How to maximize the benefits of Predictive Maintenance in Aircraft Maintenance

Aircraft maintenance is a crucial aspect of aviation, as it ensures the safe and efficient operation of aircraft. The maintenance process involves the inspection and repair of aircraft systems and components to ensure their proper functioning.

Not everyone will agree on this but, in this context, aircraft maintenance is, in essence, not that complicated: it’s either reactive or it’s proactive, that’s all. Reactive is a failure based; something breaks down, so it must be fixed. Proactive aircraft maintenance offers two options; it can be preventive maintenance, A-Checks, C-Checks, an overhaul of components, etc. or we can do predictive maintenance. The big difference between these two is that preventive maintenance, the current position of the industry, is very much age-based, i.e. at certain intervals of hours, flight cycles, and/or time, there are checks to be performed and components to be overhauled…

With predictive maintenance, the idea is to still perform maintenance but make it condition-based; so, rather than doing maintenance based on a certain fixed number of flight hours, flight cycles, or calendar dates, we determine which condition of aircraft systems and components would justify performing maintenance actions. In short, reactive maintenance is too late as in AOG (aircraft on ground) situations; this approach has several disadvantages, including unexpected downtime, increased maintenance costs, and reduced operational efficiency. Preventive maintenance means that you’re doing some jobs too early and as such can be quite costly; but predictive maintenance tries to do maintenance right on time.

Predictive maintenance involves the use of the information such as sensor data, and statistical modeling to calculate what the condition of systems and components could be at a given moment in time to predict maintenance needs in advance. It helps airlines to determine when maintenance should be performed.

Maybe you read our article ‘There has never been a better time to focus on data than now - how data can help tackle the current challenges in aircraft maintenance’. The increasing shortage of ground engineers is one of the major challenges in aviation aircraft maintenance. One of the solutions mentioned was also making use of predictive maintenance. ?

First of all, let's have a look at a few key benefits of using predictive maintenance:

1. Improved Safety

By predicting component failures before they occur, maintenance crews can take proactive measures to address the issue and prevent unsafe conditions. This protects not only the aircraft but also its passengers and crew.

2. Reduced Downtime

Another benefit of predictive maintenance is reduced downtime. By identifying potential component failures before they occur, maintenance crews can schedule repairs and maintenance during planned downtime, rather than in an emergency situation. This not only reduces downtime but also ensures that repairs are performed efficiently and effectively.

3. Improved Staff Planning

If airlines can predict when maintenance will be needed, it is possible to schedule the workforce with the right certification to perform the maintenance at the right time. This will also improve overall efficiency.

4.?Reduce Operational Costs

If airlines can reduce unexpected downtime and improve efficiency, they can reduce operational costs and increase their overall efficiency. This can result in increased profitability for the airline, as well as increased customer satisfaction.

5. Better Asset Management

Predictive maintenance also enables better asset management. By monitoring the health of aircraft components, airlines can make informed decisions about the replacement or repair of components, ensuring that they are replaced only when necessary. This can help to extend the lifespan of aircraft components, reducing the overall cost of maintenance.

Maximize the Benefits of Predictive Maintenance

To be able to maximize the benefits of predictive maintenance, it is important to utilize data effectively. Hereby are a few steps you need to take:

1. Data Collection

The first step in maximizing the benefits of predictive maintenance is to collect data. ?Often airlines store data in multiple systems. ?Collecting and identifying the data itself and having it stored in different systems doesn’t provide any value—an airline needs to process it and has only one single source of truth. ?The problem with this process is that it can take up a lot of time and effort for airlines to get the data they need into a usable format, centralize and validate it. An airline needs a way to transform data quickly and easily from its original format into the shape, format, or model they need it to be, to validate all the data, and to have a data standard to be able to drive value. Automatic data integration and data exchange is the key here.

2. Data Management

Once the data has been collected, it must be managed effectively. This includes ensuring the data is stored securely and can be easily accessed when needed. It is also important to ensure that the data is cleaned, organized, and analyzed effectively. Everyone knows the world-famous rubbish in is rubbish out. Keeping your aircraft data healthy and maintaining a single source of truth is a continuous job. It is necessary to be on top of things to prevent flawed data. Human error is natural, and more data is added to the systems daily resulting in constant changes. Plus, tons of rows of new data are created by the aircraft every day and added to the systems so it’s challenging to keep an overview and identify issues. This means an airline needs a quick and trustworthy way to check all data to address any issues as soon as they appear and are still manageable, to prevent things from spiraling out of control to keep trust and confidence in the aircraft data, at all times.

3. Data Analysis

Data analysis is a crucial aspect of predictive maintenance. The data collected and managed in a single source of truth should be analyzed to identify patterns and trends that can be used to predict component failures. This should result in optimized maintenance planning based on the predictions generated by the data analysis. However, making a pie chart in Excel is not difficult but managing a data warehouse, presenting information in a logical cognitive matter, and making use of new data technologies such as natural language processing (NLP) or machine learning (ML) is a field of its own.?This means an airline needs the right people and/or partners with the skills and knowledge to create value from data and maximize the benefits of predictive maintenance.

4. Continuous Monitoring and Improvement

Finally, it is important to continuously monitor and improve the predictive maintenance process. This includes regularly reviewing the data collected and analyzing the results of maintenance planning to identify areas for improvement. The predictive maintenance process should be continuously fine-tuned to ensure that it is providing the maximum benefits possible.

Predictive maintenance has the potential to revolutionize the way that aircraft maintenance is performed. Using data analysis to predict component failures and schedule maintenance, airlines can reduce downtime, improve operational efficiency, and enhance safety. To maximize the benefits of predictive maintenance, it is important to have the right people and/or partners with the right skills to utilize data analysis effectively and continuously monitor and improve the process.?