PhD thesis (co-tutelle) at NTUA & University of Luxembourg

Data-driven workflows for prediction, sensitivity analysis and uncertainty quantifications of industrial deposition processes

The objective of the thesis is to develop a data-driven framework for prediction, sensitivity analysis and uncertainty quantification in industrial-scale processes used to produce hard coatings and wear protection. The core of the production process is Chemical Vapor Deposition (CVD) reactors with different set-up but common goal: uniform coatings with strict quality requirements. The proposed computational framework will identify different clusters of reactors, with different set-up but similar qualitative characteristics of the coating. The goal is then to develop in each one of the clusters, predictive models able to correlate the inputs of the process to the output. These efficient and accurate process models will be implemented in the context of uncertainty quantification and sensitivity analysis with the ambition to contribute to process efficiency by reducing scrap rate and improve quality by enhancing homogeneity.
The successful PhD candidate willbe part of an international and interdisciplinary group, headed by Prof. A.G. Boudouvis (NTUA) and Prof. S.P.A. Bordas (University of Luxembourg) within a co-tutelle framework. The project is supported by Ceratizit S.A., a high technology engineering group specialized in cutting tools and hard material solutions, based in Luxembourg.

Please address CVs to Dr. Eleni Koronaki: ekor@mail.ntua.gr