New working group on predictive quality: Reducing testing efforts
Reducing testing efforts and thus increasing productivity and sustainability: These are the goals of a new working group on predictive quality that the Machine Tool Laboratory WZL at RWTH Aachen University has set up together with the Fraunhofer Institute for Production Technology IPT in Aachen.
Together with the Fraunhofer Institute for Production Technology IPT in Aachen, the Machine Tool Laboratory WZL of RWTH Aachen University has launched a new industry working group for "Predictive Quality". The aim is to significantly reduce joint testing efforts on a pre-competitive basis and to realize higher productivity by eliminating physical testing processes, as well as to continue to achieve higher quality through a reduction in scrap, end-to-end quality monitoring and knowledge generation from the models, and increased sustainability through more resource-efficient production.
Predictive quality reduces testing efforts
Modern quality management has more and more data at its disposal faster and faster. At the same time, advanced algorithms enable ever more detailed images and models of production. These data and models form the basis for the field of predictive quality. Predictive quality describes the data-based prediction of quality characteristics. Using a learned relationship between process parameters and quality characteristics, time-consuming physical inspection processes, which are often only carried out in random samples, can be replaced by low-effort model-based 100% inspection. Predictive quality has already been successfully implemented in industry-related research projects in which testing efforts were significantly reduced and productivity increased.
has been increased. At the same time, more and more data-based quality management tools are being developed and deployed by manufacturing companies in digitization and Industrie 4.0 projects, software companies are providing advanced infrastructures for data acquisition and storage, and start-ups are forming business models via the provision of corresponding algorithms for data evaluation.
Faster dissemination of research results
The two Aachen institutes support companies from the manufacturing sector (e.g. automotive, metal processing, chemicals, pharmaceuticals, medical technology) as well as software companies specializing in the extraction, storage and processing of data (e.g. CAQ, MES, sensor manufacturers, cloud providers) in the working group with their many years of experience. The industry working group is financed by an annual membership fee and serves new members to
rapid dissemination and utilization of research results and networking and is based on three pillars. Two community meetings a year are intended to facilitate exchange between the members of the working group. In addition, current findings and results from industry and research are to be presented at the meetings. On a topic-specific basis, one study per year is conducted within the working group to gain insights into the current state of the art in the companies, challenges and new approaches. The topics are chosen by a majority vote of the working group members. In one demonstrator project per year, new ideas and approaches are specifically tested by the Machine Tool Laboratory WZL and Fraunhofer IPT. For example, different algorithms for quality prediction or preprocessing can be implemented and compared. The demonstrators can either come from the halls of the Machine Tool Laboratory WZL and Fraunhofer IPT or be provided by a company. Joint project results are available to the partners without restriction.
Source and further information: www.wzl.rwth-aachen.de
