Classified analysis on energy consumption of machine tools

2017 ◽  
pp. 1273-1276
Author(s):  
Shuang Liu ◽  
Jie Meng ◽  
Jin Chen
Keyword(s):  
Energy Consumption ◽  
Machine Tools

Development of an energy consumption monitoring procedure for machine tools

CIRP Annals ◽  
2012 ◽  
Vol 61 (1) ◽  
pp. 43-46 ◽  
Author(s):  
Thomas Behrendt ◽  
André Zein ◽  
Sangkee Min
Keyword(s):  
Energy Consumption ◽  
Machine Tools ◽  
Monitoring Procedure

Energieverbrauchssimulation von Werkzeugmaschinen*/Process-specific energy simulation of machine tools

2016 ◽  
Vol 106 (03) ◽  
pp. 163-168
Author(s):  
S. Braun ◽  
P. Schraml ◽  
E. Prof. Abele
Keyword(s):  
Energy Consumption ◽  
Specific Energy ◽  
Machine Tools ◽  
Value Added ◽  
Energy Simulation ◽  
Prediction System ◽  
Critical Quality Attributes ◽  
Milling Operations ◽  
Nc Program ◽  
Modern Machine

Energie- und Ressourceneffizienz beschreiben Qualitätsmerkmale, die auch für moderne Werkzeugmaschinen gelten. Der Energieverbrauch von Maschinen bis zu gesamten Fertigungsstandorten muss im Verhältnis zur erzielten Wertschöpfung deutlich gesenkt werden, um wettbewerbsfähig zu bleiben und unserer Verantwortung gegenüber der Umwelt zu entsprechen. Der Fachbeitrag präsentiert anhand eines Fräsprozesses ein modellgestütztes Simulations- und Prognosesystem des Energieverbrauchs von kompletten Bearbeitungsoperationen auf einer Werkzeugmaschine als Basis energetischer Optimierungen. Teil 1 des Fachaufsatzes ist erschienen in der wt-Ausgabe 1/2-2016 auf den Seiten 60 bis 64.   Resource efficiency and energy consumption are critical quality attributes of modern machine tools. The energy consumption of machine tools, plants and facilities must be significantly reduced relative to the value added in order to stay competitive and fulfil our responsibility towards the environment. This article presents a model-based simulation and prediction system of the expected energy consumption of machine tools executing a given process NC-program as a basis for energetic optimization measures. It is exemplified by milling operations.

Energieverbrauchssimulation von Werkzeugmaschinen*/Process-specific energetic simulation of machine tools

2016 ◽  
Vol 106 (01-02) ◽  
pp. 60-64
Author(s):  
S. Braun ◽  
P. Schraml ◽  
E. Abele
Keyword(s):  
Energy Consumption ◽  
Machine Tools ◽  
Value Added ◽  
Quality Attributes ◽  
Resource Efficiency ◽  
Prediction System ◽  
Critical Quality Attributes ◽  
Milling Operations ◽  
Nc Program ◽  
Modern Machine

Energie- und Ressourceneffizienz sind Qualitätsmerkmale, die auch für moderne Werkzeugmaschinen gelten. Der Energieverbrauch von Maschinen bis zu gesamten Fertigungsstandorten muss im Verhältnis zur erzielten Wertschöpfung deutlich gesenkt werden, um wettbewerbsfähig zu bleiben und unserer Verantwortung gegenüber der Umwelt zu entsprechen. Dieser Beitrag präsentiert anhand eines Fräsprozesses ein modellgestütztes Simulations- und Prognosesystem des Energieverbrauchs von kompletten Bearbeitungsoperationen auf einer Werkzeugmaschine als Basis energetischer Optimierungen.   Resource efficiency and energy consumption are critical quality attributes of modern machine tools. The energy consumption of machine tools, plants and facilities must be significantly reduced relative to the value added in order to stay competitive and fulfil our responsibility towards the environment. This article presents a model-based simulation and prediction system of the expected energy consumption of machine tools executing a given process NC-program as a basis for energetic optimization measures. It is exemplified by milling operations.

