08-16-2017, 10:29 PM
Abstract
In foam extrusion, material density is the most significant factor affecting the product cost and therefore the profitability of the manufacturing process. A reduction in the density of extruded parts reduces the raw material cost and therefore increases its profitability. On the other hand, a reduction in foam density degrades the mechanical properties and geometrical accuracy of extruded parts. Therefore, a critical balance has always to be achieved in order to minimize the material cost while maintaining adequate strength and accuracy. Density of foam PVC can be controlled by varying the type and amount of compound additives, processing parameters, or both. Ultrasound waves propagating at a nominal frequency of 2.25 MHz were pulsed through polymer melt flowing inside a slightly modified extrusion die to accommodate the ultrasound transducer. Acoustic properties of the melt such as, acoustic impedance and attenuation coefficient were measured and successfully correlated to the density of the foamed parts using statistical methods and artificial neural networks (ANN). This techniques can also be applied to monitor the characteristics of polymer compounds on-line during extrusion process, thus improving quality and reducing cost of making plastic parts.
In foam extrusion, material density is the most significant factor affecting the product cost and therefore the profitability of the manufacturing process. A reduction in the density of extruded parts reduces the raw material cost and therefore increases its profitability. On the other hand, a reduction in foam density degrades the mechanical properties and geometrical accuracy of extruded parts. Therefore, a critical balance has always to be achieved in order to minimize the material cost while maintaining adequate strength and accuracy. Density of foam PVC can be controlled by varying the type and amount of compound additives, processing parameters, or both. Ultrasound waves propagating at a nominal frequency of 2.25 MHz were pulsed through polymer melt flowing inside a slightly modified extrusion die to accommodate the ultrasound transducer. Acoustic properties of the melt such as, acoustic impedance and attenuation coefficient were measured and successfully correlated to the density of the foamed parts using statistical methods and artificial neural networks (ANN). This techniques can also be applied to monitor the characteristics of polymer compounds on-line during extrusion process, thus improving quality and reducing cost of making plastic parts.