Changes in Management of Coventry Airport

Abstract

This report will try to analyse and allocate arrival and departure of airplanes at Coventry airport in the United Kingdom. The main aim of the paper is to reduce the number of flights that are diverted to Birmingham international airport at the same time reduce the time the planes spent queuing on land before take off. Another aim will be o increase the size of aeroplane that land at the airport and reduce the time spent by aeroplane queuing before landing.

The report will start by examining the existing system and the looking at ways to improve the system with under various scenarios. Therefore, two scenarios will be taken into consideration. The first scenario is sequencing while the second scenario is to observe some delays at the two terminals of the airport. Various factors will not be ignored such as the initial capital outlay required to make the airport efficient, the number of staff required to be employed and the benefit that will accrue from necessary changes.

Introduction

The paper will begin with the current system and potential improvement that need to be carried out in order to reduce the queuing system and diversion of airplanes to Birmingham international airport. This will reduce the cost of operation and increase the revenue for the airport. The model that will be used in this system will show the entry of an aeroplane and the queuing time the aeroplane spent in the system. There are eight gates and there are 2,795 light aeroplane arrivals, 1807 medium planes and 871 jumbo jets that arrive at the airport. It is estimated that aeroplanes arrive at the airport at an average of 44 minutes exponentially and the percentage arrival is distributed as follows.

The proposal will consider the idea of improving the terminals where the queuing of aeroplanes will be reduced using simulation. It will also reduce the number of aeroplanes that are diverted to Birmingham international airport.

The current model

Take off and arrival sequencing

The main problem of the current system is that most aeroplanes are diverted to Birmingham international airport while others are put on hold in the air where they end up loosing fuel as they wait to land. The single runway of the airport pauses also a problem, which means to be sorted out. In the airport, there are two terminals 1 and 2, which is used by passengers in arriving and departing. Terminal 2 has its own gates as well as terminal one. The numbers of aeroplanes that land into the airport are as follows.

Terminal one has 1, 2, 3, 4 and 5 while terminal 2 has got 6 to 8. These terminals have the following queuing probabilities.

It is possible for aeroplanes to be delayed longer than normal in the air or on land before landing or taking off respectively. There is need to separate take off and landing times for aeroplanes. The separation between landing off and taking off aeroplanes will depend on the three types of aeroplanes that arrive at the airport. Their arrival is not asymmetric therefore a model will be required to help in designing and improving the airport landing and take off system.

Consideration should be taken about the aeroplanes but arrive and take off at the same time because there is only one run away in the airport. The idea of consecutive landing should be taken to consideration and its effects on the security of the passengers also taken into consideration. The weather and time of the day will also be another impending factor while designing a system for the aeroplane takes off.

However, the system will be designed without considering the above-mentioned factors as they cannot be controlled therefore the rooting system will be designed based on the runway available. Delay of airplanes arrival and departure is a performance measure on part of the management, as it will involve cost, which can be very high. Improvement on delay and departure is therefore an improvement on part of the management is very important (Atkin, Burke and Greenwood, 2009).

The management should be able to reschedule it arrivals rates in order to have a cost saving. This will involve a simple model or system that has one terminal and one gate thus a single crew. The queue discipline is first-come, first served, and it is assumed that a Poisson distribution and service time can approximate the airplane arrival rate by negative exponential distribution. There is no limit on length on length of queue.

Planes circle in stack before being given permission to land in airports. Unfortunately, we cannot eliminate waiting without incurring in ordinate expenses. In fact, all we can achieve is to reduce its adverse impact to tolerable levels.

Queuing deals with quantifying the phenomenon of waiting in lines using representative measures of performance, such as average waiting time in queue, and average facility utilization. The results of queuing analysis can be used in the context of a cost optimisation model, where the solution of the costs offering the service and of waiting in minimized. The cost of service increases with the increase in the level of service. At the same time, the cost of waiting decreases with the increase in level of service and vice-versa (Atkin, Burke and Greenwood, 2009).

Plane is a finite source because the passengers are being limited the arriving service by waiting the plane to land in an airport. From the standpoint of analysing queues, the arrival process is represented by the inter-arrival time between the plane and the service described by the service time per plane. The inter-arrival and service times can be probabilities as in the operation or deterministic as in the arrival of a plane.

A model for sequencing

The current model of the aeroplane arrival and take off is designed as follows.

Let d_j the actual arrival or take off time from Coventry airport and et_j be the earliest time an airplane can run or leave the airport. Let t_s be the time the aeroplane is at the airspace. Therefore, the model will have the following objective (Atkin, Burke, Greenwood and Reeson, 2008).

