Part 2: Moving Beyond the Relative Viscosity Curve — New Method to Find Optimum Plastic Flow Rates
Explore the use of the injection unit velocity capability, which determines a machine’s injection speed linearity to find optimum flow rates, and proposes a second method.
In our previous article, we focused on the use of the viscosity curve — at times referred to as relative viscosity, effective viscosity or an in-mold rheology curve — to determine the optimum plastic flow rates.
While this method is simple and widely accepted, it doesn’t adequately address the overall impact on processing, and the possibility that specifically selecting one plastic flow rate can be optimized beyond the relative or effective viscosity curve. Furthermore, its primary premise is based on using the shape of the curve while, at times, applying extremely low and unrealistic plastic flow rates and equations that aren’t applicable to or corresponding with a plastic’s apparent viscosity.
In this article we will explore the use of another common scientific injection molding experiment, the injection unit velocity capability study, which determines a machine’s injection speed linearity, and propose a second method.
Injection Unit Velocity Capability or Injection Speed Linearity — Method 1
This methodology is considered the benchmark that’s taught and used throughout the industry. The experiment is typically conducted as a machine benchmarking exercise when comparing machines for purchase, undertaking in-plant assessments, performing troubleshooting or simply determining the linear response of the injection unit over its available plastic flow rates. One limitation of this experiment includes small shot sizes, which do not allow for proper acceleration and stabilization of the injection speed.
In this study, the same eight-cavity cold runner mold referenced in the prior article is utilized. Experimental results are illustrated in Table 1, demonstrating that as plastic flow rate setpoints increase, the machine’s ability to achieve the programmed setpoint decreases. This phenomenon can be attributed to the limitations in instantaneous acceleration: As the target plastic flow rate increases, the time for the machine to accelerate and stabilize to the setpoint also increases.
As plastic flow rate setpoints increase, the machine’s ability to achieve the programmed setpoint decreases.
Table 2 displays the plastic flow rate setpoints and actual data generated between setpoints of 0.25 and 11.76 in/sec. over a function of time. Noteworthy is that the acceleration rate is consistent throughout each experiment and is ideal as it indicates that the machine’s acceleration remains consistent across all setpoints. It has not been adjusted to favor higher or lower plastic flow rates, which can occur with some machines.
To generate the velocity capability curve, the actual machine fill time is noted, and the expected fill time, average plastic flow rate and percentage of the plastic flow rates are calculated and displayed in Table 1. Typically, a percentage of the plastic flow rate that is greater than 80% is considered capable and as such, all plastic flow rates for this experiment would be deemed capable and acceptable. For example, a plastic flow rate setpoint of 10 in/sec. produced an average plastic flow rate of 8.81 in/sec. which is 88.1% of the setpoint.
The plastic flow rate setpoints and actual data generated between setpoints of 0.25 and 11.76 in/sec. over a function of time show a consistent acceleration rate.
While this seems reasonable, I would consider this statement to be misleading. Since most processors and technicians have a spreadsheet to input data, I have seen this done without truly considering what the data represents. Without viewing the actual curves, we are making a broad assumption of capability with perhaps erroneous determinations.
Consider the following hypothetical graph of plastic flow rate as a function of time in Figure 1. After acceleration to the setpoint, noting that Area 1 equals Area 2, the actual plastic flow rates are precisely over and under the setpoint for the same amount of time. Without observing the graph and simply entering the data into the spreadsheet, we would calculate well over 95% of plastic flow rate at setpoint. However, nothing could be further from the truth. Without properly viewing the outputs on the graph, you would erroneously consider this as an acceptable plastic flow rate.
FIG 1: After acceleration to the setpoint, the actual plastic flow rates are precisely over and under the setpoint for the same amount of time.
Consider the additional hypothetical graph in Figure 2. Upon reaching the setpoint, the plastic flow rate is unstable and would be considered a decreasing oscillating waveform throughout the entire machine fill time. This is indicative of an injection unit that may need maintenance or perhaps recalibration.
FIG 2: Upon reaching the setpoint, the plastic flow rate is unstable and would be considered a decreasing oscillating waveform throughout the entire machine fill time.
Consider Figure 3 with a similar decreasing oscillating waveform but which stabilizes during the machine fill time. Again, in both situations, without physically observing the data, one would not suspect this plastic flow rate to be incapable and unacceptable.
FIG 3 shows a similar decreasing oscillating waveform but one that stabilizes during the machine fill time.
Injection Unit Velocity Capability or Injection Speed Linearity – Method 2
To capture and document incapable plastic flow rates as noted in Figures 1-3, I have developed a second method that I have used and taught since 2007.
This method captures the actual amount of the filling time that the plastic flow rate is at setpoint and does not calculate an average plastic flow rate as done in method one. Evaluating the plastic flow rates from Figures 2 and 3, we calculate the percentage of the machine fill time in which the plastic flow rate has stabilized and is at the desired setpoint. From this method we can see that at a plastic flow rate of 0.25 to 6.0 in/sec. (see Table 2), we become stable at 80% or greater of the machine fill time versus method one in which all plastic flow rates are deemed acceptable.
The proposed second method forces you to observe and obtain actual data from the plastic flow rate curves and thereby adds another dimension in determining capable plastic flow rates.
Please note that the time to stabilize is somewhat subjective, based on the observer and, in this case, stabilization was considered only when the actual and programmed plastic flow rate were completely stable. For example, at 10 in/sec. the plastic flow rate initially exceeds the setpoint; then is under the setpoint slightly before it finally stabilizes at approximately 0.12 in/ sec. However, you could establish a tolerance of ±0.10 or 0.15 in/sec., which would increase the capability at higher plastic flow rates. Noteworthy, is that this data assumes that after stabilization, the remainder of the fill time is at the desired plastic flow rate, however, the machine is actually decreasing the plastic flow rate in anticipation of the velocity to pressure transfer (VPT). The data is not corrected for the decrease in plastic flow rate.
In closing, we reviewed the industry standard of determining a machine’s velocity capability and further proposed a second method in which the capability is defined as the time the actual plastic flow rate has stabilized and is at the programmed plastic flow rate for 80% or greater of the actual machine fill time. This second method forces you to observe and obtain actual data from the plastic flow rate curves and thereby adds another dimension in determining capable plastic flow rates.
While you may choose to use one or both methods, the key point is that molders should physically note and observe the actual plastic flow rate curve, generating additional insight and information to make the best-informed decision regarding the optimum plastic flow rate or ranges for an injection molding process.
In the next article, we will compare the results of the velocity capability study and apply them to multiple machine sizes, as well as discuss the effect that the plastic flow rate may have on the balance of fill for a multicavity, cold runner mold.
ABOUT THE AUTHOR: Umberto Catignani is president of Orbital Plastics Consulting Inc., a consulting firm that has more than 125 years of combined experience in scientific injection molding, training, material selection, part and mold design review, in-mold instrumentation, project management and equipment selection. Catignani is a past president of the Southern Section of the Society of Plastics Engineers (SPE) and has more than 30 years of hands-on injection molding experience. He has certified and trained hundreds of plastic professionals and served as an expert witness. Past employers include IBM, General Motors, Delphi Automotive and Husky Injection Molding Systems. Catignani earned a master’s degree in Polymer Engineering from The University of Akron and a bachelor’s degree in Materials Engineering from the University of Cincinnati. Contact: 404-849-6714; umberto@orbitalplastics.com.