Procedia Manufacturing
Volume XXX, 2015, Pages 1–10
43rd Proceedings of the North American Manufacturing Research
Institution of SME http://www.sme.org/namrc
Energy Consumption Characteristics in Finish Hard
Milling of Tool Steels
Z.Y. Liu1, M.P. Sealy1, Y.B. Guo1*, Z.Q. Liu2
1
Dept. of Mechanical Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA
2
School of Mechanical Engineering, Shandong University, Jinan 250061, China
Abstract
Energy consumption is a serious concern for manufacturing industry because it not only consumes
substantial amounts of energy but also produces huge amount of greenhouse CO2 emissions. Previous
research has focused on the relationship between energy consumption and process conditions at the
machine tool and spindle levels. However, little has been done to investigate the energy consumption
in actual material removal at the process level. In this study, power profile and energy consumption at
the machine tool, spindle, and process levels were characterized in hard milling. A new concept at the
process level, net cutting specific energy, was defined to investigate the energy consumed by actual
material removal. The relationship between cutting conditions and energy consumption at each level
was studied. The results indicate that net cutting specific energy may not be predicted by the
traditional model.
Keywords: Energy consumption, dry cutting, sustainable manufacturing
1 Introduction
1.1 Energy consumption in metal cutting
Energy consumption is of serious concern for manufacturing companies because of the
considerable costs and environmental impact. In fact, more than 20% of the operating cost throughout
the entire life of a machine tool is from electrical energy consumption (Abele et al., 2011). In US,
nearly 80% of the energy used to operate machine tools comes from electricity produced by burning
fossil fuels, which emit a considerable amount of greenhouse gas (Dahmus & Gutowski, 2004).
Electrical energy consumption during milling can be minimized by carefully selecting process
parameters. The difficulty is selecting process parameters that balance the requirement to lower energy
consumption with the need to maintain sufficient surface integrity. Energy consumption can be
*
Corresponding author
Tel.: 1-205-348-2615; fax: +1-205-348-6419. E-mail address: [email protected]
Selection and peer-review under responsibility of the Scientific Programme Committee of NAMRI/SME
c The Authors. Published by Elsevier B.V.
1
Energy Consumption Characteristics in Finish Hard Milling of Tool Steels
Liu, Sealy, Guo and Liu
lowered several orders of magnitude at high material removal rates at the sacrifice of surface integrity.
The converse is also true. Superior surface integrity is achievable by lowering material removal rates
at a cost of increased energy consumption. Suitable selection of process parameters can strike a
balance between energy consumption and surface integrity. The difficulty is in determining how to
select process parameters.
Typically, process parameters are chosen to minimize energy consumption at the machine tool or
spindle motor levels. Analyzing energy consumption at these macro-levels leads to a gross oversight
of the energy used to generate a new surface. Energy consumption to generate a new surface must be
considered since it directly relates to surface integrity. Therefore, a thorough study on the relationship
between process parameters and energy consumed on each level is needed to better understand the
delicate balance between energy consumption and surface integrity in manufacturing.
1.2 Classification of energy consumption
Energy consumption of a machine tool can be evaluated at different levels: machine tool, spindle,
and process levels, see Fig. 1. At the machine tool level, the energy consumed by the whole machine
tool (e.g. control systems, cooling and lubrications units, drive systems, spindle motor, manufacturing
process, etc.) is considered. Understanding the relationship between energy consumption and cutting
conditions at this level is practical for improving the overall efficiency of machine tools. The problem
of analyzing energy consumption on this level is that it is machine tool dependent. Comparing
different manufacturing processes or even the same process that uses different machine tools is
impractical.
At the spindle level, the energy consumed by the spindle motor is considered. The electricity
consumed by the spindle motor rotates the cutting tool in milling. It has been reported that the spindle
can consume more than 15% of the total energy (Dietmair et al., 2006). Energy consumption at this
level may be useful in analyzing spindle motor efficiency; however, the problem is analogous to that
of the machine tool. The spindle energy is dependent on the motor which widely varies across
machine tools. In addition, spindle energy is incomparable to other manufacturing processes.
At the process level, only the energy consumed by actual material removal is included and is
independent of the machine tool. Energy consumption at the process level governs chip formation and
surface generation. Therefore, this energy should be considered when selecting process parameters
where the objective is to balance energy consumption with surface integrity.
