eLearning-Tools zur Verbesserung verständlichen Schreibens.

Thema dieses Artikels ist das Schreiben von Texten in verständlicher Form. Die zunehmende digitale und webbasierte Bearbeitung von Texten lässt die für Lehre und Forschung relevante und allgemeine Frage auftauchen, ob oder inwiefern die Qualität des Schreibens sich verändern wird. Innerhalb des eLearning-Projekts "Verständlich Schreiben", welches an der Universität Wien am Institut für Bildungswissenschaft in Kooperation mit dem Institut für Knowledge and Business Engineering durchgeführt wird, wird hier die konkrete Frage gestellt: Wie kann die Qualität des verständlichen Schreibens mittels eLearning-Tools verbessert werden? \ud \u

An Approach for Secure Data Transmission in a Distributed Production Environment

The exchange of data along the supply chain can be viewed as one of the key characteristics of advanced manufacturing concepts, frequently labeled as industry 4.0 . Intelligent products produced in shorter life cycles, increasing cost and quality pressures from global supply chains, increasingly complex regulatory requirements, as well as decreasing costs of advanced sensors are major drivers for this trend. Large amounts of data generated as a by-product of this trend represents an opportunity for advanced data analytics. However, the exchange of data across organizational boundaries bears also the risks of being in the focus of cyber-attacks. In this paper, we tackle the challenge of securing the data transfer in an Industry 4.0 environment. We first identify the security requirements within our use case. Based on these requirements, we present an approach for secure data transmission and discuss how our solution meets the identified requirements

Industrial Production Process Improvement by a Process Engine Visual Analytics Dashboard

Digitalization reshapes production in a sense that production processes are required to be more flexible and more interconnected to produce products in smaller lot sizes. This makes the process improvement much more challenging, as traditional approaches, which are based on the learning curve, are difficult to apply. Data-driven technologies promise help in learning faster by making use of the massive data volumes collected in production environments. Visual analytics approaches are particularly promising in this regard as they aim to enable engineers with their rich domain knowledge to identify opportunities for process improvements. Based on the assumption that process improvement should be connected with the process engine managing the process execution, we propose a visual analytics dashboard which integrates process models. Based on a case study in the smart factory of Vienna, we conducted two pair analytics sessions. The first results seem promising, whereas domain experts articulate their wish for improvements and future work

Using sensory tool holder data for optimizing production processes

Today's highly automated manufacturing specifies the service time of a tool in a way that the tooling costs are balanced against the potential costs of a tool failure. However, the potential cost induced by a tool malfunctioning are rather high. Therefore, the current state-of-the art tackles this issue by replacing the tools prematurely at fixed intervals. To tap into the potential of under-utilized tool runtime this work purposes the use of sensory-tool holders and an interfering feedback loop to the machine tool control system. Besides its real-time closed loop control, to avoid tool failure, it also provides data in the context of (a) the work order, (b) the produced part, (c) the NC-block and command line, on (d) specific machines. Based on this data an ex-post analysis to optimize tool-life and productivity scenarios becomes possible, e.g. custom NC-programs for certain work-orders, configurations and machines. Furthermore, downstreamed work steps can be changed e.g. only to measure produced workpieces if abnormal vibrations are reported by in-process-monitoring