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Combining BPN and TM to build a prediction model of process parameters: a case study

In general, thermal expansion and contraction of PVC (polyvinyl chloride) can occur when the environmental temperature changes. Therefore, the process parameters of PVC plastic spiral pipes have to be changed often to prevent the production of defective products. Traditionally, experienced workers have been relied upon to adjust the process parameters to suit the changing external temperature. To replace the manual adjustments of the experienced workers, this study empirically collected data from a manufacturer of extruded PVC plastic spiral pipes, and used a combination of the back-propagation network and the Taguchi method to establish a parameter prediction model that can predict the extrusion process parameters necessary for the changing external temperature. With a higher than 99% prediction accuracy, the proposed model can assist manufacturers in automatically and accurately adjusting the PVC pulling (or rotating) speed of the haul unit during extrusion.