Development of an energy consumption monitoring procedure for machine tools

CIRP Annals - Manufacturing Technology 61 (2012) 43–46
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CIRP Annals - Manufacturing Technology
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Development of an energy consumption monitoring procedure for machine tools
Thomas Behrendt a, André Zein a,b, Sangkee Min (2)c,*
a
b
c
TU Braunschweig, Braunschweig, Germany
Joint German-Australian Research Group ‘Sustainable Manufacturing and Life Cycle Management’, Sydney, Australia
Laboratory for Manufacturing and Sustainability (LMAS), University of California, Berkeley, CA, USA
A R T I C L E I N F O
A B S T R A C T
Keywords:
Energy
Monitoring
Machine tool
A systematic method to assess energy consumption of machine tools for comparable analysis of data and
to accurately evaluate the energy efficiency of various machine tools is necessary with increasing
interests in green manufacturing. This paper proposes a novel and coherent methodology by presenting a
detailed description of different test procedures based on standardized workpieces. The methodology
was successfully applied to nine machining centers. Energy consumption characteristics of the studied
machine tools are compared and the potential of using the obtained data for energy labeling of machine
tools is discussed.
ß 2012 CIRP.
1. Introduction
Energy reduction strategies are increasingly important with the
constant increase in electricity costs and the rising environmental
awareness of both manufacturers and customers. Machine tools
highly contribute to energy consumption in the industrial sector,
which is the most energy-consuming sector in the U.S. with a share
of 31% in 2010. At the same time, costs for energy have increased by
almost 70% since the late 1990s [1]. The high environmental
impact of these products was also declared by the European
Commission within its ‘‘Energy using products’’ directive, which
was created for improving the environmental performance of
products with excessive energy consumption [2].
Most research provided only little insight into how the data
mining was done. This results in challenging interpretations when
comparing data of different machines. Thus, the development of
effective optimization strategies that are valid for the majority of
machine tools urgently requires standardized test procedures. The
work presented here addresses this problem by deriving formalized assessment procedures and developing a novel standard
test piece.
2. Energy consumption of machine tools
Most studies provided in literature focus on measuring the
power consumption of different types of machine tools as a basis
for identifying optimization potentials. A commonly accepted
energy breakdown by Dahmus and Gutowski divides the power
demand of machine tools into three different modes: idle mode,
run-time mode, and production mode. In idle mode, the machine is
ready for production and components such as the operation panel
and fans accumulate to a constant power demand. During run-time
mode, further auxiliaries are activated, which, once turned on,
* Corresponding author.
0007-8506/$ – see front matter ß 2012 CIRP.
http://dx.doi.org/10.1016/j.cirp.2012.03.103
have a constant power demand (e.g. spindle motor and coolant
pumps). The production mode represents the power demand while
removing material. This portion is variable and dependent on the
load applied to the machine [3].
Numerous studies showed that the power necessary for
removing the actual material has only little impact on the overall
energy consumption [4,5]. Thus, different approaches aimed to
reduce the constant part by either improving specific components
or by reducing the overall cycle time [6,7]. Influences on power
demand were identified, such as process parameters [8], selection
of tooling [9], and workpiece material [10]. Hence, power
measurements are highly dependent on a variety of preconditions
that directly affect the obtained data and therefore require
standardized test procedures.
3. Standards in energy evaluation of machine tools
Based on the above-mentioned variability of power data, a
controversial discussion about standardized procedures has
recently evolved. Dornfeld noted that unambiguous data created
through standards is necessary to accomplish reliable environmental evaluations [11]. In addition, Kuhrke et al. emphasized the
need of further standardization efforts and point out that the
definition of such procedures is essential for each component in
order to ensure the calculation of energy consumption on the same
basis [12].
The Japanese Standards Association (JSA) published an initial
approach towards standardized power data in 2010 [13]. This
methodology describes different procedures for power measurements of the three previously described modes, including a
standard workpiece for three-axis milling machines. Abele et al.
pointed out that this workpiece, however, could only be used by
companies for comparing their energy efficiency improvements
without being able to compare among different manufacturers
[14].
