Capacity Planning Overview

Transcription

1 Capacity Planning Overview Brazil Strategic Airport Capacity Improvement Project August 2016

2 1. Capacity Primer

3

4 Capacity Basics Capacity is how much stuff something holds Measurement depends on the stuff May include a time component All about space

5 Airport Capacity Basics How much demand a system can accommodate Measurement depends on type of demand May include a time component All about space

6 Basics of Airport Capacity Sized to accommodate peak passenger volumes Peak demand derived from annual activity Capacity is a function of desired Level-of- Service

7 Capacity assessment is all about space

8 Selected Airport Systems

9 Selected Airport Demand

10 A chain is only as strong as its weakest link

11 How many aircraft can I park?

12 How many people can fit?

13 How many bags can fit?

14 2. Level-of-Service

15

16 Level-of-Service Basis for capacity assessments Service and convenience Congestion or crowding Waiting/processing times Length of passenger queues

17 Qualitative

18 Intangible

19 Space, time, and perception

20 ADRM LoS Parameters Optimum recommended as the minimum design objective Overdesign viewed as having no upper bound and may be considered excessive Suboptimum an environment that is constrained and not comfortable for passengers

21 ADRM LoS Parameters Space Time Previous ranking Overdesign Excessive or empty Overprovision of resources A, B Optimum Sufficient to accommodate necessary functions comfortably Acceptable processing and waiting times B, C, D Suboptimum Crowded and uncomfortable Unacceptable processing and waiting times D, E

22 ADRM LoS Parameters Excessive or empty space Accommodates functions comfortably Crowded and uncomfortable Overprovision of resources Overdesign Optimum Sub-Optimum Acceptable processing and waiting times Unacceptable processing and waiting times Optimum Optimum Sub-Optimum Sub-Optimum Sub-Optimum Under-Provided

23 Examples Different Terminals Seoul-Incheon Airport Check-in Lobby LoS A/B LaGuardia Airport Check-in Lobby LoS E/F Vast check-in lobbies, comfortably sized hold rooms, high capacity baggage claim belts May be considered over-built by industry standards Older and capacity constrained Have not adapted airport operations and technology change Political decisions may impact improving LoS

24 Overdesign will not necessarily result in better level-of-service

25 Examples Same Terminal Guarulhos Airport Check-in Lobby (LoS A/B) Guarulhos Airport Check-in Lobby (LoS E/F) A facility can operate under LoS A or B during a certain season or time of day, but may operate at LoS E or F during other times Terminal facilities should be designed to maintain a minimum LoS, even during peak periods

26 Simulation

27 Direct Observation

28 Good baseline data is essential for calculating capacity

29 Santos Dumont Airport 2014 Statistics Pax 9.7M Ranking 7 th Ops 128,000 Airlines 4 Markets Domestic 12 International 0 Daily departures +160 Fleet Check-in Mainline jet 73% Turboprop/ regional jet 27% Counters 51 Kiosks 53 Security checkpoint lanes 8 Code Code Total B C Terminal contact stands Apron remote stands Total Baggage claim devices 6 Operator Infraero Terminal complex (m 2 ) 19,000

30 SDU Passenger Terminal 2 1

31 SDU Passenger Terminal 4 3

32

33 # of Flights Seats SDU Operational Profile Arrivals Departures Departure Seats Arrival Seats Represents a typical busy weekday, August 2015

34 SDU Space Allocation Space category Area (a) Passenger processing areas Check-in lobby 1,800 Security screening checkpoint 440 Total 2,240 Holdrooms Domestic 2,840 International - Total 2,840 Baggage processing Baggage make-up area 560 Baggage claim area 1,360 Baggage claim frontage (m) 135 Total 1,920 Customs and immigration - Public space Restrooms - landside 630 Restrooms - airside 140 Restrooms baggage claim 130 Public circulation 5,890 Secure circulation 2,080 Total 8,870 Space category Area (a) Concessions Non-secure concessions 2,260 Secure concessions 410 Concessions support Unk Total 2,670 Other Airline support 390 Airline ticket offices 470 Vacant Unk Total 860 Total area (b) 19,000 (a)areas rounded to the nearest 10 m 2. (b)inclusive of terminal area not listed above.

