Operations Management in the Aviation Industry

Operations management involves managing processes that result in the transformation of inputs into products and services that create value addition to the customer.  Operations management, therefore, aims at maximising efficiency while generating services or products that effectively satisfy the needs of customers (Koksalmis, 2019).  The aviation industry has experienced tremendous growth over the past few decades, owing to their safety, convenience, and speed of aircraft. That being said, there is a high demand for airline companies to have a competitive advantage of their rivals.  To gain this advantage, operations management has been utilised immensely.  To provide high-quality aviation services and at minimum costs, airlines spend enormous effort and resources for generating cost-effective and profitable flight schedules, aircraft routes, crew scheduling, fare classes, gate assignments, fleet plans, etc. (Flin et al., 2012).  This paper analyses and evaluates how operations management in the aviation industry enables the attraction and maintenance of customers alongside enhancing competition for airports and airlines. Therefore, the discussion reviews operations management techniques and applications, including fleet assignment, demand forecasting, crew scheduling, gate assignment, runaway scheduling problem, and aircraft routing..

To begin with, implementing airline operations management and planning requires several operations and activities. The planning kicks off with strategic decisions that take a lengthy lead time, for instance, demand forecasting (that is, collecting supply and demand) (Deshpande & Arıkan, 2012). Afterwards, various interconnected planning decisions are taken into account, for example, aircraft routing, fleet assignment and crew scheduling. Generally, these planning processes are finished at least a month the schedule is implemented. Then, the operations phase occurs when implementing the planned schedule; this accounts for flight as well as schedule recoveries (McFadden & Hosmane, 2015). It should be noted that the process of operations planning may differ across airlines, and it is complex because decisions regarding resource scheduling have to be made on fleet assignment, crew scheduling, demand forecasting, etc.

Demand forecasting is a strategic operation that helps in predicting the airline passengers’ preferences for different airport alternatives.  Models for demand forecasting help to estimate it by considering factors like whether or not to travel, whether to utilise direct or connected flights and the specific flight hub to use when using connected flights (Linda & Cheryl, 2012).  Thus, accurate forecasting is not only crucial for airports and airlines but also for airport authorities in charge of a specific location. While airline companies could make more beneficial planning utilising a correct demand forecast, fellow agencies could also formulate well-informed airport-based plans by relying on these predictions (Wilpert & Qvale, 2016).  Hence, creating accurate models is equally beneficial to stakeholders.  Airlines and airports can be overwhelmed by high density of passengers but this problem can be overcome in two ways.  First, airports can be expanded or an airport be constructed that can balance demand and supply (Brittoa, et al., 2012).  Secondly, it can be overcome by increasing and efficiently using the capacity through the utilisation of methods like pricing. Several factors affect the passengers’ decision to utilise air transport. They can be classified into three: route-related characteristics (arrival and departure time, waiting times, size/type of aircraft, price, number of connections, flight time and airline company’s characteristics), passengers’ social-economic character (airline loyalty, gender, income, club membership, age), journey’s character (vacation or business, international, arrival or departure airport i.e. time zone and location) (Daft & Albers, 2012). Typically, passengers favour airlines that have few connections, are cheaper, reputable, and those that have appropriate take-off and landing time.

Another vital activity in airline operations management is the fleet assignment. The FAP (Fleet Assignment Problem) is concerned with assigning each aircraft depending on the specific flights and in accordance with the potential capacity, profitability and equipment it possesses (Bratu & Barnhart, 2011).  Decisions on FAP profoundly impact the competitive ability and profitability of airlines and are among the most crucial components as far as scheduling problems are concerned. For example, assigning an aircraft with an inadequate capacity could lead to poor demand management while assigning a big aircraft could result in unsold seats. To address these problems, airlines can use four different FAP models.  One of them is basic FAP model which ensures that every flight has a network balance, there is no exceeding aircraft capacity, etc. (Gopalan & Talluri, 2012). Another one is the integrated FAP model that addresses and manages activities like arrival/departure times, maintenance periods, flight crew and cycle planning. Integrated FAP model offers a better solution as opposed to dealing with the said problems separately and independently. The other one is FAP having additional coverage. This model addresses flight assignment problems by eliminating assumptions of basic FAP like fixed demand, daily planning and fixed costs; it, therefore, incorporates activities such as weekly planning as opposed to daily planning (Maksymov & Yurchenko, 2018). The fourth one is dynamic FAP model that can handle fleet re-timing and reassignment at the same time aiming at responding to dynamics such as demand.

