Abele, Eberhard ; Braun, Steffen ; Schraml, Philipp (2015)
Holistic Simulation Environment for Energy Consumption Prediction of Machine Tools.
Procedia CIRP – The 22nd CIRP conference on Life Cycle Engineering, Published by Elsevier B.V..
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Resource efficiency and energy consumption more and more become high-profile quality attributes of modern machine tools. The energy consumption of machine tools, plants and facilities must be significantly reduced related to the value added in order to stay competitive, but not least in liability towards our environment. This article presents a model based simulation and prediction of the expected energy consumption of machine tools using a comprehensive simulation environment, which serves as a basis for energetic optimizations. The simulation system will be exemplarily presented by reference to turning and milling operations. This system is extended by adaptive control and optimization of the energy states of the machine tool through application of artificial neuronal network controller networks and additional expert knowledge data-base.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2015 |
| Autor(en): | Abele, Eberhard ; Braun, Steffen ; Schraml, Philipp |
| Art des Eintrags: | Bibliographie |
| Titel: | Holistic Simulation Environment for Energy Consumption Prediction of Machine Tools |
| Sprache: | Englisch |
| Publikationsjahr: | 2015 |
| Band einer Reihe: | 29 |
| Veranstaltungstitel: | Procedia CIRP – The 22nd CIRP conference on Life Cycle Engineering, Published by Elsevier B.V. |
| Kurzbeschreibung (Abstract): | Resource efficiency and energy consumption more and more become high-profile quality attributes of modern machine tools. The energy consumption of machine tools, plants and facilities must be significantly reduced related to the value added in order to stay competitive, but not least in liability towards our environment. This article presents a model based simulation and prediction of the expected energy consumption of machine tools using a comprehensive simulation environment, which serves as a basis for energetic optimizations. The simulation system will be exemplarily presented by reference to turning and milling operations. This system is extended by adaptive control and optimization of the energy states of the machine tool through application of artificial neuronal network controller networks and additional expert knowledge data-base. |
| Freie Schlagworte: | Energy Efficiency; Machine Tools; Process Simulation; Machine Simulation; ECOMATION |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) > Umweltgerechte Produktion (am 01.07.2018 umbenannt in ETA Energietechnologien und Anwendung in der Produktion) |
| Hinterlegungsdatum: | 14 Jul 2015 07:44 |
| Letzte Änderung: | 28 Jun 2017 08:49 |
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