automation

Production automation is well established in large companies for high volume products. But robot-based assembly automation in mid-sized companies is still in its infancy. This study uses results from 19 expert interviews and a survey to identify obstacles to and drivers of automation in this field. Among the obstacles is the low flexibility of the robotic systems. One driver for automation is the increasing shortage of skilled workers. Based on the empirical findings, the study proposes options to increase the use of automation.

Robotic Process Automation (RPA) stands for the software-supported operation of software solutions via their user interface. The primary goal that RPA seeks to achieve is the automated execution of routine tasks that previously required human intervention. However, the potential of RPA to improve processes in the long term is very limited. Automating processes and bridging front-end media disruptions leads to a variety of dependencies and conditions, which are summarized in this article. The path to a sustainable enterprise architecture (and the processes and systems comprised therein) requires open, adaptive systems with modern architecture that are characterized by a high degree of interoperability at various levels.

Remanufacturing, previously characterized by manual and cost-intensive processes, is a critical step on the way to a resource-efficient circular economy. Industry and research agree that the introduction of Industry 4.0 technologies is the key to the development of automated and economical remanufacturing systems. Based on a systematic literature review, this paper is dedicated to the analysis of promising Industry 4.0 approaches with a focus on the overall process as well as the sub-processes of disassembly and inspection. The results suggest that there is a need for additional knowledge, experience and research in the development and real demonstration of the approaches and their transferability to broader application fields.

Smart Factory is the vision of a production environment in which manufacturing plants and logistics systems organize themselves as far as possible without human intervention. The article describes a project, at the start of which none of the participants created a relation to “Smart Factory” or “Industry 4.0”. Rather, the objective was to drastically reduce the current delivery time of 6-8 weeks. The result is a completely digitized business process from order creation, product development, design, manufacturing as well as processing for “batch size 1” with a reduction in lead time to less than 10 %.

In process engineering, one thinks of production operations that are controlled or regulated by sensors and actuators. And any realization of matter transformation is based on a physical substratum, which holds equally for living systems and their behaviour. The article distinguishes between three system levels: the functional level, the interface to the environment and the cognitive level of. Using these three levels, the learning cycle or the previous Cognitive Loop can be very well illustrated. If one compares with this way of distinction the Bio-Informatization of human intelligence with the technical development stages of mechanization, automation, regulation and deep learning, then the cybernetic-sociological term “operational closure” becomes understandable. It becomes obvious that in the context of a digitized culture of production and organization, we should be prepared for a new kind of cognitive loop based on silicon (SI), an intelligent system behavior via ...