Energy consumption of computer numerical control (CNC) machines is significant and various empirical models have been developed to model the specific energy consumption (SEC) of CNC machines. However, most of the models are developed for specific machines and hence have limited applications in manufacturing industry. In this research, a general empirical SEC model for milling machine at certain power level is developed based on actual cutting experimental data. In this model, stand-by power and spindle power are used in the SEC model for the first time. The material removal rate (MRR) is used to represent the cutting parameter. The proposed model is fitted by the regression analysis and validated using experimental data. Results show that the proposed model can be applied on various milling machines with an average absolute residual ratio of 6%. The model is also validated through a series of cutting experiments on a machine center, with an accuracy of 91.5%, for the SEC calculation.

References

References
1.
U.S. EIA, 2014, “
Manufacturing Energy Consumption Survey
,” Energy Information Administration, Washington, DC.
2.
U.S. EIA, 2017, “
Monthly Energy Review
,” Office of Energy Statistics, Washington, DC, Report No. DOE/EIA-0035(2017/4).
3.
Branham
,
M.
,
Gutowski
,
T. G.
,
Jones
,
A.
, and
Sekulic
,
D. P.
, 2008, “
A Thermodynamic Framework for Analyzing and Improving Manufacturing Processes
,”
International Symposium on Electronics and the Environment
, San Francisco, CA, May 19–22, pp. 1–6.
4.
Li
,
T.
, and
Yuan
,
C.
, 2013, “
Numerical Modeling of Specific Energy Consumption in Machining Process
,”
ASME
Paper No. MSEC2013-1247.
5.
Zhou
,
L.
,
Li
,
J.
,
Li
,
F.
,
Meng
,
Q.
,
Li
,
J.
, and
Xu
,
X.
,
2016
, “
Energy Consumption Model and Energy Efficiency of Machine Tools: A Comprehensive Literature Review
,”
J. Cleaner Prod.
,
112
, pp.
3721
3734
.
6.
Gutowski
,
T.
,
Dahmus
,
J.
, and
Thiriez
,
A.
,
2006
, “
Electrical Energy Requirements for Manufacturing Processes
,”
13th CIRP International Conference on Life Cycle Engineering
, May 31–June 2, pp. 623–638, pp.
623
638
.http://web.mit.edu/2.813/www/readings/Gutowski-CIRP.pdf
7.
Kara
,
S.
, and
Li
,
W.
,
2011
, “
Unit Process Energy Consumption Models for Material Removal Processes
,”
CIRP Ann. Manuf. Technol.
,
60
(
1
), pp.
37
40
.
8.
Li
,
L.
,
Yan
,
J.
, and
Xing
,
Z.
,
2013
, “
Energy Requirements Evaluation of Milling Machines Based on Thermal Equilibrium and Empirical Modelling
,”
J. Cleaner Prod.
,
52
, pp.
113
121
.
9.
Rodrigues
,
A. R.
, and
Coelho
,
R. T.
,
2007
, “
Influence of the Tool Edge Geometry on Specific Cutting Energy at High-Speed Cutting
,”
J. Braz. Soc. Mech. Sci. Eng.
,
29
(
3
), pp.
279
283
.
10.
Guo
,
Y.
,
Loenders
,
J.
,
Duflou
,
J.
, and
Lauwers
,
B.
,
2012
, “
Optimization of Energy Consumption and Surface Quality in Finish Turning
,”
Procedia CIRP
,
1
, pp.
512
517
.
11.
Mori
,
M.
,
Fujishima
,
M.
,
Inamasu
,
Y.
, and
Oda
,
Y.
,
2011
, “
A Study on Energy Efficiency Improvement for Machine Tools
,”
CIRP Ann. Manuf. Technol.
,
60
(
1
), pp.
145
148
.
12.
Aramcharoen
,
A.
, and
Mativenga
,
P. T.
,
2014
, “
Critical Factors in Energy Demand Modelling for CNC Milling and Impact of Toolpath Strategy
,”
J. Cleaner Prod.
,
78
, pp.
63
74
.
13.
Budinoff
,
H.
,
Bhinge
,
R.
, and
Dornfeld
,
D.
,
2016
, “
A Material-General Energy Prediction Model for Milling Machine Tools
,”
International Symposium on Flexible Automation
, Cleveland, OH, Aug. 1–3, pp.
161
164
.
14.
Diaz
,
N.
,
Redelsheimer
,
E.
, and
Dornfeld
,
D.
,
2011
, “
Energy Consumption Characterization and Reduction Strategies for Milling Machine Tool Use
,”
Glocalized Solutions for Sustainability in Manufacturing
,
Braunschweig, Germany
, pp.
263
267
.
15.
Kordonowy
,
D.
,
2003
, “
A Power Assessment of Machining Tools
,” Bachelor thesis, Massachusetts Institute of Technology, Cambridge, MA.
16.
Gutowski
,
T.
,
Dahmus
,
J.
,
Thiriez
,
A.
,
Branham
,
M.
, and
Jones
,
A.
,
2007
, “
A Thermodynamic Characterization of Manufacturing Processes
,”
IEEE
International Symposium on Electronics and the Environment
,
Orlando, FL
,
May 7–10
, pp.
137
142
.
17.
Campatelli
,
G.
,
Lorenzini
,
L.
, and
Scippa
,
A.
,
2014
, “
Optimization of Process Parameters Using a Response Surface Method for Minimizing Power Consumption in the Milling of Carbon Steel
,”
J. Cleaner Prod.
,
66
, pp.
309
316
.
18.
Li
,
C.
,
Xiao
,
Q.
,
Tang
,
Y.
, and
Li
,
L.
,
2016
, “
A Method Integrating Taguchi, RSM and MOPSO to CNC Machining Parameters Optimization for Energy Saving
,”
J. Cleaner Prod.
,
135
, pp.
263
275
.
19.
Li
,
C.
,
Chen
,
X.
,
Tang
,
Y.
, and
Li
,
L.
,
2017
, “
Selection of Optimum Parameters in Multi-Pass Face Milling for Maximum Energy Efficiency and Minimum Production Cost
,”
J. Cleaner Prod.
,
140
, pp.
1805
1818
.
20.
Yoon
,
H.-S.
,
Lee
,
J.-Y.
,
Kim
,
M.-S.
, and
Ahn
,
S.-H.
,
2014
, “
Empirical Power-Consumption Model for Material Removal in Three-Axis Milling
,”
J. Cleaner Prod.
,
78
, pp.
54
62
.
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