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TFD2017-11-13T22:14:02+00:00

Project Description

CLIENT
TFD logo
PROBLEM

A new model of aircraft enters the marketplace, and the client wishes to investigate the value in making upgrades to existing aircraft or replacing them with the new model.

The existing fleet has two types of aircraft which flew three types of missions. The new aircraft are more expensive to run (per flight hour) but have an increased flying speed and cargo carrying capacity. The time frame considered is 30 years.

BRIEF

The client wishes to test a range of schedules of upgrades and replacements. Several schedule scenarios need to be compared by metrics of cost, flights hours per month, cargo productivity and residual value of the fleet.

One key challenge in this investigation is the complexity of the daily fleet mission requirements and the timing of when to upgrade or retire existing aircraft, and when to purchase new aircraft.

The client needs a visually captivating model which allows scenarios to be created and compared quickly and easily.

SOLUTION

Due to the complexity of the fleet activities and the stochastic nature of the flying programme, it was decided that an Optimisation procedure may be too computationally demanding. Simulation is able to model complexity and stochastic elements neatly and quickly.

decisionLab built an agent-based Simulation model of the fleet management process. The user inputs the state of the current fleet and their proposed upgrade, replacement and retirement schedule. The simulation visualises the fleet performing its duties over 30 years, and gives the user options to adjust input parameters in order to compare scenarios.

Uncertainty in the system is accounted for by considering probability distributions on some of the parameters, e.g. the average age of current aircraft. An aircraft’s age is taken as an indicator of its current value.

decisionLab also provided a rich picture of the fleet management process as a visual aid to the client’s presentation meeting.

Conceptual Modelling, Mathematical Modelling, Analytical Modelling, Agent Based Modelling, Multi Method Modelling
data analytics, data science, optimisation, simulation, asset management, artificial intelligence
Conceptual Modelling, Mathematical Modelling, Analytical Modelling, Agent Based Modelling, Multi Method Modelling
SUCCESS

The simulation is able to capture the complexity of the process, and give the user an impression of how the metrics were behaving over time. The user is able to test the robustness of proposed upgrade and replacement schedules using the scenario comparisons.

FEEDBACK

“TFD Europe Ltd would like to express their complete satisfaction in regard to the C130 High Level Operations Fleet Simulation Tool that you recently developed. This was a potentially complex problem which you analysed quickly and which was reduced to a simple, clear solution. The working model was produced in under 2 weeks and I can report that the pace, presentation and utility of the model delighted the end customer. Once again, thank you very much.”

Allan Goody, Director, Services and Solutions, TFD Europe Limited

FUTURE PLANNING

The client has invited decisionLab to examine its existing optimisation procedures and offer insight.