[APDIO] PhD opportunity: Predictive Maintenance using Data Driven Approaches and Digital Twins

[Miguel Anjos <Miguel.F.Anjos@ed.ac.uk>]

There is an opening for a PhD researcher to work on the project "Predictive Maintenance of Complex Systems using Data Driven Approaches and Digital Twins". This position is shared between Edinburgh University (Edinburgh, UK) and IRT SystemX (Paris, France). 

Starting from a given physical asset or a complex industrial system, a Digital Twin (DT) representation consists in twinning, thanks to virtualization techniques, the different physical components, the relevant flows, and the environment in which the physical asset is evolving. This DT will rely on different and heterogenous data collected from many deployed sensors on the physical asset and will propose data driven models to achieve given objectives and offer some services, while providing the physical system with rationale feedback.

Given such a complex system and its DT, we need to plan the predictive maintenance and its dynamic grouping based on heterogenous data collected in near real time. This thesis will investigate mathematical modelling based on optimization under uncertainty (stochastic optimization, chance-constrained optimization, distributionally robust optimization (DRO), etc. to propose scalable predictive maintenance under uncertainty. Moreover, the optimization will take into account carbon footprint, production and resource limitation constraints. The solutions provided by the digital twin will be used as feedback to the physical asset (use-case) to reconfigure or modify the maintenance plans accordingly. We propose to use at least one industrial use-case which will show and highlight the important role of the DT in constrained and data-driven predictive maintenance of complex systems.

See the attachment for further details. 

The salary is 2700 €/month (before taxes).

For more information or to apply, please contact makhlouf.hadji@irt-systemx.fr or miguel.f.anjos@ed.ac.uk

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Miguel F. Anjos, Ph.D., P.Eng., FHEA, SMIEEE, FEUROPT, FCAE

Chair of Operational Research and Head of Theme (Data & Decisions)

Deputy Head, School of Mathematics, University of Edinburgh, U.K.

Schöller Senior Fellow, University of Erlangen-Nürnberg, Germany

Chair-Elect, Mathematical Optimization Society

Vice-President for International Activities, INFORMS

http://www.miguelanjos.com/

The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. Is e buidheann carthannais a th’ ann an Oilthigh Dhùn Èideann, clàraichte an Alba, àireamh clàraidh SC005336.

JNI3_Thesis_1_Miguel_HM_V4.pdf
Description: JNI3_Thesis_1_Miguel_HM_V4.pdf