Q&A
Condition Based Airline Fleet Maintenance explained in 7 questions

Current aircraft maintenance is carried out following two strategies:

  • Reactive, also known as ‘fix when it fails’. The disadvantage of this maintenance strategy is that it leads to unexpected maintenance that could cause delays for the passengers.
  • Preventive, also known as pre-scheduled or fixed-interval-maintenance. According to the maintenance planning document from the aircraft manufacturer parts are replaced after a defined number of flight hours, flight cycles or calendar days, whichever comes first. The disadvantage of this time-based maintenance strategy is that parts are replaced while still in good health. This leads to waste of time and resources, thus ‘over-maintenance’.

In this video, we explain the available aircraft maintenance strategies.

With Condition Based Maintenance the health of a component or structure is monitored and are only repaired when damaged or replaced when close to failure. The number of sensors present in a modern aircraft, the accessibility and fast communication of the vast data obtained from these sensors, and the increasing capability of data analytics create the ideal context for Condition Based Maintenance in the aviation industry as you can read in this article.

In ReMAP data collected from sensors from dissimilar aircraft systems and structures will be analysed through machine learning diagnostic and prognostic algorithms to create real-time adaptive maintenance plans. A fleet-level approach will be followed since the potential of CBM can only be achieved by monitoring the health of all aircraft in a fleet, managing maintenance resources and operational needs. The result is an Integrated Fleet Health Management (IFHM) solution that replaces fixed-interval inspections with adaptive condition-based interventions.

In this video, we explain the unique selling points of ReMAP.

According to ACARE, it is expected that by 2035 the Condition Based Maintenance philosophy will be accepted as a standard approach to monitor aircraft health and to plan aircraft maintenance. By 2050, all new aircraft will be designed for Condition Based Maintenance. CBM will result in a significant 40% reduction in Maintenance Repair & Overhaul (MRO) process time and costs, increase in aircraft availability, and maximization of asset utilization. As Ludovic Simon (Thales), Member of the ReMAP Advisory Board, states in his blog: “Now we must prove that condition-based maintenance is mature enough to implement into aviation

In this ReMAP welcome video, stakeholders explain the importance of CBM in aviation and the purpose of ReMAP.

Listen also to this interesting Podcast from Project Leader Bruno Santos with more details on ReMAP.

A generalized application of CBM is still far from feasible. Despite the existence of thousands of sensors in modern aircraft, the attempts, so far, have focused on system health diagnostics or prognostics health management for specific systems, mainly engines and auxiliary power units. Moreover, there is a lack of knowledge on how to incorporate these diagnostics and prognostics for efficient maintenance management. To fully exploit CBM benefits a systematic end-to-end approach is necessary: from sensor data to fleet maintenance. ReMAP does that. ReMAP research is split into the next technical working packages:

  1. Development of an open IT ecosystem of cloud services that will enable information load, data management, processing, visualization and sharing. Learn about its features in this video.
  2.  The procurement, development and integration of the most promising sensor technologies for damage monitoring in aeronautical composite structures (SHM), such as Piezo sensors and Lamb Wave Detection Systems LWDS. Watch our lamb waves detection system video at: https://h2020-remap.eu/lamb-waves-detection-system-lwds-cedrat-technologies/
  3. Development of Structural Health Management (SHM) Diagnostics and Remaining Useful Life Prognostics. Discover the ReMAP SHM-approach in this video.
  4. Development of the core analytics technology chain for system and component level diagnostics, prognostics and health management (PHM).
  5. Development of the Maintenance Decision Support Tool that delivers the adaptive maintenance plans
  6. Assessment of the safety of the condition-based maintenance technologies in ReMAP. Discover more here.
  7. Demonstration test in a relevant environment (KLM and KLM City Hopper). Discover more here.
Find all technical details and the research progress in ReMAP’s bi-annual newsletter. You can download them here: https://h2020-remap.eu/news/ ReMAP scientific results can be downloaded here: https://h2020-remap.eu/documents/

When a new technology, such as CBM using artificial intelligence, is being introduced, one has to first identify the effects of this technology on the safety of people, goods and environment. This is called ‘hazard identification’. “According to the regulatory framework defined by EASA and FAA, once you are aware of potential hazards, the next step consists in finding solutions to deal with these hazards and assessing the efficiency of the proposed solutions”, says ReMAP-partner Pierre Bieber (ONERA) who shares his investigation in his blog.

