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DEVELOPING A MODEL TO ANALYZE THE IMP ACTS OF SELF-SERVICE AND WEB CHECK-IN AT AIRPORTS ANNEXURE A Results of Statistical Analysis for Processing Time

Annexes Mihir Baxi

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DEVELOPING A MODEL TO ANALYZE THE

IMPACTS OF SELF-SERVICE AND WEB

CHECK-IN AT AIRPORTS

ANNEXURE A

Results of Statistical Analysis for Processing Time

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Developing a Model to analyze the impacts of Self- ervice and Web Check-in at airports

Annexure A- Results of Statistical Analysis for Processing Time

A-1

ANOVA TES T

The processing times where observed at three airports and it was felt necessary to

analyze if the data at all three airports has significant variations in the data due to the

change in the group size or number of bags per passenger.

Thus, statistical analysis was carried out to confirm the same. The single factor Analysis

of Variance was performed for all the check-in modes. The results of the test are

shown in Table 1, Table 2 and Table 3. It was concluded that there is no significant

variations in the data collected at three airports and all the samples can be pooled

together.

SUMMARY F TEST FOR CHECK IN COUNTERS

roups Count um Average Variance

LCY 78 1:43:18 01:19 00:00

MAN 149 3:40:30 01:29 00:00

ANOVA

ource of Variation S Df MS P-value F crit  

Between Groups 00:00 1 00:00 07:03 0.186607 11:42

Within Groups 00:07 225 00:00

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A-2 Developing a Model to analyze the impacts of Self-service and Web Check-in at airports

nnexure A- Results of Statistical Analysis for Processing Time

SUMMARY

Groups Count Sum Average Variance

LCY 32 1:01:21 01:55 00:00

MAN 28 0:31:45 01:08 00:00

LHR 101 2:28:35 01:28 00:00

ANOVA

ource of Variation S Df MS F P-value F crit  

Between Groups 00:00 2 00:00 02:17 0.0246 16:41

Within Groups 00:08 158 00:00

Total 00:09 160

Table 3 - Results of ANOVA test for Self-Service Kiosks

PROCESSING TIME FOR  MODEL

The ANOVA test shows that there is no significant variation in the data observed at

three airports thus the all the samples were pooled together. The pooled samples

were than analyzed for the probability distributions and the results of the analysis are

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Developing a Model to analyze the impacts of Self- ervice and Web Check-in at airports

Annexure A- Results of Statistical Analysis for Processing Time

A-3

Self-Service Kiosks

Mean 01:56

Standard Error 00:03

Median 01:47

Mode 02:00

Standard Deviation 00:58

Sample Variance 00:00

Kurtosis 46:40

Skewness 20:15

Range 06:05

Minimum 00:10

Maximum 06:15

Count 384

Largest(4) 05:49

Smallest(4) 00:19

Confidence Level (95.0%) 00:06

Table 5 - Statistical data of pooled samples for Self-Service Kiosks

ff

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A-4 Developing a Model to analyze the impacts of Self-service and Web Check-in at airports

nnexure A- Results of Statistical Analysis for Processing Time

0

10

20

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60

70

80

90

       F      r      e      q      u      e      n      c      y

Processing Time

Processing Time- Check-In

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Developing a Model to analyze the impacts of Self- ervice and Web Check-in at airports

Annexure A- Results of Statistical Analysis for Processing Time

A-5

Figure 2 - Histogram of Processing Time for Self-Service Kiosks

Fi 3 Hi t f P i Ti f B D ff

0

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30

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       F      r      e      q      u      e      n      c      y

Processing Time

Processing Times - Bag Drop-off 

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DEVELOPING A MODEL TO ANALYZE THE

IMPACTS OF SELF-SERVICE AND WEB

CHECK-IN AT AIRPORTS

ANNEXURE B

Simulation Model: Description and Users Guide

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Developing a Model to analyze the impacts of Self-service and Web Check-in at airports

Annexure B - Simulation Model: Description and Users Guide

B-1

INTRODUCTION

The Simulation model is designed in MS Office Excel 2007. The simulation model

simulates the check-in process at airport with self-service and web check-in. It is

designed to estimate the requirements for a two step self service check-in, which

includes kiosks and bag drop-off at the airport. The model enables the users to

analyze the impacts of the changes made in resources and estimate the requirements

of check-in counters, kiosks and bag drop-off. The structure of the model, the inputs

required and interpretation of results have been explained to enable the user to get

the maximum utility from the model.

The model has been kept as simple as possible and there is no additional software or

macros required to run the simulation. The model is limited to the size of the inputs.

The model can only compute for maximum 2500 Peak hour passengers or maximumresources of 25 in each mode.