T. Behrendt et al. / CIRP Annals - Manufacturing Technology 61 (2012) 43–46
44
Another work on standardized energy data is currently
developed by the International Organization for Standardization
(ISO) within the framework ‘‘Environmental evaluation of machine
tools’’ (ISO/NP 14955) [15]. The scope of this standard is to define
the environmental performance of machine tools regarding their
design with a focus on metal cutting and forming machines. The
energy consumption, associated CO2-emissions, and consumption
of materials are taken into account as the main environmental
impacts [16]. However, methods and procedures are yet to be
defined.
Fig. 1. Spindle and axis movement [13].
4. Development of a standardized test procedure
The developed test procedure is composed of three assessment
methods revising the energy demand in idle mode, in operational
sequences, and machining operations.
In order to ensure a scalability of the test procedures, 232
machine tools of four major manufacturers were surveyed that
identified the work area (i.e. X- times Y-travel) as the parameter
that correlates most accurately with the size of a machine tool. The
work area (A) of the studied machine tools varies between 0.02 m2
and 10 m2. Three main groups of machine tool sizes are
subsequently
classified:
small
(A 0.1 m2),
medium
(0.1 m2 < A 1 m2), and large (A > 1 m2). Small machine tools
account for only 2%, whereas medium-sized machine tools account
for 58% and large machine tools for 40% of 232 machines,
respectively.
4.1. Standby power
First, a ‘‘standardized start-up procedure’’ evaluates the power
demand during idle mode, which is independent on the size of the
machine and actual material processing. Power measurements
shall be commenced according to the sequence given in Table 1,
which ensures an accurate measurement of standby power.
4.2. Component power
The ‘‘component cycle’’ was derived to assess in detail the
power consumed by the remaining main components, which
provided a process-induced power demand. Each peripheral was
activated for three times, while the machine dwelled in each mode
for 10 s to achieve statistically significant data. The power
consumption of the spindle at different speeds was measured as
suggested by the JSA (Fig. 1(left)). The drives were actuated by
moving the spindle along a cubic motion pattern following a–b–c–
d–a–e–h–d–f–h–a–g–b–a (Fig. 1(right)).
Five different feed rates were used during the motion pattern,
including maximum feed rate (fmax), rapid traverse rate and 1/4, 1/
8, and 1/2 fmax. If featured by the machine, the worktable or spindle
was rotated around the 4th and 5th axis (including rapid traverse
rate). The travel distance between the vertices of the cube was
doubled from small (100 mm) to medium (200 mm) and again
from medium to large (400 mm).
Table 1
Standardized start-up procedure.
#
Component
Power meter
1
2
Main switch
3
Transformera
4
Panel
5
Door
Standby power
6
Panel
7
Transformera
8
Main switch
9
Power meter
a
Operation
Time [min]
Start recording
On
On
On
Open/close
00:00
00:30
01:00
01:30
03:00
Off
Off
Off
Stop recording
09:00
09:30
10:00
10:00
Only true for machine tools that are equipped with this component.
Fig. 2. Standard test piece (small size).
4.3. Machining power
Due to the lack of a specific standard for test workpieces for
machining energy testing, a test workpiece was derived based on
the suggestion of the JSA standard. The limitation of the JSA
workpiece was overcome by scaling the dimensions of the
workpiece matching the capabilities of the machine under study.
Dimensions were doubled from small to medium and from
medium to large test piece, respectively. This generated an
appropriate level of load that allowed comparing different sizes
properly. The developed test piece included 17 different features
and incorporated face milling, grooving, pocketing, and drilling
operations (Fig. 2).
Six main features can be distinguished in the design shown
above, which were machined in following order: face milling (1),
three large grooves (2), three small grooves (3), X-, Y-, and 458pockets (4), a trochoidal groove (5), and six holes (6). According to
the previous classification of machine tools, three different sizes of
test pieces were designed (small, medium, and large).
The facing operation was achieved by a face-mill with five
inserts and a 908 angle. The end-milling operations were machined
with three sizes of a 4-fluted end-mill. A 2-fluted high precision
drill with a tip angle of 1408 and a TiN/TiAlN multilayer coating was
used for drilling the six holes. Cold rolled AISI/SAE 1018 steel was
used as the workpiece material. Table 2 summarizes the main
parameters for machining the test piece.
5. Experimental setup
A Yokogawa CW240 clamp-on powermeter was used in a threephase, single-load setup for measuring the power consumption
while performing the procedures of the developed methodology.
