Key Performance Indicators for Performance-Based Airport Management from the perspective of airport operations

Transcription

1 Key Performance Indicators for Performance-Based Airport Management from the perspective of airport operations Lisa Kosanke and Michael Schultz Since the total number of flight movements increases annually, existing capacity restraints at airports are expected to worsen and new restrains will arise considering the air traffic demand and current airport infrastructure. In this context, the current airport operations have to be significantly optimized using the given infrastructure and new airport operational strategies have to be developed regarding to the ambitious targets of Europes Flightpath 2050 and the associated Strategic Research and Innovation Agenda of the ACARE organization. To evaluate the performance of the airport operations reliable, quantifiable and resilient Key Performance Indicators are required. In the context of air traffic, performance is primarily characterized by the amount of flight movements, handled aircrafts on ground, delays in operations and passengers operated. The objective of our research is to derive a consolidated set of Key Performance Indicators, primary focuses the airport airside operations, which will allow both a comprehensive view of the airport system and an efficient, holistic and performance based management of the day of operations enabled by realtime measurements and modelbased predictions for the future system states. To meet this challenge, factors with relevant impact on the airport airside performance are identified, clustered and evaluated to derive reasonable Key Performance Indicators. Three Key Performance Indicators are chosen which are determined with the help of 22 Performance Indicators split in two levels. Applying those Key Performance Indicators in the concept of Performance-Based Airport Management an improved airport performance is expected as the knowledge about upcoming disturbing events during the operations enables the various stakeholders to intervene ahead of time and such to reduce negative impacts. The validation of the chosen Key Performance Indicators and expansion of investigations on further impacts will be in focus of future research. Nomenclature A/C ACZT ADIT ADORC AEZT AIBT ALDT AOBT AT DR AT F T AT LR AT OT AT RO AT T T EDIT EDORC Aircraft Actual Commencement of De-icing Time Actual De-icing Time=AEZT-ACZT Actual Duration of Runway Closure Actual End of De-icing Actual In-Block Time Actual Landing Time Actual Off-Block Time Actual Time of Driving on the Runway Actual Time of Fly Over the Threshold Actual Time of Leaving the Runway Actual Take-Off Time Actual Time of Runway Occupancy Actual Turn-round Time Estimated De-icing Time Estimated Duration of Runway Closure German Aerospace Center, l.kosanke@tu-braunschweig.de German Aerospace Center, Michael.Schultz@dlr.de 1 of 7

2 ET T T GH ICAO KP A KP I P BAM SESAR Estimated Turn-round Time Ground Handling International Civil Aviation Organisation Key Performance Area Key Performance Indicator Performance-Based Airport Management Single European Sky ATM Research Programme I. Introduction There are several approaches to improve the performance of Airport Management and to raise the efficiency of an airport, although the traffic volume at airports increases at the same time. These include amongst others Airport Collaborative Decision Making (A-CDM), Total Airport Management (TAM) 1, 2 and Performance-Based Airport Management (PBAM), 4, 5 a new concept which is currently under development at the German Aerospace Center. All of these aim better cooperation between the various stakeholders operating at an airport to reach performance improvements. To evaluate the performance of the airport operations Key Performance Indicators (KPIs) are required and for PBAM they are also applied as constant control mechanism. The International Civil Aviation Organisation (ICAO), 6 EUROCONTROL 7 and other institutions establish KPIs. SESAR D1 8 and SESAR D2 9 specify eleven Key Performance Areas (KPAs), which are clustered in three groups called: Societal Outcome, Operational Performance and Performance Enablers. KPAs are defined as a way of categorizing performance subjects related to high-level ambitions and expectations by ICAO Today KPIs are mainly individual or applied for post analysis and are slightly used for pre-planning of airport processes. 10 Other than that, this paper deals with the derivation of Key Performance Indicators, which permit the management of daily flight operations through real-time measurements and predictions for the day of operations. Furthermore those KPIs aim at a better situation awareness, which allows more reasonable reactions from the airport stakeholders. The paper considers the performance of the airport air-side and ignores the airport land-side as well as network effects. These effects will be analysed in a next step. II. Methodology Section II.A explains the approach to derive KPIs in general. Therefore schematic methods exist, which are described in ICAO 6 and EUROCONTROL. 11 Afterwards the specific derivation of KPIs describing the airport operations of the airport air-side is made in section II.B. II.A. Necessary steps to determine air-side Key Performance Indicators The purpose of this paper is to determine possible air-side Key Performance Indicators which allow controled airport processes based on KPIs. To identify KPIs fulfilling those demands six steps are supposed to be passed through. 12 These steps are shown in figure 1. The target of step 1 is determining goals to improve the airport air-side operations. Therefore it is necessary to be aware of possibly arising difficulties, which may significantly influence the normal operations. After analysing the potential difficulties objectives can be derived and used for the establishment of KPAs. During the second step KPIs are identified. Therefore the impact of the influencing factors on the airport air-side operations is analysed and rated. Afterwards measures detecting the arising impact are deduced and clustered. The selection of reasonable KPIs takes place in step 3 based on certain selection criteria, 12 see table 1. The regulation EC 691/ describes the requirements for the KPIs as follows: Key performance indicators should be selected for being specific and measurable and allowing the allocation of responsibility for achieving the performance targets. The associated targets should be achievable, realistic and timely and aim at effectively steering the sustainable performance of air navigation services. 2 of 7

