Aircraft IT MRO Issue 59: Spring 2024

Aircraft IT MRO Issue 59: Spring 2024 Cover


Name Author
WHITE PAPER: Current Trends in the Predictive Maintenance Aftermarket Dr Ip-Shing Fan, Senior Lecturer in Enterprise Systems at Cranfield University and John Maggiore, senior aerospace leader and consultant and Senior Advisor to the Integrated Vehicle Health Management (IVHM) Centre at Cranfield University View article
CASE STUDY: Making a good digital start at Heston Airlines Edgaras Knyzas, Head of CAMO, Heston Airlines View article
CASE STUDY: Production planning and control at China Airlines Wei-Fong Wang (Matt), Senior Engineer, Maintenance Division, China Airlines View article
CASE STUDY: An RFID cabin monitoring tool at AirAsia Thailand Banyat Hansakul, Group Head of Engineering, AirAsia and Nazrulazli Najmudin, Senior manager, Product and Technology, Asia Digital Engineering (ADE) View article

WHITE PAPER: Current Trends in the Predictive Maintenance Aftermarket

Author: Dr Ip-Shing Fan, Senior Lecturer in Enterprise Systems at Cranfield University and John Maggiore, senior aerospace leader and consultant and Senior Advisor to the Integrated Vehicle Health Management (IVHM) Centre at Cranfield University


Words: Dr Ip-Shing Fan, Senior Lecturer in Enterprise Systems at Cranfield University and John Maggiore, senior aerospace leader and consultant and Senior Advisor to the Integrated Vehicle Health Management (IVHM) Centre at Cranfield University

Predictive Maintenance (PMx) is part of the ecosystem of digital solutions for aviation aftermarket that has been maturing over the past 20 years. We can describe ‘digital aviation’ in a general sense as: knowledge or insights embodied and delivered via software on, at, or about an aircraft to deliver value to aircraft operations. Operations can be divided into major verticals, including Flight Operations, Technical Operations, Ground Operations and Passenger Operations. Focusing on the Technical Operations vertical, we can categorize the aftermarket digital offerings into several key capability themes. These themes include:

  • Digital and Mobile Maintenance Documentation;
  • Maintenance Planning / Systems of Record;
  • Electronic Tech Log / Electronic Logbook;
  • Digital Records Management;
  • Asset Lifecycle Optimization / Leasing;
  • Proactive and Predictive Maintenance / Health Management.

The offerings are highly inter-connected. For example, PMx depends on having digital data that could come from one or more of the different record and documentation systems. The capabilities of the digital solutions are enabled by the rapid advance in Data Science and AI, on-board Data Acquisition and Edge Computing and Data Connectivity.

Predictive Maintenance (PMx) emerges as the area with most promise and investment within the Technical Operations digital ecosystem. Recently there have been multiple new entrants into the market space keen to promote the value proposition of PMx to the operators. That value proposition includes quantifiable benefits spanning operational performance, asset utilization, and labor costs and utilization1.

To clarify some terminology, Predictive Maintenance is a sub-category of Integrated Vehicle Health Management (IVHM)2. ‘Health Management’ refers to the use of data to manage the current or future serviceability of an asset. ‘Serviceability’ is the degree to which an asset can achieve its intended mission. Of course, in the case of IVHM, the asset is a ‘vehicle’ and, for the purposes of this article we’ll assume that the vehicle is an aircraft or is related to aircraft or their operations. Aircraft Health Management, Airplane Health Management and Engine Health Management (EHM) are specific applications of health management to assets. ‘Proactive/Predictive Maintenance’ are complementary terms, and related to Health Management, but with focus on actual maintenance activities. Proactive Maintenance is using data to manage a condition or failure which has already occurred. For example, moving the planning to the ‘left’ so the fix/fly decision can be made as soon as possible, with the highest degree of accuracy, in the most efficient manner possible. Predictive Maintenance (PMx) builds upon Proactive Maintenance to use data and information to predict, before it happens, and with a reasonable certainty, that a failure or condition which will impact serviceability will occur.


We can observe through publicly available information the on-going transformation of the PMx ecosystem, with innovations in the established PMx aftermarket participants such as Engine and Airframe Original Equipment Manufacturers (OEMs), and accelerated activity by Equipment Providers, Operators and Independent Providers.

