Annual Report 2017 KPI

Annual Report 2017 KPI

Version History: Version Date Remark Author 0.1 16/02/18 Initial Draft Barboff 0.2 22/02/18 Data analysis, first conclusions Editorial Board 0.3 23/02/18 Inserted first charts Barboff 0.4 22/03/18 Completed charts, adjusted layout Barboff 0.5 17/04/18 Edited Editorial Board 0.6 25/04/18 Added latest data, outlook Barboff, Hilger 0.7 02/05/18 Added source attribution Barboff, Hilger 1.0 08/05/18 Final version Barboff Annual KPI Report Page 2 of 25

Imprint Publisher: DFS Deutsche Flugsicherung GmbH on behalf of Initiative Deutsche Harmonisierung A-CDM@GER Am DFS-Campus 10 D- 63225 Langen GERMANY Contacts: Erik Sinz & Sebastian Barboff, TWR/M Tower Management Services Editorial Board: Sebastian Barboff DFS Deutsche Flugsicherung GmbH Am DFS-Campus 10 D-63225 Langen GERMANY Boris Breug Flughafen Berlin Brandenburg GmbH D-12521 Berlin GERMANY Stefan Hilger Fraport AG Frankfurt Airport Services Worldwide D-60547 Frankfurt am Main GERMANY Nico Ruwe Flughafen Stuttgart GmbH Flughafenstraße 32 D-70629 Stuttgart GERMANY Date: 08 May 2018 Pages: 25 All rights reserved. Any use outside of the limits set by the German Urheberrechtsgesetz requires written permission of the publisher. Violations will be prosecuted in civil and criminal court. This includes copying, translating, microfiching, and storing and processing in electronic systems. DFS Deutsche Flugsicherung GmbH 2018 Annual KPI Report Page 3 of 25

Content 1 MANAGEMENT SUMMARY 5 2 GERMAN HARMONISATION INITIATIVE ACDM@GER 6 3 PURPOSE OF THE REPORT 8 4 RESULTS 9 4.1 GENERIC 10 4.1.1 NUMBER OF IFR DEPARTURES 10 4.1.2 SHARE OF REGULATED IFR DEPARTURES 12 4.1.3 SHARE OF IFR DEPARTURES REQUIRING DE-ICING 14 4.2 PROCEDURE ADHERENCE 15 4.2.1 ASAT QUALITY 15 4.2.2 AORT QUALITY 16 4.3 PROCEDURE PLANNING 17 4.3.1 TSAT QUALITY AND DEVIATION 17 4.3.2 EDIT QUALITY AND DEVIATION 19 4.4 CONNECTION TO NETWORK MANAGEMENT 21 4.4.1 ATFM SLOT ADHERENCE AND DEVIATION 21 4.4.2 AVERAGE ATFM DELAY 23 5 OUTLOOK 24 LIST OF SOURCES 25 Annual KPI Report Page 4 of 25

1 Management Summary Introduction This report covers a set of general Key Performance Indicators (KPIs) that were deemed by the Editorial Board to be comparable among the A-CDM airports Munich, Frankfurt, Düsseldorf, Berlin-Schönefeld, and Stuttgart. Hamburg Airport fully implemented A-CDM during the course of the reporting period 2017, its data will be included for the first time in the subsequent Annual KPI Report 2018. The KPIs contained within this report serve to continuously monitor the A-CDM process and usually portray only individual parts of the overall process. The KPIs allow a measurement of A-CDM uses and steering of the process. They are the basis for local reporting at the individual airports. The KPIs were defined using input from EUROCONTROL s A-CDM Implementation Manual, experiences of the local German Airport CDM airports, as well as local and future necessities. The report is intended to provide a general overview of KPI trends at the A-CDM airports, as well as serve as basis for decisions regarding adjustments to or steering of the A-CDM process. This report describes the experiences, measurements and results of the calendar year 2017. It utilises regular evaluations and measurements on a monthly basis, the conclusions that are drawn address points that were mutually agreed by ACDM@GER which are reflected in the ACDM@GER KPI Concept. Summary of Results and Tendencies Compared to the preceding year, 2017 has shown a marked increase in the share of regulated flights, while the overall number of flights only shows a slight increase. Individual airports, especially Frankfurt Airport, also experienced much more frequent CTOT updates during the summer season. This seems to indicate that the European ATM Network approached its saturation limit during that period. In this state, each additional quantum of demand increases the network load exponentially. This development is expected to continue in the summer flight plan period 2018. Annual KPI Report Page 5 of 25

