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Auflistung nach Autor:in "Kern, Roman"

1 - 7 von 7
  • Workshopbeitrag
    Cyber-Physical Systems as Enablers in Manufacturing Communication andWorker Support
    (Mensch und Computer 2019 - Workshopband, 2019) Gursch, Heimo; Cemernek, David; Wuttei, Andreas; Kern, Roman
    The increasing potential of Information and Communications Technology (ICT) drives higher degrees of digitisation in the manufacturing industry. Such catchphrases as “Industry 4.0” and “smart manufacturing” reflect this tendency. The implementation of these paradigms is not merely an end to itself, but a new way of collaboration across existing department and process boundaries. Converting the process input, internal and output data into digital twins offers the possibility to test and validate the parameter changes via simulations, whose results can be used to update guidelines for shop-floor workers. The result is a Cyber-Physical System (CPS) that brings together the physical shop-floor, the digital data created in the manufacturing process, the simulations, and the human workers. The CPS offers new ways of collaboration on a shared data basis: the workers can annotate manufacturing problems directly in the data, obtain updated process guidelines, and use knowledge from other experts to address issues. Although the CPS cannot replace manufacturing management since it is formalised through various approaches, e. g., Six-Sigma or Advanced Process Control (APC), it is a new tool for validating decisions in simulation before they are implemented, allowing to continuously improve the guidelines.
  • Konferenzbeitrag
    Flexible Scheduling for Human Robot Collaboration in Intralogistics Teams
    (Mensch und Computer 2018 - Workshopband, 2018) Gursch, Heimo; Silva, Nelson; Reiterer, Bernhard; Paletta, Lucas; Bernauer, Patrick; Fuchs, Martin; Veas, Eduardo; Kern, Roman
    The project Flexible Intralogistics for Future Factories (FlexIFF) conducts research into human robot collaboration for intralogistics teams in the electronics manufacturing industry. These teams are creating a cyber-physical system out of human workers, mobile manipulators, manufacturing machinery, and manufacturing information systems. AR and VR devices are used by workers to interact with the robots and machinery. The right information at the right time is key to make this collaboration successful. Hence, scheduling of tasks for mobile manipulators and human worker must be undertaken closely linked with enterprise information systems giving all actors on the shop floor a common view of the current manufacturing status. FlexIFF should provide useful, well tested, and sophisticated solutions for cyber-physicals systems in intralogistics where humans and robots can bring in their strengths and help each other.
  • Konferenzbeitrag
    Ein Industrie 4.0-Use Case in der Motorenproduktion
    (Mensch und Computer 2018 - Workshopband, 2018) Stanisavljevic, Darko; Rosenberger, Manfred; Lechner, Gernot; Körner, Stefan; Kern, Roman; Jeitler, Bernd; Stocker, Alexander
    Im Allgemeinen sind Erkenntnisse aus dem Fehlverhalten in der Produktion und dem Betrieb von Produkten die wesentlichen Treiber in deren Weiterentwicklung. Eine proaktive Weiterentwicklung ist so aufgrund unbekannter bzw. nicht untersuchter Wirkketten allerdings nicht möglich. Mit der im Umfeld von Industrie 4.0 diskutierten vollständigen Digitalisierung über den gesamten Produktlebenszyklus, beginnend beim Konzept über die Produktentwicklung, der Produktion und der Nutzung bis hin zum Service, soll phasenübergreifend handlungs- und entscheidungsrelevantes Wissen durch eine gezielte Analyse und Vernetzung der gesammelten Daten ermöglicht werden. Im vorliegenden Beitrag wird anhand eines Industrie 4.0-Use Case aus der Motorenentwicklung und -produktion aufgezeigt, welches Potenzial in diesem Digitalisierungsansatz steckt und wie dieses durch die Anwendung von Methoden aus dem Data Science-Bereich gehoben werden kann.
  • Workshopbeitrag
    KI-Waste - Combining Image Recognition and Time Series Analysis in Refuse Sorting
    (Mensch und Computer 2021 - Workshopband, 2021) Gursch, Heimo; Ganster, Harald; Rinnhofer, Alfred; Waltner, Georg; Payer, Christian; Oberwinkler, Christian; Meisenbichler, Reinhard; Kern, Roman
    Refuse sorting is a key technology to increase the recycling rate and reduce the growths of landfills worldwide. The project KI-Waste combines image recognition with time series analysis to monitor and optimise processes in sorting facilities. The image recognition captures the refuse category distribution and particle size of the refuse streams in the sorting facility. The time series analysis focuses on insights derived from machine parameters and sensor values. The combination of results from the image recognition and the time series analysis creates a new holistic view of the complete sorting process and the performance of a sorting facility. This is the basis for comprehensive monitoring, data-driven optimisations, and performance evaluations supporting workers in sorting facilities. Digital solutions allowing the workers to monitor the sorting process remotely are very desirable since the working conditions in sorting facilities are potentially harmful due to dust, bacteria, and fungal spores. Furthermore, the introduction of objective sorting performance measures enables workers to make informed decisions to improve the sorting parameters and react quicker to changes in the refuse composition. This work describes ideas and objectives of the KI-Waste project, summarises techniques and approaches used in KI-Waste, gives preliminary findings, and closes with an outlook on future work.
  • Konferenzbeitrag
    Multi-Loop Feedback Hierarchy Involving Human Workers in Manufacturing Processes
    (Mensch und Computer 2017 - Workshopband, 2017) Gursch, Heimo; Cemernek, David; Kern, Roman
    In manufacturing environments today, automated machinery works alongside human workers. In many cases computers and humans oversee different aspects of the same manufacturing steps, sub-processes, and processes. This paper identifies and describes four feedback loops in manufacturing and organises them in terms of their time horizon and degree of automation versus human involvement. The data flow in the feedback loops is further characterised by features commonly associated with Big Data. Velocity, volume, variety, and veracity are used to establish, describe and compare differences in the data flows.
  • Konferenzbeitrag
    Parameter Forecasting for Vehicle Paint Quality Optimisation
    (Mensch und Computer 2016 – Workshopband, 2016) Gursch, Heimo; Körner, Stefan; Krasser, Hannes; Kern, Roman
    Painting a modern car involves applying many coats during a highly complex and automated process. The individual coats not only serve a decoration purpose but are also curial for protection from damage due to environmental influences, such as rust. For an optimal paint job, many parameters have to be optimised simultaneously. A forecasting model was created, which predicts the paint flaw probability for a given set of process parameters, to help the production managers modify the process parameters to achieve an optimal result. The mathematical model was based on historical process and quality observations. Production managers who are not familiar with the mathematical concept of the model can use it via an intuitive Web-based Graphical User Interface (Web-GUI). The Web-GUI offers production managers the ability to test process parameters and forecast the expected quality. The model can be used for optimising the process parameters in terms of quality and costs.
  • Konferenzbeitrag
    Unified Information Access for Knowledge Workers via a Federated Recommender System
    (Mensch und Computer 2015 – Workshopband, 2015) Gursch, Heimo; Ziak, Hermann; Kern, Roman