1. Structure of Model

The model is designed in Excel2007. To use the model and give inputs, it is first

necessary to understand the structure of the model. The data is arranged in number of 

h t E h t h dl diff t t f th d l d h b i d

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B-2 Developing of Model to analyze the impacts of Self-service and Web Check-in at airports

nnexure B – Simulation Model: Description and Users Guide

Figure 1 - Layout of the Excel Worksheet

The sheets are arranged in order of the importance to user. The first two sheets

“Inputs” and “Arrival profiles” are the input sheets where the user has to input the key

l d ti f th d l Th t f h t “Q i Ti ” “S

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Developing a Model to analyze the impacts of Self-service and Web Check-in at airports

Annexure B - Simulation Model: Description and Users Guide

B-3

2. Inputs in the Model

To run the model it is necessary to give correct inputs. Each input parameter is

discussed and the key characteristics and limitations are discussed in this section to

enable the user to give correct inputs. The input sheet is as shown in the Figure 2.

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B-4 Developing of Model to analyze the impacts of Self-service and Web Check-in at airports

nnexure B – Simulation Model: Description and Users Guide

2.3. Check-in Open Times

This is the opening time for the all the counters, kiosks and bag drop-off. The time has

to be given in minutes. It is necessary to decide the check-in open times as that will

govern the number of passengers arriving at the airport. This input cannot be Zero.

2.4. Check-in Close Times before STD

It is time in minutes for closing of check-in counters before departure time of the

flight. If assumed zero, the model considers the full duration between check-in opentimes and departure.

2.5. Passengers by each Check-in Mode

This is expected breakup of the passengers using each mode to check-in in

percentages. The user needs to provide the information such that the expected break

up totals 100%. The numbers for each mode is calculated by the model and shown in

the next cell to it, which cannot be modified by the user. If any of the modes are not

available at the airport the user can input zero for the mode, but the total of all three

cells should be 100. The user can modify these proportions to analyze the impacts on

the available resources.

2.6. Resources Required

Th ll h i d f i h Th ll

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Developing a Model to analyze the impacts of Self-service and Web Check-in at airports

Annexure B - Simulation Model: Description and Users Guide

B-5

times and is to be given by user and thus has been converted to percentages. So the

user has to first convert the total time in percentage and passengers arriving at each

10% time interval should be calculated and used as input in one of the three columns

B, C & D as see in the Figure 3.

Figure 3 - Input for Arrival Profile

Th h ld h h h di f h fil d ill b bl i l

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B-6 Developing of Model to analyze the impacts of Self-service and Web Check-in at airports

nnexure B – Simulation Model: Description and Users Guide

Figure 4 - Queuing Times and Other details

The table also summarizes the Maximum Wait Time and Average Wait Time for each

mode. The average Total process times is also indicated in the last column. The total

process time includes the waiting time and processing time.

3.2. Server Usage

This sheet shows how many passengers were processed by each server in proportion

and in numbers. The table enables the user to understand usage of server. The user

can compare the performance of each server and decide if he/she wants to reduce one

server which is underutilized.

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Developing a Model to analyze the impacts of Self-service and Web Check-in at airports

Annexure B - Simulation Model: Description and Users Guide

B-7

Fi 6 W it Ti G h

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B-8 Developing of Model to analyze the impacts of Self-service and Web Check-in at airports

nnexure B – Simulation Model: Description and Users Guide

Fi 7 P Ti G h

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D EV ELO PI NG A MO DE L T O A NA LYZE

IMPACTS OF SELF-SERVICE AND WEB

CHECK-IN AT AIRPORTS

ANNEXURE C

Results from Simulation Model:

Scenario 1-Scenario 5

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Cranfield University | Department of Air Transport C-1 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

As-is Model

Figure -1 Wait Times, Check-in Counters - As-is Model

Figure -2 Process Times, Check-in Counters - As-is Model

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Cranfield University | Department of Air Transport C-2 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

As-is Model

Figure -3 Wait Times, Bag Drop-off - As-is Model

Figure -4 Process Times, Bag Drop-off - As-is Model

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Annexure C- Results from Simulation Model

Scenario 1

Figure -5 Wait Times, Check-in Counters - Scenario 1

Figure -6 Process Time, Check-in Counters - Scenario 1

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Cranfield University | Department of Air Transport C-4 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

Scenario 1

Figure -7 Wait Times, Self Service Kiosk - Scenario 1

Figure -8 Process Times, Self Service Kiosk - Scenario 1

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Cranfield University | Department of Air Transport C-5 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

Scenario 1

Figure -9 Wait Times, Bag Drop-off - Scenario 1

Figure -10 Process Times, Bag Drop-off - Scenario 1

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Annexure C- Results from Simulation Model

Scenario 2

Figure -11 Wait Times, Check-in Counters - Scenario 2

Figure -12 Process Times, Check-in Counters - Scenario 2

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Annexure C- Results from Simulation Model

