Measured Performance of Variable Speed Drives on ...

Measured Performance of Variable Speed Drives on Injection Molding Machinery Scott L. Englander, New England Power Service Company Carl H. Remley, Energy Management Consulting & Equipment Inc.

To characterize the performance and savings potential of variable speed drives (VSDs) retrofit on hydraulic pumps of plastic injection molding machines, twelve installations at seven sites were monitored. The objectives of the evaluation were to estimate energy and coincident demand savings for each installation based on short-term measurements performed at the sites, and to develop a model of savings as a function of pertinent operational parameters for the purpose of estimating savings for installations not measured. It was found that the savings associated with VSD retrofits on injection molding machines varies widely, and increases with the percentage of time the machine spends in the “idle” step of the molding sequence. The relationship between percent savings and percent idle time developed in this study can be used in conjunction with pre- or post-retrofit power and timing measurements to reliably predict savings. Pre-retrofit power, in cases where measurements are not available, can be reliably estimated as a function of machine capacity in tons, motor size, and percent idle time using the model developed in this study.

Introduction Variable speed drives (VSDs) are becoming an increasingly common retrofit on hydraulic pumps in plastic injection molding machines (IMM). In 1992 and 1993, VSDs were retrofit on 6,340 motor horsepower in injection molding applications as part of the commercial and industrial conservation programs of the New England Electric System (NEES) companies. The utility recently began to offer incentives specifically intended for VSD retrofits on IMMs. Because plastics manufacturers are common in New England, and account for 14% of the Companies’ industrial sector revenues, this measure is thought to have large market potential in the service territories of NEES’s retail affiliates. Little is known, however, about how energy and demand savings due to retrofits of VSDs on injection molding machines are influenced by operating parameters and machine characteristics. To set appropriate financial incentive levels and eligibility criteria, accurately predict savings, and demonstrate savings to regulators and other interested parties, the utility needed to quantify the energy and demand savings due to the installation of VSDs on IMMs, based on measured results. The utility commissioned a study whose objectives were to estimate energy and coincident peak demand savings for several installations based on short-term measurements performed at the sites, and to develop a model of savings

as a function of pertinent operational parameters for the purpose of predicting and estimating savings for installations not measured. In this project, a total of eight installations at four manufacturing sites in Massachusetts were studied. The sites were chosen from among those customers who had applied for incentives in 1992. Machine characteristics are listed in the complete report (EMCEI, 1993). 1 In addition to this effort, four other installations (at three sites) were monitored: three through the utility’s Performance Engineering program-in which third-party contractors receive incentives to measure savings—and one as part of an earlier utility pilot study. Table 1 lists the participant sites, the products they manufacture, and the machines monitored. Three of the sites are job shops—they have no products of their own but manufacture for other companies. For the 12 IMMs tested at seven sites, operating hours at the sites ranged from one eight-hour shift to three, the sizes of the machines ranged from 90 tons to 700 tons, the motors controlled ranged from 20 to 60 horsepower, and the machines were made by four different manufacturers. The diversity of sites, machines, sizes, horsepower, and operating hours chosen was intended to provide a range of conditions broad enough to allow the influence of key determinants

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of consumption and savings to be seen. Only one of the machines monitored (MBA8) had more than one motor (a 20 HP and a 50 HP).

Retrofit Description For each batch of parts produced, an injection molding machine goes through a cycle which generally lasts 20 60 seconds2 and consists of six steps: mold close, injection high, injection low, screw rotate, idle or cooling, and mold open. The duration of each step of the cycle is set when a given mold is installed; plant personnel generally try to minimize the cycle time to maximize production while still achieving quality of the part produced. Under constant speed control, hydraulic control valves throttle and shunt fluid to cylinders in different parts of the machine. Although pressure and flow requirements vary drastically between different steps of the cycle, the input power to the motor under constant speed operation does not, as the pump must overcome the frictional resistance of throttled valves or bypass fluid pathways. A VSD dynamically modulates motor speed—and therefore hydraulic pressure and flow-to that required to perform the task of each part of the cycle; the duration of each step remains the same as for constant speed control. Motor speed, as well as acceleration rate (or ramp time) can be finely tuned for each phase of the cycle to optimize efficiency. In addition to improving efficiency, a VSD also improves the power factor for injection molding machinery because motors designed for peak machine capacity often run at lower loads. A VSD assembly is supplied in two parts: The drive is mounted in one cabinet normally near the main IMM control panel. A second cabinet contains a small control center, where setup and control is done. Lights on the control panel tell the setup person what part of the cycle

