Development of an Empirical Model for Optimization of Machining Parameters to Minimize Power Consumption

被引:12
作者
Garg, Girish Kant [1 ]
Garg, Suman [2 ]
Sangwan, K. S. [1 ]
机构
[1] BITS Pilani, Dept Mech Engn, Pilani 333031, Rajasthan, India
[2] BHSBIET Lehragaga, Dept Comp Engn, Sangrur 148031, Punjab, India
来源
INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN MATERIALS & MANUFACTURING TECHNOLOGIES | 2018年 / 346卷
关键词
RESPONSE-SURFACE METHODOLOGY; ENERGY-CONSUMPTION; CUTTING PARAMETERS; TAGUCHI DESIGN;
D O I
10.1088/1757-899X/346/1/012078
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The manufacturing sector consumes huge energy demand and the machine tools used in this sector have very less energy efficiency. Selection of the optimum machining parameters for machine tools is significant for energy saving and for reduction of environmental emission. In this work an empirical model is developed to minimize the power consumption using response surface methodology. The experiments are performed on a lathe machine tool during the turning of AISI 6061 Aluminum with coated tungsten inserts. The relationship between the power consumption and machining parameters is adequately modeled. This model is used for formulation of minimum power consumption criterion as a function of optimal machining parameters using desirability function approach. The influence of machining parameters on the energy consumption has been found using the analysis of variance. The validation of the developed empirical model is proved using the confirmation experiments. The results indicate that the developed model is effective and has potential to be adopted by the industry for minimum power consumption of machine tools.
引用
收藏
页数:8
相关论文
共 17 条
[1]  
Abhang L.B., 2010, J ENG SCI TECHNOLOGY, V3, P116, DOI [10.25103/jestr.031.20, DOI 10.25103/JESTR.031.20]
[2]   Estimating the effect of cutting parameters on surface finish and power consumption during high speed machining of AISI 1045 steel using Taguchi design and ANOVA [J].
Bhattacharya A. ;
Das S. ;
Majumder P. ;
Batish A. .
Production Engineering, 2009, 3 (01) :31-40
[3]   Optimization of cutting parameters for minimizing energy consumption in turning of AISI 6061 T6 using Taguchi methodology and ANOVA [J].
Camposeco-Negrete, Carmita .
JOURNAL OF CLEANER PRODUCTION, 2013, 53 :195-203
[4]   A comparative analysis of the environmental impacts of machine tool manufacturing facilities [J].
Diaz-Elsayed, Nancy ;
Dornfeld, David ;
Horvath, Arpad .
JOURNAL OF CLEANER PRODUCTION, 2015, 95 :223-231
[5]   A new approach to scheduling in manufacturing for power consumption and carbon footprint reduction [J].
Fang, Kan ;
Uhan, Nelson ;
Zhao, Fu ;
Sutherland, John W. .
JOURNAL OF MANUFACTURING SYSTEMS, 2011, 30 (04) :234-240
[6]   A modeling method of task-oriented energy consumption for machining manufacturing system [J].
He, Yan ;
Liu, Bo ;
Zhang, Xiaodong ;
Gao, Huai ;
Liu, Xuehui .
JOURNAL OF CLEANER PRODUCTION, 2012, 23 (01) :167-174
[7]  
Kant G, 2015, PROCEDIA CIRP
[8]   Predictive Modelling for Energy Consumption in Machining using Artificial Neural Network [J].
Kant, Girish ;
Sangwan, Kuldip Singh .
CIRPE 2015 - UNDERSTANDING THE LIFE CYCLE IMPLICATIONS OF MANUFACTURING, 2015, 37 :205-210
[9]   Predictive Modeling for Power Consumption in Machining using Artificial Intelligence Techniques [J].
Kant, Girish ;
Sangwan, Kuldip Singh .
12TH GLOBAL CONFERENCE ON SUSTAINABLE MANUFACTURING - EMERGING POTENTIALS, 2015, 26 :403-407
[10]   Prediction and optimization of machining parameters for minimizing power consumption and surface roughness in machining [J].
Kant, Girish ;
Sangwan, Kuldip Singh .
JOURNAL OF CLEANER PRODUCTION, 2014, 83 :151-164