potential analysis

Research and industry have agreed on the aims of Industry 4.0. Contrary to what this suggests, a variety of issues and related challenges, e.g. complexity, big data, security, etc., will not make a revolution at the push of a button easy. Humans in particular will also play a crucial role on the way to adaptive, networked and resource efficient factories and directly influence the factory of the future. The Fraunhofer IFF Magdeburg is therefore pursuing research on collaborative robots that will assist humans.

Mechatronic systems have to fulfill increasingly advanced functions and requirements to serve future customer needs and create reliable, resource-efficient and user-friendly systems. To realize tomorrow’s technical systems, solutions in context of self-optimization can be used. Thus, intelligent behavior can be integrated in technical systems. These systems are able to adapt their behavior autonomously and react to outer influences. The Leading-Edge Cluster “Intelligent Technical Systems OstWestfalenLippe (it’s OWL)” focuses on the described innovation leap from mechatronics to intelligent technical systems. Within this contribution we explain the capabilities of solutions in context of self-optimization on the example of machine learning methods. Furthermore, an approach for the identification of potentials for the integration of self-optimization in mechatronic systems will be introduced.

Today, an efficient product ramp-up is a precondition of the success of a company. The ramp-up management provides the coordination and management of the ramp-up process. The Fraunhofer Institute for Manufacturing Engineering and Automation and the company Schnitzer Anlauf- und Projektmanagement GmbH has developed a tool for analysing the product ramp-up process in order to achieve potentials for optimization. Ramp-up projects can be evaluated and best practices can be identified.