2 German Harmonisation Initiative ACDM@GER 2.1 European A-CDM Concept Airport Collaborative Decision Making (A-CDM) is the operational approach (idea/concept/process) to achieving an optimal turnaround process at airports. A-CDM covers the period from EOBT -3 h until take-off. It is a continuous process beginning with processing of the ATC flight plan, via landing of the inbound flight, the turnaround process on the ground, to departure. By exchanging estimated landing and take-off times between the A-CDM airports and Network Management Operations Centre (NMOC), airports can be further integrated into the European ATM Network EATMN. A-CDM improves operational collaboration between the partners: Airport Operator, Aircraft Operators, Handling Agencies, Ground Handling Agencies, Air Navigation Service Provider, and European Air Traffic Flow Management (NMOC). A-CDM in Germany is based upon the European A-CDM spirit, the Community Specification of A-CDM, as well as recommendations by the German Harmonisation Initiative ACDM@GER. A-CDM aims to optimise utilisation of available capacity and operational resources at airports and within European airspace through high-quality target times and efficiency increases in the individual steps of the turnaround process. 2.2 German Harmonisation Initiative for A-CDM European A-CDM fundamentally relies on Community Specification EN 303212. However, development of A- CDM in Germany has shown a need of harmonisation to a level of detail that is beyond the Specification s scope. The A-CDM partners recognised this need and founded the German Harmonisation Initiative ACDM@GER. Collaboration within the Initiative is determined by a Letter of Intent that was signed by all partners. Partners within ACDM@GER are currently: Deutsche Flugsicherung GmbH (DFS) Munich Airport (FMG) Frankfurt Airport (Fraport) Berlin Airports (FBB) Düsseldorf Airport (FDG) Stuttgart Airport (FSG) Hamburg Airport (FHG) Annual KPI Report Page 6 of 25

ACDM@GER s goals are, among others: Exchange of information and best practices between the various A-CDM airports, Common understanding of A-CDM in Germany and common representation towards international partners (Eurocontrol, EU, ICAO, IATA) Harmonisation in the interest of partners and customers ( one face to the customer ) Best Practices developed within ACDM@GER can be provided to other European A-CDM projects and working groups to advance harmonisation. Creation and coordination of harmonised procedures and documentations are achieved within ACDM@GER s working groups and regular harmonisation meetings. Annual KPI Report Page 7 of 25

3 Purpose of the Report This document shows A-CDM KPIs that are generally comparable across A-CDM airports in Germany. KPIs fit for inclusion in this report were selected by a working group with participation of all A-CDM airports as well as DFS. The group also defined required data to be gathered and calculation rules. This report is not intended to replace local KPIs, nor does it pre-empt local KPI reporting routines. It is designed as a baseline to which local KPI concepts and reports can add additional indicators or even measure the same KPIs using different criteria. The common reporting that serves as basis for the KPIs contained within this report provide A-CDM airports with the opportunity of highlighting changes and developments, recognising potential for improvements, and developing harmonised A-CDM subprocesses. Further details regarding the A-CDM process and its specifics at the individual airports are described within the local A-CDM procedure descriptions and publications. Annual KPI Report Page 8 of 25

4 Results In order to achieve the local operational and network benefits associated with A-CDM, the quality of target times and process adherence are essential. For this reason, commonly available indicators from the following categories were selected: Generic Traffic Numbers Procedure Adherence of A-CDM partners Procedure Planning Connection to Network Management Generic Procedure Adherence Procedure Planning Connection to Network Management Number of IFR Departures A-CDM Alerts DPI Quality (E/T/S/A) ATFM Slot Adherence/ Deviation Share of Regulated IFR Departures ASRT Quality SOBT Quality CTOT Quality/ Deviation/ Stability Share of IFR Departures Requiring De--Icing ASAT Quality TSAT Quality/ Deviation/ Stability Average ATFM Delay AORT Quality EIBT Quality EDIT Quality/ Deviation Position Change On Short Notice The KPIs coloured in light grey are not yet part of this report but are planned for inclusion in the subsequent Annual KPI Report 2018. Annual KPI Report Page 9 of 25

4.1 Generic 4.1.1 Number of IFR Departures Description Number of IFR departures within the calendar year as well as the previous calendar year Goal Show the amount of traffic and its trend Charts Figure 1: Number of IFR departures 2017 (dark green) and 2016 (light green) Annual KPI Report Page 10 of 25

Conclusion In the year 2017, the six German A-CDM airports generated 66.5% of all IFR departures within Germany. Airport CDM Hamburg was fully implemented in August 2017. Over the whole year of 2017, the largest A-CDM airports showed only slightly higher or stagnant traffic numbers compared to 2016. However, individual months showed significant increases or decreases. Düsseldorf Airport saw considerably lower traffic numbers in the last months of the year due to its main carrier Air Berlin ceasing operations. Annual KPI Report Page 11 of 25

