Refine
Year of publication
Document Type
- Article (13)
- Conference Proceeding (4)
- Part of a Book (3)
- Book (1)
Keywords
- anlagenplanung (1)
- augmented reality (1)
Nach Schulte ist in vielen akademischen Ausbildungen die transzendentale Integration von ökonomischen Querfunktionen, insbesondere das heranwachsende »Gründertum-Gen« ausbaufähig. Ein Studium zum Intra- oder Entrepreneurship bildet zunächst die Grundlage.
Darüber hinaus muss zusätzlich ebenfalls praktisch ausprobiert und erlebt werden. Dieses Erfahrungslernen gilt auch in der heutigen Zeit der digitalen Transformation...
The results of the empirical study based on an AR Landolt C vision were examined to compare real and virtual visibility as a function of stimulus size on an HMD (e.g. MS HoloLens 2). A counterbalanced within-subject-design study with n = 32 probands was conducted. The results show on one hand a visibility loss between real and immersive systems by the same size of representation. On the other hand, a transfer function can be derived to ensure comparable visibility between the systems. This transfer function can be used to compensate for the visibility loss as a design guideline for immersive applications. In approximation, the Weber-Fechner's relation can be applied on AR visibility versus size of stimuli.
In the context of urban production and sustainable reuse of existing buildings, a detailed planning of the later usage is indispensable. One approach is to enable large-scale AR simulation on site with a sufficient Level of Detail (LoD) and stability. To determine performance metrics, a technology-stack is created and presented that enables a realistic field experiment in an industrial environment (area of 1,314 m2) using Microsoft HoloLens 2. For the experiment, a 3D model was instantiated as often as possible up to the limit of system stability and in different LoDs (100% down to 10%). The result shows that it is feasible to represent 2.63 million polygons (equivalent to about 1,909 m3 of augmented space) on LOD-35%; LoD-100% is equivalent to 327.38 m3 and 1,284 million polygons. Polygonal density [polygons/m3] is introduced as new indicator for better comparability when using 3D models. Thus, it is possible to immersively visualize urban production planning processes in large-scale scenarios. This expands the functional planning space of Urban Production and overcomes previous technical limitations.
Although the increasing use of automation in industry, manual assembly stations are still common and, in some situations, even inevitable. Current practice in manual assembly lines is to balance them using the takt-time of each workstation and harmonize it. However, this approach mostly does not include ergonomic aspects and thus it may lead to workforce musculoskeletal disorders, extended leaves, and demotivation. This paper presents a holistic human-centric optimization method for line balancing using a novel indicator ̶ the ErgoTakt. ErgoTakt improves the legacy takt-time and helps to find an optimum between the ergonomic evaluation of an assembly station and its balance in time. The authors used a custom version of the ErgoSentinel Software and a Microsoft Kinect depth camera to perform online and real-time ergonomic assessment. An optimization algorithm is developed to find the best-fitting solution by minimizing a function of the ergonomic RULA-value and the cycle time of each assembly workstation with respect to the worker's ability. The paper presents the concept, the system-setup and preliminary evaluation of an assembly scenario. The results demonstrate that the new approach is feasible and able to optimize an entire manual assembly process chain in terms of both, economic aspects of a well-balanced production line as well as the ergonomic issue of long term human healthy work.
Currently, many sources predict increasing use of AR technology in the industrial environment. The task of immersive productive assistance systems is to provide information contextually to the industrial user. Therefore, it is essential to explore the factors and effects that influence the visibility and the corresponding quality of this information. Caused by the technical limitations of additive display technology and application conditions, this new approach has evaluated the immersive visibility of Landolt Rings in various greyscales against ambient illuminance levels on different industrial-like surfaces, coupled with and without a white virtual background. For this purpose, an empirical study in a within-subjects-design with full factorial experimental design (n=23) was conducted on Microsoft HoloLens 2 hardware. The mean values of the main effects indicate that visibility is significantly affected by ambient illuminance (best results at lower level), greyscale (best results at middle level) and virtual background (best results with background). In contrast, the choice of surface is shown to have no statistically significant effect on visibility, however it affects the response time. Additionally, cross-interactions of variables were analyzed and lead to a design recommendation for immersive industrial applications.
