Maintenance Workflow Optimization: Streamlining Aircraft Repair Processes

Maintenance Workflow Optimization: Streamlining Aircraft Repair Processes

Warner Robins Air Logistics Center stands as one of three key bases responsible for the maintenance and repair of the United States Air Force's aircraft. Its responsibilities span across a variety of aircraft types. As a vital hub for aircraft repair and overhaul, the Center specializes in comprehensive maintenance tasks.

In one of our earlier case studies, we explored the Warner Robins Center approach to planning aircraft maintenance and the way they used AnyLogic. In this case study, however, we will focus on their strategy to optimize work processes and meet the target KPIs.

Contents:

  1. Problem
  2. Solution
  3. Results

Problem

Warner Robins Air Logistics Center faced significant challenges in managing aircraft maintenance and repair. The main problems were in the complex processes applied to different aircraft types, which caused:

Given the difficulties in workflow management, Warner Robins managers decided to prioritize maintenance optimization.

Solution

To tackle the maintenance optimization challenges head-on, the Center embraced the "Art of the Possible" management system presented in the AFSC H60-101 manual. It serves as a foundational framework, guiding leadership behavior and operational practices toward standardized and efficient procedures.

Organization of a gated process within the maintenance optimization system

Organization of a gated process within the "Art of the Possible" maintenance optimization system

One of the main concepts implemented within the system is a Gated process. It represents the movements of the elements through the maintenance process and results in a structured approach to maintenance optimization.

Following the "Art of the Possible" guidelines, the Warner Robins team used AnyLogic simulation software to model all the processes in one project. The model had two goals:

The model was tailored to the Center's specific needs and considered all maintenance stages that an aircraft goes through.

The general design of the maintenance optimization model with 12 gates A close-up view on one of the gates

The design of the maintenance optimization model in general and a close-up of a gate (click to enlarge)

On the model run, Warner Robins engineers noticed an unusual Delay block behavior.

Technical challenge: Delay block behavior within the Warner Robins model

In AnyLogic simulation modeling, a Delay block is a component that introduces a time delay to entities passing through it. It mimics real-world waiting or processing times, allowing for a more realistic simulation of processes.

The Delay block has built-in utilization data. When an item doesn't leave the block within the set time, it shows full utilization. In the Warner Robins case, this feature leads to unrealistic output data because it differs from the Center's workflow adjustment.

Comparison of the Delay block utilization results

The difference in Delay block utilization results

Simulation modelers added a simple fix to solve this issue: placing a Queue block after each Delay block. This adjustment resulted in accurate utilization statistics. To correct the Delay block behavior in the maintenance workflow optimization model, the final solution goes as follows:

  1. Set max capacity (with restrictedAreaStart)
  2. Process the Delay block
  3. Queue
  4. Exit (with restrictedAreaEnd)

A part of the model with a corrected Delay-Queue block chain

A part of the model with a corrected Delay-Queue block chain

Once the technical challenge was solved, the team returned to the initial project goal of maintenance optimization. To succeed, the team set two main tasks: develop a unified KPI dashboard and integrate the workflow model into the maintenance procedure.

Task 1: Develop a KPI dashboard based on the maintenance workflow model

KPI dashboard sourcing data from the maintenance workflow optimization model

KPI dashboard sourcing data from the maintenance workflow optimization model (click to enlarge)

The dashboard processes the simulation model data, considers the gates' workload, and visualizes the maintenance processes in solid numbers. As every Warner Robins department works under the same management system, the numbers and terms are unified and clear for everyone involved, whether an engineer or a leadership member.

Task 2: Integrate the workflow model into the maintenance procedure

A central idea of the project was a standardized simulation model, which could help cut the hourage. The maintenance workflow model developed in AnyLogic recreated the Center's aircraft workflow in detail, following the "Art of the Possible" guide. So, any team involved in aircraft repair could optimize the processes.

Prior to the model integration, the maintenance processes at Warner Robins Center took about a month and had four stages. At first, they designed how the maintenance model would work. Then, they gathered and checked the data, put it into the model, and adjusted it.

Now the Center has a standardized model considering all the gates an aircraft goes through. Engineers no longer need to recreate the modeling stage repeatedly. This allows them to save weeks of work and allocate their time to other tasks.

The new maintenance workflow goes as follows:

  1. The modeler and process engineer discuss the project (30 minutes).
  2. Both go through the maintenance workflow model gate-by-gate (1.5 hours).
  3. Find where dependencies and resource constraints need to be added.

Results

With the implementation of simulation modeling and standardized processes, Warner Robins Center experienced numerous benefits, including:

This case study shows how AnyLogic simulation modeling software and standardized processes can optimize aircraft maintenance workflow and support better decision-making in complex environments.

Matt Walker of the United States Air Force Warner Robins Air Logistics Complex presented the case study at the AnyLogic Conference 2023.

The slides are available as a PDF file.


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