A practical energy consumption prediction method for CNC machine tools: cases of its implementation

Reducing machine tool energy consumption is critical for the manufacturing industry to achieve sustainable development. An improved energy consumption model is proposed based on the classification of computer numerical control (CNC) machine tool components. The model can be applied in various machine tools and express the machine tool operations flexibly and accurately. To facilitate the application of the model in the workshop, a corresponding procedure is proposed including data acquisition experiment, coefficient estimation, and numerical control (NC) program interpretation. The implementation of the method (i.e., the model and the procedure together) is illustrated in a grinder and a vertical machining center. The results show that the method has a good performance in predicting the power trend of machine tools during their working period. The energy consumption predictive accuracy is more than 96% in the two cases, which demonstrates the high robustness of the method.

[1]  Yufeng Li,et al.  A framework for characterising energy consumption of machining manufacturing systems , 2014 .

[2]  José Carlos Miranda-Valenzuela,et al.  Optimization of cutting parameters to minimize energy consumption during turning of AISI 1018 steel at constant material removal rate using robust design , 2016 .

[3]  Michael P Sealy,et al.  Energy consumption and modeling in precision hard milling , 2016 .

[4]  T. Gutowski,et al.  Environmentally benign manufacturing: Observations from Japan, Europe and the United States , 2005 .

[5]  Song Zhang,et al.  Empirical models and optimal cutting parameters for cutting forces and surface roughness in hard milling of AISI H13 steel , 2010 .

[6]  Wei Cai,et al.  Energy benchmarking rules in machining systems , 2018 .

[7]  Tao Li.  Recent Research and Development of Typical Cutting Machine Tool’s Energy Consumption Model , 2014 .

[8]  Ying Liu,et al.  Therblig-embedded value stream mapping method for lean energy machining , 2017 .

[9]  Ming Cheng,et al.  Quantitative Comparison of Flux-Switching Permanent-Magnet Motors With Interior Permanent Magnet Motor for EV, HEV, and PHEV Applications , 2012, IEEE Transactions on Magnetics.

[10]  Wei Cai,et al.  Development of dynamic energy benchmark for mass production in machining systems for energy management and energy-efficiency improvement , 2017 .

[11]  Stephen Malkin,et al.  Grinding Technology: Theory and Applications of Machining with Abrasives , 1989 .

[12]  Zhiqiang Liu,et al.  Embodied Energy in Dry Cutting under Consumption of Tool and Materials , 2017 .

[13]  Chaoyang Zhang,et al.  Energy-aware integration of process planning and scheduling of advanced machining workshop , 2017 .

[14]  Paul Mativenga,et al.  Critical factors in energy demand modelling for CNC milling and impact of toolpath strategy , 2014 .

[15]  Ying Liu.  A Cardan Angular Model of Rigid Bodies for Woven Fabrics Based on the Dynamics of Multibody Systems , 2014 .

[16]  Christoph Herrmann,et al.  An Investigation into Fixed Energy Consumption of Machine Tools , 2011 .

[17]  Uwe Heisel,et al.  Simulation and Prediction of Process-Related Power Consumption of Machine Tools , 2014 .

[18]  Taylan Altan,et al.  Feed rate optimization based on cutting force calculations in 3-axis milling of dies and molds with sculptured surfaces , 1994 .

[19]  David Dornfeld,et al.  Energy Consumption Characterization and Reduction Strategies for Milling Machine Tool Use , 2011 .

[20]  J. Haider,et al.  Measurement of specific cutting energy for evaluating the efficiency of bandsawing different workpiece materials , 2009 .

[21]  Byung-Kwon Min,et al.  Simulation-based energy usage profiling of machine tool at the component level , 2014 .

[22]  Sami Kara,et al.  An empirical model for predicting energy consumption of manufacturing processes: a case of turning process , 2011 .

[23]  Andrea Matta,et al.  Analysis of Energy Consumption in CNC Machining Centers and Determination of Optimal Cutting Conditions , 2013 .

[24]  Yingli Luo,et al.  Time-stepping finite element analysis on the influence of skewed rotors and different skew angles on the losses of squirrel cage asynchronous motors , 2011 .

[25]  Wei Cai,et al.  A tool for assessing the energy demand and efficiency of machining systems: Energy benchmarking , 2017 .

[26]  Alexander Verl,et al.  A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing , 2009 .

[27]  Paul Mativenga,et al.  Specific energy based evaluation of machining efficiency , 2016 .

[28]  Sung-Hoon Ahn,et al.  Empirical power-consumption model for material removal in three-axis milling , 2014 .

[29]  G. Miragliotta,et al.  Energy management based on Internet of Things: practices and framework for adoption in production management , 2015 .

[30]  Xun Chen,et al.  Empirical modelling of grinding force based on multivariate analysis , 2008 .

[31]  Liu Shuang,et al.  Multi-period Energy Model of Electro-mechanical Main Driving System during the Service Process of Machine Tools , 2012 .

[32]  Peiji Liu.  Calculating Method for Additional Load Loss Coefficient of Spindle System of CNC Machine Tools , 2016 .

[33]  Adriana Giret,et al.  Energy-efficient scheduling for a flexible flow shop using an improved genetic-simulated annealing algorithm , 2013 .

[34]  Sami Kara,et al.  Towards Energy and Resource Efficient Manufacturing: A Processes and Systems Approach , 2012 .

[35]  Paul Xirouchakis,et al.  A production planning in highly automated manufacturing system considering multiple process plans with different energy requirements , 2014 .

[36]  Tao Wu,et al.  Analysis and estimation of energy consumption for numerical control machining , 2012 .

[37]  Paul Xirouchakis,et al.  Evaluating the use phase energy requirements of a machine tool system , 2011 .