New
surface
(a) machine tool level
(b) spindle level
(c) process level
Fig. 1 Energy consumption classification.
2
Energy Consumption Characteristics in Finish Hard Milling of Tool Steels
Liu, Sealy, Guo and Liu
1.3 Related work
The development of analytical models of energy consumption is critical for reducing energy
consumption in manufacturing. A model developed by Gutowski et al. decomposes energy use into
idle and cutting states and is based on direct energy required at the machine tool level (Gutowski et
al., 2006). The model by Kara and Li characterizes the relationship between energy consumption at the
machine tool level with material removal rate (MRR) (Li & Kara, 2011). This model accounts for
actual cutting, air cutting, auxiliary motors through constants in the model. In contrast, the measured
energy consumption at spindle level was used in the model by Diaz et al. to establish the relationship
between specific energy and MRR (Diaz et al., 2011). Schlosser et al. proposed a fundamentally
different model format based on the unit specific cutting force and an equalizing correction factor
(Schlosser et al., 2011). However, the specific cutting energy for this model is also at the spindle level.
The model by Draganescu et al. is at the spindle level and incorporates efficiency of the motor
(Draganescu et al., 2003).
Previous models are focused on the relationship between energy consumption and process
parameters at the machine tool or spindle levels. However, little work has been done to characterize
energy consumption at the process level, i.e. the energy consumed by the actual cutting process. At the
process level, the relationship between specific energy and process parameters is poorly understood.
Since energy consumption at the process level is responsible to chip formation and surface generation,
a thorough study of energy consumption at this level is critical to understanding and optimizing a
machining process.
In this study, dry milling of hardened tool steel AISI H13 was conducted since it is a finishing
process widely used in mold/die manufacturing. Compared to grinding, hard milling can be conducted
without the use of cutting fluids, thus generating less wastes and better sustainability (Klocke et
al., 2005). Also, the material removal rate (MRR) in hard milling is relatively small, which is better
suited for achieving a favorable surface integrity. The objectives of this paper are to (1) characterize
the cutting power consumption characteristics in hard milling, (2) evaluate the energy consumption at
the machine tool, spindle, and process levels, and (3) establish a relationship between energy
consumption and process conditions.
2 Experiment Setup and Energy Measurement
2.1 Workpiece material and cutting tool
Hardened AISI H13 tool steel (50 ± 1 HRC) was end milled with a CICINNATI Arrow 500 3-axis
machining center without cutting fluid. Workpiece dimensions were 100 mm × 20 mm × 12 mm with
the longest being the cutting length. The surface of the sample was face milled to remove any heat
treatment induced surface defects. The cutting tool used in this experiment was a 20 mm diameter end
mill cutter with two (Ti,Al)N/TiN coated carbide inserts (SECO XOMX120408TR-D14, 30M). The
tool was kept at a sharp condition as the flank wear (VB) was less than 0.06 mm for all experiments to
minimize the influence of tool wear effect on energy consumption.
2.2 Energy measurement
The power of the machine tool and spindle were measured with a Fluke NORMA 5000 power
analyzer. The experimental setup is shown in Fig. 2. A laptop was connected to the power analyzer for
recording and processing power signals. The sampling rate was 341 kHz. Data was averaged and
output every 150 ms or 300 ms depending on the cutting conditions.
3
Energy Consumption Characteristics in Finish Hard Milling of Tool Steels
Liu, Sealy, Guo and Liu
Insert before
cutting
Cutting
tool
250 µm
Power
meter
Workpiece
Insert after
cutting
VB < 60 µm
250 µm
Fig. 2 Experimental setup of power measurement and tool condition.
2.3 Experiment design
The experiment design is given in Table 1. The effect of cutting speed (v), feed per tooth (fz), radial
DoC (ae), and cutting mode (up/down) on energy consumption was investigated. The v, fz, and ae were
studied at three levels reflective of typical finish machining conditions. In order to reduce
experimental error, each process condition was repeated three times.