the IMM is in at any time. A digital display on the panel shows the percent of full speed at any time. All of the VSDs installed on IMMs to date under NEPSCo’s programs were sold and installed by a single vendor, who also provided training. Installation of the VSD requires a licensed electrician, because motor power input must be interrupted and rerouted through the drive. Installation takes approximately four to five hours by factory-trained service people. Once the drive is installed, it must be tested; the parameters must be optimized for the IMM and the particular mold that will be run. If the savings are to be optimized, the optimization must take place each time a new mold is installed. Each of the employees who changes molds must be trained to set up and optimize the VSDs, or else savings may deteriorate. It is uncertain how widely optimization of new molds is practiced, although recent improvements in the design of the controls interface have likely facilitated this, as is discussed further below. Once a mold has been optimized, the parameters can be documented and reprogrammed the next time the mold is installed in that machine. The newer control interfaces installed with VSDs on three of the machines included in this analysis (NM4, NM5, CM10) included “memory modules” which store the timing and speed parameters, so that when a given mold is reinstalled, the controls can be easily and properly configured. The new interfaces also monitor power in kW and HP and log energy use, enabling operators to gauge efficiency.3

Measurement Approach On nine of the machines tested, energy consumption and power were measured for an hour or more before and after installation; for the three machines measured under

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the Performance Engineering program (NM4, NM5, and CM10), measurements were taken over 1.5 to 48 hours. In addition, one machine was tested with two different molds. Because cycle time varied from 22 to 54 seconds for the machines tested, at least 66 cycles were included in the measurement period.

cycle can be shorter than the two second polling frequency and might therefore be excluded from short-term averages. The measurements done on the three machines monitored through the Performance Engineering program were done with a datalogger capable of accurately measuring power for distorted wave forms.

For most of the measurements, a sophisticated portable power monitor was used, with the capability to measure and record to diskette RMS voltage, RMS current, true power, apparent power, reactive power, true power factor, displacement power factor, total harmonic distortion, and frequency over time. To sample voltage and current simultaneously, three voltage and three current signals are routed through a multiplexer to a 14-bit analog-to-digital converter. Each cycle is sampled at high frequency (7,680 Hz, 128 times each cycle for eight 60 Hz cycles). Digital data are passed to a 80C186 CPU and 80C187 coprocessor where the samples are processed every two seconds. From the seven groups of 1024 sampled data points, the monitor computes RMS volts, RMS amps, imbalance, power factor, and true power in watts and VA every two seconds for a three phase circuit.

For eight of the machines monitored, cycle and idle time were measured using a stopwatch, and are accurate to the nearest second. For the other four, times were read off the control display. In addition to measured data, information such as operating schedules and polymer used were collected through interviews with plant personnel; motor HP and rated clamping force in tons were taken from nameplates.

Because high frequency harmonic distortion caused by VSDs requires high frequency sampling, the monitor chosen appears to be a good choice for this type of monitoring, with one caveat: data must be accumulated over a period that far exceeds the length of a single injection molding cycle, because individual steps in the

Results Average power for each case was calculated by dividing total consumption for the monitoring period by the duration of the period. Billing demand savings were simply the difference between pre- and post-retrofit average power; summer and winter coincident peak demand and savings were determined by multiplying average power by the fraction of time machines operated during the utility peak demand periods, 11 a.m. - 3 p.m. summer weekdays, and 5 p.m. - 7 p.m. winter weekdays. Energy consumption and savings were calculated by multiplying average power by annual operating hours. Pre- and post-retrofit test results and savings summaries are presented in Tables 2 through 4.

