The commercial aviation sector is going through continuous changes and challenges. The global airplane fleet size is expected to grow in big numbers over the coming decade. New, more fuel efficient, aircrafts pushes old planes into early retirement and carriers do not want to be the last operating an expiring plane type. Portfolio decisions about fleet replacements and configurations must go hand-in-hand with operational planning and MRO strategies. Strategic fleet management plays a central part in laying the puzzle, but connecting all the dots and balancing all factors in these decisions is hard and complex. The Opus Suite with its holistic modelling approach has the ability to replicate this complex reality, connect the dots, and produce the insights needed to make even smarter decisions.
How should the ramp up schedule for a new fleet look like? What does it depend on, and what depends on it? These are simple questions to ask but not so simple to answer. Perhaps another older fleet will be retired and phased out in parallel. The phase in and phase out schedules will then have dependencies to consider. How can these be scrutinized and managed? The demand of e.g. rotables will certainly grow for the new fleet as it ramps up, and likewise will the demand for repairs and reorders decline for the fleet being phased out. Surely it isn’t justifiable from a financial point of view to buy all the rotables for the new fleet on day one – can we lease or pool the heavy components? If so, how should we configure the stock assortment and allocation, and when should we reconfigure? Needless to say, these types of interconnected questions are complex, and grow exponentially. Aircraft leasing, MRO outsourcing, and full service agreements with availability guarantees can be convenient options, but how do we know that the cost isn’t too high? To successfully negotiate terms in those kind of contracts a thorough understanding of the baseline is a must. Luckily, these types of questions are Systecon’s bread and butter and what the Opus Suite has been, and continuously is, developed for.
The aviation markets is also fiercely competitive so finding the right economic balance between AOG and stocking costs is more important than ever. Some carriers set a goal for technical dispatch reliability (TDR) and assume AOGs are so costly, they must minimize them despite the cost. That is a rigid rule, and ignores wide variation in AOG costs. AOGs can cancel flights or delay them for a couple of hours. Early morning AOGs throw off schedules for the rest of the day—late domestic AOGs do not. Aircraft size, load factor and passenger mix all affect AOG costs. And AOGs can happen at any airport.
There are some general rules for estimating costs. For passenger airlines, fare revenue is not lost since passengers are rebooked on other flights. But cargo carriers may lose all revenue if cargo is not delivered on time. That is one reason cargo carriers tend to keep spare aircraft more frequently than passenger airlines. In the EU, there are penalties for delays, and these costs count. Costs for overnight delays include meals, transport and accommodations for passengers. Extra crew costs are determined by labor agreements. Mechanics require overtime to deal with AOGs, and expedited-shipping costs are incurred. Marketers use intent-to-repurchase models to estimate future business lost due to the AOG experience of passengers.
Finally, cascade effects—including all the above costs on the rest of the schedule—should be included. The results are a series of “what if” costs for AOGs of varying severity and condition.
With Opus Suite you can estimate the probability of occurrence for each kind of AOG. This starts with the reliability of no-go parts, category 1 on the minimum-equipment list, whose malfunction grounds aircraft immediately. Utilizing part reliability, AOG costs, planned flying hour requirements, criticality, target availability, repair TAT, and more in the algorithms to plan and optimize both rotable and consumable inventories for airlines and MROs. We focus on optimizing how many to hold, where to keep them, how many to repair and what service level to seek, and finally how to execute this optimized plan.
Our market leading software optimizes stocks based on desired service levels, for example having critical parts available 95% of the time they are needed, while accounting for how e.g. spare aircrafts, flight plans, and operations schedules impact the risk of AOG. The result can be used in several ways to both optimize the location of parts to meet that objective, or predict AOGs based upon a fixed level of stocks.
Opus Suite integrates with MRO or ERP systems for streamlined and accurate updates, utilizing the latest information available. With Opus Suite's sophisticated optimization and simulation capabilities, it is possible to reduce AOGs by 30% or more while often decreasing the capital expense of spare parts by at least 20%.