Scenario 2

Figure -13 Wait Times, Self Service Kiosk - Scenario 2

Figure -14 Process Times, Self Service Kiosks - Scenario 2

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Annexure C- Results from Simulation Model

Scenario 2

Figure -15 Wait Times, Bag Drop-off - Scenario 2

Figure -16 Process Times, Bag Drop-off - Scenario 2

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Annexure C- Results from Simulation Model

Scenario 3

Figure -17 Wait Times, Check-in Counters - Scenario 3

Figure -18 Process Times, Check-in Counters - Scenario 3

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Annexure C- Results from Simulation Model

Scenario 3

Figure -19 Wait Times, Self Service Kiosks - Scenario 3

Figure -20 Process Times, Self Service Kiosks - Scenario 3

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Annexure C- Results from Simulation Model

Scenario 3

Figure -21 Wait Times, Bag Drop-off - Scenario 3

Figure -22 Process Times, Bag Drop-off - Scenario 3

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Cranfield University | Department of Air Transport C-12 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

Scenario 4A

Figure -23 Wait Times, Check-In Counters - Scenario 4A

Figure -24 Process Times, Check-In Counters - Scenario 4A

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Cranfield University | Department of Air Transport C-13 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

Scenario 4A

Figure -25 Wait Times, Self Service Kiosks - Scenario 4A

Figure -26 Process Times, Self Service Kiosks - Scenario 4A

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Cranfield University | Department of Air Transport C-14 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

Scenario 4A

Figure -27 Wait Times, Bag Drop-off - Scenario 4A

Figure -28 Process Times, Bag Drop-off - Scenario 4A

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Annexure C- Results from Simulation Model

Scenario 4B

Figure -29 Wait Times, Check-In Counters - Scenario 4B

Figure -30 Process Times, Check-In Counters - Scenario 4B

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Annexure C- Results from Simulation Model

Scenario 4B

Figure -31 Wait Times, Self Service Kiosks - Scenario 4B

Figure -32 Process Times, Self Service Kiosks - Scenario 4B

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Annexure C- Results from Simulation Model

Scenario 4B

Figure -33 Wait Times, Bag Drop-off - Scenario 4B

Figure -34 Process Times, Bag Drop-off - Scenario 4B

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Annexure C- Results from Simulation Model

Scenario 4C

Figure -35 Wait Times, Check-In Counters - Scenario 4c

Figure -36 Process Times, Check-In Counters - Scenario 4C

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Annexure C- Results from Simulation Model

Scenario 4C

Figure -37 Wait Times, Self Service Kiosks - Scenario 4C

Figure -38 Process Times, Self Service Kiosks - Scenario 4C

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Annexure C- Results from Simulation Model

Scenario 4C

Figure -39 Wait Times, Bag Drop-off - Scenario 4C

Figure -40 Process Times, Bag Drop-off - Scenario 4C

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Cranfield University | Department of Air Transport C-21 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

Scenario 5A

Figure -41 Wait Times, Check-In Counters - Scenario 5A

Figure -42 Process Times, Check-In Counters - Scenario 5A

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Cranfield University | Department of Air Transport C-22 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

Scenario 5A

Figure -43 Wait Times, Self Service Kiosks - Scenario 5A

Figure -44 Process Times, Self Service Kiosks - Scenario 5A

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Cranfield University | Department of Air Transport C-23 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

Scenario 5A

Figure -45 Wait Times, Bag Drop-off - Scenario 5A

Figure -46 Process Times, Bag Drop-off – Scenario 5A

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Cranfield University | Department of Air Transport C-24 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

Scenario 5B

Figure -47 Wait Times, Check-In Counters - Scenario 5B

Figure -48 Process Times, Check-In Counters - Scenario 5B

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Cranfield University | Department of Air Transport C-25 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

Scenario 5B

Figure -49 Wait Times, Self Service Kiosks - Scenario 5B

Figure -50 Process Times, Self Service Kiosks - Scenario 5B

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Annexure C- Results from Simulation Model

Scenario 5B

Figure -51 Wait Times, Bag Drop-off - Scenario 5B

Figure -52 Process Times, Bag Drop-off - Scenario 5B

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Annexure C- Results from Simulation Model

Scenario 5C

Figure -53 Wait Times, Check-In Counters - Scenario 5C

Figure -54 Process Times, Check-In Counters - Scenario 5C

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Annexure C- Results from Simulation Model

Scenario 5C

Figure -55 Wait Times, Self Service Kiosks - Scenario 5C

Figure -56 Process Times, Self Service Kiosks - Scenario 5C

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Cranfield University | Department of Air Transport C-29 Developing a Model to Analyze the impacts of Self-service and Web Check-in at Airports

Annexure C- Results from Simulation Model

Scenario 5C

Figure -57 Wait Times, Bag Drop-off - Scenario 5C

Figure- 58 Process Times, Bag Drop-off - Scenario 5C