All defined hazards are translated into models for aircraft maintenance, with and without CBM incorporated by PhD Juseong Lee, his supervisor Mihaela Mitici (TU Delft), and Floris Freeman (KLM). From that point, the impact on aircraft safety when CBM is incorporated is assessed.


These field tests will focus on the KLM fleet of Boeing 787 airplanes (twenty per 2020) and KLM City Hopper Embraer 175 (ten per 2020).

Data sharing is one of the key aspects to incorporate CBM. With CBM data acquired from sensors is used to calculate the remaining useful life of components, through a model-based approach. To create such a model huge amounts of data have to be gathered. To increase the accuracy of the model and to create a company independent IFHM-solution, multiple airlines need to participate and share data. This can be challenging due to data privacy and data ownership issues.

In ReMAP, strategies are explored to train and share CBM models without the need to share the data. Federated Learning is a new technique that has the potential to solve the data sharing problem among companies and stakeholders while offering data-private model learning. Advanced settings increase the convergence speed hence models can be generated faster by reducing the amount of data needed to be sent to the server. 

Watch the ReMAP video in which we explain the architecture of the IT-platform that offers the Integrated Fleet Health Management-solution using Federated Learning.

Considering an airline’s profitability goal, the objective of the maintenance organization is to contribute to maximizing the airline fleet’s earning potential: maximizing the fleet availability and dispatch reliability (the proportion of planned flights that can be realised), at minimum cost. CBM has the potential to contribute to this but estimating that actual potential is challenging. “Nobody in the industry is able yet to perform a robust economic analysis, simply because there is no sufficient and extensive CBM experience and data to support such analysis”, states Roberto Hirschman (Embraer), Member of the ReMAP Advisory Board in his blog.“ That’s why ReMAP is an excellent initiative and opportunity to exercise CBM addressing all aspect of its implementation and adoption.” But estimating the ultimate benefit that CBM technologies will provide in an airline environment can be challenging, as Floris Freeman of KLM states. An assessment is needed on what is realistic in terms of technology performance, and what benefits are to be expected (download ReMAP-deliverable)


ReMAP will test its IFHM solution in an unprecedented 6-month operational demonstration, involving more than 12 systems in two different aircraft fleet of KLM and KLM City Hopper (twenty Boeing 787 airplanes and ten Embraer 175). Research will be done on the expected impact from CBM on the short- and long-term on fleet availability, maintenance cost and system complexity and weight benefits. Complementary the potential of CBM to deliver operator benefits will be examined.

For structures, health prognostics algorithms will be demonstrated in a laboratory setting. Representative structural composite subcomponents are subjected to a spectrum of fatigue loading. Part of the demonstration will estimate the structural weight benefits out of the SHM technology adoption in primary structures.

The ambition for both demonstrations is to prove that, under the current regulatory framework, ReMAP’s IFHM solution will lead to:

  • a 4.5% reduction of direct maintenance costs (110 thousand euros less per year for a long-haul aircraft);
  • a 3 to 7% weight reduction of structural composite components; and
  • a 10% missed failures reduction, reducing the need for systems redundancy and reducing complexity.

  • Group 2Created with Sketch. How is airline fleet maintenance performed today?

