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Mold Better PET Preforms!
When it comes to injection molding PET preforms, defects that can’t easily be observed usually cause the biggest problems. For example excessive loss of intrinsic viscosity (IV) is a defect that is known to complicate the process of reheat stretch blow molding, reduce resistance to stress cracking, and lead to other bottle quality concerns. Historically molders couldn’t easily “see” IV, but that is no longer the case and a manufacturer at the top of their game should never find themselves in the position of unknowingly shipping preforms or bottles that don’t meet the specification.
The intrinsic viscosity measurement of PET correlates to molecular weight. Bottles having a high molecular weight or intrinsic viscosity are known to have better physical performance and barrier properties than bottles having a low molecular weight or intrinsic viscosity. This makes high IV resins ideally suited for the packaging of pressurized beverages such as carbonated soft drinks. Resins specified for these applications usually have a starting IV in the range of 0.83-0.86dL/g. Some loss of IV during melt processing should be expected and a widely accepted value for the minimum bottle IV is 0.80dL/g for a carbonated soft drink application.
Excessive IV loss that occurs during injection molding is usually attributed to improper drying or melt processing conditions. However, it can also result from the blending of lower molecular weight materials such as regrind, recycled PET, colorant, and other additives. Simply receiving virgin resin that is out of specification could also lower the resulting preform IV. Regardless of the source of excessive IV loss, it can easily go unnoticed on the production floor without the right tools and training. However, this doesn’t have to be the case.
With the proper training and instrumentation your injection technicians and quality team can be given the ability to predict preform IV in real-time for every machine cycle. The minimum requirement to gain this capability is usually a day of machine time followed by analytical testing. Once the data is compiled it can be used to set limits to trigger alarms on a molding machine or provide meaningful limits for statistical process control systems. Alternately the machine can be upgraded with a system to directly report the predicted preform IV. An example of the display of such a device is shown in this figure.