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Out-of-Mold Sensor-Based Process Parameter Optimization and Adaptive Process Quality Control for Hot Runner Thin-Walled Injection-Molded Parts.
Cheng, Feng-Jung; Chang, Chen-Hsiang; Wen, Chien-Hung; Hwang, Sheng-Jye; Peng, Hsin-Shu; Chu, Hsiao-Yeh.
Afiliación
  • Cheng FJ; Department of Mechanical Engineering, National Cheng Kung University, Tainan 701401, Taiwan.
  • Chang CH; Department of Mechanical Engineering, National Cheng Kung University, Tainan 701401, Taiwan.
  • Wen CH; Department of Mechanical Engineering, National Cheng Kung University, Tainan 701401, Taiwan.
  • Hwang SJ; Department of Mechanical Engineering, National Cheng Kung University, Tainan 701401, Taiwan.
  • Peng HS; Department of Mechanical and Computer-Aided Engineering, Feng Chia University, Taichung 407102, Taiwan.
  • Chu HY; Department of Mechanical Engineering, Kun Shan University, Tainan 71070, Taiwan.
Polymers (Basel) ; 16(8)2024 Apr 11.
Article en En | MEDLINE | ID: mdl-38674978
ABSTRACT
Injection molding is a highly nonlinear procedure that is easily influenced by various external factors, thereby affecting the stability of the product's quality. High-speed injection molding is required for production due to the rapid cooling characteristics of thin-walled parts, leading to increased manufacturing complexity. Consequently, establishing appropriate process parameters for maintaining quality stability in long-term production is challenging. This study selected a hot runner mold with a thin wall fitted with two external sensors, a nozzle pressure sensor and a tie-bar strain gauge, to collect data regarding the nozzle peak pressure, the timing of peak pressure, the viscosity index, and the clamping force difference value. The product weight was defined as the quality indicator, and a standardized parameter optimization process was constructed, including injection speed, V/P switchover point, packing, and clamping force. Finally, the optimized process parameters were applied to the adaptive process control experiments using the developed control system operated within the micro-controller unit (MCU). The results revealed that the control system effectively stabilized the product weight variation and standard deviation of 0.677% and 0.0178 g, respectively.
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Polymers (Basel) Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Polymers (Basel) Año: 2024 Tipo del documento: Article