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A Common Software Framework for Energy Data Based Monitoring and Controlling for Machine Power Peak Reduction and Workpiece Quality Improvements

Bauerdick, Christoph ; Helfert, Mark ; Menz, Benjamin ; Abele, Eberhard :
A Common Software Framework for Energy Data Based Monitoring and Controlling for Machine Power Peak Reduction and Workpiece Quality Improvements.
[Online-Edition: https://doi.org/10.1016/j.procir.2016.11.226]
In: Procedia CIRP, 24th CIRP Conference on Life Cycle Engineering, Kamakura (Japan) Elsevier B.V., 61 pp. 359-364. ISSN 2212-8271
[Artikel], (2017)

Offizielle URL: https://doi.org/10.1016/j.procir.2016.11.226

Kurzbeschreibung (Abstract)

A standardized and high frequent collection of energy data is a powerful tool to enhance industrial energy efficiency and has also proved to be most valuable in condition and process monitoring tasks in recent researches. For these monitoring and controlling functions in production sites a common software framework is essential. In this paper the development of such a software framework is presented. Further on two new approaches utilizing this software framework are introduced: Firstly the recognition and automatic reduction of power peaks between connected machine tools. Secondly the usage of energy data of machine tools for quality monitoring purposes.

Typ des Eintrags: Artikel
Erschienen: 2017
Autor(en): Bauerdick, Christoph ; Helfert, Mark ; Menz, Benjamin ; Abele, Eberhard
Titel: A Common Software Framework for Energy Data Based Monitoring and Controlling for Machine Power Peak Reduction and Workpiece Quality Improvements
Sprache: Englisch
Kurzbeschreibung (Abstract):

A standardized and high frequent collection of energy data is a powerful tool to enhance industrial energy efficiency and has also proved to be most valuable in condition and process monitoring tasks in recent researches. For these monitoring and controlling functions in production sites a common software framework is essential. In this paper the development of such a software framework is presented. Further on two new approaches utilizing this software framework are introduced: Firstly the recognition and automatic reduction of power peaks between connected machine tools. Secondly the usage of energy data of machine tools for quality monitoring purposes.

Titel der Zeitschrift, Zeitung oder Schriftenreihe: Procedia CIRP, 24th CIRP Conference on Life Cycle Engineering, Kamakura (Japan) Elsevier B.V.
Band: 61
Freie Schlagworte: Software Framework Production Machines Energy Controlling Industry 4.0 Quality Monitoring Condition Monitoring Workpiece Monitoring
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Institut für Produktionsmanagement, Technologie und Werkzeugmaschinen (PTW)
16 Fachbereich Maschinenbau > Institut für Produktionsmanagement, Technologie und Werkzeugmaschinen (PTW) > Umweltgerechte Produktion
Hinterlegungsdatum: 28 Aug 2017 13:17
Offizielle URL: https://doi.org/10.1016/j.procir.2016.11.226
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