NEWS
Call for Papers for the 2nd SEA4DQ Workshop.
After the successful celebration of the 1st International Workshop on Software Engineering and AI for Data Quality in Cyber-Physical Systems (SEA4DQ), InterQ and DAT4.ZERO projects join forces again for the organization of the second edition.
InterQ 18M General Assembly and Midterm Review.
InterQ consortium met together on the 5th and 6th of May in Brussels to celebrate the 18M General Assembly and the Midterm Review.
A big showcase of SEVEN projects for zero-defect manufacturing.
In the last ten years, many industrial production sites in Europe have started strategic work towards a digital transformation into the fourth-industrial revolution termed Industry 4.0.
Tutorial on Erroneous Data Repair
SINTEF is working on software to repair erroneous data.
4ZDM Digital Technologies for Zero-Defect Manufacturing
The ZDM cluster is organizing a webinar on Digital Technologies for Zero-Defect Manufacturing.
Creating dedicated digital twins by experience.
Digital twins use models to replicate a physical object or the behaviors of a complex process.
Gamesa energy Transmission covers casting, machining, heat treatment and assembling capacities.
The main quality problems faced by GET are related to raw material quality (castings and forgings), gear grinding and machining process deviations due to manual parameter adjustment done by operators.
An introduction to the next generation of digital twin technologies.
Tributech’s open source digital twin stack enables applications with a holistic view along the value chain and life cycle.
New 4ZDM cluster website available.
The 4ZDM cluster website is available! Visit https://zdmanufuture.org/ to find information about the different ZDM projects, including InterQ.
Quality must be produced, not just controlled.
Quality is an extremely important objective in many high value-added applications.
One of the most attractive aspects of this project is the diversity of partners who participate in it.
With the results of the InterQ project, we expect to have improved process capability and product quality in machining operations, obtaining real time data analyzes to predict machine behaviour.
Investigate approaches to detect and repair data quality errors during the manufacturing process.
Monitoring data quality is a pre-requisite to zero-defect manufacturing as the quality of the data reflects the quality of the process and the product.