Table 1 End Milling Experiment Design
Cutting speed
v
(m/min)
100
200
300
200
200
200
200
Feed per tooth
fz
(mm/tooth)
0.1
0.1
0.1
0.05
0.2
0.1
0.1
Radial DoC
ae
(mm)
0.5
0.5
0.5
0.5
0.5
0.3
0.4
Axial DoC
ap
(mm)
1.0
1.0
1.0
1.0
1.0
1.0
1.0
Cutting
mode
up, down
up, down
up, down
up, down
up, down
up, down
up, down
3 Results and Discussion
3.1 Power profile characteristics
A power profile for a representative cutting pass at the machine tool, spindle, and process levels
which includes idle state, spindle acceleration/deceleration, air cutting, and milling is shown in Fig. 3.
The total power (Fig. 3a) begins at approximately 1.4 kW for the first 10 seconds until the spindle
motor is accelerated. This power is attributed to auxiliary systems needed to run the machine tool.
Naturally, the power consumed by the spindle motor is zero until the spindles are turned on and
accelerated to the appropriate rotational speed, see Fig. 3b. Once the spindle motor was turned on, a
high power peak was observed as the spindle accelerated. The power profiles indicated that the
4
Energy Consumption Characteristics in Finish Hard Milling of Tool Steels
Liu, Sealy, Guo and Liu
acceleration of the spindle against inertia consumed a significant amount of energy in a very short time
span. Also, the total and spindle power profiles show that the deceleration of the spindle produces a
negative power peak because the machine tool has a regenerative supply module which can reconvert
the spindle kinetic energy into electrical energy during the deceleration process. The spindle power
increased from 0.45 kW to approximately 0.49 kW when cutting started. For this particular case, only
40 W was attributed to material removal.
spindle
deceleration
10
0
0
-10
10
20
Time (s)
30
(b) 20
(c) 0.55
10
cutting
0
0
-10
10
20
30
Spindle power (kW)
spindle
acceleration
Spindle power (kW)
Total power (kW)
(a) 20
air
cutting
cutting
air
cutting
0.50
ܲ݊ܿ‫ݏ‬
Ps
ܲ݊ܿ
ܲܽܿ‫ݏ‬
tc
ܲܽܿ
݂
0.45
݂
0.40
Time (s)
10
15
20
Time (s)
Fig. 3 Representative power profile in one cutting pass at (a) machine tool, (b) spindle, and
(c) process levels.
Table 2 Power Terminology
tୡ
Cutting time
ୱ
Pୟୡ
Starting power at air cutting
୤
Pୟୡ
Final power at air cutting
Pୱ
Spindle power
ୱ
P୬ୡ
Starting net cutting power
୤
P୬ୡ
Final net cutting power
P୬ୡ
Net cutting power
A representative power profile of cutting at the process level and related terminology are shown in
Fig. 3c and defined in Table 2. Spindle power (௦ ) is power consumption of the spindle during
material removal. The power consumption of spindle during air cutting is defined as air cutting power
௦
(௔௖ ). Starting power at air cutting (௔௖
) is the spindle air cutting power before material removal. Final
௙
power at air cutting (௔௖ ) is the spindle air cutting power after material removal.
Net cutting power (௡௖ ) more accurately represents power consumed in generating a new surface.
௡௖ is defined as the difference between the power consumption of spindle during material removal
௦
(௦ ) and air cutting (௔௖ ), which is an average of the starting net cutting power (௡௖
) and final net
௙
௦
cutting power (௡௖ ). Starting net cutting power (௡௖ ) is the difference between the spindle power (௦ )
௙
௦
and the start power at air cutting (௔௖
). Final net cutting power (௡௖ ) is the difference between ௦ and
௙
௙
௦
the final power at air cutting (௔௖ ). There was on average a 1.3% difference between ௔௖
and ௔௖
.
5
Energy Consumption Characteristics in Finish Hard Milling of Tool Steels
Liu, Sealy, Guo and Liu
The specific energy of cutting has historically been defined as the energy consumption to remove a
unit volume of material. With this definition, there is ambiguity as to which energy consumption
(total, spindle, or net cutting) should be considered when determining the specific energy of cutting. In
this study, specific energy is defined at three levels, the total specific energy (Ut), spindle specific
energy (Us), and net cutting specific energy (Unc). At each level, the specific energy was calculated by
the corresponding power consumption divided by material removal rate.
