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19009 DEFAINE (Design Exploration Framework based on AI for froNt-loaded Engineering)

Reference number
Coordinator Chalmers Tekniska Högskola AB - Industri och materialvetenskap
Funding from Vinnova SEK 8 576 634
Project duration September 2020 - February 2024
Status Completed
Venture Eureka cluster co-funding 

Purpose and goal

The project has, with the help of AI technology such as machine learning has developed methods and tools in several disciplines to be able to effectively explore and optimize a larger number of construction alternatives, a design space. Being able to prepare (Front-loading) project for this type of activities aims to: · Reduce recurring costs when designing aircraft by 10% and · Reduce design update lead time by 50%. Methods and tools have been demonstrated in various use cases. The project has been presented in various events and publications.

Expected effects and result

The targeted KPIs were met, demonstrated in the project´s use cases: - Number of design objectives traded (target:20 achieved:24) - Design space dimensionality (target 50% increase, achieved = 400%) - Lead time for design update (target 50% decrease, achieved: 91%) - Number of design variants evaluated(target: 10x, achieved:40x-steady state, 15x -transient model) - Lead-time for design update (target: 8-40hrs, achieved: 0.5-1hrs ) - Simulation workflow set up (target: 1 week, achieved: 5 hours) - Conference publications (target: 8, achieved: 12) - Events (achieved: 7)

Planned approach and implementation

The work has been carried out with Swedish partners and partners from the Netherlands through workshops (physical and virtual). The project suffered from a slow start due to covid and the inability to have a proper physical kick-off of the project. After the first real physical workshop, work could really begin and virtual workshop was possible in an effective way. Another contingency was due to the fact that key partners from two countries (Germany and Belgium) were not funded within their own national funding applications, leading to a significant and time-consuming re-scoping.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 26 April 2024

Reference number 2020-01951

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