• d_j ≥ et;
• dj ≥ ec;
• d_j ≥ d_i +Rs_ij i s.t ts_i ts_j

Time taken to land and take off

The airplanes takes 44 minutes to land and the take off time can be estimated using the estimate formula:

• d_j ≥ et;
• dj ≥ ec;
• d_j ≥ d_i +Rs_ij i s.t ts_i ts_j

“In order to predict when an aircraft would take off for a given take-off sequence, it is necessary to determine the earliest time at which it can do so. Predicting this prior to the aircraft reaching the holding area requires knowing the time at which an aircraft will be ready to push back from the stand and the taxi time from the stand to the runway. Due to the difficulty of predicting the time at which an aircraft will be ready for push back and the time required to reach the holding area, the current mode of operations is to release aircraft from the stands as soon as the workload for the ground controller will permit, get them to the runway holding area, and allow the runway controller to perform the take-off sequencing once they get there” (Atkin, Burke and Greenwood, 2009).

As stated earlier the model depends on weather and the number of airplanes in the queue to land or take off. However, I should clarify at moment that an airplane takes off (Atkin, Burke, Greenwood and Reeson, 2007).

Identifying the key areas of problem

For Coventry Airport, the business model is built targeting larger segment of customers, reaching out to more destinations along with the additional customer relationship programs they offer. Apart from all these, hub-and-spoke network has to be backed by a highly sophisticated information system and developed infrastructure to compliment the complexity of their operations. According a study the low cost carriers reduce their prices by paying lower salaries to employees, using cheaper pilots side by side they are leveraging all their resources efficiently to attain cost leadership. According to the study conducted by Beasley, Krishnamurthy, Sharaiha and Abramson, only 5 percent of the cost gap is explained by the extra services the hub-and-spoke network offers (Beasley, Krishnamurthy, Sharaiha and Abramson, 2000).

The major difference is contributed by the production model choice. It attributes to about 65 percent of the cost gap. Thus, the relative levels of complexity, which makes the difference between the two segments. However, airports like Coventry Airport are constantly trying to cut down on cost on the labour and employee segment, by announcing stiff pay cuts and sacking of employees. Nevertheless, hardly has it seemed to solve the problems for them.

To compete in long term they have to look at other aspects, like to focus on the fundamental structural differences. To make their business model competitive Coventry Airport has to focus on some key parameters. However, it is an industry driven company but certain level of adjustment is required to adapt to the situation.

These changes are required in their core business structure only. In their present form of operation, the hub-and –spoke airports schedule flights in a wave system, according to which departures and arrivals are more concentrated during the peak hours to cater to maximum number of customers at a time. This system affects negatively, resulting in longer aircraft turnaround, traffic congestions and aircraft downtime at the hub cities. This will certainly result in lower resource utilization (Bolender and Slater, 2000).

The common strategy observed among the major airports is to concentrate on the frequent fliers connecting to shorter destination. This is done mainly with an aim to fill up the empty seats that would have otherwise been empty. Various studies shows that this process results in the complications in the logistic system, which ultimately raises the cost of the airports. Thus, the airport should carefully trade-off between the effectiveness of operation and connectivity.

This approach seems to simplify the landing handling operations also cost reduction on the top of it. Airports industry can address to various industries that have successfully reduced the amount of complexity. The underlying principle of this approach is to segment the various complex operations under different business streams.

That means to address separate complex activities, separate processes have to created and each complexity in the process should be addressed on the amount of money a customer is paying for that added benefit provided. This breaking down of the work helps in identifying the areas where most costs are being incurred without much perceived benefits. However, currently the business model of Coventry Airport along with other hub-and-spoke model of airports is following the exact opposite practice. They have concentrated in applying the same standard of sophisticated process in almost all the situations.

These added on to the unnecessary costs on to their process. Such processes may not also be flexible enough to coupe up with the changes, as huge restructuring is to be done. If the airports adapt TBS, it will simplify their strategies, and by streamlining their core processes, they can reduce a number of activities done at the airport (Beasley, Krishnamurthy, Sharaiha and Abramson). A company, which is having large divisions, has the tendency to drain a huge amount of cash, until its operations are fully discounted.

It will again save a huge amount of both time as well as money. The breaking up of processes can result in the formation of many customer centric units that will resolve the problems faced by the customers in much lesser time and it would not be necessary to implement all the processes in every situation. At airports, processing staffs can be appointed who will deal with customers needing changes and iterations (Beasley, Krishnamurthy, Sharaiha and Abramson, 2000).

In this way the customers would also be served quickly, which will thereby increase customer service quality and the service delivery will also be improved. These changes should be implemented across the system to implement a more efficient business model.