3 Step1 Definition ofobjectivesandderivationofkpas Step2 Identificationofpossibleindicators Step3 Selectionofindicators Step4 Quantificationofindicators Step5 Implementationofindicators Step6 Assessmentofresults Figure 1. Selection process used for derivation of air-side KPIs, cf. HELM 12 Although these requirements are set for KPIs measuring the performance of air navigation services, they can be used as evaluation basis of the Key Performance Indicators monitoring air-side airport operations as well. The main selection criteria used in this paper are based on HELM 12 and are shown in table 1. Significance and measurability are described by EUROCONTROL. 11 The number of covered objectives is important, because the objectives which are set are used to find the KPIs. To be able to measure the performance it is necessary to get a reliable and complete set of required data. Real-time ability is needed to fulfill the criteria in the context of PBAM to provide KPIs with control abilities. Table 1. Selection criteria for KPIs for the airport air-side operations, HELM 12 Criteria Significance Number of covered objectives Measurability Data availability Real-time availability Description KPI has the ability to monitor respective airport activity Changes in performance should be clearly recognizable in KPI value changes Each objective defined in step 1 needs to be covered by at least one KPI KPIs covering several objectives are preferred General ability to be measured is prerequisite Direct measurement of KPI is possible or need of expressing the KPI in terms of supporting metrics Performance is quantitatively expressed Abidance to privacy regulations Necessary investments to provide required data Sufficient data quality is a prerequisite Necessary data granularity Calculation of KPIs has to be possible in real-time KPIs should be able to be forecasted for a time-frame of 24 hours The quantification of the indicators in step 4 is necessary, that it can be used as decision support indicating deviations during the airport operations. In this context a quantified indicator is more significant than 3 of 7

4 a quality statement, which could be used as decision support as well. The quantified standard values vary from one airport to another, which leads to necessary adaptations for each airport using the chosen KPIs. If the KPIs are defined, the implementation in the airport system is the next step (step 5). Therefore it is important to get all data in an adequate quality. In step 6 the quality of the KPIs is reviewed and improvements of the airport air-side operations are supposed to be observed. This represents a feedback loop, whether the identified indicators fulfill their requirements. II.B. Realization of steps to determine air-side Key Performance Indicators This section describes the implementation of necessary steps to derive air-side KPIs. Step 1: Possible impacts on the airport air-side operations are shown in figure 2. The solid line framed factors build the exterior framework and define the capacity a. Factors which influence the daily operation are framed with a dashed line. The dotted framed factors occur unpredictable, which means that a control is impossible. The result is that the dotted framed factors are ignored in further investigations. The dashed framed factors build the basis for the determination of the KPIs. The analysis of the dashed bordered influencing factors results in the identification of three objectives: improved resource usage, improved capacity usage and improved efficiency. These aims lead to two Key Performance Areas: capacity and efficiency, which goes hand in hand with resource usage. Step 2: The identification of potential KPIs is made by analysing the impact of the influencing factors on Airport layout (location, geometry, number of runways, orientation, surrounding obstacles, type and location of taxiway exits, etc). Aircraft types Separation minima Construction works Number of parking positions Legend: Exterior framework Personnel deployment Daily influencing factors Strike Unpredictable influencing factors De-icing Parking position of the aircraft Arrival sequencing organisation in the air and departure sequencing organisation on the ground Separation minima Weather phenomena affecting Air Traffic Management operations Demand shift Aircraft technology failures System failures Communication Priorities Aircraft types Parkingposition of the aircraft Number of passengers Number of luggage Number/size of hand luggage Instrument approach equipment (ILS, VOR/DME, RWY Lighting System) Surveillance Systems (TAR, SMR, A-SMGCS) Landside infrastructure impacting airside operations Noise constraints on runway usage (e.g. ban on nightflights) Number of allocated airportslots Figure 2. Influencing factors on the performance of the airport air-side. Factors, which build the exterior framework and define the declared capacity are framed with a solid line. Factors with an influence on the daily operation are framed with a dashed line, while dotted framed factors describe unpredictable incidents. a Capacity is a measure of the maximum number of A/C operations which can be accommodated on the airport or airport component in an hour. 3 4 of 7

