Aircraft Maintenance Planning: Intuition vs Modeling for High Performance

Overview

The Warner Robins Air Logistics Complex (WR-ALC) is a crucial entity among the numerous units of the United States Air Force. Operating under the Air Force Sustainment Center (AFSC) umbrella, the WR-ALC assumes a pivotal role in the aircraft maintenance planning and repairment of the United States Air Force's most substantial aircraft.

The WR-ALC functions mainly as a manufacturing company. The complex is a leader in dealing with tough challenges in keeping and improving the Air Force's aerial abilities, thanks to its special way of operating. In this case study, we delve into a specific instance of the WR-ALC team, focusing on multiphase modeling for planned maintenance optimization.

Problem

This case revolves around delays in the repair process of radomes sourced from a supplier. The radomes are delivered in batches of 8–10 items. The repair process involves two groups on different levels: the Commodities Maintenance Group (CMXG) and the Electronics Maintenance Group (EMXG), and three squadrons.

One radome repairment falls into five stages:

1. Depack by CMXG 571st
2. Depaint by CMXG 571st
3. Repair by CMXG 573rd
4. Paint by CMXG 571st
5. Test by EMXG

The Repair Turnaround Time (RTAT) agreement is to get the radomes back in 60 calendar days, which results in 43 working days.

With the current structure and queue, the WR-ALC faced several issues that negatively affected productivity:

1. Missed RTAT agreement days.
2. Overly long wait time in between stages.
3. Departments blame each other for the missed schedule.

Solution

Initially, an intuitive solution emerged with a timeline of over a month for implementation and an estimated cost of approximately $25,000. However, before execution, the team took the opportunity to model the solution with AnyLogic. Despite the intuitive nature of the planned maintenance optimization approach, the management wanted to confirm its effectiveness.

Intuitive solutions

At first, the team assumed the original solution was correct, but the simulation revealed that it wouldn't work out. The key matter was the lack of carts. There were only five radome carts present in the last three stages of the repairment process, despite the supplier delivering 8–10 radomes at a time. Consequently, 3–5 radomes were left on hold during the intermediate stages.

The initial idea for addressing this issue was to buy more carts. However, the aircraft maintenance simulation model revealed that increasing the cart number from 5 to 10 may result in only a 10-day duration decrease.

Considering the current cycle duration of 150 days, the cut of 10 days didn’t meet the expectations or the RTAT.

Facing this setback, a shift in perspective became imperative. As an alternative for maintenance optimization, the team shifted the focus from the base equipment to human and time resources. The research highlighted that there is only one person at the repair stage, and they can manage two radomes at a time. So, the team modeled the repair process with five carts and additional people on hand, but the solution turned into a training issue. It proved ineffective for planned maintenance optimization.

However, these void hypotheses led the team to the approach that became the basis for the solution: to meet the 60-day RTAT, the team could only effectively manage 2–3 radomes at a time.

The real solution

With this idea, the team decided to meet with the leadership and stakeholders, present the model, and collectively explore the options for improving aircraft maintenance planning. The meetings had multiple rounds, introducing ideas that needed to be carefully tested in the model.

The U.S. Air Force chose to keep the final solution they implemented for aircraft maintenance planning confidential. However, those meetings led to the establishment of new business rules:

1. Supplier adjustment: The supplier is directed to reduce the batch size of radomes from 10 to 3.
2. Repair stage optimization: Given that there's only one mechanic at the repair stage capable of handling two radomes simultaneously, if a third radome arrives and a cart is available, a mechanic from another area should be assigned to work on it.
3. Testing protocol modification: The new approach suggests testing more than one radome at once causes interference. So, if a tester already has one machine for testing, they may continue. However, if a second one appears, the next one to be tested must come from those available.

These rules aim to enhance efficiency and streamline the overall maintenance process.

Results

With these new agreements and business rules, the Warner Robins Air Logistics Complex has successfully met the Repair Turnaround Time. All departments are content with the current pace of work, and the complex saved $25,000 with a better and more effective solution.

Modeling is essential to making big improvements in different manufacturing processes. The U.S. Air Force case shows how being adaptable and working together results in overcoming complicated workflow challenges.

The success of the aircraft maintenance planning case is primarily due to the team's dedication to implementing ideas through simulation and effective communication; this emphasizes the importance of simulating hypotheses before putting them into practice.

The case study was presented by Matt Walker, of The Warner Robins Air Logistics Complex, at the AnyLogic Conference 2023.

The presentation is available in video and PDF file.