4.1.2 Share of Regulated IFR Departures Description Share of IFR departures with ATFM slot (CTOT) Goal Illustrate the monthly share of IFR departures that were subject of an air traffic flow measure by NMOC. Charts Figure 2: Share of unregulated (light green) and regulated (dark green) IFR departures 2017, and 2016 share (yellow) Annual KPI Report Page 12 of 25

Conclusion Compared to the previous year, the share of regulated flights increased substantially. This is due to Traffic growth above predictions while capacities in airspace and airports remained essentially unchanged, Significant weather events in airspace and at airports, and Shortage of operational staff at European Air Navigation Service Providers. Aside from a generally higher number of regulated flights all over Germany, especially Frankfurt Airport saw a considerable increase in the frequency of CTOT updates per flight. This resulted in operational problems with planning and provision of start-up and off-block clearances, as well as in high utilisation of parking positions. During sequence planning, the many regulated flights and CTOT updates affected TSAT stability of both regulated and non-regulated flights and pushed it to levels below what was desired. Due to this observation, the editorial board intends to extend this report in the future by additional KPIs that show CTOT and TSAT stability. Annual KPI Report Page 13 of 25

4.1.3 Share of IFR Departures Requiring De-Icing Description Share of IFR departures that required aircraft de-icing Goal Show the monthly share of IFR departures whose turnaround process was prolonged by de-icing. Charts Figure 3: Share of IFR departures 2017 requiring aircraft de-icing on stand (dark green) and remotely (light green) Conclusion This KPI provides context for further KPIs below (e.g. TSAT Quality). Most airports only do remote de-icing, i.e. on designated de-icing areas. In this case, de-icing takes place after TSAT. In the case of on-stand de-icing the flight are de-iced on their parking stands, i.e. after TOBT, but before TSAT. Planned de-icing begin and duration are included in the TSAT calculation. In Munich, a vast majority of flights is de-iced remotely, only very few aircraft types on stand. Annual KPI Report Page 14 of 25

4.2 Procedure Adherence 4.2.1 ASAT Quality Description Percentage of IFR departures that received start-up approval (ASAT) within TSAT ± 5 min via radio Goal Measure procedure adherence of Air Traffic Control (Tower) Charts Figure 4: Percentage of IFR departures that received start-up approval within TSAT ± 5 min via radio Conclusion Especially airports with a lower number of movements show a bigger share of flights that received start-up approval outside of TSAT ±5 min. One reason might be that small violations of the TSAT tolerance are more readily accepted there, as ATCOs feel sufficient capacity is available to accommodate flights that operate slightly outside of planned parameters. Annual KPI Report Page 15 of 25

4.2.2 AORT Quality Description Percentage of IFR departures that asked for their off-block clearance (AORT) within the window of 1. ASAT + 5 min (start-up via radio) 2. TSAT ± 5 min (start-up via datalink) Goal Measure procedure adherence of the Flight Crew Charts Munich did not provide data for the year 2016. Berlin-Schönefeld did not provide data for AORT quality. Figure 5: Percentage of IFR departures 2017 with conformant AORT (green) compared to 2016 (grey) Conclusion AORT quality after start-up approvals via datalink is much lower in Frankfurt und Düsseldorf compared to start-up approvals via radio. Datalink clearances are often requested long before ground handling is actually finished, which makes later adherence to the TSAT tolerance less reliable as TSAT seems not immediately relevant. Requests via radio, however, mostly take place after ground handling is complete, which makes it more likely that off-block clearance is also requested soon thereafter. Annual KPI Report Page 16 of 25

4.3 Procedure Planning 4.3.1 TSAT Quality and Deviation TSAT Quality Description Monthly share of last TSATs that were equal to TOBT, in % per airport Goal Operational adherence to planning on the day of operations. Charts Figure 6: Percentage of regulated (light green) and unregulated (dark green) IFR departures 2017 where last TSAT = TOBT Annual KPI Report Page 17 of 25

TSAT Deviation Description Monthly mean deviation of TOBT and last TSAT Goal Show mean deviation of planning on day of operations versus actual operations Charts Figure 7: Mean deviation of last TSAT and TOBT for regulated (light green) and unregulated (dark green) flights Conclusion In the case of unregulated flights, a low TSAT quality shows that local capacity constraints have caused delays. For regulated flights, TSAT is calculated based on CTOT and therefore correlates more with ATFM delay. Annual KPI Report Page 18 of 25

