Three Articles are published Cost of Delay, Winners Vs Losers, and Airport Forecasting all topic are related to airlines and aviation industry

1. Civil Aviation & Meteorology Authority (Yemen) July - September 2012, issue 16
Winners vs. Losers
Aday in Sheharah
Airports Forecasting
www.camamagazine.com
The new Aviation
Systems
More Safety and Welfare for the Passenger

2. study 21
CAMA Magazine | issue 16 | September, 2012
Cost of Delay,
Rescheduling and
Cancellation In Airlines
Introduction
Usually Airlines are suffering from flights delay issues, but most of them control these problems and their causes, so the issue of flight delay may
create a bad impression on the airline image and its brand name in the market, and consequently it is directly related to the concerned airline
operation divisions and departments, from maintenance, flight operation, commercial and customer service, as they are interacted and integrated
divisions that serve for one mission, so every division has its own rules and impacts on dispatch the flight on time, and any negligence may reflects
on airline final performance, and cause the delay of the flight. In aviation industry the cost of delay is considerably high due the high gained revenue
of the flights and high direct fixed operating cost for a certain type of aircraft hence we measure the activities of an airline by its performance which
usually addressed by the performance report of Operation Control Committee OCC. Where the maintenance and material divisions are the main airline
departments that support the operation, as they are responsible for aircraft technical readiness and fulfill the provision of spare parts of the aircraft,
and tracking/ monitoring the technical operating performance by papering reliability report, which is similar as performance report, but its results are
technical oriented, i.e defining technical problems and failure diagnostic before its happen and cause a delay or cancelation, which play a major rule
in preventive maintenance program for the aircraft. Finally by referring to Boeing Company reports, the engineering and maintenance issues and
problems for aircraft are represents 30-40% of total delay cost for the flight in airline industry.8
Prepared by: Mohammed Salem Awad
Research Scholar – Aviation Management

3. STUDY22
OCC Operation Control
Committee:
The weekly report of this
committee is one of the main
sources of airline activity
evaluation and it is an effective tool
to explore and define deviations so
a proper action may take on time
and most of operating and serving
departments represents in the
committee, so this report rise the
initial signals to predicate defect
or trouble a certain failure in the
airline activity for one week period.
Delay Cost:
It is too complicated to evaluate
and calculate the delay cost in the
airline industry and its impacts on
the image and the brand of the
airline. So we can refer to Boeing
terms and definitions for delay
cost that addressed in AGIFORS -
Denver which are;
1- Passenger direct cost
2- Direct Operating Cost
3- Cost of unavailability of
scheduling Aircraft
4- Cost of losing the image and
the loyalty for the airline.
In our case we will use only two
factors in the analysis only:
1- Passenger direct cost
2- Direct Operating Cost
the calculation of delay or
cancellation cost will as the
following:
Direct Operating Cost + expected
income revenue of the delay or
cancelled flight.
And according to the study of
American Airlines – domestic
routes, the results are:
Delay from:
0 ~ 15 minute
No Calculation of Cost
16 ~ 60 minute
0.25 % ticket/min/pax
1 ~ 2 Hours
0.5 % ticket /min/pax
Approximately 1 out 8 passengers
will probably not buy their next
ticket on this airline.
2 ~ 5 Hours
All passengers will probably not
buy tickets on this airline again
for at least a year. And in this
stage the growth of delay cost
increase exponentially until reach
to 5 hours delay period (out of
business).
While the next figure explain the
relationship between these costs
and its average values, indicating
the direct cost of passenger may
happen after 20 min of delay time,
and its impact on the passenger
loyalty, image and the brand value
of the airline.
Impacts of Engineering and
Maintenance:
Referring to the Boeing Study,
the share impact of maintenance
and engineering causes may
reach 30-40 of total delay
causes. And the technical
causes are the main reasons for
cancellation of the flights and as
its shows in the previous figures,
the maximum delay period for
maintenance cause is 45-120
if there is no cancellation. And
the consequential effects of late
aircraft arrival play a major rule in
rescheduling the flights again.