From a historical standpoint the Engine OEMs were the original pioneers of PMx and health management, making significant investments in and progress on engine health management, pathing the way for much of what would come later. This focus continues today, as the engine maintenance aftermarket is a vast part of the MRO landscape, and PMx is a major enabler of engine maintenance programs. Examples of Engine OEMs focused on PMx include General Electric, Pratt and Whitney, Rolls-Royce and Safran.

Airframe OEMs such as Airbus and Boeing have each had significant focus on health management offerings for over 20 years. The reasons for this are obvious. Airframe OEMs and Engine OEMs have the major stake in the efficient operation of their deployed fleets, and an imperative to maintain product intimacy with the in-service aircraft for continued design improvements, along with normal aftermarket revenue imperatives. Airbus goes to market with its Skywise3 suite of offerings (in partnership with Palantir, one of the independent providers discussed below). Boeing offers Airplane Health Management (AHM)4 and the recently announced Insight Accelerator5.  Embraer has an aftermarket health management offering called Aircraft Health Analysis and Diagnosis (AHEAD)6.

Tier 1 Equipment Providers are increasingly active within the PMx domain. A Tier 1 supplier is a company that supplies components, or services directly to the assembly plant. These providers supply systems large and small, some of which are the equipment being monitored (e.g., an auxiliary power unit) or are core aircraft capabilities such as integrated avionics suites. Equipment Providers who are active in the PMx aftermarket include Collins Aerospace’s Vehicle Health Monitoring Systems (VHMS)7 and its Ascentia8 AHM platform, and Honeywell’s Forge Flight Efficiency Analytics Platform9. Parker Aerospace is also investing in PMx via design and build predictive algorithms in cooperation with their manufacturing division engineering team.

Jeff Smith, Head of Digital Product Programs at Parker Aerospace says, “Parker Aerospace is very focused on predictive maintenance. We are actively pursuing direct data sharing agreements with operators and platform owners and have built a robust data science team to understand data associated with the operation of our parts while on-wing of the aircraft. Knowing when a part is starting to fail helps us engineer more reliable parts and helps our customers reduce cancellations and delays.”

For commercial Operators the imperative to remain profitable and competitiveness continues to motivate the majority to use at least one PMx solution. In recent years we have also seen operators evaluate and deploy multiple PMx solutions to maximize the realized benefits. For some larger airlines their size and scale points to the efficacy of investing in in-house capabilities. Operators do have some key advantages with the PMx value chain. Recently we have seen Operators extend these in-house capabilities into the aftermarket via their aftermarket commercial entities. For example, Lufthansa Teknik offers their AVIATAR suite of digital offerings which include their ‘Condition Monitoring’ PMx offering10. Notably, AVIATAR is part of the Lufthansa Group’s Digital Tech Ops Ecosystem which also includes AMOS maintenance planning software and FlyDocs digital records software11. In addition, the industrial branch of the Air France-KLM group has launched Prognos, their aftermarket predictive maintenance solution12 13.

Independent Providers make up a diverse group, some of which are focused primarily on the data science angle of PMx, while others approach the problem from a data acquisition standpoint. Examples of Independent Providers who approach PMx from an analytics standpoint include Palantir14, SparkCognition and Freya Systems. As mentioned above, Palantir is an example of a large analytics provider extending into PMx, among other applications. In a similar way SparkCognition15 also applies AI to PMx related problems. We also see smaller analytics companies which are exclusively focused on Aviation such as Freya Systems16 making advances in PMx.

Ben Johnson, CEO of Freya Systems says, “We are certainly seeing an increase in both positive outcomes and the use of PMx in the aviation space, our primary niche. With the improvements in sensor data capture on the aircraft and MRO digital transformation initiatives which are improving maintenance records, data fidelity is improving daily. We work in tight collaboration with Subject Matter Experts who grow ever more excited about the significant results we can regularly deliver with custom Machine Learning / Artificial Narrow Intelligence solution due to these data improvements.”

Other Independent Providers bring data acquisition and connectivity to bear to the problem of PMx execution. For example, Shift517 is focused on Cyber Resilience and PMx via increased data observability through edge computing and AI. Teledyne Controls offers a PMx solution18 based on Quick Access Recorder (QAR) data for selected aircraft systems, leveraging their broad data acquisition portfolio. FLYHT Aerospace Solutions provides PMx aftermarket solutions19 leveraging their air-to-ground connectivity capabilities.

While not an exhaustive list of PMx participants, we clearly see a drumbeat of continued focus and investment by an increasingly diverse set of PMx actors.