35 SDU Space Allocation

36 Porto Alegre International Airport 2014 Statistics Pax 8.4M Ranking 9 th Ops 92,960 Airlines 10 Terminal 1 Markets Domestic 17 International 5 Daily departures +100 Fleet Check-in Mainline jet 65% Turboprop/ regional jet 35% Counters 50 / 23 Kiosks 12 / 6 Security checkpoint lanes 9 / 4 Baggage claim devices 4 / 2 Operator Terminal complex (m 2 ) Infraero 37,600 / 15,500 Code C Terminal 1 Terminal contact stands 10 Apron remote hardstands 6 Terminal 2 Terminal contact stands 5 Apron remote stands 4 Total 25

37 POA Passenger Terminal 1 2 1

38 POA Passenger Terminal 2 4 3

39

40 # of Flights Seats POA Operational Profile Arrivals Departures Arrival Seats Departure Seats Represents a typical busy weekday, August 2015

41 POA Space Allocation Space category (a) Terminal 1 Terminal 2 Passenger processing areas Check-in lobby Security screening checkpoint Total 1, Holdrooms Domestic 1, Swing International Total 1, Baggage processing Baggage make-up area 1, Baggage claim-area 2, Baggage claim frontage (m) Total 3, Customs and immigration Public space Restrooms - landside Restrooms - airside Restrooms baggage claim Public circulation 5,980 1,150 Secure circulation 1,050 - Total 7,590 1,370 Space category (a) Terminal 1 Terminal 2 Concessions Non-secure concessions Secure concessions Concessions support unk unk Total 1, Other Airline support Airline ticket offices Vacant unk unk Total Total area (b) 37,600 15,500 (a)areas rounded to the nearest 10 m 2. (b)inclusive of terminal area not listed above.

42 POA Space Allocation Terminal 1 Terminal 2 8% 5% 6% 11% Passenger processing areas Holdrooms Baggage processing 5% 3% 18% 44% 4% 22% Customs and immigration Public space Concessions 34% 0% 23% 17% Other

43 Sinop Airport 2014 Statistics Pax 222,600 Ranking <30 th Ops 3,200 Airlines 2 Markets Domestic 3 International 0 Daily departures 6 Fleet Check-in Mainline jet 0% Turboprop/ regional jet 100% Counters 2 Kiosks 0 Security checkpoint lanes 1 Code C Terminal contact stands 0 Apron remote stands 2 Total 2 Baggage claim devices 1 Operator Sinop Terminal complex (m 2 ) 700

44 OPS Passenger Terminal

45

46 OPS Operational Profile Represents a typical busy weekday, August 2015

47 OPS Space Allocation Space category Area (a) Passenger processing areas Check-in lobby 100 Security screening checkpoint 20 Total 120 Holdrooms Domestic 120 International - Total 120 Baggage processing Baggage make-up area 60 Baggage claim area 140 Baggage claim frontage (m) 20 Total 200 Customs and immigration - Public space (b) Restrooms - landside unk Restrooms - airside unk Restrooms baggage claim unk Public circulation unk Secure circulation - Total unk Space category Area (a) Concessions Non-secure concessions 80 Secure concessions - Concessions support - Total 80 Other (c) Airline support 50 Airline ticket offices - Vacant - Total 50 Total area (d) 700 (a)areas rounded to the nearest 10 m 2. (b)information was not provided by the Airport. (c)some support space provided on an upper level of the building is not included. (d)inclusive of terminal area not listed above.

