Combined Discrete-Continuous Simulation for Maintenance Training and Execution

Paper #:
  • 2017-01-2025

Published:
  • 2017-09-19
DOI:
  • 10.4271/2017-01-2025
Citation:
Rodriguez, E., "Combined Discrete-Continuous Simulation for Maintenance Training and Execution," SAE Technical Paper 2017-01-2025, 2017.
Author(s):
Affiliated:
Pages:
5
Abstract:
One of the most important activities associated with the Aerospace or Defense industry is maintenance. Maintainability procedures have a direct impact on safety and operational availability of systems. The processes and procedures that are used during maintenance activities, whether removing and replacing a component of a system, or conducting troubleshooting, are generally discrete by design, and in most cases, a maintainer, or a field service representative (FSR), will follow a sequence of steps as part of a maintenance work package or work instruction to complete the necessary tasks. Depending on the system, those maintenance activities could be complex, requiring a large maintenance window and the availability of resources to ensure completion. In order to successfully accomplish those complex tasks, besides having access to the required hardware/software and tools, one of two alternatives need to exist: either the maintainer is well trained and experienced, or the maintenance work instructions are extremely detailed and precise; both options can be time consuming and expensive to achieve. In addition, and depending on the FSR, or how the work instructions were captured, the maintenance task will be done in a particular way, not leaving room for process improvement.Maintenance activities are generally conducted by utilizing a series of discrete steps, although the process of developing maintenance procedures can be open to interpretation, depending on how and who created the procedure. By utilizing the maintenance procedures, system data, and the information on the component(s) affected, the approach users take to accomplish the particular maintenance task can be collected in the form of quantitative data. Utilizing that data, discrete-continuous models can be generated for specific maintenance activities in order to maximize efficiency and reduce system downtime.
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