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Holistic Simulation Environment for Energy Consumption Prediction of Machine Tools

Abele, Eberhard and Braun, Steffen and Schraml, Philipp :
Holistic Simulation Environment for Energy Consumption Prediction of Machine Tools.
In: Procedia CIRP – The 22nd CIRP conference on Life Cycle Engineering, Published by Elsevier B.V..
[Conference or Workshop Item] , (2015)

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.

Item Type: Conference or Workshop Item
Erschienen: 2015
Creators: Abele, Eberhard and Braun, Steffen and Schraml, Philipp
Title: Holistic Simulation Environment for Energy Consumption Prediction of Machine Tools
Language: English
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.

Volume: 29
Uncontrolled Keywords: Energy Efficiency; Machine Tools; Process Simulation; Machine Simulation; ECOMATION
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Production Management, Technology and Machine Tools (PTW)
16 Department of Mechanical Engineering > Institute of Production Management, Technology and Machine Tools (PTW) > Sustainable Production (new name since 01.07.2018 ETA Energy Technologies and Applications in Production)
Event Title: Procedia CIRP – The 22nd CIRP conference on Life Cycle Engineering, Published by Elsevier B.V.
Date Deposited: 14 Jul 2015 07:44
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