Current aircraft maintenance is carried out following two strategies:

  • Reactive, also known as ‘fix when it fails’. The disadvantage of this maintenance strategy is that it leads to unexpected maintenance that could cause delays for the passengers.
  • Preventive, also known as pre-scheduled or fixed-interval-maintenance. According to the maintenance planning document from the aircraft manufacturer parts are replaced after a defined number of flight hours, flight cycles or calendar days, whichever comes first. The disadvantage of this time-based maintenance strategy is that parts are replaced while still in good health. This leads to waste of time and resources, thus ‘over-maintenance’.

In this video, we explain the available aircraft maintenance strategies.

  • Group 2Created with Sketch. What is Condition Based Maintenance?

With Condition Based Maintenance the health of a component or structure is monitored and are only repaired when damaged or replaced when close to failure. The number of sensors present in a modern aircraft, the accessibility and fast communication of the vast data obtained from these sensors, and the increasing capability of data analytics create the ideal context for Condition Based Maintenance in the aviation industry as you can read in this article.

In ReMAP data collected from sensors from dissimilar aircraft systems and structures will be analysed through machine learning diagnostic and prognostic algorithms to create real-time adaptive maintenance plans. A fleet-level approach will be followed since the potential of CBM can only be achieved by monitoring the health of all aircraft in a fleet, managing maintenance resources and operational needs. The result is an Integrated Fleet Health Management (IFHM) solution that replaces fixed-interval inspections with adaptive condition-based interventions.
In this video, we explain the unique selling points of ReMAP.

  • Group 2Created with Sketch. Why should we use Condition Based Maintenance in aviation now?

According to ACARE, it is expected that by 2035 the Condition Based Maintenance philosophy will be accepted as a standard approach to monitor aircraft health and to plan aircraft maintenance. By 2050, all new aircraft will be designed for Condition Based Maintenance. CBM will result in a significant 40% reduction in Maintenance Repair & Overhaul (MRO) process time and costs, increase in aircraft availability, and maximization of asset utilization. As Ludovic Simon (Thales), Member of the ReMAP Advisory Board, states in his blog: “Now we must prove that condition-based maintenance is mature enough to implement into aviation
In this ReMAP welcome video, stakeholders explain the importance of CBM in aviation and the purpose of ReMAP.

Listen also to this interesting Podcast from Project Leader Bruno Santos with more details on ReMAP.

  • Group 2Created with Sketch. How do you bridge the technological ‘valley of death’ of Condition Based Maintenance in aviation?
A generalized application of CBM is still far from feasible. Despite the existence of thousands of sensors in modern aircraft, the attempts, so far, have focused on system health diagnostics or prognostics health management for specific systems, mainly engines and auxiliary power units. Moreover, there is a lack of knowledge on how to incorporate these diagnostics and prognostics for efficient maintenance management. To fully exploit CBM benefits a systematic end-to-end approach is necessary: from sensor data to fleet maintenance. ReMAP does that. ReMAP research is split into the next technical working packages:
  1. Development of an open IT ecosystem of cloud services that will enable information load, data management, processing, visualization and sharing. Learn about its features in this video.
  2.  The procurement, development and integration of the most promising sensor technologies for damage monitoring in aeronautical composite structures (SHM), such as Piezo sensors and Lamb Wave Detection Systems LWDS. Watch our lamb waves detection system video at: https://h2020-remap.eu/lamb-waves-detection-system-lwds-cedrat-technologies/
  3. Development of Structural Health Management (SHM) Diagnostics and Remaining Useful Life Prognostics. Discover the ReMAP SHM-approach in this video.
  4. Development of the core analytics technology chain for system and component level diagnostics, prognostics and health management (PHM).
  5. Development of the Maintenance Decision Support Tool that delivers the adaptive maintenance plans
  6. Assessment of the safety of the condition-based maintenance technologies in ReMAP. Discover more here.
  7. Demonstration test in a relevant environment (KLM and KLM City Hopper). Discover more here.
Find all technical details and the research progress in ReMAP’s bi-annual newsletter. You can download them here: https://h2020-remap.eu/news/ ReMAP scientific results can be downloaded here: https://h2020-remap.eu/documents/
  • Group 2Created with Sketch. How can we prove that condition-based aircraft maintenance is efficient and safe?