Nevertheless, during simplifying their processes Coventry Airport should also keep in mind the quality of customer service they are delivering. They can gain customer loyalty by providing differential services to their frequent fliers (Beasley, Krishnamoorthy, Sharaiha and Abramson, 2000). They can separate both the services given to a customer on airport and onboard, keeping in mind the type of customer. To implement strategy at the business or operational level, the firm has to integrate its functional and operational domain to provide particular product and services for a specific set of customers (Ernst, Krishnamoorthy and Storer, 1999).

This would be done with an aim of giving more valuable services to that segment of customer who will generate more profit in the end. So here, cost of giving same service quality to all the customers would be reduced by segmenting the customers. This process may help in the formation of purer and more profitable business, delivering service quality to different segments of customers at their perceived level.

The large carriers like Coventry Airport can never compromise with the service quality they provide to the customers. Here in how they are different from the other low cost carriers. This approach would certainly give much more product distinction than that is present. It is likely that these changes in the business model would help the larger airports like Coventry Airport to fulfil dual purposes. It will cut down on the cost and time that the company is incurring now as well as it would maintain the level of customer satisfaction against the amount that they are paying. It is clear that the restructuring in the business model are interdependent in nature.

If the coordination of these changes in the business model is present, it will definitely change the pace of the airport operation, reduce the complexity that these kinds of airports are dealing with currently, the redundancy of operations and will make service delivery more accurate and targeted to specific segments (Ernst, Krishnamoorthy and Storer, 1999).

It can be said with certainty that implementing such changes would not be easy for the company, especially in the period of economic crisis. The fear is that after implementing the change that will involve a great amount of revenue the cost will certainly not fall a great deal immediately. Though the revenue may fall down in the connecting market, the airports could make up this loss by the lower cost structure. However, while implementing this model a company should make sure that system matches the restructure designing, otherwise a bad fit would spoil the entire operation. Any company should make sure to take the optimal path, after thoroughly studying the alternatives. (Pinol and Beasley, 2006)

With a negative exponential distribution, the probability is high that the random variable will assume a value close to zero. Moreover, the probability decreases as the specified value of the random variable increases. The probability that a random variable will take on a value greater than some specified value T, given that the variable can be described by an exponential distribution with a mean equal to 1 / λ is given by the equation. P(t≥T)-e –λt. In the simulation varous factors are taken into consideration, this include the airport objectives, the key queues that are currently used and how performance is measured

Solution model

The method that could be used in reducing the problem aeroplanes waiting will depend on the number of aeroplanes in the queue landing and the taking off time. This method will make sure that resources are allocated well in order to reduce the queue in the waiting area as well as the queue in the air. It will provide the best take off times for airplanes as well as make sure that fuel wasted in the air is saved (Idris, Clarke, Bhuva and Kang, 2002).

The airport should adopt many queuing systems but not exiting three units to serve its customers well; this is because processing occurs on a first-come, first served basis. In such cases, a multiple-priority model is useful for describing customer-waiting times.

Large number of terminals poses both security and financial challenges to the airport. Reduced number of terminals will improve profitability and increase security. The first important step that can be taken by the airport is to reduce terminals to three to improve the involvement of a few employees. When exposed to more market forces, regulation for proper adherence will automatically and effectively replace long-standing and rather complacent government involvement as has happened in the transport and banks.

It is evident that airports are always willing to pay for assured quality of service and therefore not only is it prudent to strengthen government regulation but also allow more airports to ensure good quality service delivery. This would allow more market-generated information incidental for improved security checks and reduced cost of landing and what really pleases the customers. This will not only rid government complacency or passing on the blame, but conform to competitive market processes to make airport safer and better ((Idris, Clarke, Bhuva and Kang, 2002).

In theses systems, arriving customers are assigned to one of several priority terminals, according to a predetermined assignment method. Aircrafts are then allowed to come in. Within each class, processing first-come, first served. Thus, all customers in the highest class would be processed before those in the next lower class, then processing would move to that class, and then to the next lower class. Exceptions would occur only if a higher-priority customer arrived; that customer would be processed after the aircraft currently being processed.

This model incorporates all the assumptions of the basic multiple-server model except that it uses priority serving instead of first come- first served. Arrivals to the system are assigned a priority as they arrive (e.g. highest priority=1, next priority class= 2, next priority class=3 and so on.

An existing queue might look something like this.

Priority class

Within each class, waiting units are processed in the order they arrived. Thus, in this sequence, the first 1 would be processed as soon as a server was available. The second 1 would be processed when that server or another one became available.

