Scholarlink

<p>If there is insufficient process parameter information, highly subjective and difficult-to-quantify index weight allocation and conflicting multiple quality characteristics (MQCs) for metal injection molding (MIM), this study optimizes the metal shafts (MSs) of laptops using the multi-attributive ideal-real comparative analysis (MAIRCA) weighting method and a hybrid grey relational analysis-ideal solution similarity ranking method (GRA-TOPSIS). Analysis using a comprehensive evaluation index system for the MQCs (air traps, warpage, and shear stress) of the MSs is used to determine the combined weight values using entropy and criteria importance and intercriteria correlation (CRITIC). Grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) are used with Moldex3D software to verify the MQCs (air traps, warpage and shear stress) for the metal shafts using process parameters (injection temperature (A), injection speed (B), holding pressure (C), and mold temperature (D)) to determine the optimal combination (A<sub>3</sub>B<sub>2</sub>C<sub>1</sub>D<sub>2</sub> (A = 195&#xa0;°C, B = 70&#xa0;mm/s, C = 800 kgf/cm<sup>2</sup> and D = 100&#xa0;°C)). Meanwhile, green parts of MS were fabricated using the optimized process parameters, and the results of simulation and instrument testing demonstrated good performance in reducing air traps and warpage. Simulation results show that the optimized process parameters decrease air traps by 75.00%, warpage by 11.83% and shear stress by 25.70%. The ranking results for the hybrid GRA-TOPSIS method using different weights are consistent and discrimination is better than that for the GRA or TOPSIS methods.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Exploring the optimization of process parameters for multi-quality characteristics of metal shafts in metal injection molding using a mold flow analysis software and the MAIRCA-GRA-TOPSIS method

  • 期刊论文

  • 发表日期：

    2026年5月29日

查看全文
  • Ming-Chang Wu,
  • Tai-Yu Chiu,
  • Chuug-Chen Tsao

摘要

If there is insufficient process parameter information, highly subjective and difficult-to-quantify index weight allocation and conflicting multiple quality characteristics (MQCs) for metal injection molding (MIM), this study optimizes the metal shafts (MSs) of laptops using the multi-attributive ideal-real comparative analysis (MAIRCA) weighting method and a hybrid grey relational analysis-ideal solution similarity ranking method (GRA-TOPSIS). Analysis using a comprehensive evaluation index system for the MQCs (air traps, warpage, and shear stress) of the MSs is used to determine the combined weight values using entropy and criteria importance and intercriteria correlation (CRITIC). Grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) are used with Moldex3D software to verify the MQCs (air traps, warpage and shear stress) for the metal shafts using process parameters (injection temperature (A), injection speed (B), holding pressure (C), and mold temperature (D)) to determine the optimal combination (A3B2C1D2 (A = 195 °C, B = 70 mm/s, C = 800 kgf/cm2 and D = 100 °C)). Meanwhile, green parts of MS were fabricated using the optimized process parameters, and the results of simulation and instrument testing demonstrated good performance in reducing air traps and warpage. Simulation results show that the optimized process parameters decrease air traps by 75.00%, warpage by 11.83% and shear stress by 25.70%. The ranking results for the hybrid GRA-TOPSIS method using different weights are consistent and discrimination is better than that for the GRA or TOPSIS methods.