Delay Cost - Yemenia Case
Study:
The period of 02/01/2010 to
12/03/2010 characterize by
repeated many delays in flights
–Yemenia. Among of that , the
technical delays and engine
failures of B737-800 fleet which
create a total mess in the flight
scheduling program. So the dealy
cases can be address in two
directions;
First: counting the repeated
delays issues
Second: the delay time
So delays can be caused by one
of the following reasons:
1- Delay of the flight of the
same aircraft type.
2- Delay of the flight may
cause the need to change
the type of the aircraft from
bigger to smaller capacity
which lead to extra cost of
spill passengers.
3- Delay of the flight may
cause the need to change
the type of the aircraft from
smaller to bigger capacity
CAMA Magazine | issue 16 | September, 2012
Figure (1) Measuring the time period costs American Airlines Study.
Figure (2) Delay Cost Elements - American Airlines Study.

4. 19STUDY 23
CAMA Magazine | issue 16 | September, 2012
Delay Time in Minute
Figure (3) Delay Factors of Yemen Airways
Figure (4) Frequency Distribution of Delay Periods
Delay Categories
FrequenciesFrequencies
which lead to extra cost of losing the
opportunity of un utilize seats for sale in last
minutes.
4- Aircraft Grounded cost, by sending another
aircraft for taking the passengers and
supported spare parts.
5- Some time suddenly two aircrafts ground
in the same time, and rise a hard time for
planners and consequently may lead to
cancel the flight.
6- Un readiness of the aircraft for unexpected
time.
7- Longer maintenance programs may lead to
delay the flights.
Analysis:
In spite of defining Boeing Company the main
factors that may cause the delays, pointing out the
maintenance /engineering and bad weather but
yemenia analysis results indicates another factors
that impact high influence of those mentioned
in Boeing Study. However technical and engine
failures remains the main factor in the period of
02/01/2010 to 12/03/2010
1- Transit Passengers
2- Technical Problem
3- Airport Security
4- ATC
5- Late Arrival of Aircraft
6- Bad Weather
7- Maintenance Problems
8- Other factors
As indicated in graph, the other factors take the
large share in the delay reasons, yemenia should
review all the delay items category so that the other
reasons well defined in the analysis and re casted
in the right way. Also similar category should be
merge to be one category as maintenance and
technical.
This lead us to the result of the analysis, so
Number of Delays
with less than 20 min =121 delays
with cumulative time = 1355 min
Number of Delays
with greater than 20 min =87 delays
with cumulative time = 4185 min
but for technical delays, it take larger time to fix
and rectify in spite of hidden function issues
Summary:
1- The analysis show the un availability of support
fleet, as the scheduling designed with one
supported aircraft. But in some cases of two
aircraft grounded in the same time led to a total
mess in scheduling that need to rescheduling
and delay the other flights.
2- The technical delay have the majority causes
of delays, and when its happen, its take a long
time.
3- In spite of the impact of transit passengers on
delay, the maximum allowable time period for
transit passengers is 45-60 min, but the delay
period may reach to 5 hours or more and effects
on the airline image in the market.
4- Advanced and prior corporation between
commercial and technical departments so that
they adapted and implemented a the right
scheduling without interruption based on the
sound of the market.
5- Brand name of the airline in the market may
get lose, if the airline repeat these delays, and
changing the capacities of aircrafts in the last
minutes.■
30~40%
from the total delay
cost for the flight in
airline industry in
the engineering and
maintenance issues
and problems for
aircraft.

5. 24 study
Winners vs. Losers
A
irline industry is a perishable industry. Today big names in the aviation world declare their bankruptcy, why!, I don’t think they don’t have the
facilities and tools to afford recovery and repositioning their carriers tracks. Actually it is like a big ship sinking and deriving (driving) everything
down. Today airline business runs as a wheel. If airlines make a good start and continue fairly with economic shocks from time to time, unless it
will collapse. In some cases for political reasons airline survive, while some counties prefer to spend the money on their flag carriers.
