Over the last several years predictive maintenance and predictive analytics have become one of the major priorities for commercial airlines. This being driven by more and more data becoming available for aircraft, lower costs for data storage and newer technology becoming available to analyse this data effectively. However, 10 to 15% of aircraft in our industry are not operated commercial airlines but are business jets, which do not fly typical commercial operations. This raises the question as to what business jet operators could potentially stand to gain from predictive maintenance and if there are any notable differences when compared to commercial airlines. In order to explore this further, we first need to look at the key distinct differences as well as the similarities between commercial airline operated aircraft and business jet operations.

Clear similarity between business jet operations and commercial airlines is the fact that for both, the same set of airworthiness regulations apply. This brings the advantage that a large set of required data is effectively available for predictive analytical purposes. You can think of items such as:

  • Maintenance program
  • Minimum Equipment List
  • Component Removal & Installation records
  • Pilot reported defects
  • Maintenance reported defects
  • Base maintenance task card findings
  • Aircraft Utilization
  • On board data such as FDR/QAR data

However, one must note here that a portion of aircraft types classified as business jets are actually lighter than the regulatory threshold of 5.700KG. For instance, the Embraer Phenom series. For these aircraft a "light" set of airworthiness regulations applies, and hence also a smaller set of aircraft data is expected to be available for predictive analytical purposes.

Key differences in business jet operations

Next to this, there are a two main key differences in business jet operations that further impact the way in which we can do predictive maintenance with business jet operators. These include:

Most, if not all, business jet operators do not fly a regular scheduled flights operation. This makes it hard to detect the conditions under which the aircraft will operate for future flights. Think of airports it will fly to/depart from, weather likely to encounter or even detecting if the aircraft will be exposed to prolonged dry of humid operations.
Customer experience is a crucial aspect for business jet operators. Even more so then for commercial airlines. Arguably rightful so, as people flying with these jets are paying a considerable amount for those aircraft being available when they need it and, in the condition, they want to have it. This makes that items such as operational galley equipment, inflight entertainment, cabin lighting, at seat power and general wear and tear of seats and other cabin items are considerably more significant than they are for commercial airlines.

What to consider for business jet operators

In order to accommodate this in any predictive maintenance system, business jet operators need to consider the following for their predictive maintenance projects:

Components to monitor cannot be limited to airworthiness related components only, and need to include passenger convenience classified items on board the aircraft
Predicting wear & tear and probability of failure of such passenger convenience items requires a different modelling technique in order to predict a level of when they potentially need to be replaced. This due to low availability of usage data such as sensor or FDR parameters
Accuracy of future expected flight operations is going to be lower than for commercial airline scheduled flight operations. As system deployed for predictive maintenance purposes in business jets should look at AOG risk factors per aircraft rather than full prediction of component failure.

When looking to embark on a predictive maintenance project as a business jet operator, also have a look at this article: Are you ready for predictive maintenance?. In order to gauge how ready your organization is for adopting predictive maintenance technologies and processes.

How EXSYN can help

EXSYN's team of aircraft data and aviation experts utilize a proven framework and methodology for adoption of predictive analytics in aviation. It has been applied to numerous fleets and aircraft and includes:

  • EXSYN’s pre-build Avilytics environment of analysis modules, widgets, formulas and algorithms on a wide range of ATA chapters and components
  • Workshops to identify the specific maintenance complaints to be monitored for each fleet operated by your airline
  • Implementation of identified complaints per aircraft type and registration into the Avilytics environment. Including data mining, validation and user interface design.
  • Native integration of the Avilytics modules in your own platform or hosting in the digital environment in case your airline does not have a data warehouse yet
  • Training of identified user groups
  • Adoption workshops to support successful day-to-day usage of the predictive analytical techniques and business models
  • Machine Learning to identify future potential maintenance complaints to be monitored
  • Ongoing software maintenance support for modules implemented

Schedule a free session with one of our experts so that we can learn more about your situation and see how we can help you: