretical analyses of the impact of airport capacity expansion must model or make assumptions about the effect of capacity on demand, airline competition, aircraft types, fares and other characteristics of a given airport. In this paper, we use empirical data on historical schedules, fares, delays and demand for the busiest 150 airports in 2015 to examine the typical impact of historical capacity expansions. We find significant diversity in outcomes, with over half the expanded airports either using less than their pre-expansion capacity or remaining constrained even at post-expansion capacity by 2016. Many of the expected impacts, such as reductions in typical aircraft size, either do not materialise or are dominated by other effects (for example, recessions; airlines beginning or ending operations at an airport; changes in regulation). Behaviour on expansion is affected by slot control regulations and whether the airport is initially capacity-constrained. In particular, slot-controlled airports typically add new destinations and carriers on expansion rather than making significant changes to existing schedules.     

The impact of airport capacity constraints on future growth in the US air transportation system

This paper simulates airline strategic decision making and its impact on passenger demand, flight delays and aircraft emissions. Passenger flows, aircraft operations, flight delays and aircraft emissions are simulated for 22 airports in the US, under three airport capacity scenarios. The simulation results indicate that most system-wide implications for operations and environmental impact seem to be manageable, but local impacts at congested hub airports may be significant. The response of the air transportation system to avoid airports with high delays could significantly impact passenger demand and air traffic for these and directly dependent airports. The simulations also suggest that frequency competition effects could maintain flight frequencies at high levels, preventing a significant shift toward larger aircraft, which would otherwise reduce the impact of the capacity constraints.     

Probabilistic assessment of fleet-level noise impacts of projected technology improvements

Demand projections for civil aviation have forecast increases in operations in future decades. Increases in demand are beneficial to the growth and advancement of the aviation industry, but also come with the threat of significant increase in environmental impacts. In response, the industry is focusing on programs to develop technologies for reductions in fuel burn, NO_x emissions, and noise. While aircraft-level impacts are an obvious metric of success, it is difficult to make informed robust technology investment decisions with respect to noise without understanding the fleet-level impacts. Fleet-level predictions of noise for technology explorations are especially complicated because it is computationally expensive, highly combinatorial, and airport-specific. Recently, rapid automated airport noise models have been developed, which can be simulated using Design of Experiments (DOE). The results of these simulations are used to generate surrogate models for airport noise contour area, which can be summed to yield a fleet-level impact. These models make use of simplifying assumptions to provide estimates of airport-level noise that are substantially cheaper to compute. They can be used to perform parametric trade-off analyses in conjunction with the equivalency assumption. Equivalency asserts that environmental impacts of a technology infused aircraft can be represented by scaled operations of the baseline aircraft in the same class. This simple assumption allows for the modeling of technology and market penetration factors under the same units: operations. This research uses surrogate models in conjunction with the equivalency assumption to examine two potential technology scenarios in a target forecast year, simulating technology and market performance factors to identify vehicle classes that could have the greatest impact in reducing contour area. Results show that technology and market performance of future notional Small Single Aisle and Large Single Aisle vehicle aircraft have the highest positive correlations with potential reductions in contour area.     

The impacts of emerging aviation trends on airport infrastructure

The demands on airport infrastructure around the world are both growing and changing. This paper explores what problems these changing demands imply for airports, and how they are coping with them. Growth in demand imposes a problem of allocation of scarce capacity in the short run—how well mechanisms such as the slot system are coping with them is explored. In the long term, increases in capacity are warranted, and how the emerging ownership and regulatory environments for airports will handle these is examined. Changes in patterns of demand will come from new business models, such as low-cost carriers and from new aircraft types, such as the Airbus A380—the implications of these for airports of these are considered. Finally, the issue of airport cost efficiency, and how ownership and regulatory environment impact on it, is examined.     

Efficient aircraft spare parts inventory management under demand uncertainty

In airline industries, the aircraft maintenance cost takes up about 13% of the total operating cost. It can be reduced by a good planning. Spare parts inventories exist to serve the maintenance planning. Compared with commonly used reorder point system (ROP) and forecasting methods which only consider historical data, this paper presents two non-linear programming models which predict impending demands based on installed parts failure distribution. The optimal order time and order quantity can be found by minimizing total cost. The first basic mathematical model assumes shortage period starts from mean time to failure (MTTF). An iteration method and GAMS are used to solve this model. The second improved mathematical model takes into account accurate shortage time. Due to its complexity, only GAMS is applied in solution methodology. Both models can be proved effective in cost reduction through revised numerical examples and their results. Comparisons of the two models are also discussed.     

Scenario tree airline fleet planning for demand uncertainty

This paper proposes an innovative multi-period modeling approach to solve the airline fleet planning problem under demand uncertainty. The problem is modeled using a scenario tree approach. The tree is composed of nodes, which represent points of decision in multiple time stages of the planning horizon, and branches, representing demand variation scenarios. The branches link the decision nodes in consequent time stages and compose scenario paths. Fleet decisions are modeled according to these scenario paths, resembling the real-life process in which fleet plans are not defined in a single moment but instead are adjusted according to the demand development. Given that some scenario paths share common decision nodes, decisions among scenarios need to be synchronized. A mixed-integer linear programming model is proposed to determine the ideal fleet composition for each scenario in the tree and to describe this interdependency between scenarios. Considering the probability of a scenario, fleet composition probabilities for each time-period can be determined. Two real-world based case studies are performed to show the validity of the model. Results show that the proposed scenario tree approach can provide flexible multi-period airline fleet plans, which are more robust to future demand scenarios than fleet solutions obtained using the traditional approach of considering a single deterministic demand evolution scenario.     

A multi-time scale management structure for airport ground handling automation

The sustainability of air travel relies on proper and timely aircraft ground handling at airports. This research proposes a ground handling management structure which allows the automation of operations to face the growing demand for this service. It is shown how at operations level, information exchange with the airport collaborative decision-making system turns possible on-line fleet assignment to ground handling tasks. This is done by designing different heuristics for assignment of fully automated or semi-automated vehicles to ground handling tasks. Numerical results for an actual airport are presented to illustrate the potential performance of automated ground handling operations.