4.3.2 EDIT Quality and Deviation EDIT Quality Description Monthly percentage of IFR departures 1. with on-stand de-icing 2. with remote de-icing whose EDIT was within ADIT ±3 min, per airport Goal Verify the reliability of estimated de-icing duration as input parameter for A-CDM. Charts Figure 8: Percentage of flights with remote (light green) and on-stand de-icing (dark green) where EDIT = ADIT±3 min Annual KPI Report Page 19 of 25

EDIT Deviation Description Monthly mean deviation of ADIT and EDIT in minutes for IFR departures 1. with on-stand de-icing 2. with remote de-icing per airport Goal Verify the accuracy of estimated de-icing duration as input parameter for A-CDM. Charts Figure 9: Mean deviation of EDIT and ADIT for on-stand (dark green) and remote de-icing (light green) Conclusion At most airports, the first prediction of the de-icing duration (EDIT) is based on aircraft type and weather conditions. De-icing requested during the warmer months is usually due to very cold aircraft surfaces, so de-icing duration can usually only be determined when the concrete extent of required de-icing is communicated by the flight crew. This results in a lower EDIT quality for planning purposes. Annual KPI Report Page 20 of 25

4.4 Connection to Network Management 4.4.1 ATFM Slot Adherence and Deviation ATFM Slot Adherence Description Level of adherence to Slot Tolerance Window prescribed by NM Goal Measure procedure adherence when regulated flights are concerned, i.e. flights with ATOT within the Slot Tolerance Window (STW, usually CTOT -5/+10 min but may be extended in special conditions). Adjustment of the CTOT to the local TTOT within the A-CDM process improves ATFM slot adherence, pre-departure sequence and procedure adherence. To better identify the relation of ATOT to CTOT, two supporting measurements were made. Early flights have an ATOT before the STW begin, late flights have their ATOT after the STW end. Charts Figure 10: Share of flights with ATOT before (dark green left), within (light green) and after (dark green right) STW Annual KPI Report Page 21 of 25

ATFM Slot Deviation Description Mean Deviation from the STW prescribed by NM Goal Measure the level of slot deviations for regulated flights. This measurement counts only flights whose ATOT was outside of the Slot Tolerance Window, and measures the distance in minutes between ATOT and the STW limit. Early flights have an ATOT before the STW begin, late flights have their ATOT after the STW end. Charts Figure 11: Mean deviation of ATOT and STW for early (light green) and late (dark green) departures Conclusion ATFM slot adherence at German A-CDM airports is significantly above the European average. Although a larger percentage of flights was started up outside of their TSAT tolerances at airports with lower traffic levels (see chapter 4.2.1), this does not translate into lower ATFM slot adherence there. This seems to indicate that mainly unregulated flights are started up outside of the TSAT tolerance. Annual KPI Report Page 22 of 25

4.4.2 Average ATFM Delay Description Average ATFM delay per regulated departure Goal Measure the average ATFM delay for regulated departures Charts Figure 12: Average ATFM Delay per airport Conclusion Compared to a selection of airports without Airport CDM, the German A-CDM airports show a lower ATFM delay per flight especially during the summer months. Annual KPI Report Page 23 of 25

5 Outlook During the reporting year 2017, a higher traffic demand both locally and within the ATM Network has influenced the dynamics of target time calculation. Based on the available forecasts, this tendency will likely continue in the year 2018. Therefore, one goal of ACDM@GER is to find a harmonised way of compensating the increased dynamics in the planning systems. This will ensure more reliable planning across the entire A-CDM process for all partners. Stability-related KPIs shall be added to the report that allow to measure the effectiveness of measures that target this area. In particular, indicators related to stability of TSAT and CTOT seem promising. Regarding data related to ASRT quality, DFS is planning to implement an updated version of its Tower Flight Data Processing System which will enable a valid calculation of that indicator. The software update will be rolled out sequentially to all A-CDM airport towers, and as this roll-out progresses, the indicator will be added for each airport. The year 2018 will be the first complete year with full A-CDM implementation at Hamburg Airport. Starting with the Annual KPI Report 2018, KPIs for Hamburg will be available as well. Annual KPI Report Page 24 of 25

List of Sources CHAPTER KPI SOURCE 4.1.1 Number of IFR Departures DFS Deutsche Flugsicherung 4.1.2 Share of Regulated IFR Departures NM ATFCM Monthly Summary per Airport 4.1.3 Share of IFR Departures Requiring De-Icing Airports 4.2.1 ASAT Quality Airports 4.2.2 AORT Quality Airports 4.3.1 TSAT Quality and Deviation Airports 4.3.2 EDIT Quality and Deviation Airports 4.4.1 ATFM Slot Adherence and Deviation NM ATFCM Monthly Slot Adherence 4.4.2 Average ATFM Delay NM ATFCM Monthly Summary per Airport Annual KPI Report Page 25 of 25