3.2 Specific energy vs. MRR
The calculated total energy and net cutting specific energy vs. MRR are presented in Fig. 4. The
empirical models reported by (Li & Kara, 2011) (Eq. 1) and (Diaz et al., 2011) closely approximate
the measured total specific energy with an R2 value of 99.1%. However, the regression curve fits the
data poorly when this model is used to analyze net cutting specific energy. Therefore, the traditional
model has poor predictive capabilities for net cutting specific energy. In contrast with total specific
energy, net specific cutting energy cannot be predicted solely with MRR. A more accurate modeling
approach is required to establish the relationship between net cutting specific energy and MRR.
U௧ =
Total specific energy
Ut (J/mm3)
500
1327.9
+ 10.3
MRR
Net cutting specific energy
Unc (J/mm3)
600
ܴଶ = 99.1%
400
300
200
100
0
0
5
10
15
16
U௡௖ =
16.2
+ 3.0
MRR
12
8
4
0
0
5
10
15
(b) Material removal rate, MRR (mm3/s)
(a) Material removal rate, MRR (mm3/s)
Fig. 4 Net cutting specific energy and total specific energy vs. MRR
U=
‫ܥ‬ଵ
+ ‫ܥ‬଴
MRR
(1)
3.3 Specific energy vs. cutting conditions
The effect of process parameters (i.e. cutting speed, feed per tooth, and axial depth of cut) on the
total, spindle, and net cutting specific energy is shown in Figs. 5-7, respectively. The total and spindle
specific energy show the same trends. Of course, the magnitude of the total specific energy is higher
than that of the spindle because of the power used by auxiliary systems is included within the data.
Again, this is the shortfall of analyzing specific energy at the machine tool and spindle levels; the data
is machine tool/spindle motor dependent. As each process parameter increased, the total and specific
energies decreased. At these levels, there was a negligible difference between up and down milling.
At the process level, it can be seen from the Fig. 7 that the net cutting specific energy also dropped
when the fz and ae increased. In contrast, the net cutting specific energy increased with higher cutting
6
Energy Consumption Characteristics in Finish Hard Milling of Tool Steels
Liu, Sealy, Guo and Liu
speeds. This may be explained by strong strain hardening caused by the higher strain rate. It can also
be seen at the process level that up milling consumed more energy than down milling (8.5% on
average). This is contributed by the longer tool/chip contact length during up milling as compared to
down milling that requires more energy to remove.
Total specific energy
Ut (J/mm3)
600
ae = 0.5 mm
ae = 0.5 mm
ap = 1.0 mm
ap = 1.0 mm
fz = 0.1 mm/tooth v = 200 m/min
ap = 1.0 mm
v = 200 m/min
fz = 0.1 mm/tooth
Up
Down
500
400
300
200
100
0
100 200 300
0.05 0.1 0.2
0.3 0.4 0.5
Cutting speed
v (m/min)
Feed per tooth
fz (mm/tooth)
Axial DoC
ae (mm)
Fig. 5 Influence of process parameters on total specific energy.
Spindle specific energy
Us (J/mm3)
250
ae = 0.5 mm
ae = 0.5 mm
ap = 1.0 mm
ap = 1.0 mm
fz = 0.1 mm/tooth v = 200 m/min
ap = 1.0 mm
v = 200 m/min
fz = 0.1 mm/tooth
Up
Down
200
150
100
50
0
100 200 300
Cutting speed
v (m/min)
0.05 0.1 0.2
0.3 0.4 0.5
Feed per tooth
fz (mm/tooth)
Axial DoC
ae (mm)
Fig. 6 Influence of process parameters on spindle specific energy.
7
Energy Consumption Characteristics in Finish Hard Milling of Tool Steels
Liu, Sealy, Guo and Liu
Net cuttng specific energy
Unc (J/mm3)
16
12
ae = 0.5 mm
ap = 1.0 mm
fz = 0.1 mm/tooth
ae = 0.5 mm
ap = 1.0 mm
v = 200 m/min
ap = 1.0 mm
v = 200 m/min
fz = 0.1 mm/tooth
Up
Down
8
4
0
100 200 300
Cutting speed
v (m/min)
0.05 0.1 0.2
Feed per tooth
fz (mm/tooth)
0.3 0.4 0.5
Axial DoC
ae (mm)
Fig. 7 Influence of process parameters on net cutting specific energy.
3.4 Energy efficiency
The energy efficiency (η) of cutting at various process parameters is shown in Fig. 8. The
efficiency is defined as the ratio of the net cutting specific energy (Unc) to the total specific energy
(Ut). The energy efficiency at the various conditions in this experiment varies from 1% to 6%. Results
show that energy efficiency increases as v, fz, and ae increase. Even though energy efficiency increases
with MRR, surface roughness increases which sacrifices the surface integrity of a precision part.