The maximum sampling frequency of the used device is 10 Hz. In
total, nine different machine tools were studied including four 3axis vertical milling machines (Mori Seiki (MS) NVD1500 (24,000
and 40,000 rpm), MS Dura Vertical (DV) 5060, and Haas VF-0), a 4axis horizontal milling center (MS NH8000), two 5-axis vertical
milling machines (MS NMV1500 and MS NMV5000), a mill-turn
center (MS NT1000), and a CNC lathe (MS NL200SY).
6. Experimental results
The following results on energy consumption were calculated
of at least 40 data points. The resulting averaged values guarantee
the reproducibility of the test procedure for each machine tool.
T. Behrendt et al. / CIRP Annals - Manufacturing Technology 61 (2012) 43–46
45
Table 2
Cutting parameters (medium-sized test piece).
Operation #
1
DOC [mm]
Feed rate [mm/min]
1.0, 2.0, 3.0
160
Feed/tooth [mm/tooth]/feed/revolution [mm/rev]
0.05
2
3
4
5
6
200
240
280
0.05
0.06
0.07
400
480
560
0.05
0.06
0.07
400
400
20.0
100, 200, 300, 400, 500, 600
0.05
0.05
0.05, 0.1, 0.15, 0.2, 0.25, 0.3
Fig. 3. Standby power of studied machine tools.
6.1. Standby power
The studied standby power varied significantly across and
within the three different classes (Fig. 3). Additionally, standby
power increased with the complexity of a machine tool. The small
and complex 5-axis NMV1500, for instance, has a standby power
that is almost 2 kW above the medium-sized Haas machine. Even
within one (medium-sized) class of machine tools the standby
power value varied up to about 3.7 kW.
6.2. Component power
Comparing the obtained spindle data across the three classes of
machine tool size revealed that the three groups could also be
separated by the power consumption ratio (slope of the graph)
(Fig. 4). While small machine tools have a low ratio with a large
range of rotational speeds, large machines, in comparison, have a
very high ratio but a rather small range. The maximum power
value of the nine machines at the maximum spindle speed varied
from 650 to 2000 W. At similar rotational speeds, the energy
consumption varied significantly across different machines and
depends on the torque provided by the motors. At 5000 rpm, for
example, the power demand ranged from 78 W for the NVD1500
(40,000 rpm-version) up to 1265 W for the NH8000.
The spindle speed and power demand for the turning spindles
of the NT1000 and NL2000 follow a linear relationship. Since the
workpiece was mounted directly to the spindle, the motors had to
provide significantly more torque than the milling spindles. This
resulted in power demands of about 2–9 kW at 5000 rpm.
In addition, the power consumed by the remaining components
such as coolant pumps, chip conveyor, tool changer, and drives was
assessed using the components cycle. Sankey diagrams were
Fig. 4. Spindle power of studied machine tools.
Fig. 5. Component power of the NH8000.
created for each machine for visualizing the energy consumed by
each component relative to the overall energy consumption. Three
different shadings were chosen for separating the energy and
easing the analysis of gathered data through colored coding: black
for the components that contribute to standby power, dark gray for
components in run-time mode, and light gray for the spindle and
axes with variable energy consumption. The thickness of each
arrow reflects the percentage on overall energy, shown at the top of
the diagram. The spindle power is given for 50% of the maximum
spindle speed. The axis power is given for the average power
consumed by each axis at a feed rate of 2500 mm/min, which in
most cases is also 50% of the maximum cutting feed rate. As an
example, Fig. 5 shows the component power of the MS NH8000.
The main power consuming components of all of the nine
machine tools were the coolant pumps, spindle, controller, tool
change system (only using energy when tool change is performed),
and the hydraulics. Fig. 6 shows that the components that
accumulate to the constant power demand of the machine tool
account for up to 41% on total power demand. However, these are the
components that are always turned on, regardless of the machine’s
operational status. Again, this figure shows that the total power
consumption is highly dependent on both the size and complexity of
the machine tool. In this study, total power varied from about 1.6 to
19.4 kW.
6.3. Machining power
The contribution of the material removal process is determined
by machining the standard test piece on six of the nine machine
tools. As indicated in Table 3, cycle times (TCycle) of 10:45 min,
15 min, and 1:16:15 h for the small, medium, and large test pieces
were designed. The energy (E) used during this process was
Fig. 6. Component power of studied machine tools.
