design & molding

Improved Cooling Time Predictions

By Chris Brown, National Physical Laboratory, United Kingdom

Good heat transfer is at the core of successful polymer processing. The accurate prediction of heat transfer allows manufacturers to optimize both cycle time and product quality.

There are a number of parameters involved when calculating heat transfer, such as specific heat, latent heat of crystallization, thermal conductivity, and heat transfer coefficient. The parameter that is the most critical in polymer processing is normally thermal conductivity.

The National Physical Laboratory (NPL), the United Kingdom's national measurement and standards laboratory, conducted a study into the measurement of thermal conductivity of polymer melts and its subsequent effect on production. The report concluded that accurately measuring thermal conductivity has benefits for processors by allowing more reliable forecasts of the cooling time for a product, thus enabling cycle times to be optimized. Also, by using the correct values for thermal conductivity, hot spots and burn marks, which lead to poor quality molded parts, can be avoided.

Temperature, pressure, and amount of filler are the main factors affecting the thermal conductivity of polymer melts. Thermal conductivity values can vary by as much as 50 percent from room temperature to typical processing temperatures. The figure below shows the effect of an error of just 20 percent in thermal conductivity on cooling time prediction for a hubcap. A variation in cooling time prediction is seen from 69 seconds to less than 40 seconds. This is a good illustration of the need for high quality, thermal conductivity data.

Cooling time distribution for standard thermal conductivity at 60Mpa (left) and when thermal conductivity is decreased by 20% at 60Mpa (right). Lower thermal conductivity means the part will take longer to cool. Accurate thermal conductivity data is critical to predicting cooling time distributions successfully.

Earlier versions of Moldflow allowed only single values of thermal conductivity and specific heat to be used, however, all that has now changed since the release of Moldflow Plastics Insight^TM (MPI^®) version 3.0 and subsequent versions. The current version of MPI can handle tabulated thermal conductivity and specific heat data, taking into account the effects of temperature and pressure on these parameters. Such information is expected to become readily available from research centers such as NPL, leading the way to even more accurate predictions of cooling times and reducing further the probability of degradation during molding.

For more information about NPL, contact Chris Brown at Tel +44 (0) 208 943 6769 or Email chris.brown@npl.co.uk or visit their Web site at www.npl.co.uk/npl/cmmt/polyproc