It may be a surprise to some that PMx might increase maintenance costs. Fundamentally, the operators pay for the scheduled maintenance, and with additional charges for any unscheduled maintenance. PMx triggers additional unscheduled events which incur the associated costs. PMx is only beneficial when the cost is offset by the value of improved Serviceability. Within operational performance the area that most people are aware of is the idea of reducing schedule interruptions (e.g., delays, cancellations, and air turn backs). If we go deeper into the delays area, we can divide this into a reduction of the number of delays and a reduction of their duration – i.e. delays still take place but through PMx activities they can be reduced in length. Another key operational performance area is the reduction of minimum equipment list (MEL) items, or reduction of dispatch deviations. That is, the reduction of times when we dispatch the aircraft with items against the MEL; by reducing these there is a quantifiable value. In addition, by operating with fewer dispatch deviations, airlines can avoid both reduced performance penalties such as reduced fuel consumption and onerous performance limitations such as ETOPS limitations. Perhaps the most significant saving in this area is the reduction of unscheduled maintenance. That is, maintenance which might have been done in an unscheduled fashion that can be scheduled into an appropriate scheduled maintenance slot via predictive maintenance awareness provided via PMx compliance and cyber resilience.

Asset utilization (sometimes called asset optimization) is a broad topic which is receiving increased attention. The goal of asset optimization is to get the maximum benefit for an asset throughout its lifecycle; to create more capacity in the system and reduce the cost of ownership. An asset can be an aircraft, an engine, an APU, or any sub-assembly worthy of optimization. The data and health information created via PMx is a key part of the asset optimization calculations. In addition, the efficiencies which flow from PMx support lower parts and sub-assembly consumption, especially those which might involve rushed shipping of parts or even borrowing of parts from other airlines.

PMx has measurable and quantifiable saving for both labor and maintenance costs. For instance, the effort it takes for maintenance planning can be reduced because of a forward-looking, predictive situational awareness. In addition, the maintenance control function within an airline is much streamlined with this forward-looking information. Aircraft turnarounds are more efficient with knowledge of the aircraft’s health at landing. Of course, reducing no fault founds (NFF) and the accompanying shop maintenance cost is another direct savings within the maintenance cost area.


We have observed that intelligent PMx end users gain significant value from their PMx investment by changing their operations, maintenance planning and spares management practice to effectively PMx derived insights. For the many operators starting on the PMx journey, the inherent difficulty of deployment at an enterprise scale is often overlooked and underestimated. Each airline has its own rules and operations philosophy. Each aircraft has its unique history built up from its flight and maintenance history. While the PMx solution provides a platform for data consolidation and analytics, the operators need to make PMx choices according to its business and fleet character. While there are many lessons that could be learnt from others, the PMx model for each airline is unique.

The key questions of the steps are:

  • Demand and Priorities: What specific equipment and conditions are causing disruptions or excessive costs?
  • Data Access and Opportunity: What data are available to monitor, and what is the best approach to leverage the data?
  • Domain Knowledge: How to secure the rights to access the data, and the specifications which describe and define the data thus making it usable?
  • Knowledge Development and Maintenance: How to acquire and sustain the resources in engineering analysis; data science and other analytics required to create and maintain a usable set of knowledge which supports the scope of the PMx project?
  • Delivery and Action: How to establish and embed new working practices so that all the users and stakeholders within their job roles across the enterprise can effectively leverage the PMx insights to support operations decisions for maximum business return? Also, how to deliver the decision support information to a global end-user community within their various job roles?

The feedback loop from Delivery back to Knowledge Development is also a fundamental requirement of any PMx. That is, are the PMx recommendations effective, and how can they be improved and updated.

The first four steps cost investment. The PMx deployment returns value only if the final step delivers business benefits beyond the investment.


There have been major PMx signings announced in the last 12 months. The PMx technology providers are presenting use cases and can demonstrate that PMx technology is ready.

The airline community is in the expand stage according to Cambier’s innovation adoption diagram (figure 3). A number of the large airlines are reaping the benefits of their PMx investment and extending their PMx usage. These airlines historically have strong reliability engineering programs and an established practice of proactive maintenance.

Cambier, A. (2018). Big Data: Racing to platform maturity. ICF.

The new PMx signatories are convinced about the potential business benefits. However, many are attracted by the promise of PMx but do not necessarily understand the associated business transformation requirement to reap the benefits.

The first hurdle is training. Some PMx participants are not sure who to send to the PMx training. Engineering specialists rising through the ranks from licensed engineers/technicians did not enter the career because of their aptitude in statistics and mathematical modelling, much less programming. Establishing a PMx function to generate usable insights could need new talents and building cross functional teams.