T. Behrendt et al. / CIRP Annals - Manufacturing Technology 61 (2012) 43–46
46
Table 3
Characteristics of machining process.
Value
Small
NVD1500
TCycle [h]
E [kWh]
qCut [%]
PPeak [W]
PF [%]
0:10:45
0.1845
3.65
3320
98
Medium
NMV1500
Haas VF-0
0.7142
1.85
20,130
64
0:15:00
0.3638
20.53
15,610
66
computed by integrating the power data over TCycle. The NVD1500
used 0.19 kWh for machining the small test piece, while the
NH8000 used 9.3 kWh for the large test piece. The energy that is
used for the cutting process only (ECut) was determined by
measuring at first the energy used for performing an air cut (EAir) of
the exact same cycle (i.e. no material was removed). Subtracting
EAir from E reveals ECut, which is given as a percentage of E (qCut)
and varies between 2% and 20%. For the complex machines,
however, this value accounts for only 2–8% (NVD1500, NMV1500,
NMV5000, and NH8000). This observation shows the little impact
contributed by the machining process. The peak power (PPeak)
while machining is essential for power grid design and varied from
3.3 kW for the NVD1500 to 55.6 kW for the NH8000. The power
factor (PF) is an important measure for the energy efficiency of an
electric system. Most power consumed in industry is contributed
by inductive loads (e.g. electric motors, drives, coolant pumps, and
transformers), representing some of the main components of
machine tools that accumulate to a low power factor. Increased
current flow and voltage drops are caused by low PFs, which reduce
the electrical system’s distribution capacity and cause penalty
charges for PFs less than 85% (plant level) [17]. Five of the six
machine tools have a power factor of less than 70%, Table 3.
6.4. Standardized energy reporting
The standardized data can further be used for creating standardized energy data sheets. In addition to the main characteristics, the
components contributing to standby power, the spindle power at
certain rotational speeds, the component power consumption, and
the energy data obtained through machining the test piece can be
summarized. The Sankey diagrams with colored coding support the
comprehensive display of energy data. In comparison to categorizing
the machine tools regarding the use of energy, the data sheets provide
a detailed overview of the different energy consumptions and their
sources. Publishing the energy consumption data would enforce the
competitiveness among manufacturers and foster the activities
towards a reduction of energy use of their machines.
7. Conclusion
Efforts to improve the energy demand of machine tools
increasingly rely on effective methods and assessment procedures
to derive functional data as a mandatory input to subsequent
analysis and improvement. In addition to measuring the power
demand in operational states, this paper proposed the use of
standard assessment procedures to characterize the power demand
of machine tools. The applicability is validated on diverse machine
tools indicating the high potential of formalized assessment
procedures as a basis for improvement and exchange of information.
The presented three-step methodology for measuring the main
groups of power demand can be applied by potential users according
to the desired level of the detail. First, identifying the highly
dominant idle power might be sufficient for sole customers of
machine tools. Optimization strategies that aim to switch the
machine in idle mode when not in use can now be evaluated. Second,
component manufacturers might expand their assessment activities
to the second step, which allows evaluating the effectiveness of
optimization efforts regarding specific components such as drives,
spindles, and coolant pumps. Including the third step mainly
addresses machine tool manufacturers for questioning the overall
Large
DV5060
NMV5000
NH8000
0.5557
14.7
16,440
69
1:16:15
1.9323
4.25
36,900
51
9.2907
7.57
55,600
69
machine tool concept. The required data for evaluating and
optimizing the operational behavior of a machine is generated by
executing all three steps of the presented methodology. The
proposed methodology is useful for companies wanting to establish
some standard practices until such time as a standard is established.
It can also provide useful input to the standards organization with
respect to basic requirements for standard parts (i.e. scalability,
accommodating critical elements, ease of implementation, etc.) [15].
Acknowledgments
This work was supported in part by Mori Seiki, the Digital
Technology Laboratory (DTL), the Machine Tool Technology
Research Foundation (MTTRF), Sandvik, and other industrial
partners of the Laboratory for Manufacturing and Sustainability
(LMAS). The authors would also like to thank Prof. D. Dornfeld and
Prof. C. Herrmann for valuable insight and advice.
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