If in the interim, another 1 arrived, it would be next in line ahead of the first 2. If there were no new arrivals, the only 2 would be processed by the next available server. At that point, if a new 1 or 2 arrived, it would be processed ahead of the 3s and the 4. Conversely, if a new 4 arrived, it would take its place at the end of the line. Obviously, a unit with a low priority could conceivably wait a rather long time for processing. In some cases, units that have waited more than some specified time are reassigned to a higher Priority. The appendix gives the appropriate formulas for this multiple-channel priority service model. However, due to the extent of computations involved, it is best to use the appropriate excel template for computations.

An airplane is assigned a priority based on urgency of the need for that tool. A Poisson distribution can describe requests for repair. Arrival rates are λ₁=2 per hour, λ₂ = 2 per hour, and λ₃=1 per hour.The service rate is one terminal per hour for each plane, and there are six three allowable terminals in the airport. Determine the following information.

1. The system utilization
2. The average time a plane in each of the priority classes will wait for service
3. The average time a too spends in the system for each priority class.
4. The average number of planes waiting for in each terminal.

• Λ= ∑ λ_k= 2 +2 +1 = 5 per hour
• M = 3 terminals
• μ = 1 planes per hour

The arrival rate at the system of a plane is the rate given to customers per unit time. The number of customers in the system is defined to include those in service and those waiting in queue. A convenient rotation for summarizing the characteristic of the queuing situations is given by the following:

• a= arrivals
• b= departures (service time) distribution
• c= number of parallel servers (=1, 2…)
• d= queue discipline

An airport is planning to open a satellite served by one terminal and one gate. It is estimated that requests for arrivals will average 15 per hour, and requests will have poison distribution.service time is assumed to be exponentially distributed. Previous experience with similar satellite operations suggests that mean service time should average about three minutes per request. Determine each of the following:

1. System utilization
2. Percentage of time the terminal will be idle
3. The expected number of airplanes waiting to be served
4. The average time airplanes will spend in the system
5. The probability of zero customers in the system and the probability of four airplanes in the system.

Waiting area for take off

Coventry should lay out well the waiting are for aeroplanes waiting to take off. The runway should be controlled in a manner that various aeroplanes from various locations are able to access the runway, which is. Constraints should be removed to make sure the runway is used adequately. The agency of the aeroplane is taken into consideration when allocating the take off time. The time that is paid while waiting at the runway is very important for the aeroplanes to take off.

Conclusion

This report has taken into consideration the arrival and takes off system of Coventry airport. The problem of the airport is complicated because of one runway and 2 terminals which are supposed to be used by over 5,000 aeroplanes that frequent the airport annually. The main problem has been diversion and waiting time of aeroplanes in the air. The queuing system used by this paper has shown that it is easier to reduce the cost and waiting time of the aeroplane in the air.

The paper assumed various factors such as easier predictability of tax time and pushback times for the controller runway. This method provides the management good benefits, which will increase the profitability of the airport. The system that has been proposed will provide improved service and reduce diversion of aeroplanes to Birmingham international airport (Atkin, Burke and Greenwood, 2009).

Reference List

Atkin, J, Burke, E, & Greenwood, J 2009, “A comparison of two methods for reducing take-off delay at London Heathrow airport”. MISTA.

Atkin, J, Burke, E, Greenwood, J, & Reeson, D 2008, “On-line decision support for take-off runway scheduling with uncertain taxi times at London Heathrow airport,” The Journal of Scheduling, vol. 11, no. 5, pp. 323–346.

Atkin, J, Burke, E, Greenwood, J, & Reeson, D 2007, “Hybrid meta-heuristics to aid runway scheduling at London Heathrow airport,” Transportation Science, vol. 41, no. 1, pp. 90–106.

Beasley, J, Krishnamoorthy, M, Sharaiha, Y, & Abramson, D 2000 “Scheduling aircraft landings -the static case,” Transportation Science, vol. 34, pp. 180–197.

Bolender, M, & Slater, G 2000, “Analysis and optimization of departure sequences,” in proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit, Denver, CO, pp. 1672– 1683.

Ernst, A, Krishnamoorthy, M, & Storer, R 1999, “Heuristic and exact algorithms for scheduling aircraft landings,” Networks, vol. 34, pp. 229– 241.

Idris, H, Clarke, R, Bhuva, R, & Kang, L 2002, “Queuing model for taxi-out time estimation,” Air Traffic Control Quarterly (ATCA Publications), vol. 10, no. 1, pp. 1–22.

Pinol, H, & Beasley, J 2006 “Scatter search and bionomic algorithms for the aircraft landing problem,” European Journal of Operational Research, vol. 171, pp. 439–462.