If the Thumb is characterized by 32 marks and Eye by 520 marks, then how we can define airline characteristic of point to point airline business
model. Definitely the basic airline data are Traffic Demand, Market Fare, and Operating Network (Distances). So each airline is characterized by these
three mean factors, while the fourth one is its Operating Cost. We will span and manipulate those three factors while cost element will be considered
as defined single figure (as step function). Off course we can use the actual value of the airline cost in the analysis, but that will be meaningless as the
objective is to develop the optimum operating curve of airline which represents the characteristic of the airline.So based on the airline inputs the issue
can be classified by multi-dimensional matrix which develop and reflect the outcomes of optimum operating curve of the airline. Consequently defining
airline positioning in that Matrix as winner or loser airline!.
Mohammed Salem Awad
Research Scholar Aviation Management
CAMA Magazine | issue 16 | September, 2012

6. 25study
Summary
The key principle of the analysis is to
position the tangible line that landmark
the coordinate of the matrix on the
curve. The outcome results will be of
RASK and CASK; while by mapping
optimum operating curve, the board
explores the complete financial
picture of airline position in region.
In case mix fleet airline, the annual
final results may give some initial
signals of airline financial health.■
Survival Airline:
This represents upper-right part above
the optimum operating curve. It is initially
started by Low Cost Carriers and ended by
Mega Carriers driven by cost and relayed on
economy of scale, fleet commonalty, large
capacity, higher frequency and many economic
factors that maintain the airline in survival level.
It is hardly gaining its profits with a very tight
margin. Its RASK is slightly higher than the
CASK. This situation is more likely to move
winners situation if they reduce their cost.
Critical Airline:
This is the lower-left part below the optimum
operating curve. Airlines suffer a hard
situation where they are operating by small
capacities in a low yield environments. It
may represents some regional airlines where
their CASK is usually matching their RASK.
It is more likely to move the loser situation.
The issue of these airlines is serving a wrong
markets. They don’t define their markets
properly. While they can be moved to winner
situation if they apply cost reduction strategy
and implement turnaround philosophy.
Loser Airline:
Most of airlines located in this part. It
is the lower-right part, simply indicated
when CASK is greater than RASK. It is
characterized by higher cost with low yield.
These airlines need urgent restructuring e
and implementing cost reduction strategy.
Carries do not have a clear vision and
strategy. It may represent flag carriers. Some
mega carriers that have poor brand name.
RASK & CASK:
The main product of the airline is offering seat
to move from one city to another city, i. e.
distance, in aviation terminology called ASK,
Available Seat Kilometers. The related cost
element is called CASK, i . e. Cost/ASK.
Likewise in revenue part, the income
revenue determine by the term
RASK, i. e. Revenue/ASK.
Simply Profit equal Revenue minus Cost
while in airline industry may represent by
dividing this equation by ASK, resulting
the following form: PASK = RASK-CASK
where PASK represent Profit per ASK.
Allocating the Right Aircraft Capacity:
The main factor for successful airlines is
to match the demand passengers/market
demand by the right configuration of aircraft.
Based on airline inputs of passengers, fares
and proposed network, using the concept
of U curve technique, the right capacity can
be defined. It might be matched the exciting
aircraft capacity it might be not. If it matches,
the airline on right track. If not, the airline
needs to reposition and restructure its fleet.
Airline Optimum Operating Curve:
In point to point airline business model, airline
can be defined by its Designed Network,
Market Fares, and Demand Passengers.
These are the basic factors that derive
Optimum Operating Curve of the airline. It acts
as thumb for airline that differentiates airline
from other airlines,, no two airline can be
similar. The unit cost per ATK or ASK is used
as step function in these scenarios, to plot and
map optimum operating curve of the airline.
Mathematically, the airline formula is
defined by the following terms ,i. e,
(Capacity, Frequency) = function of (Pax, Fare,
Distance, and Cost). Based on airline strategy,
either to emphasis on capacity or frequency,
these two terms have a counteract effects.
So the airline can position its fleets
according to the actual cost the aircraft and
its configurations and capacities in terms
of seats, i. e. aircrafts that lay on the curve
represent the best solution for the airline.
But if we look closely to the curve, we
can read and explore airline heath
situation by defining the boundaries of the
analysis in multi-dimensional matrix.
Winner vs Loser Position Matrix
Based on the output of optimum operating
curve of the airline, the exciting fleet will plot
and map on the graph, there will be four
decision outcomes to reach the healthy
situation of airline. These situations are
Winner, Survival, Critical and Loser airlines.
