Browsing by Title

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    A case study on the haptic understanding in the teaching of Geometrical Product Specifications (GPS)
    (University of Wuppertal, 2024) Sersch, Alina ; Steger, Tobias ; Sauder, Christian ; Gust, Peter
    This case study examines haptic understanding in the teaching of Geometrical Product Specifications (GPS). As part of a lecture in the field of GPS, mechanical engineering students were given a group task involving the standard-compliant creation of a technical drawing. During their work, they were divided into three groups and subjected to a short knowledge test. Depending on their group assignment, they were given the following tools, partly from a hybrid learning kit: technical drawings, technical drawings and 3D CAD model, technical drawings and a haptic model. Finally, the tools were evaluated.
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    A survey on the teaching of Geometrical Product Specifications (GPS) in mechanical engineering studies at universities in Germany
    (University of Wuppertal, 2024) Sersch, Alina ; Sauder, Christian ; Steger, Tobias ; Gust, Peter
    This study examines the teaching of the GPS system in higher education. The focus is on determining the scope, teaching methods, experiences and potential in bachelor’s degree courses in mechanical engineering in Germany. In total, lecturers from 85 of the 115 selected universities took part in the survey, which was conducted between May and September 2023.
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    Multivariate Sensor Dataset of an Industrial Rotogravure Printing Press (MSDIRPP)
    (University of Wuppertal, 2022-05-31) Tobias Enk
    We present a multivariate sensor dataset for machine learning research in context of industrial print application. The dataset contains 7608 rolls of pre-processed multivariate sensor data of a single production scale rotogravure printing press. The data volume corresponds to 43.181 km of printed paperboard and paper. For each roll we provide high-resolution sampled inline sensor data, machine condition labels and several meta information. Besides basic information like machine speed the dataset contains web movement data such as web edge and web tension measurements, material measurement like web moisture and print quality data such as register measurements in cross and machine direction for 11 print units. We publish the dataset to provide data researchers a strong baseline dataset for several applications in industrial printing.
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    Stepper Motor Dataset
    (University of Wuppertal, 2020-07-07) Goubeaud, Maxime ; Grunert, Tim ; Lützenkirchen, Jan ; Joussen, Philipp ; Kummert, Anton
    This is the first publicly available dataset for mechanical stop detection of unipolar stepper motors. With the help of various current-, voltage- and vibration-signals, it is possible to gain information about the prevailing operating mode of the stepper motor and to detect when the stepper motor is operated outside its specified operating range. By detecting the mechanical stop, unnecessary wear and additional noise pollution can be avoided.
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    Teaching Example 1: Curves of constant width (Reuleaux polygons)
    (University of Wuppertal, 2024-05-03) Alina Sersch ; Christian Sauder ; Tobias Steger
    This dataset contains teaching examples with regard to curves of constant width to show form deviations and the problem of linear sizes.
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    Teaching Example 2: Envelope requirement
    (University of Wuppertal, 2024-07-31) Alina Sersch ; Christian Sauder ; Tobias Steger
    This dataset contains teaching examples with regard to the envelope requirement.
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    The Concept of Failure-Cause-Searching and Solution-Finding Algorithm (FusLa)
    (University of Wuppertal, 2021-12-01) Ansari, A. ; Schlüter, N. ; Heinrichsmeyer, M.
    The solution proposed in this fundamental research is a Failure-Cause-Searching and Solution-Finding Algorithm (FusLa), which should enable the identification and elimination of failure causes in the production system based on complaint information from the use phase of a product system. To realize this, a four-phase algorithm was designed. In the first phase, automated information probing is performed, which filters out the relevant information from the complaints and prepares it for further processing. In the second phase, the FusLa then automatically determines a priority value for each complaint based on the probed information. Based on the prioritization, the algorithm is able to localize potential causes for the identified failures in the third phase. Based on the localized failure causes, the algorithm then derives suitable measures.