Anass El Houd's Ph.D. Thesis - Details Soon!
Artificial Intelligence Approach for the Automatic Generation and Optimization of Manufacturing Scenarios
Anass El Houd
Started in 2022 at Faurecia Clean Mobility, France.
FEMTO-ST Institute - University of Franche-Comte.
This CIFRE thesis is a part of a project with Faurecia, funded by the Ministry of Higher Education and Research of France, managed by the Association Nationale de la Recherche et de la Technologie (ANRT).
Abstract
The creation of a production line is a complex process which consists in finding an optimal solution among a number of combinations of assembly actions almost infinite, involving automated systems more and more numerous and diverse as well as operators. The optimization of these lines consists in finding a solution which minimizes the production costs and the assembly time of the parts while respecting the constraints of the work code for the operators (in terms of handling of load, working time...). The objective of this thesis is to propose and develop a simulation environment called Digital Twin by Deep Learning (DTbyDL) allowing to build automatically a production line architecture and a complete and optimal production scenario from a list of components.
References
My thesis is based on the following publications: Coming soon. -->
Thesis Committee
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Document
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Slides
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Code/Datasets/Models
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References
My thesis is based on the following publications: Coming soon. -->