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Gulfstream Aerospace Uses Predictive Simulation to Optimise Maintenance Hangar Expansion

Gulfstream Aerospace is the world’s most famous business aviation company, known for its superior engineering and 24/7 global support. Service is a competitive advantage, and so optimising capacity and throughput across its maintenance network is critical to growth.

The challenge: Determining the optimum time and place to invest in maintenance hangars

One of Gulfstream’s biggest strategic challenges is understanding where and when to build maintenance hangars. Each hangar equals $20 to $50 million investment, creating 200 highly skilled technical jobs. It is crucial that the business doesn’t incur the investment cost too early, creating unnecessary capacity, or too late, risking an erosion of customer confidence.

Gulfstream currently have 12 hangers worldwide, and with demand increasing, Gulfstream recognised the need for additional Maintenance hangers, however there were several challenges complicating hangar investment decisions.

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First of all, maintenance is a highly variable process. Gulfstream has 6 current aircraft models, with approximately 10 older ones still in service. These have a range of maintenance requirements and operating characteristics, and the company needs to accommodate these varied demands and service schedules within its support network.

In 2020, the company will be releasing 2 new aircraft – the first time it has launched 2 at once. Launches introduce further complexity into maintenance capacity planning due to constraints on the tooling and trained manpower available for the new models.

Gulfstream also provides aircraft for a variety of government and special mission applications. These create unique constraints as modifications and security requirements can lead to long periods of time in the hangar, which affects available space.

Finally, in addition to its 12 hangars worldwide, Gulfstream has a mobile support network of people, parts, trucks and aircraft. They needed to factor in how these mobile support capabilities could be used to offset hangar requirements and defer additional capital investment, for example by identifying scenarios when tech teams can go to a customer instead of having the aircraft come to the hangar.

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Lanner’s approach: Proof-of-concept model delivers practical insight in just 10 weeks

Gulfstream’s first attempts at modelling used simple Fermi estimations based on the percentage of the fleet in maintenance at any given time. Looking at future production schedules, the team could extrapolate the number of hangar slots in line with fleet expansion.

However, when the team started connecting work order data to run basic ‘what-if’ scenarios, the spreadsheet quickly became unwieldy. For example, they wanted to analyse requirements based on aircraft operating characteristics, customer segments, technical headcount, market conditions and digital transformation investment. These key business questions were too complex to model in the spreadsheet, so Gulfstream turned to Lanner to take it to the next level.

Using the spreadsheet as a baseline, within 10 weeks, Lanner developed a proof-of-concept model using WITNESS  predictive simulation technology. It aggregated data from disparate enterprise systems and visualised it in practical, user-friendly pivot tables.

Once we had this high-level architecture, Gulfstream used machine learning and data warehouse automation to segment its data and fill in information gaps. We then developed the model’s capabilities, so the team could test different scenarios in a risk-free environment. This included the ability to experiment with aircraft maintenance demands, hangar space availability, manpower levels and service centre scheduling rotas. We moved from pivot tables to advanced slicers, eventually integrating ‘R’, an open-source data analysis platform, to deliver more dynamic visualisation.

The outcome: A robust business case for $20 million of investment

The Gulfstream team used the model as part of the business case presented to its parent company, General Dynamics. It helped justify more than $20 million of investment for 4 hangar expansions in the US and UK.

Following this success, Lanner worked with Gulfstream to refine the models, making them easier to maintain while increasing their business value and accuracy. This has included enhanced visualisation, improved reporting and increased data processing speeds.

With Gulfstream continuing to develop its fleet and maintenance offering, predictive simulation is playing a vital role in optimising throughput and capacity – and helping it make informed investment decisions.

“Lanner’s approach started with a high-level model that we could drill into to reveal deeper levels of detail. Through successive refinement, we achieved complex and accurate representations of actual processes while making the model easier to use. We were also able to leverage Big Data tools to enhance analysis and visualisation. As a result of this approach, we very rapidly got value from the model, using it to help execute the largest expansion plan in our history.”
-Dan Ellis, Gulfstream Aerospace
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Gulfstream Aerospace Corporation designs, manufactures, markets and supports the world's most technologically-advanced business jet aircraft. It has the largest customer support structure in business aviation, with 12 global locations, 4,700 employees and more than 2,700 aircraft in service.

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