Knoll Julia, Heim Hans-Peter
Institute of Material Engineering, Polymer Engineering, University of Kassel, 34125 Kassel, Germany.
Polymers (Basel). 2023 Dec 22;16(1):54. doi: 10.3390/polym16010054.
The performance of an injection molding machine (IMM) influences the process and the quality of the parts manufactured. Despite increasing data collection capabilities, their machine-specific behavior has not been extensively studied. To close corresponding research gaps, the machine-specific behavior of two hydraulic IMMs of different sizes and one electric IMM were compared with each other as part of the investigations. Both the start-up behavior from the cold state and the behavior of the machine at different operating points were considered. To complement this, the influence of various material properties on the machine-specific behavior was investigated by processing an unreinforced and glass-fiber-reinforced polyamide. The results obtained provide crucial insights into machine-specific behavior, which may, for instance, account for disparities between computer fluid dynamic (CFD) simulations and experimental results. Furthermore, it is expected that the description of the machine-specific behavior can contribute to transfer knowledge when applying transfer learning algorithms. Looking ahead to future research, it is advised to create what is referred to as a "machine fingerprint", and this proposal is accompanied by some preliminary recommendations for its development.
注塑机（IMM）的性能会影响生产过程以及所制造零件的质量。尽管数据收集能力不断提高，但它们的特定机器行为尚未得到广泛研究。为了填补相应的研究空白，作为调查的一部分，对两台不同尺寸的液压注塑机和一台电动注塑机的特定机器行为进行了相互比较。研究考虑了从冷态开始的启动行为以及机器在不同运行点的行为。作为补充，通过加工未增强和玻璃纤维增强的聚酰胺，研究了各种材料特性对特定机器行为的影响。所获得的结果为特定机器行为提供了关键见解，例如，这可能解释了计算机流体动力学（CFD）模拟与实验结果之间的差异。此外，预计对特定机器行为的描述在应用迁移学习算法时有助于知识转移。展望未来的研究，建议创建所谓的“机器指纹”，并为此提出了一些初步的开发建议。