Usually the starting origin point is 160 seat
Winner Airline:
Airlines position themselves on the upper-
left part above the optimum operating curve.
They are characterized by high yields, lower
cost, medium capacity, clear strategy and well
organized and structure airline. They operate
based on the sound of the market, these
includes Air Taxi, Business Jets, and Legacy
Airlines. Simply it can be realized when, RASK
is greater than CASK in their annual reports.
Survival
Loser
Winner
Critical
CostinUS$
C Total Cost
Selected Parameter
A Cost of Services
B Cost
of Lose
Opportunity
CAMA Magazine | issue 16 | September, 2012
A321
A318
A320
A319
B737-800
B737-700
Capacity(Seat)
Cost per ATK

7. 28
Prepared by: Mohammed Salem Awad
Research Scholar – Aviation Management
Matching Long Range Data Targets
By Short Range Data Targets
“Plans are
nothing;
planning is
everything.”
Dwight D. Eisenhower
Airports Forecasting
Forecasting is the right tool for a fair decision making, we use it to create a proper plans
,activities and setting up budgets. But what is the right effective model, what are the
right parameters to measure the goodness of fits, and how to plan to match the long
range targets by a short range targets, can we get same answer from different models.
This is what we will address it in….
Nice Airport Case Study:
1- Developing Long Range Targets:
Trend Model:
Based on annual historical data period (1950-2011)
Input Data: 51 sets (Annually)
Coefficient of Determination: 99.6%
Signal Tracking: 0.0000011
Results:
Passengers Forecast 2012= 10,467,360
Passengers Forecast 2013= 10,493,391
2- Developing Short Range Targets:
Seasonality Model:
Based on monthly 3 years data period (2009-2011)
Input Data: 36 sets (Monthly)
Coefficient of Determination: 96.7%
Signal Tracking: -30.14
Results:
Passengers Forecast 2012= 10,467,360
Passengers Forecast 2013= 10,493,391
Summary:
The results are fairly matched, so it possible to plan in such a way that, we utilize the
annual trends to meet the annual cumulative forecast of the seasonality model for two
forecasted years, keeping in mind the pre-request constrains for both models.
400000
500000
600000
700000
800000
900000
1000000
1100000
1200000
1300000
NoofPassengers
TIME (Month)
Forecast
Actual
0
2000000
4000000
6000000
8000000
10000000
12000000
Passengers
Years
Forecast
Passengers
Forecasting 2012, 2013
Seasonlity Model
Forecasting 2012, 2013
1950 - 2011 Passengers
Coefficient of
Determination = 0.996
Signal Tracking = 0.0000011
R
2
= 96.7%
S.T.= -30.17
2012 (F)= 10,467,360 Pax
2013 (F)= 10,493,391 Pax
2012(F)= 10,467,360 Pax
2013(F)= 10,493,391 Pax
CAMA Magazine | issue 16 | September, 2012

8. 29AIRPORTS Forecasting
Airports Forecasting:
Airport forecasting is an important issue in
Aviation industry. It becomes an integral parts of
transportation planning. It sets targets and goals
for the airports, either for long term or medium term
planning. The primary statistical methods used in
airport aviation activity forecasting are market share
approach, econometric modeling, and time series
modeling.
Model Used:
BaBased on a historical data of the airports, (3
years on monthly bases) the mathematical model is
developed where its fairness and goodness of fit can
be defined by two important factors:
R
2
(Coeff. Of Determination) > 80%
S. T (Signal Tracking) ..(-4 < S.T. < 4)
This time we try to set (S.T.) to Zero
Airport Performances:
There are many factors that may measure the airport
performance, mainly:
1) Number of Passengers
2) Aircraft Movement and;
3) Freight
SANA’A Airport
Sana’a International Airport or El Rahaba Airport
(Sana’a International) (IATA: SAH, ICAO: OYSN) is
an international airport located in Sana’a, the capital
of Yemen. Recently Yemen passes in a transition
phase, as results a democracy. This situation effects
on 2011 data base.