48 5. Capacity Assessment Process

49 Capacity Assessment Process Calculation 1: INPUTS Peak hour passengers OUTPUTS Area required Calculation 2: Area available Theoretical capacity Area required / area available = over / undersized Compare peak hour passenger throughputs to determine constrained areas

50 Functional Areas Assessed Departing Arriving

51 If you ve seen one airport, you ve seen one airport

52 Demand Analysis 1. Identify the peak month 2. Identify the average day 3. Apply load factors 4. Create daily profile

53 Identify the Peak Month CY2015 Monthly Seats and Operations Salvador International Airport

54 Daily Seats Identify the Average Day January 2015 Daily Seats Salvador International Airport Average /01/ /01/ /01/ /01/ /01/2015

55 Load Factors and Daily Profile Load factors transform seat counts into passenger counts Peak hour may not occur at top of every hour Distribute flights into 10-minute bins Plot on rolling 60-minute timeline Load factors can be obtained from airline investor reports, IATA, Diio, Oliver Wyman reports, etc.

56

57 Apron Capacity Match flights Count flights Compare against existing contact and remote stands

58 8. Planning for the Future

59 A Good Plan is Affordable Can be constructed Embraced by stakeholders Adaptable

60 Aircraft trends Source: Flight Global

61 Transportation Systems Declining use of auto ownership among millennials and city dwellers Increased use of ride-sharing apps and car sharing

62 Transportation Systems Self driving cars could affect parking needs and congestion on airport roadways Leading automakers expected to release self-driving cars within next five years

63 Check-in Trends Major Increase in Self-Service Check-in Source: SITA s 2015 Passenger IT Trends Survey, conducted globally in Q1 2015, in 17 countries across 5 continents, including Brazil.

64 Mobile Check-in Percentage of Passengers Carrying a Device Source: SITA s 2015 Passenger IT Trends Survey New Mobile Services in the Future Source: SITA s 2015 Passenger IT Trends Survey

65 Passenger Check-in Trends: Near-Term US airlines are rolling out home printed bag tagging, while Asian and European airlines are rolling out permanent bag tagging. Between mobile check-in and remote bag tagging, the check-in lobby will change significantly.

66 Self-Service Bag Drop Qantas was one of the first airlines to renovate an entire terminal to this process Several US airports such as Chicago O Hare have slowly begun to introduce the service with select airlines

67 Security Screening is Changing ANAC recently implemented extra security measures for domestic flights Mirrors international security Stricter bag spot checks Removal of electronic items Random passenger body checks Suggest passengers arrive two hours before their flight instead of 30 minutes Steep learning curve security line at CGH extended into arrivals hall and delayed five flights

68 Security Screening Worldwide Trends Transition security as a necessity to security as a service Known traveler programs Technology to improve experience Smart Security pilots

69 Boarding Biometric authentication: Alaska Airlines testing use of fingerprints as form of identification Self-boarding gates: JetBlue has self boarding gates at McCarran International Airport

70 Concessions Quick Response (QR) barcodes Decentralize / free up retail space Make purchases on a tight schedule Virtual shopping walls (Frankfurt and Delhi)

71 Concessions Targeted Marketing By developing demographic profiles of passengers, concessionaires will be able to target specific travelers Biometric technology could be used to augment the collection and utilization of passenger profile information Could be incorporated into virtual shopping or on-flight entertainment

72 Concessions Integration JFK T5: Centralized airside concessions mall JFK T5: Holdroom / Concessions integration LAX TBIT: Artist rendition of the Great Hall an airside concessions node SFO T2: Holdroom/Concessions integration

73 Concessions Integration Holdrooms with FIDS Comfortable varied seating Workspaces and waiting spaces Daylight and views J

74 Self-Service Trends Aruba s Queen Beatrix International Airport is the first airport in the world to provide a 100% self-service passenger experience.

75 Pax Flow: How Will It Change?

76 Sustainability at Airports

77 Capacity Terms Dynamic - maximum rate of persons through a system per unit of time Static - holding capacity of an area; number of units that can be held at one point in time