An analytical investigation on energy efficiency of high-speed dry-cutting CNC hobbing machines

Abstract Energy efficiency analysis has been recognised as an effective measure for the energy prediction, energy assessment and energy benchmarking in the machining system. However, study on energy efficiency of CNC hobbing machines, especially high-speed, dry-cutting CNC hobbing machines (HSDC-CHM), is still scarce. The energy consumption by HSDC-CHM is generally considered larger, and energy efficiency lower, than wet-cutting CNC hobbing machines (WC-CHM). Therefore, this paper summarises the investigation of energy efficiency of HSDC-CHM and establishes energy efficiency models of CNC hobbing machines. Energy efficiency of HSDC-CHM and WC-CHM are compared and analysed based on energy efficiency models established. Through the theory analysis, results show that, in the production line, although HSDC-CHM possess larger transient energy consumption, its energy efficiency is higher than energy efficiency of WC-CHM. Moreover, it is difficult to obtain quantitative energy efficiency of two types of hobbing machines due to massive relevant hard-to-acquire parameters using energy efficiency models; for this reason, experiments are performed to compare and analyse energy efficiency of HSDC-CHM and WC-CHM. The experiments results indicate that energy efficiency of HSDC-CHM is excellent and far higher than WC-CHM. The study results have a positive significance for the development and application of HSDC-CHM.

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

[2]  Renzhong Tang,et al.  Pareto fronts of machining parameters for trade-off among energy consumption, cutting force and processing time , 2017 .

[3]  Konrad Wegener,et al.  The Total Energy Efficiency Index for machine tools , 2016 .

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

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

[6]  T. Gutowski,et al.  Electrical Energy Requirements for Manufacturing Processes , 2006 .

[7]  Qiulian Wang,et al.  Mathematical Model of Multi-source Energy Flows for CNC Machine Tools , 2013 .

[8]  Fei Liu,et al.  Multi-objective optimization of machining parameters considering energy consumption , 2013, The International Journal of Advanced Manufacturing Technology.

[9]  Liao Mei-ying Losses calculation of IGBT module and heat dissipation system design of inverters , 2011 .

[10]  Li Chao A Kind of Vortex Type Line Geometry Parameter Optimization Method , 2005 .

[11]  Konrad Wegener,et al.  Methods for evaluation of energy efficiency of machine tools , 2015 .

[12]  Wei Cai,et al.  Fine energy consumption allowance of workpieces in the mechanical manufacturing industry , 2016 .

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

[14]  Wei Cai,et al.  An energy management approach for the mechanical manufacturing industry through developing a multi-objective energy benchmark , 2017 .

[15]  Hui Ding,et al.  An investigation on quantitative analysis of energy consumption and carbon footprint in the grinding process , 2014 .

[16]  Sami Kara,et al.  Unit process energy consumption models for material removal processes , 2011 .

[17]  David Dornfeld,et al.  Machine Tool Design and Operation Strategies for Green Manufacturing , 2010 .

[18]  Patrick Wheeler,et al.  Comparison of calculated and measured losses in direct AC-AC converters , 2001, 2001 IEEE 32nd Annual Power Electronics Specialists Conference (IEEE Cat. No.01CH37230).

[19]  S. Tridech,et al.  Low Carbon Manufacturing: characterisation, theoretical models and implementation , 2011, Int. J. Manuf. Res..

[20]  Wei Cai,et al.  An energy-consumption model for establishing energy-consumption allowance of a workpiece in a machining system , 2016 .