When a new technology, such as CBM using artificial intelligence, is being introduced, one has to first identify the effects of this technology on the safety of people, goods and environment. This is called ‘hazard identification’. “According to the regulatory framework defined by EASA and FAA, once you are aware of potential hazards, the next step consists in finding solutions to deal with these hazards and assessing the efficiency of the proposed solutions”, says ReMAP-partner Pierre Bieber (ONERA) who shares his investigation in his blog.

All defined hazards are translated into models for aircraft maintenance, with and without CBM incorporated by PhD Juseong Lee, his supervisor Mihaela Mitici (TU Delft), and Floris Freeman (KLM). From that point, the impact on aircraft safety when CBM is incorporated is assessed.

These field tests will focus on the KLM fleet of Boeing 787 airplanes (twenty per 2020) and KLM City Hopper Embraer 175 (ten per 2020).

  • Group 2Created with Sketch. How is the confidentiality of data from multiple airlines in one CBM-cloud assured?

Data sharing is one of the key aspects to incorporate CBM. With CBM data acquired from sensors is used to calculate the remaining useful life of components, through a model-based approach. To create such a model huge amounts of data have to be gathered. To increase the accuracy of the model and to create a company independent IFHM-solution, multiple airlines need to participate and share data. This can be challenging due to data privacy and data ownership issues.

In ReMAP, strategies are explored to train and share CBM models without the need to share the data. Federated Learning is a new technique that has the potential to solve the data sharing problem among companies and stakeholders while offering data-private model learning. Advanced settings increase the convergence speed hence models can be generated faster by reducing the amount of data needed to be sent to the server. 

Watch the ReMAP video in which we explain the architecture of the IT-platform that offers the Integrated Fleet Health Management-solution using Federated Learning.

  • Group 2Created with Sketch. What aspects of CBM have the most potential to deliver operator benefits?

Considering an airline’s profitability goal, the objective of the maintenance organization is to contribute to maximizing the airline fleet’s earning potential: maximizing the fleet availability and dispatch reliability (the proportion of planned flights that can be realised), at minimum cost. CBM has the potential to contribute to this but estimating that actual potential is challenging. “Nobody in the industry is able yet to perform a robust economic analysis, simply because there is no sufficient and extensive CBM experience and data to support such analysis”, states Roberto Hirschman (Embraer), Member of the ReMAP Advisory Board in his blog.“ That’s why ReMAP is an excellent initiative and opportunity to exercise CBM addressing all aspect of its implementation and adoption.” But estimating the ultimate benefit that CBM technologies will provide in an airline environment can be challenging, as Floris Freeman of KLM states. An assessment is needed on what is realistic in terms of technology performance, and what benefits are to be expected (download ReMAP-deliverable)


ReMAP will test its IFHM solution in an unprecedented 6-month operational demonstration, involving more than 12 systems in two different aircraft fleet of KLM and KLM City Hopper (twenty Boeing 787 airplanes and ten Embraer 175). Research will be done on the expected impact from CBM on the short- and long-term on fleet availability, maintenance cost and system complexity and weight benefits. Complementary the potential of CBM to deliver operator benefits will be examined.

For structures, health prognostics algorithms will be demonstrated in a laboratory setting. Representative structural composite subcomponents are subjected to a spectrum of fatigue loading. Part of the demonstration will estimate the structural weight benefits out of the SHM technology adoption in primary structures.

The ambition for both demonstrations is to prove that, under the current regulatory framework, ReMAP’s IFHM solution will lead to:

    • a 4.5% reduction of direct maintenance costs (110 thousand euros less per year for a long-haul aircraft);
    • a 3 to 7% weight reduction of structural composite components; and
    • a 10% missed failures reduction, reducing the need for systems redundancy and reducing complexity.
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