5 the airport air-side. Possibilities to measure the arising impact are deduced and clustered. A preselection based on the degree of influence on the airport process is made to minimize the number of potential Performance Indicators. Step 3: The selection of KPIs is based on the selection criteria shown in table 1. De-icing, Snow removal and utilization rate are the chosen KPIs, which are described by several Performance Indicators, see figure 3. These Performance Indicators are necessary to evaluate the chosen KPIs and to point out possible deviations. De-icing is evaluated by de-icing resources per interval, de-icing-queue per interval and the de-icing duration per interval. If deviations concerning the airport operations in one of those fields occur, it will be indicated by changing the displayed KPI De-icing. Snow removal is characterized by the limitation of aircraft stands and taxiways, the snow removal duration of the runway, which leads to a runway closure and thus to a significant decline of capacity. The third KPI Utilization rate is divided into four lower levels. These Performance Indicators deal with the utilization rate regarding taxiways, apron, runway and turnaround process. These four Performance Indicators are subdivided again and described by the red marked indicators in figure 3. The necessary measurement variables to determine the Performance Indicators are summarized in table 2. Figure 3. Chosen Key Performance Indicators with their describing Performance Indicators in two levels. Key Performance Indicators Performance Indicators (Level 1) Performance Indicators (Level 2) De-icing De-icing resources per interval De-icing queue per interval Keeping the de-icing duration per interval Snow removal resources per interval Snow removal Limitation of aircraft stands per interval Limitation of taxiways per interval Keeping the snow removal duration of the runway per interval Taxiway utilization rate per interval Runway queue per interval Taxiway resources per interval Utilization rate Apron utilization rate per interval Runway utilization rate per interval A/C stand resources per interval Keeping the planned A/C stand per interval Runway occupancy time per interval Runway utilization rate per interval Utilization rate per interval (departure) Utilization rate per interval (arrival) Turn-round process utilization rate per interval Equipment resources per interval Waiting queue for GH-service per interval Keeping the estimated duration of turnround per interval 5 of 7

