Evaluation of polymer injection molded parts via density‐based magnetic levitation

Abstract

The quality of polymer injection molded parts is definitely related to the molding process. Polymer injection molded parts with different properties differ in density and internal density distribution. This paper proposes a novel evaluation method for polymer injection molded parts through magnetic levitation (MagLev) to detect the differences among products by means of their densities and density distributions. Three cases of polycarbonate lenses are employed as samples in the experiments: lenses produced at different processing parameters, lenses obtained from different cavities in one mold, and those with different interior defects. The lenses obtained at different processing parameters differ in density, and those with different defects exhibit different behaviors during the levitation. The MagLev testing method shows its capability in distinguishing minute differences among the densities (< 0.0005 g cm−3) that even the subtle distinctions among the lenses formed from different cavities in one mold can be detected. Further analysis demonstrates that minute changes in thickness (2.5 μm) can also be detected. The theoretical analysis and experimental results indicate that the MagLev testing method is applicable to the evaluation of polymer injection molded parts. Moreover, the method affords advantages, such as high accuracy, high sensitivity, and convenience.

Advanced density-based methods for the characterization of materials, binding events, and kinetics

“…4). 111,112 Lenses fabricated with different molding parameters displayed different densities and could hence be distinguished by their different levitation heights. 112 The major advantages of using MagLev for quality control are that this method is simple, inexpensive and non-destructive.…”

Intelligent Injection Molding on Sensing, Optimization, and Control

“…Recently, our research group further analyzed the correlation between the position of the defects and the levitation posture of the sample [94,95]. is method is further applied in the evaluation of washers [82] and injection molded lens [96] and subtle differences could be detected (cf. Figure 9(c)).…”

Intelligent injection molding: Parameters self‐learning optimization using iterative gradient‐approximation adaptive method

“…Unsuitable parameters can lead to defects on the products. 4 Therefore, it is of great importance to determine the optimal settings of the process parameters to guarantee the product quality.…”

“…As stated by Dang et al, 3 the process parameters are the important factors affecting product quality, productivity, and energy consumption. Unsuitable parameters can lead to defects on the products 4 . Therefore, it is of great importance to determine the optimal settings of the process parameters to guarantee the product quality.…”