To deliver demonstrable business benefits, PMx alerts and warnings need to be acted on and effects measured. It is the airlines responsibility to act on them and decide on additional inspections or parts removal. There are instances where these work instructions were pushed back when they were issued without reasoning that the engineers can understand. There is also the practical argument of whose budget should the PMx triggered work be charged to.

David Miret Mora, Technical Director at AJW Group21, emphasizes the need for collaborative discussion among aviation stakeholders to address the regulatory and contractual complexities related to Predictive Maintenance (PMx) removals. He points out uncertainties in scenarios like finding no fault in a shop check (NFF) and questions whether the part should be set to full life or only for the remaining duration from the removal point. Additionally, Mora suggests reconsidering the approach to Beyond Economic Repair (BER) or Overhaul, emphasizing the impact on the cost benefits of PMx implementation. These issues are not showstoppers to adopting PMx. However, they are important ones to address before successful PMx roll out.

The case for PMx has been made and new contracts are signed. This is the time for the industry to use the PMx insights effectively and book the financial benefits in the company accounts, and not only isolated use cases. Beyond the successful PMx innovators, the wider industry needs a lot more people who have the business understanding and technical skills to fully gain the benefits of PMx.


Given the above one can make basic assessments of the relative advantages and disadvantages the different participants bring to the various Value Chain elements. This is by nature an inexact and subjective assessment, but it takes into account one or more PMx solutions, the value chain and what providers can or cannot realistically execute at scale. Of course, for a given PMx project, a focused scope (e.g., a smaller set of monitored equipment or conditions) rather than an entire airframe or equipment, the assessment against the value chain will likely be quite different.

Predictive Maintenance is a key element of the Technical Operations digital ecosystem, with compelling and quantifiable benefits. Moreover, these benefits are not theoretical but have been shown to be realizable.

Graham, Graham Braithwaite, Director, Transport Systems at Cranfield University says, “Cranfield University is proud to help to advance the state of the art regarding efficiency and sustainability within the global aerospace and transportation network. The complex and expanding discipline of predictive maintenance is an excellent example of this. We are delighted to team with our industrial partners via the IVHM Centre and Digital Aviation Research Technology Centre (DARTeC) to best align our students’ research with the most relevant and pressing real-world challenges.”

Ultimately, the full PMx Value Chain must be executed for value to be delivered. However, the actual execution of the required value chain is not trivial. This can be done by one or by multiple participants. Each PMx participant brings their own technical specialization, business objectives and intrinsic advantages/disadvantages to the PMx ecosystem. Each has an important role to play, and an opportunity to deliver meaningful value to operations. For these reasons, investment, and innovation in PMx is poised to continue for the foreseeable future.


The Integrated Vehicle Health Management (IVHM) Centre is a joint effort by industry and academia to develop state-of-the-art capabilities that change the way services are provided today. IVHM is the unified capability of systems to assess the current or future state of the member system health and integrate that picture of system health within a framework of available resources and operational demand. It is a very wide-reaching capability encompassing: business cases and models; legislation, certification and standards; architecture and design; as well as algorithms for prognostics, diagnostics and reasoning.

The IVHM Centre was launched in 2008 by Cranfield University, Britain’s premier postgraduate, research-intensive university, together with Boeing, Rolls-Royce, BAE Systems, Meggitt and Thales. It is located at Cranfield University in the UK. The Centre is globally recognized, having defined the subject area, and is further developing new areas of expansion. The development of the Centre, along with other areas in the University, significantly contributed to the creation of the Digital Aviation Research and Technology Centre (DARTeC). Through DARTeC, the IVHM Centre leads the MRO (maintenance, repair and overhaul) developments and activities with expertise and capabilities in UAV robotics NDT inspections, SHM sensor monitoring, and advanced digital technologies, such as artificial intelligence (AI) and digital twins (DT), tools that could be used to synchronize, monitor, and improve all processes related to aircraft MRO.

The IVHM Centre supports commercialization, reducing time to market, and combines technology, business and technology transfer solutions. We have a robust innovation cycle and applied research demonstrators with access to a world class IVHM community and new market opportunities, which influence development of industry standards and policies.

Comments (0)

There are currently no comments about this article.

Leave a Reply

Your email address will not be published. Required fields are marked *

6 + 16 =

To post a comment, please login or subscribe.