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Absolute and relative savings varied widely across machines and molds. Absolute demand savings varied from 2.2 kW to 13.8 kW, energy savings varied from 13.2 MWh/y to 78.7 MWh/y, and relative savings varied from 4% to 61%, averaging 37%. Interestingly, power and savings normalized by motor size varied widely as well. It was thought that this variation in absolute, relative, and normalized savings could be explained by variation in other system parameters. In particular, because the greatest reduction in motor speed occurs in idle mode, it was expected that percent idle time (idle time/cycle time) would be a strong determinant of percent savings. It was also hypothesized that percent savings would depend to a lesser degree on capacity and size characteristics of the machines. Exploratory visual data analysis and stepwise regression were used to discern relationships between pre-retrofit power and savings and variables such as machine capacity, motor size, and idle time. It can be seen in Figure 1 that although percent savings are strongly related to percent idle time, there is considerable scatter and the relationship is not quite linear. It makes sense, especially for large idle times, that savings would level off in the limit, a machine idling 100% of the time would not save close to 100%. Reasoning that modeling savings as a diminishing function of idle time (e.g. logarithmic) made sense, we found through visual analysis and regression that the square root of percent idle

where Sf = fractional reduction in power H = motor size, HP T = rated clamping force, tons I = fractional idle time The t-ratios for all variables in the regression were significant; predicted vs. measured savings are shown in Figure 2.4

Figure 2. Percent savings predicted by the regression model compared to measurements. Absolute reduction in power (in kW) can be reliably predicted by multiplying measured pre-retrofit power PC by the estimated percent (fractional) savings: (2) or, if measurements of post-retrofit power Pv are available instead, as follows: (3)

Figure 1. Percent decrease in average input power for VSDs retrofit on injection molding machines, as a function of percent idle time. time was a good determinant, and was also more symmetrically distributed than percent idle time. Remaining residuals prompted further exploration, resulting in the final model of percent savings as a function of the square root of percent idle time, motor HP, rated clamping force, and the ratio of clamping force to motor size:

Annual energy savings can then be estimated by multiplying by annual operating hours. The limitation of this model alone is that absolute savings can only be predicted if average pre- or post-retrofit power is known. When attempts to relate decrease in average power (both absolute and normalized by motor HP) to other variables proved unsuccessful, a model for pre-retrofit power was sought. Figure 3 shows that pre-retrofit power is strongly but not completely determined by machine capacity. In the same manner used to derive the model for savings, pre-retrofit power (in kW) was found to be well-determined by three variables: The estimated pre-retrofit power can then be used in Equation 2 to predict absolute savings. Predicted vs.

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(4) measured power is shown in Figure 4. The resulting model generally makes sense physically; power under constant speed operation would be expected to increase with machine capacity, decrease with the portion of the molding cycle spent idling, and increase with motor oversizing, which may be indicated by the ratio of motor to machine capacity.

Figure 3. Pre-retrofit power, for VSDS retrofit on

injection molding machines, as a function of rated clamping force.

customers ranged between 0.8 and 2.2 years with utility incentives, and 2.0 to 5.4 without. The value of kVA savings was a significant part of the total, due to improvement in power factor. Under constant speed operation, power factor ranged from 0.7 - 0.9 during the more heavily loaded steps of the molding sequence, and dipped as low as 0.4 during the idle step. VSDs consistently lifted the power factor above 0.9 in all steps of the sequence. It is likely that power factors are low under constant speed operation because the motors are typically sized to handle the short-duration but high peak loads experienced during the injection step of the cycle. Observation of VSD set-up and operation by plant personnel revealed that in at least one facility training appeared to be insufficient, resulting in improper operation of equipment (e.g., adjustments made to hydraulic valves under VSD operation, speed settings increased arbitrarily in attempts to fix problems). Personnel at this site did not appear to have been trained to optimize VSD efficiency for each mold. Systems and procedures to facilitate rapid and accurate set-up and optimization were not in place. The vendor of the VSDs reported that additional training for personnel on all shifts at this facility resolved the problems. The vendor also reported that recent improvements in the user interface have virtually eliminated such problems, due to the greater ease-of-use, and operator feedback in the form of a digital display showing power and energy use (EICS, 1994).