Companies are confronted with increasingly demanding environments, including globalization, technologization, intergenerationality, and crises such as the coronavirus pandemic. To accept uncertainties as a challenge and to recognize opportunities for development, well-educated and resilient founders are needed who can foster innovation and sustainable development within society and the economy. The majority of today’s entrepreneurs have an academic background. Hence, institutions for higher education need to provide comprehensive educational offerings and support initiatives to train and sensitize future entrepreneurs. Therefore, since 2013, agile teaching formats have been developed in our project at a Bavarian university of applied sciences. In two stages, we founded a limited company for hands-on experimentation with entrepreneurship and also conceptualized an elective course and an annual founders’ night. Based on a theoretical model and continuous teaching evaluations, we adjusted the individual modules to suit the target group. The objective is to promote the acquisition of key competencies and exert a positive influence on the startup quotient in the region. There are six startups by students who can be traced back to our project. This indicates that a target-group-oriented educational program encourages motivation and awareness of entrepreneurial thinking and action among students.
Advances in machine learning detecting changeover processes in cyber physical production systems
(2020)
The performance indicator, Overall Equipment Effectiveness (OEE), is one of the most important ones for production control, as it merges information of equipment usage, process yield, and product quality. The determination of the OEE is oftentimes not transparent in companies, due to the heterogeneous data sources and manual interference. Furthermore, there is a difference in present guidelines to calculate the OEE. Due to a big amount of sensor data in Cyber Physical Production Systems, Machine Learning methods can be used in order to detect several elements of the OEE by a trained model. Changeover time is one crucial aspect influencing the OEE, as it adds no value to the product. Furthermore, changeover processes are fulfilled manually and vary from worker to worker. They always have their own procedure to conduct a changeover of a machine for a new product or production lot. Hence, the changeover time as well as the process itself vary. Thus, a new Machine Learning based concept for identification and characterization of machine set-up actions is presented. Here, the issue to be dealt with is the necessity of human and machine interaction to fulfill the entire machine set-up process. Because of this, the paper shows the use case in a real production scenario of a small to medium size company (SME), the derived data set, promising Machine Learning algorithms, as well as the results of the implemented Machine Learning model to classify machine set-up actions.
Die Weiterentwicklung von Endgeräten wie z.B. von NReal oder die Microsoft HoloLens 2 im Bereich Augmented Reality (AR) führt zu einem erweiterten Nutzungsfeld von AR außerhalb klassischer Entwicklungs- und »Gaming«-Umgebungen. Eine der sich intensivierenden Nutzungsoptionen ist der wertorientierte Einsatz im industriellen Umfeld. In diesem Bereich bedarf es noch einer weitreichenden Identifizierung und Evaluierung der Einsatzpotenziale und des -nutzens [1]. Naheliegender Vorteil der Technologie ist die Anwendung in integrativen Planungsprozessen z.B. in der Anlagenplanung. Durch die Visualisierung von virtuellen Inhalten in einer realen Umgebung, können zukünftige Veränderungen auf mögliche Störfaktoren bereits vor Umsetzung detailliert geprüft und optimiert werden. Dies führt zu Zeit- und Kostenersparnis in Planungsphasen, da nachträgliche Änderungen signifikant kostenintensiver und komplexer sind. Eine weitere Nutzungsmöglichkeit ist die Simulation von Fertigungsprozessen und deren Auswirkungen. Die Simulation kann insbesondere bei der Identifikation unternehmensunabhängiger Probleme helfen. Auch kann der zeitliche Faktor, der jedem Prozess zugrunde liegt, eingebettet in einem virtuell erweiterten Realszenario geprüft werden. Als Beispiel kann hier die Störungsbeseitigung in industriellen Fertigungsprozessen dienen, welche meistens einer notwendigen engen Taktung unterliegen. Störungen sind häufig durch die direkte Umwelt oder Probleme in Arbeitsabläufen begründet. An diesem Punkt können die möglichen Optimierungsoptionen unter den gegebenen Bedingungen eine erste Validierung erfahren, ohne direkten Eingriff in laufende Prozesse. Diese Anwendungsmöglichkeiten gilt es zu untersuchen und in eine gebrauchstaugliche Lösung für den Einsatz im wertschöpfenden Bereichen zu überführen. Ziel dabei ist es die noch hypothetischen Potenziale zu bewerten und in einsetzbare Applikationen zu transformieren, die den Anforderungen in einer industriellen Umgebung standhalten. Um eine nutzerorientierte Forschung zu gewährleisten, ist es notwendig den Bedarf der Industrie zu erfassen. An diesem Punkt setzt das Vorhaben PlanAR an und untersucht die interdisziplinären Auswirkungen der Anwendungsmöglichkeiten und Applikationen bei industrienahen Nutzungsanforderungen.