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Maintenance

Spreading the load

Having started to use Aerogility’s multi-agent software to plan hangar slots for heavy maintenance visits, easyJet has now extended use of the system to cover landing gear and engine overhauls. Ian Harbison reports
 
Gary Vickers, CEO of Aerogility, says the holistic approach behind Aerogility means the solution can serve a number of different purposes. The initial application by easyJet was the forecasting of heavy base maintenance visits (see MRO Management, September 2018), using simulations to predict when aircraft needed to be in the hangar.
 
The concept can be extended to engines and landing gear, with the advantage all the planning can be in one place and is a joined up process, avoiding ‘swivel chair integration’. Phil Cole, Business Manager Civil Aviation at Aerogility, explains that landing gear planning has been added to the hangar visits, as they are closely aligned, while engine planning is a different function, reflecting the company’s experience with a number of airlines.
 
Thus, landing gear events will be placed outside the busy summer flying schedule and put into the winter maintenance window, enabling the airline to decide whether to move the events together. A complication here is that easyJet has a number of maintenance locations, so MRO capabilities at each site are also stored on the system, so that can be factored into the decision making process. Similarly, the Space-Flex V2 rear galley conversion programme is being carried out at a number of MROs, and so this data can be added and the simulation aspects of Aerogility can be used to determine the best time and location for each aircraft, with or without a simultaneous heavy check. 
 
 It is a very simple process to add additional tasks such as this, says Vickers, adding that, as a result, the airline has been finding increased productivity and flexibility benefits in recent months. 
 
For the engine side, which easyJet started using in December 2018, Cole says the airline has a fairly straightforward approach to overhauls, and Aerogility is being used to schedule maintenance based on an entire powerplant reaching the required number of cycles. However, some complexity is provided by there being a mix of owned and leased engines. 
 
The latter are sent in for maintenance as close to the due date as possible, even if this means putting an owned engine into the shop and losing flight cycles. Leased engines also have to be reinstalled on their dedicated aircraft when it is returned at the end of the term, which requires a high level of organisation and planning. Again, this can be resolved using Aerogility. For another customer, the company is looking at a scheduling model based on LLPs with the least remaining cycles in separate engine modules. If the core comes in on its due date, Aerogility will produce a status report on LLP life in the LPT and LPC, giving the operator the option to include them in the workscope or not. This would also be a help for leased engines. 
 
Depending on the lease conditions, some remedial work could be avoided if the LLPs are within limits. On the other hand, if the engine is at the end of its life or at the end of the lease, green time parts could be installed at lower cost to get it there. Cole comments that the mix of owned and leased engines resulted in a massive scheduling task, extending beyond just maintenance to such things as ensuring that a spare powerplant is available on site and on time.
 
Vickers adds that, while some of the business rules are uncomplicated, it is the interaction of all the processes that takes the time. The Aerogility scheduling team described it as one of the hardest projects they had worked on, involving multiple planning goals to come up with the final programme. 
 
Another aspect of the Aerogility platform, is that easyJet  will be able to identify and evaluate the impact of one department against another, helping interdepartmental communication throughout the MRO process, and allowing the airline to compare the effect each department has on the successful running of the airline over the next two years.
 
Vickers says that the fact that Aerogility handles multiple component scheduling in one solution is a big selling point compared to the processes ERP systems, and is generating a lot of airline interest. As a result, the company is focusing a lot of resources in this area to capitalise on the advantage. 
 
Coverage may also expand. APUs and thrust reversers are possible targets by airlines but the company is looking at line maintenance and lighter checks. Cole explains that there is a much greater level of detail required for line maintenance, with many more variables. A heavy maintenance visit can be scheduled in two years’ time, with a 15-day timeslot and no need for a detailed workscope. Planning an overnight slot requires a detailed programme to ensure that the work can be completed, so the aircraft is on 
the line in the morning and, if there are unscheduled arisings, that an alternative aircraft is available.
 
That plays to Aerogility’s strengths, adds Vickers, noting that is it is difficult, but the company will get there eventually. Cole says getting the data into the system and maintaining the programme with Aerogility is important, plus synchronising with the MRO involved, as each is slightly different in working methods. 
 
Vickers adds that big data and predictive maintenance is becoming more common, but is based on history, extrapolating trends from collected information. While that is important, there is a different dimension to it, as it will show up new events that have not been detected before, and so airlines will have to figure out how to resolve these challenges. He says Aerogility, with its ability to produce holistic simulations in a powerful and realistic way, will be able to help.
 
Adding a new event will enable operators to project the effect of such a case on their schedules and KPIs, then specialist personnel will be able to compare and contrast various approaches before deciding on the best approach. Alternatively, using an optimisation approach, a solution can be found based on the balance of probabilities to find the best strategy. 

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