Conclusions

Figure 4. Pre-retrofit power predicted by the regression model compared to measurements. Table 5 shows the results of a simple economic analysis intended to demonstrate the cost-effectiveness of the installations from the customer’s perspective. The effective kVA rate is used as the basis for billing demand savings because all customers are billed on this basis (facility power factor is less than 0.9). Simple payback to

The energy and coincident demand savings associated with VSD retrofits on injection molding machines vary widely. Savings increases with the percentage of the molding cycle spent idling and depends to a lesser extent on motor size and rated clamping force. This is reasonable because under constant speed operation, it is in the idle phase of the cycle that the hydraulic valves must throttle the flow of the oil the most. The model for percent savings developed in this study can be used in conjunction with pre- or post-retrofit power and timing measurements to reliably predict savings. Pre-retrofit power, in cases where measurements are not available, can be reliably estimated as a function of machine capacity in tons, motor size, and percent idle time using the model developed in this study. Although other variables such as machine make, age, and polymer used may also influence consumption and savings, not enough data were obtained in this study to draw any conclusions. The models developed here must be used with the caveats that the sample on which they are based is small relative to the number of parameters used, the distributions of values for some of the parameters (notably T/H) are less

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than symmetrical, and the few data points at the edges of the range of machine capacity limit the models’ applicability in these regions. Although most installations would be expected to operate in the range of most of our measurements, further measurement is required to extend the range of the savings and power models. Because only one machine in the sample used more than one motor, the quantitative results presented here should also not be applied indiscriminately to machines with multiple motors. Because most IMMs are likely to be operated with idle times less than 60% of cycle times, and the majority of machines in use are no larger than 500 tons and have a single motor, the models developed in this study are expected to be widely applicable. Further research is needed to develop a theoretical underpinning for the models. A substantial portion of savings could explained by percent idle time alone. Although horsepower, capacity, and the ratio of the two turned out to be good additional predictors, it is not exactly clear why. The model for constant speed power is more intuitive, but could also benefit from further study. Detailed cycle-level measurements could go a long way toward answering such questions. The VSDs were observed to consistently increase power factor. Because industrial customers often pay a penalty for low power factor, the benefits of increasing power factor can be significant. It should be noted, however, that

the VSDs increased power factor because of the dynamic and “spiky” loading pattern of the application and the commensurate oversizing of the motors; VSDs have been observed to decrease power factor in other applications where the motor under constant speed operation experiences loads close to capacity for much of the time. The anecdotal observations of set-up and operating procedure emphasize the importance of commissioning and operator interface design to achieving and maintaining savings. Plant personnel accustomed to adjusting hydraulic valves as a means of tuning machine operation may continue to do so (at the expense of savings) unless they are comfortable with adjusting VSD settings, and find it easier to do so. Unless plant personnel “buy in” to the new systems, savings may be lost once new molds are used. Acceptance by operators may be facilitated by training them how to optimize performance for each mold (and requirements by management to do so), and a user-friendly control interface which includes feedback on efficiency. Once optimum operating parameters are established, simple systems such as a card attached to the mold listing VSD settings can help ensure persistence of savings. New technologies such as memory modules which can store VSD settings for each mold can facilitate rapid and proper set-up and thereby enhance persistence of savings. Finally, future repeat measurements of the IMMs used in this study would be useful in the assessment of persistence.

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Acknowledgments Margaret Campbell of New England Power Service Company commissioned the pilot study resulting in the measurements of MBA8 presented here; the measurements were performed by Matt Russell of Power Conversion Systems. John Abraham of EES did the Performance Engineering measurements and savings estimates on three machines. All the VSDs were installed by Efficient Industrial Control Systems of Avon, Connecticut.

Endnotes 1. The additional data, results, and models presented here extend the simpler analysis documented in the complete report of the study (EMCEI, 1993). 2. The authors have come across machines operating with cycle times as long as 150 seconds, although this is uncommon.

3. Efficient Industrial Control Systems, Inc., 1994. Personal communication, Roger Fritz. 4. It should be noted that the distribution of values of T/H was asymmetric, unlike those of the other variables, opening to question the validity of including the variable.

Reference Energy Management Consulting and Equipment, Inc., 1993. Measured Performance of Variable Speed Drives on Injection Molding Hydraulic Pumps, Final Report, Report to New England Power Service Company, revised September 1993.