So the basic analysis addressing 2008, 2009, and
2010. And the forecasted period are 2011 and 2012.
But in this issue we are addressed the Yemenia and
Other Operators
Yemenia:
Passenger Forecasting 2012 = 764,398 Pax
Peak Periods: July-August
Annual Growth : (0.02) %
The Model is not fair as R = 44%
Other Operators:
Passenger Forecasting 2012 = 600513Pax
Peak Periods: July
Annual Growth : 0.08 %
The Model is not fair as R = 77%
Total –
Yemenia and Other Operators
Passenger Forecasting 2012 = 1,340,118Pax
Peak Periods: July - August
Annual Growth : 0.01 %
The Model is not fair as R = 66%
yemen Airports
Sanaa Airport, Forecasting 2011, 2012
Seasonlity Model (Other Carriers)
Sanaa Airport, Forecasting 2011, 2012
Seasonlity Model (Yemenia)
Sanaa Airport, Forecasting 2011, 2012
Seasonlity Model (IY + Other Carriers)
20000
25000
30000
35000
40000
45000
50000
55000
60000
65000
70000
NoofPassengers
TIME (Month)
Forecast
Actual
80000
90000
100000
110000
120000
130000
140000
150000
160000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 77%
S.T.= 00
2012(F) = 600,513 Pax
Annual Growth : 0.08
R
2
= 66%
S.T.= -0.00
2012(F)= 1,340,118 Pax
Annual Growth : 0.01
40000
50000
60000
70000
80000
90000
100000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 44%
S.T.= 00
2012(F)= 764,398 Pax
Annual Growth: (0.02)
CAMA Magazine | issue 16 | September, 2012

9. 30 AIRPORTS Forecasting
international Airports
Paris-Charles de Gaulle Airport
(IATA: CDG, ICAO: LFPG) (French: Aéroport Paris-
Charles de Gaulle), is one of the world’s principal
aviation centers, as well as France’s largest airport.
It is named after Charles de Gaulle (1890–1970),
leader of the Free French Forces and founder of the
French Fifth Republic. It is located within portions of
several communes, 25 km (16 mi) to the northeast
of Paris. The airport serves as the principal hub for
Air France. In 2011, the airport handled 60,970,551
passengers and 514,059 aircraft movements,
making it the world’s sixth busiest airport and
Europe’s second busiest airport (after London
Heathrow) in passengers served.
Passenger Forecasting 2012= 62,166,461 Pax
Annual Growth: 2.6%
The Model is fair fitted as R
2
= 93%
Denver International Airport
(IATA: DEN, ICAO: KDEN, FAA LID: DEN), often
referred to as DIA, is an airport in Denver, Colorado.
In 2011 Denver International Airport was the 11th-
busiest airport in the world by passenger traffic with
52,699,298 passengers. It was the fifth-busiest
airport in the world by aircraft movements with over
635,000 movements in 2010.. Denver International
Airport is the main hub for low-cost carrier Frontier
Airlines and commuter carrier Great Lakes Airlines. It
is also the fourth-largest hub for United Airlines.
Passenger Forecasting 2012 = 53,986,884 Pax
Annual Growth: 2.21%
The Model is fair fitted as R
2
= 97.7%
Chicago O’Hare International Airport
(IATA: ORD, ICAO: KORD, FAA LID: ORD), also
known as O’Hare Airport, O’Hare Field, Chicago
Airport, Chicago International Airport, or
simply O’Hare, is a major airport located in the
northwestern-most corner of Chicago, Illinois, United
States. prior to 1998, O’Hare was the busiest airport
in the world in terms of the number of passengers.
O’Hare has a strong international presence, with
flights to more than 60 foreign destinations: it is the
fourth busiest international gateway in the United
States behind John F. Kennedy International Airport
in New York City, Los Angeles International Airport
and Miami International Airport.
