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The aim of the work was to assess the influence of the iQ Weight Control System on the weight, and dimensional stability of injection-molded samples. By analyzing their effectiveness, this study seeks to contribute to the growing body of knowledge on the application of machine learning-based control systems in enhancing precision manufacturing practices. The selected materials for the tests were polyamide reinforced with glass fiber and regrind from post-production waste. Injection molding tests were performed with the self-adjusting system both activated and deactivated. These tests were conducted on both original materials and those containing 50% regrind.

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Application of Intelligent Methods of Controlling the Process in Thermoplastics Manufacturing

  • 会议论文

  • 发表日期：

    2025年

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  • Tomasz Olszewski,
  • Danuta Matykiewicz

摘要

The aim of the work was to assess the influence of the iQ Weight Control System on the weight, and dimensional stability of injection-molded samples. By analyzing their effectiveness, this study seeks to contribute to the growing body of knowledge on the application of machine learning-based control systems in enhancing precision manufacturing practices. The selected materials for the tests were polyamide reinforced with glass fiber and regrind from post-production waste. Injection molding tests were performed with the self-adjusting system both activated and deactivated. These tests were conducted on both original materials and those containing 50% regrind.