Prediction models for specific energy consumption of machine tools and surface roughness based on cutting parameters and tool wear

2020 ◽  
pp. 095440542097106
Author(s):  
Yu Su ◽  
Congbo Li ◽  
Guoyong Zhao ◽  
Chunxiao Li ◽  
Guangxi Zhao
Keyword(s):  
Surface Roughness ◽  
Energy Consumption ◽  
Tool Wear ◽  
Specific Energy ◽  
Machine Tools ◽  
Prediction Models ◽  
Specific Energy Consumption ◽  
Cutting Parameters ◽  
Experimental Results ◽  
Support Vector

The specific energy consumption of machine tools and surface roughness are important indicators for evaluating energy consumption and surface quality in processing. Accurate prediction of them is the basis for realizing processing optimization. Although tool wear is inevitable, the effect of tool wear was seldom considered in the previous prediction models for specific energy consumption of machine tools and surface roughness. In this paper, the prediction models for specific energy consumption of machine tools and surface roughness considering tool wear evolution were developed. The cutting depth, feed rate, spindle speed, and tool flank wear were featured as input variables, and the orthogonal experimental results were used as training points to establish the prediction models based on support vector regression (SVR) algorithm. The proposed models were verified with wet turning AISI 1045 steel experiments. The experimental results indicated that the improved models based on cutting parameters and tool wear have higher prediction accuracy than the prediction models only considering cutting parameters. As such, the proposed models can be significant supplements to the existing specific energy consumption of machine tools and surface roughness modeling, and may provide useful guides on the formulation of cutting parameters.

Energy Demand Simulation of Machine Tools with Improved Chatter Stability Achieved by Active Damping

2015 ◽  
Vol 805 ◽  
pp. 187-195
Author(s):  
Robin Kleinwort ◽  
Richard S.H. Popp ◽  
Benedict Cavalié ◽  
Michael F. Zaeh
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Machine Tools ◽  
Energy Demand ◽  
Removal Rate ◽  
Active Damping ◽  
Depth Of Cut ◽  
Chatter Stability ◽  
Machining Processes ◽  
Base Load

The electric base load of milling machine tools has a high share of the machine’s total energy consumption. An approach to decrease the energy demand per workpiece is to shorten the machining time by raising the material removal rate. The maximum feed depends on the tool’s wear resistance while the maximum depth of cut is often limited by the chatter stability of the machine. In this paper active damping is used to damp chatter vibrations, which leads to a higher depth of cut. To evaluate the decrease of energy consumption for any workpiece, a modeling methodology for the energy demand of machine tools was developed, which is presented in this paper. The methodology is able to estimate the energy requirements of the spindle during cutting, of the feed drives, of the auxiliary equipment and of the base load. The numerical results were experimentally validated by different 2.5D machining processes, with good agreement between the simulation model and the experimental results. Therefore, the proposed methodology can be used effectively for calculating the total energy required for the machining of any workpiece. In addition, the structural dynamics of the machine tool, the active damping system and the cutting process were modeled in order to simulate the chatter stability. This enables a straightforward determination of the optimum cutting parameters as well as a comparison of different milling part programs, both in terms of the energy demand. Furthermore, it is possible to evaluate the energy conservation by active damping and to point out for which cutting processes active damping is useful.

Simulation and Prediction of Process-Related Power Consumption of Machine Tools

2014 ◽  
Vol 907 ◽  
pp. 405-416 ◽  
Author(s):  
Uwe Heisel ◽  
Steffen Braun
Keyword(s):  
Energy Consumption ◽  
Machine Tools ◽  
Expert Knowledge ◽  
Energy State ◽  
Cutting Speed ◽  
Experimental Tests ◽  
Research Unit ◽  
Depth Of Cut ◽  
German Research Foundation ◽  
Starting Point

Today a criterion for the quality of modern machine tools is their efficient use of energy and resources. Competitiveness can only be maintained if the necessity to significantly reduce the energy consumption of machine tools, plants and facilities is put into practice. Another important aspect is the need to preserve our environment. In order to be able to energetically optimize machine tools, it is essential to know how much energy they consume at all. Hence, this paper deals with modelling the energy consumption to be expected from machining operations. Using these estimations and predictions provides a starting point for carrying out energetic optimizations. The method developed here is presented by example of turning operations. The model comprises the machine components directly associated with the cutting process as well as mediate components such as auxiliary units and peripherals. Experimental tests serve to verify the accuracy of the model. Then the energy consumed by individual components is provisionally categorized as well as their proportion of the total amount of energy consumption. Following this, it is possible to analyze the potentials for saving energy. In future it is intended to minimize and condense the complexity of the model so that it will be possible to simultaneously conduct the simulation on the NC control during the cutting operation. In this way it might become possible to influence the energy state of machine tools in realtime during machining, using expert knowledge about the adaptive control of components and drives, the adjustment of control parameters on the fly or the change of parameters such as cutting speed, feed rate and depth of cut. The investigations presented here were funded by the German Research Foundation within the Research Unit 1088 ECOMATION.

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