Projet APRIORI (Horizon Europe, appel à projets 2021)
Action : Doctoral Networks
Panel : Information Science and Engineering
Statut du projet : SIGNED

The manufacture sector is and will continue experiencing an evolving trend, marked by the exponential growth of additive manufacturing, the ongoing 4th industrial revolution (Industry 4.0) and an increasing demand of customization of the manufactured products. However, the production and economical growth of the manufacturing sector needs to meet unpostponable sustainability guidelines and criteria. Already in 2010, the International Energy Agency identified the critical areas that should lead to the undelayable reduction of C02 emissions by 2050. The area that will have the largest impact is the so-called End-Use Energy Efficiency sector, directly linked to the manufacture sector, where the aim is “doing more with less”. This means minimizing the energy losses as much as possible. To be ready for the upcoming challenge, there is a need to create a critical mass of highly skilled young engineers and innovators who will enhance Europe’s position in the engineering sciences. Specifically, these future engineers and innovators need to get familiar with two key technical challenges within the manufacturing sector: the uncertainty induced by the production process (e.g. human errors, geometrical and material variabilities caused by the manufacturing process and/or by the machine setup) and the increasing complexity of the manufactured goods characterized by the critical parts or components. The ambition of the Active PRoduct-to-Process LearnIng fOR Improving Critical Components Performance (APRIORI) training network is to train the next generation of Doctoral Candidates (DCs) to fully sustain the ongoing transition of the EU manufacturing sector. This will be achieved by developing the skills and new technologies that will enable for the first time the development of a unique integrated product design strategy that will drastically improve the performance of critical parts or components under uncertainties.

Mots clés : critical component performance product design strategy active learning and optimization integrated performance assessment uncertainty quantification manufacturing variability active learner engineer

Participants :
- Temporary works design 9 b.v. (Pays-Bas) — Partner, associated partner, Organismes privés (hors enseignement), subvention : 0.0 €
- Institut Jožef Stefan (Slovénie) — Partner, beneficiary, Recherche, subvention : 242179.2 €
- KU Leuven (Belgique) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 525240.0 €
- Ecole doctorale internationale Jožef Stefan (Slovénie) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université d'Aalborg (Danemark) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 301788.0 €
- Materialise (Belgium) (Belgique) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 262620.0 €
- Qlector, razvoj celovitih resitev za pametne tovarne doo (Slovénie) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 242179.2 €
- Université de technologie de Delft (Pays-Bas) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 823111.2 €
- Grundfos Foundation (Danemark) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 301788.0 €