6 Table 2. Chosen KPIs and possible measurement variables Performance Indicator De-icing resources per interval De-icing queue per interval Keeping the de-icing duration per interval Snow removal resources per interval Limitation of A/C stands per interval Limitation of taxiways per interval Keeping of the snow removal duration of the runway per interval Runway queue per interval Taxiway resources per interval A/C stand resources per interval Keeping the planned A/C stands per interval Runway occupancy time per interval Runway utilization rate per interval Utilization rate per interval (departure) Utilization rate per interval (arrival) Equipment resources per interval Waiting queue for GH-service per interval Keeping the estimated duration of turnround per interval Measurement Variable # used de-icing equipment # available de-icing equipment # A/C in de icing queue ADIT EDIT = AEZT ACZT EDIT # used snow removal equipment # available snow removal equipment # snow covered A/C stands (Terminal/Apron) # snow covered taxiways ADORC EDORC # A/C in runway queue # open taxiways #available taxiways # occupied stands (Terminal/Apron) #available stands (Terminal/Apron) # changed A/C stand positions (AT LR AT F T )+(AT DR AT OT ) = AROT # flight movements capacity handled traffic (departure) capacity (departure) handled traffic (arrival) capacity (arrival) # used equipment # available equipment # declared A/C for GH # handled A/C by GH AT T T ET T P = AOBT AIBT ET T P III. Conclusion The implementation of KPIs with control function for air-side airport operations aims at a better situation awareness of the airport stakeholders, resulting in an improvement of the overall air-side performance. Therefore a colour coding might be intended, which enables an identification of occurring problems and categorizing impacts in: no problem, minor problem, major problem. Deviations will be measured by Performance Indicators and are displayed by the associated KPI. To find the real problem it is necessary to investigate the Performance Indicators located at the lower level describing the KPI. It has to be considered, that the personnel disposition has an influence on the Performance Indicator De- Icing resources, Snow removal resources and the turn-round process, 14 which means that it has to be measured as well. The selection criteria Measurability and Data Availability are not completely fulfilled, because the number of snow covered stands and taxiways as well as the Actual Time of Runway Occupancy for instance is not yet measured. The Performance Indicator Runway Occupancy Time is not significant on its own. If it is high it might indicate a high number of flight movements, which stands for a satisfying utilization rate, but on the other hand it stands for a long duration of stay of the aircraft on the runway, because taxiways are closed (e.g. due to snow) or the braking distance is long (e.g. due to heavy rain), which is not an indicator for a good utilization 6 of 7

7 rate. But if both Performance Indicators are considered together a significant conclusion concerning the utilization rate is possible. Another possibility is an other definition of Runway Occupancy Time, which refers to the occupancy time by one aircraft instead of the sum of the aircrafts starting and landing. This allows a clear identification of the reason for the long occupancy time. To meet the objective of real-time measurement a reasonable interval has to be defined, which will be determined and proved in further research. A disadvantage concerning the derived KPIs is the focusing on winter conditions, which means, that there is just one KPI left which could be used perennially. But the defined objectives (see II.B) improved resource usage, improved capacity usage and improved efficiency are fulfilled even by this one KPI and its associated Performance Indicators. Last but not least step 4, 5 and 6 have to be implemented, but at the present stage a quantification is not reasonable, because the values will vary from airport to airport. The fulfilment of these steps will be in focus of next research. Although the derived KPIs are not proved until now a significant improvement concerning situation awareness is expected. References 1 TAMS Partners (Deutsches Zentrum für Luft- und Raumfahrt e.v., Siemens AG, Barco Orthogon GmbH, Inform GmbH, Flughafen Stuttgart GmbH, ARTRiCS),TAMS Operational Concept Document, Guenther, Y., Inard, A., Werther, B., Bonnier, M., Spies, G., Marsden, A., Temme, M., Bhme, D., Lane, R., Niederstrasser, H.,Total Airport Management-Operational Concept & Logical Architecture, EUROCONTROL and German Aerospace Center (DLR), Federal Aviation Administration, Airport Capacity and Delay, Helm, S., Loth, S., Guenther,Y., Schultz, M., Advancing Total Airport Management- An Introduction of Performance Based Management in the Airport Context, ATRS World Conference (accepted), Loth, S., Helm, S., Punctuality as KPI for Performance Based Airport Management, 15th AIAA Aviation Technology, Integration and Operations Conference (accepted), International Civil Aviation Organisation, Manual on Global Performance of the Air Navigation System, Performance Review Commission, ATM Airport Performance (ATMAP) Framework, EUROCONTROL, SESAR Consortium, Air Transport Framework-The Current Situation D1, Version 3.0, SESAR Consortium, Air Transport Framework-The Performance Target D2, EUROCONTROL, Airport CDM Turnround Processes and Best Practices, EUROCONTROL, Performance Review Unit. Technical Note-Measuring Operational ANS performance at Airports, 1 st ed Helm, S.,Urban, B., Werner, C., Grimme, W., Key Performance Indicators for landside processes at airports- which to choose and what to gain?, WCTR European Commission, Commission Regulation (EU) No 691/2010, Official Journal of the European Union, Oreschko,B., Schultz,M., Elflein,J., Fricke,H., Significant Turnaround Process Variations due to Airport Characteristics, First International Air Transport and Operations Symposium, of 7