VisionCopyright: Anja Wassong
The vision of the Internet of Production (IoP) is to enable a new level of crossdomain collaboration by providing semantically adequate and context-aware data from production, development and usage in real-time, on an adequate level of granularity.
The work that has been accomplished in the Cluster of Excellence "Integrative Production Technology for High-Wage Countries" since its inception in 2006 is being continued in the Cluster of Excellence "Internet of Production" (IoP).
The Cluster of Excellence "Integrative Production Technology for High-Wage Countries" (2006-2017) has focused on the development of innovative solutions to ensure the future viability and competitiveness of the local manufacturing industry. Achievements include, for example, the development of new intelligent production systems, solutions for the efficient production of customer-specific components, integrated product life cycle management (PLM), as well as increased interconnectedness and collaboration.
The emphasis on collaboration is already visible in the structural approach of the Cluster of Excellence, consisting of a network of more than 25 institutes and research institutions. Aachen's renowned scientists from production engineering, computer science, materials science and economics, as well as ergonomics and psychology, are bringing their academic expertise to the IoP in order to jointly tackle interdisciplinary challenges such as the integration of production engineering models into data-driven machine learning.
As the basis for the transfer of Aachen production technology into the age of the fourth industrial revolution, the next important milestone for the further creation of application-oriented and innovative solutions in the field of production technology is now on the agenda of the new Cluster. The IoP offers real-time, secure information availability of all relevant data at any time, at any place and is regarded as the core of industry 4.0. In this way, the IoP paves the way for a new era of production. The sum of the generated and aggregated data - the high-volume "digital shadow" of production - enables accurate forecasting to the point of reaching the goal of a production process that is consistently controlled. From the entire product development process to the fast, error-free implementation of quickly required changes in series production, cross-domain knowledge is generated and used. This approach of demand-oriented data analysis and the application of machine learning algorithms holds great potential and gives all aspects of production technology a fresh impetus.