Military Aircraft Maintenance Scheduling and Staffing Optimization

Military Aircraft Maintenance Scheduling and Staffing Optimization

Problem

Military Aircraft Maintenance Scheduling

The Corps of Royal Electrical and Mechanical Engineers (REME) maintains all electrical equipment within the British Army. REME engineers are tasked with the maintenance, recovery, repair, and manufacturing of the battle equipment to keep it in fighting order at the battlefields and at the military bases, both at home and overseas.

Among other duties, engineers maintain the Apache Attack Helicopter, one of the world’s most advanced multi-role combat helicopters. This aircraft is very maintenance demanding: it takes about 35 hours of maintenance to cover one hour of flying. That was one of the reasons REME management considered their unit understaffed and claimed that it had to expand the mechanics department. However, their supervisors from Air Army Corps felt like the REME was being over-resourced, since on average they had enough staff to manage this workload.

Lack of agreement between these two military organizations made it clear that to solve REME’s workforce planning problem, the management needed to look deeper into data to make more evidence-based decisions. They tasked dseConsulting company with the challenge to create a robust tool for improving staffing strategies that would help them optimize scheduling and manning, and then increase the availability of helicopters. For these reasons, the consultants applied AnyLogic maintenance simulation and optimization software. The consultants aimed at:

Solution

The consultants built a simulation model for analysis and further optimization of the maintenance processes during the deployment cycle. The model included three areas of complex behavior lying within the real-life system:

Maintenance optimization model built with AnyLogic

With the AnyLogic multimethod simulation approach, consultants were able to model deployment cycle processes and handle their complexity without any simplification. Among other approaches, agent-based simulation allowed the modelers to reflect the behavior of aircraft engineers in detail, including their experience and the level of burn-out, to demonstrate more robust statistics.

In the simulation model, the following statistics were collected:

By analyzing the maintenance optimization model results, the consultants concluded that the human factor aspect played an important role in deployment cycle activities. For example, if an engineer was tired and inefficient, the job would take longer and affect all related processes. However, if new staff was recruited, the efficiency level would also drop because new recruits tend to be less experienced. As a result, the REME management had to find the balance between pushing more work to the experienced personnel, causing burn-outs, and hiring less experienced contractors.

The simulation model provided some significant insights for the management:

Result

As a result of the maintenance optimization modeling project, the consultants offered the customer a decision support tool that could be used for planning staffing policies and improving staff coordination and management.

At this stage of the project, simulation indicates that with smarter planning there is the potential for a 20% aircraft fleet availability improvement at a lower cost, in addition to the organization's prime targets.

It is estimated that the second phase of the project might save REME about $2.7 million in staff costs.

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