Cluster of Excellence - Production Technology in High-Wage Countries
Cross-Sectional Processes 1
The stronger integration of information and communication technologies into production enables a new type of productivity growth by collaboration. This so-called collaboration productivity in integrative, interdisciplinary teams is in the focus of the Cross Sectional Processes. Here three main perspectives of collaboration are considered: results, employees and structure. The research results of the interdisciplinary project teams aim at increasing productivity both in the production and in the product development process, especially concerning individualized products. The aim is to integrate the contributions of the different research projects by a holistic approach to a new theory of production. This theory is supposed to increase the predictability of the behaviour of socio-technical production systems and therefore supports the decision-maker. The basis of collaboration productivity are integrative, interdisciplinary teams that are working together on technologies and models of the integrative production technology. Focus of Scientific Cooperation Engineering is to support and analyze collaboration in and across the teams. On the one hand innovation and knowledge management in interdisciplinary research teams are analyzed, on the other hand the performance and productivity of those teams are measured. The Research area Technology Transfer aims to strengthen the collaboration structures within the Cluster of Excellence by sustainable networking. With the Scientific Cooperation Portal networking structures can be tested internally. In the long-term the aim is to simplify the search of technologies for external partners. The network PROTECA (Production Technology Aachen) transfers the results and competencies into the local industry.
Link to the project website: http://www.produktionstechnik.rwth-aachen.de/cms/~gpfz/Produktionstechnik/
Professor of Human-Computer Interaction and Usable Safety Engineering
I am insterested in studying effects human-algorithm interaction and their impact on safety.