Polyplastics allows predicting voids in POM injection-molded products

Polyplastics has developed a technology that uses CAE analysis to predict the occurrence of voids in DURACON POM injection-molded products. Since this technology can predict the risk of voids forming before creating the mold, it could help reduce numbers of trial samples, shorten the development cycle, and cut down on energy usage.

There is a phenomenon in which hollow pockets form near the center of thick parts of injection-molded products, and these hollow pockets are called voids.

Parameters such as volume shrinkage that is produced as output from flow analyses had conventionally been used for void prediction, but the accuracy of this method has been problematic since the actual phenomenon cannot be recreated and for other such reasons.

Polyplastics' new technology uses CAE analysis to predict vacuum voids in DURACON POM injection-molded products.

As for analyzing the causes of defects in prototypes and products on the market, voids are now easy to discover due to the spread of non-destructive technologies for visualizing the interiors of solid objects such as X-ray computed tomography. Technologies related to controlling voids are now expected to dramatically improve.

The new technology is a new method that links flow analysis with structural analysis to predict the formation of voids according to strain arising inside molded products, taking into consideration mold shrinkage, elastic modulus, and distribution of pressure in the resin solidification process.

Since it can predict voids with high accuracy before work to create the mold begins, this technology promises to reduce the development cycle, cut down on product development costs, and reduce the consumption of energy needed for simulations.

The analysis results shown in the figures are examples obtained using this technology. The blue areas shown in the void prediction results generally match the red areas from actual test results, thus verifying that the predictions are sufficiently accurate. The company has also been testing this technology’s capabilities in various other shapes.