Projects
Data and METAdata for advanced digitalization of manuFACTURING industrial lines KU Leuven
MetaFacturing focuses on a digitized toolchain for metal part production which will lead to a more resilient production process with respect to the raw materials used (e.g. recycled materials), reduces operator effort and cost, and reduces scrap due to out-of-specification parts. The vision is to create a widely-applicable Digital Twin based process setup and control framework, fulfilling the requirements of industrial scale parts ...
Data and METAdata for advanced digitalization of manuFACTURING industrial lines Ghent University
As a relatively new concept, the digital twin (DT) is finding increased acceptance in industry. The industrial-scale production of metal parts is no exception. In this context, the EU-funded MetaFacturing project will focus on a digitised toolchain for metal part production. Its aim is to make it more resilient in terms of the raw materials used (recycled materials). It will also reduce operator effort and cost and reduce scrap due to ...
Trusted Secure Data Sharing Space KU Leuven
The lack of trusted and secure platforms and privacy-aware analytics methods for secure sharing of personal data and proprietary/commercial/industrial data hampers the creation of a data market and data economy by limiting data sharing mostly to open data. This trend will continue if different technical standards, quality levels, and legal aspects are allowed to diverge uncontrollably.
TRUSTS will ensure trust in the concept of ...
3if.eu - Industrial Internet, Industrial IoT & Industry4.0 in Flanders LSEC - Leaders In Security
Automated NDT of Industrial Composite Parts by Enhanced Optical Infrared Thermography Ghent University
Progress in materials science has led to novel high-performant materials, like fiber reinforced plastics (or composites), which are nowadays more and more used in aerospace and automotive industry. However, the composed nature of these materials makes them also sensitive to certain damage features. To assess the structural health, engineers have devised various non-destructive test approaches. One emerging technique concerns optical infrared ...
Trustworthy and insightful algorithms for industrial decision making. KU Leuven
Exploiting scene constraints to improve object detection algorithms for industrial applications KU Leuven
State-of-the-art object detection algorithms are designed to be heavily robust against scene and object variations like illumination changes, occlusions, scale changes, orientation differences, background clutter and object intra-class variability. However, in industrial machine vision applications, where objects with variable appearance have to be detected, many of these variations are in fact constant and can be seen as scene specific ...
Trustworthy and insightful algorithms for industrial decision making KU Leuven
Efficient algorithms for complex personnel scheduling problems are critical for ensuring organisations can provide a suitably qualified workforce at minimal cost while satisfying a wide variety of strict regulations meeting occupational health and safety requirements, as well as employee preferences. This PhD project will focus on nurse rostering, where nurses must be optimally allocated to work shifts in a manner that ensures their ...
Trustworthy and insightful algorithms for industrial decision making KU Leuven
Efficient algorithms for complex personnel scheduling problems are critical for ensuring organisations can provide a suitably qualified workforce at minimal cost while satisfying a wide variety of strict regulations meeting occupational health and safety requirements, as well as employee preferences. This PhD project will focus on nurse rostering, where nurses must be optimally allocated to work shifts in a manner that ensures their ...