Crew scheduling in the aviation industry is also an essential activity. The operation is complex in this sector because the employees are specialised for particular aircraft types. The major problem is reducing the labour costs and performing all activities while complying with the safety and contract laws (Bouras, et al., 2014).  Crew scheduling is different in itself in regard to the scheduling of cabin crew and pilots. Even though the cabin crew and pilots are typically evaluated together, there is a more likelihood of the cabin crew being capable of operating in another aircraft than the pilots (Suryani, et al., 2010). Characteristically, pilots can only operate particular aircraft in a similar ‘fleet type’.

It should be noted that the second-highest costs incurred by airlines after fuel costs are the costs of the crew. The process of crew planning is problematic for airline companies because the airline has to plan for pilots, cabin crew leader, as well as the cabin crew (Talluri, 2015). Crew scheduling problem can be approached from two other dimensions. One of them is that it could be classified based on the airline’s geographical location (Gopalakrishnan & Johnson, 2017). For example, European airlines have a policy of fixed price as opposed to a policy that is dependent on distance travelled and flight time.  The other problem is time-lapse in which crew scheduling problem could be classified into daily, weekly or a certain period.  Therefore, when doing crew scheduling, factors like irregular vacations, irregular days and flight time changes must be considered to maintain customer satisfaction and competitive advantage.

Operations management within the aviation sector also covers runway scheduling. Airports’ capacity expansion, for example, regarding cargo, apron, terminal areas or airstrip is a strategic decision that requires lengthy construction lead-times as well as enormous investments (Medard & Sawhney, 2015).  To attain the most efficient utilisation of such limited resources, developing thoughtful planning strategies is imperative.  One major problem experienced by airlines worldwide is flight delays that lead to billions of dollars in losses every year.  It means that there is a persistent and pressing need to explore air-traffic policies which could eliminate such costly and frequent inefficiencies. Runways are the most limited resource whose planning profoundly impacts the overall airline performance (Dinga, et al., 2016).  Runway assignment is dependent of the configuration of the airport (interesting or parallel runways, single-runway or their combination), the arriving aircraft’s direction, and the aircraft departure route (Bennel, et al., 2011).  Runway capacity defines the aircraft’s maximum rate of departures or arrivals that multiple or a single runway can accommodate. Elements affecting the capacity of the runway include runway occupancy time, weather conditions, taxiway availability, aircraft type, etc.  One primary strategy that could address runway scheduling problems is sequencing decisions that jointly optimise aircraft assignment to runways and sequencing aircraft arrivals and departures of each airport’s runway.

Aircraft routing represents another crucial activity in airlines operations management. It aims at determining the specific aircraft that will operate on a designated route.  This also covers aircraft maintenance activities usually labelled A, B, C and D. Level A maintenance, for example, involves inspection of the major systems like landing gear and engine (Clare & Richards, 2011).  A frequently and adequately maintained aircraft usually attracts and is preferred by customers. Similarly, it increases the competition of an airline company because, with high-quality aviation services, it will create a competitive advantage over rivals.

Lastly, gate assignment constitutes another significant activity as far as operations management in airports and airline sector is concerned.  The gate assignment problem entails the challenge to match the gates that links terminal areas and aircraft (Sherali & Bish, 2013). It should be noted that only a single gate has to be assigned to each aircraft.  Inadequacy of gates implies that aeroplanes have to stay at the apron while service vehicles transport passengers to the terminal.  This problem can be addressed through the following; the minimisation of the unassigned aircraft, maximising the appropriate gate assignments for certain aircraft types, minimisation of the passengers’ walking distance and minimising the difference between the reference and current schedules (Rexing, et al., 2019).

In conclusion, the aviation sector has grown tremendously because of the increased customer preference to travel by air owing its convenience, safety, fastness and ability to cover long distances. However, the industry has its problems related to demand forecasting, fleet assignment, runway scheduling, aircraft routing, gate assignment and crew scheduling. Management of these operations can help address the various challenges.  Therefore, as has been discussed above, operations management has a significant impact on attracting and maintaining customers alongside enhancing competition for airlines and airports.

