Abstract
This paper presents an improved monitoring system for the failure detection of engraving tool steel inserts during the injection molding cycle. This system uses acoustic emission PZT sensors mounted through acoustic waveguides on the engraving insert. We were thus able to clearly distinguish the defect through measured AE signals. Two engraving tool steel inserts were tested during the production of standard test specimens, each under the same processing conditions. By closely comparing the captured AE signals on both engraving inserts during the filling and packing stages, we were able to detect the presence of macro-cracks on one engraving insert. Gabor wavelet analysis was used for closer examination of the captured AE signals' peak amplitudes during the filling and packing stages. The obtained results revealed that such a system could be used successfully as an improved tool for monitoring the integrity of an injection molding process.
Highlights
Injection molding is one of the more commonly used processes in today’s plastic manufacturing industry
After the production of both test specimens, we cut their runners in order to minimize any warpage
After the 24 hours, measurements on both test specimens were carried out at ambient temperature by using the ATOS II SO 3D scanning system which has an accuracy of a few hundredths of a mm
Summary
Injection molding is one of the more commonly used processes in today’s plastic manufacturing industry. The injection stage and afterwards the packing stage start, where the clamp unit keeps the empty mold closed and the screw moves forward as a whole ram that forces the melt into the mold cavity. When the mold cavity is almost volumetrically filled, the screw is held in the forward position in order to maintain a holding pressure At this time the melt cools down and volumetrically shrinks. In the case when a stress is applied to the injection mold engraving insert, an active flaw releases acoustic energy as an elastic waveform from the source (e.g., macro-cracks) throughout the structure. This can be further detected, located, and characterized by the AE measurement system. A close examination of AE signals and their events are necessary because we want to know when a particular event took place
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