Passenger Forecasting 2012 = 67,859,340 Pax
Annual Growth: 1.34 %
The Model is fair fitted as R
2
= 97.3%
Forecasting 2012, 2013
Seasonlity Model
Forecasting 2012, 2013
Seasonlity Model
Forecasting 2012, 2013
Seasonlity Model
3000000
3500000
4000000
4500000
5000000
5500000
6000000
6500000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 93 %
S.T.= 0
2012(F)= 62,166,461 Pax
2013 (F)= 63,812,317 Pax
Annual Growth= 2.6%
3000000
3500000
4000000
4500000
5000000
5500000
6000000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 97.7 %
S.T.= 0
2012 (F)= 53,986,884 Pax
2013 (F)= 55,184,393 Pax
Annual Growth: 2.21%
3000000
3500000
4000000
4500000
5000000
5500000
6000000
6500000
7000000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 97.3%
S.T.= 0.00
2012 (F)= 67,859,340 Pax
2013 (F)= 68,773,005 Pax
Annual Growth: 1.34%
CAMA Magazine | issue 16 | September, 2012

10. Edmonton International Airport
(IATA: YEG, ICAO: CYEG) is the primary air
passenger and air cargo facility in the Edmonton
region of the Canadian province of Alberta. It is
a hub facility for Northern Alberta and Northern
Canada, providing regularly scheduled nonstop
flights to over fifty communities in Canada, the
United States, Latin America and Europe. It is one
of Canada’s largest airports by total land area, the
5th busiest airport by passenger traffic, and the
10th busiest by aircraft movements. Operated by
Edmonton Airports and located 14 NM (26 km; 16
mi) south southwest of downtown Edmonton, in
Leduc County, and adjacent to the City of Leduc, it
served over 6.2 million passengers in 2011.
Passenger Forecasting 2012 = 6,329,057 Pax
Annual Growth : 1.4 %
The Model is fair fitted as R2 = 91.9 %
London Heathrow Airport or Heathrow
(IATA: LHR, ICAO: EGLL) is a major international
airport serving London, England, United Kingdom.
Located in the London Borough of Hillingdon, in
West London, Heathrow is the busiest airport in
the United Kingdom and the third busiest airport in
the world (as of 2012) in terms of total passenger
traffic, handling more international passengers than
any other airport around the globe. It is also the
busiest airport in the EU by passenger traffic and the
third busiest in Europe given the number of traffic
movements, with a figure surpassed only by Paris-
Charles de Gaulle Airport and Frankfurt Airport.
Passenger Forecasting 2012 = 70,557,827 Pax
Annual Growth : 2.6 %
The Model is fair fitted as R2 = 89 %
Nice Côte d’Azur Airport
(IATA: NCE, ICAO: LFMN) is an airport located
3.2 NM (5.9 km; 3.7 mi) southwest of Nice, in the
Alpes-Maritimes department of France. The airport
is positioned 7 km (4 mi) west of the city centre,
and is the principal port of arrival for passengers
to the Côte d’Azur. It is the third busiest airport in
France after Charles de Gaulle International Airport
and Orly Airport, both in Paris. Due to its proximity
to the Principality of Monaco, it also serves as the
city-state’s airport, Some airlines marketed Monaco
as a destination via Nice Airport. it is also serves as
a hub for Air France.
Passenger Forecasting 2012 = 10,496,380 Pax
Annual Growth : 2.62 %
The Model is fair fitted as R2 = 98.3 %
31AIRPORTS Forecasting
international Airports
Forecasting 2012, 2013
Seasonlity Model
Forecasting 2012, 2013
Seasonlity Model
Forecasting 2012, 2013
Seasonlity Model
400000
500000
600000
700000
800000
900000
1000000
1100000
1200000
1300000
NoofPassengers
TIME (Month)
Forecast
Actual
Optimum Solution
R
2
= 98.3 %
S.T.= 0
2012 (F)= 10,496,380 Pax
2013 (F)= 10,772,005 Pax
Annual Growth : 2.6 %
450000
470000
490000
510000
530000
550000
570000
590000
610000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 91.9%
S.T.= 0
2012(F)= 6,329,057 Pax
2013 (F)= 6,419,625 Pax
Annual Growth= 1.4%
4000000
4500000
5000000
5500000
6000000
6500000
7000000
7500000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 89%
S.T.= 0
2012(F)= 70,557,827 Pax
2013(F)= 72,406,685 Pax
Annual Growth: 2.6%
CAMA Magazine | issue 16 | September, 2012