References

Bennel, J., Mesgarrpour, M. & Potts, C., 2011. Airport Runway Scheduling. Available on: https://link.springer.com/article/10.1007/s10288-011-0172-x [March 31,2020]. Volume 9, pp. 65-72.

Bouras, A., Ghaleb, M., Suryahatmaja, U. & Salem, A., 2014. The Airport Gate Assignment Problem: A Survey. The Scientific World Journal , pp. 219-227.

Bratu, S. & Barnhart, C., 2011. Flight Operations Recovery: New Approaches Considering Passenger Recovery. Journal of Scheduling, 9(2), pp. 167-179.

Brittoa, R., Dresner, M. & VolteS, A., 2012. The Impact of Flight Delays on Passenger Demand and Societal Welfare. Transportation Research Part E: Logistics and Transportation Review, 48(2), pp. 460-469.

Clare, G. & Richards, E., 2011. Optimisation of Taxiway Routing and Runway Scheduling. Available on: https://doi.org/10.1109/TITS.2011.2131650[March 31,2020]. pp. 1000-1013.

Daft, J. & Albers, S., 2012. A Profitability Analysis of Low-Cost Long-Haul Flight Operations. Available on: https://doi.org/10.1016/j.jairtraman.2012.01.010[March 31, 2020]. Journal of Air Transport Management, Volume 19, pp. 49-54.

Deshpande, V. & Arıkan, M., 2012. The Impact of Airline Flight Schedules on Flight Delays. Manufacturing & Service Operations Management, 14(6), pp. 88-102.

Dinga, H., Limb, A., Rodrigues, B. & Zhu, Y., 2016. The Over-Constrained Airport Gate Assignment Problem. Computers & Operations Research, 33(2), pp. 33-45.

Flin, R., O’Connor, P. & Mearns, K., 2012. Crew Resource Management: Improving Team Work in High-Reliability Industries. Team Performance Management, 12(2), pp. 67-78.

Gopalakrishnan, B. & Johnson, E., 2017. Airline Crew Scheduling: State-of-the-Art. Annals of Operations Research, 140(3), pp. 147-154.

Gopalan, R. & Talluri, K., 2012. The Aircraft Maintenance Routing Problem. Operations Research, 47(2), pp. 198-213.

Koksalmis, G., 2019. Operations Management Perspectives in Air Transport Management. Available on: https://www.researchgate.net/publication/331749327_Operations_Management_Perspectives_in_the_Air_Transport_Management [March 31, 2020]. Journal of Business Administration Research, 2(1), pp. 2-10.

Linda, E. & Cheryl, S., 2012. Crew Factors in Flight Operations IX: Effects of Planned Cockpit Rest on Crew Performance and Alertness in Long-Haul Operations. 3(1), pp. 34-48.

Maksymov, V. & Yurchenko, O., 2018. Forecast of Demand for Aviation Maintenance and Air Navigation Specialists for the Next 20 Years. Available on : https://doi.org/10.1109/MSNMC.2018.8576268[March 31, 2020].

McFadden, K. & Hosmane, B., 2015. Operations Safety: An Assessment of a Commercial Aviation Safety Program. Journal of Operations Management, 19(6), pp. 127-136.

Medard, C. & Sawhney, N., 2015. Airline Crew Scheduling from Planning to Operations. European Journal of Operational Research, 183(7), pp. 201-216.

Rexing, B. et al., 2019. Airline Fleet Assignment with Time Windows. Transportation Science, 36(1), pp. 654-667.

Sherali, H. & Bish, E., 2013. Airline Fleet Assignment Concepts, Models, and Algorithms. European Journal of Operational Research, 172(3), pp. 56-76.

Suryani, E., Chou, S.-Y. & Chen, C.-H., 2010. Air Passenger Demand Forecasting and Passenger Terminal Capacity Expansion: A System Dynamics Framework. Available on: https://doi.org/10.1016/j.eswa.2009.07.041[March 31, 2020]. Expert Systems With Applications, 37(3), pp. 2324-2339.

Talluri, K., 2015. The Four-Day Aircraft Maintenance Routing Problem. Transportation Science, 33(6), pp. 123-134.

Wilpert, B. & Qvale, T., 2016. Reliability and Safety in Hazardous Work Systems: Approaches to Analysis and Design. s.l.: Psychology Press. ISBN: 0863773095, 9780863773099.