A Simulation Approach to Enhancing Aircraft Availability

A Simulation Approach to Enhancing Aircraft Availability

Massoud Bazargan (Embry-Riddle Aeronautical University (ERAU), Daytona Beach, FL, USA), Ken Byrnes (Embry-Riddle Aeronautical University (ERAU), Daytona Beach, FL, USA), Ali Mazhar (Embry-Riddle Aeronautical University (ERAU), Daytona Beach, FL, USA), Adedoyin Adewumi (Embry-Riddle Aeronautical University (ERAU), Daytona Beach, FL, USA) and Qing Liu (Embry-Riddle Aeronautical University (ERAU), Daytona Beach, FL, USA)
DOI: 10.4018/ijasot.2014010105


This study presents a simulation approach to evaluate a potential strategy for dispatching aircraft at Embry – Riddle Aeronautical University. The current method of assigning aircraft to students is based on the highest utilization. A new strategy is proposed where the maintenance time is also incorporated into the aircraft utilization. Various performance measures such as aircraft availability, number of cancellations due to unavailability of aircraft, maintenance manpower and number of aircraft at maintenance hangar are examined under both methods. The analysis of the two methods suggests that changing the priority method in aircraft dispatch does not produce significant change in the system. Although both models are similar, the large deviations and variations in the proposed dispatch method discourage it from being implemented in its current form.
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Literature Review

This case study has some similarities to multiple asset management, which have been extensively studied in the literature. In multiple asset management, the focus is to manage multiple resources to meet demand typically at different locations. Examples include rental cars (see for example Pachon, et al., 2006, Li & Tao 2010), rail cars (Papier & Thonemann, 2007, Bojovic, 2002) and truck assignments (Miao, et al., 2009). In these research streams the focus is typically at assigning multiple resources to a number of customers at different locations at minimum cost. They do not, however, address varying cost of maintenance with usage. These problems adopt a variety of network optimization models to satisfy demand at different locations. A particular paper by Hertz, et al. (2009) considers varying maintenance cost in a rental car company. The scope of their research is an inventory control model where the number of cars is identified by examining the existing fleet and purchasing new ones.

Other related research work include parallel machine scheduling (see for example Cheng et al., 2011; Kubzin & Strusevich 2006) where only one maintenance activity is allowed throughout the makespan. The airlines’ aircraft dispatching/assignment in the literature is primarily studied under a series of interrelated optimization models starting with schedule, fleet and tail assignment/routing (Bazargan, 2010). In these models, maintenance is included as a side constraint to insure the aircraft is at the right hub for maintenance after certain number of flight hours (See for example Barnhart, 1998; Li & Wang 2005).

Although the above research works provide some information on standardized problems, they do not capture the scope and nature of the current case study where maintenance cost varies with usage.


A major task of Flight Operations is to assign students, instructors, and aircraft to the flight blocks. In the present method of scheduling approach, students are assigned to specific instructors for the entire duration of a course. Each instructor submits a request for an aircraft during the assigned flight block. The scheduling looks at the availability of the fleet and makes the resources available accordingly.

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