7%
Energy efficiency (η)
6%
ae = 0.5 mm
ap = 1.0 mm
fz = 0.1 mm/tooth
ae = 0.5 mm
ap = 1.0 mm
v = 200 m/min
ap = 1.0 mm
v = 200 m/min
fz = 0.1 mm/tooth
5%
4%
3%
2%
1%
0%
100 200 300
Cutting speed
v (m/min)
0.05 0.1 0.2
Feed per tooth
fz (mm/tooth)
0.3 0.4 0.5
Axial DoC
ae (mm)
Fig. 8 Relationship between energy efficiency and process parameters.
8
Energy Consumption Characteristics in Finish Hard Milling of Tool Steels
Liu, Sealy, Guo and Liu
4 Summary and Conclusions
The power consumed by dry hard milling tool steel AISI H13 was measured and analyzed. Energy
consumption was investigated at the machine tool, spindle, and process levels. The concept of net
cutting specific energy was defined to characterize energy consumed by the actual material removal.
The effect of cutting parameters on total, spindle, and net cutting specific energies was investigated.
The key conclusions are summarized as follows:
• Energy consumption at machine tool level can be described with a traditional empirical
model effectively. However, this model is incapable of predicting energy consumption at the
process level. Therefore, it is insufficient when balancing low energy consumption with a
superior surface integrity.
• Specific energy at machine tool, spindle, and process levels decreases when increasing the
process parameters except cutting speed.
• Up milling consumes slightly more energy than down milling. This difference is negligible at
the machine tool and spindle levels due to the relatively small percentage of energy
consumption at the process level.
• Energy efficiency of hard milling varies from 1% to 6% at different cutting conditions.
Although efficiency during dry hard milling can be increased with a higher MRR, care must
be taken to appropriately select process conditions that do not sacrifice part quality for the
sake of efficiency.
5 Acknowledgements
The corresponding author would like to thank Prof. John Sutherland for discussing the concept of
specific cutting energy.
6 References
Abele, E., Sielaff, T., Schiffler, A. (2011). Analyzing energy consumption of machine tool spindle
units and identification of potential for improvements of efficiency. Glocalized Solutions for
Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life
Cycle Engineering, Springer-Verlag, Berlin, 280-285.
Dahmus, J.B., Gutowski, T.G. (2004). An environmental analysis of machining. Proceedings of the
ASME 2004 International Mechanical Engineering Congress and Expo (IMECE), Anaheim, CA,
643-652.
Diaz, N., Redelsheimer, E., Dornfeld, D. (2011). Energy consumption characterization and reduction
strategies for milling machine tool use. Glocalized Solutions for Sustainability in Manufacturing:
Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, SpringerVerlag, Berlin, 263-267.
Dietmair, A., Verl, A. (2009). Energy consumption forecasting and optimisation for tool machines.
Modern Machinery Science Journal, 63-67.
Draganescu, F., Gheorghe, M. Doicin, C.V. (2003). Models of machine tool efficiency and specific
consumed energy. Journal of Materials Processing Technology, 141(1), 9-15.
Gutowski, T., Dahmus, J., Thiriez, A. (2006). Electrical energy requirements for manufacturing
processes. 13th CIRP International Conference of Life Cycle Engineering, Leuven, 31, 1-5.
Klocke, F., Brinksmeier, E., Weinert, K. (2005). Capability profile of hard cutting and grinding
processes. CIRP Annals - Manufacturing Technology, 54(2), 22-45.
9
Energy Consumption Characteristics in Finish Hard Milling of Tool Steels
Liu, Sealy, Guo and Liu
Li, W., Kara, S. (2011). An empirical model for predicting energy consumption of manufacturing
processes: a case of turning process. Proceedings of the Institution of Mechanical Engineers, Part
B: Journal of Engineering Manufacture, 225(9), 1636-1646.
Schlosser, R., Klocke, F., Lung, D. (2011). Sustainabilty in manufacturing – energy consumption of
cutting processes. Advances in Sustainable Manufacturing: Proceedings of the 8th Global
Conference on Sustainable Manufacturing, Springer-Verlag, Berlin, 85-89.
10