期刊文献+

基于层次分析和灰色关联分析的注塑工艺多目标优化 被引量:11

Multi-objective Optimization of Injection Molding Process Based on AHP and GRA
下载PDF
导出
摘要 针对制品的翘曲、收缩、缩痕等多个质量指标要求,提出层次分析法和灰色关联分析法相结合的注射成型工艺优化方法。运用层次分析法,对3个质量指标进行综合评判,得到各自的权重。通过田口正交试验设计和Moldflow成型模拟,得到了各质量指标的预测值,计算试验序列的各质量指标的灰色关联系数,进而通过层次分析法(AHP)和灰色关联分析(GRA)综合评价模型,得出各试验序列的灰色关联度,并进行均值分析。结果表明,二段保压压力对综合的质量指标影响最显著,注射时间次之;最优的成型工艺参数是注射时间为1.2s、一段保压120 MPa、二段保压120 MPa、三段保压80 MPa;手机壳体实例验证了方法的有效性。 A multi-objective optimization method was proposed through the combination of analytic hierarchy process (AHP) and grey relation analysis (GRA) applying to multiple quality indexes, such as warp, volume shrinkage ratio, and sink index. The normalized weighting value of three quality index was obtained by means of analytic hierarchy process. Injection molding process was simulated by using Moldflow and orthogonal experiment design, and the predicted value of each quality index was obtained. The grey relational coefficient of experiment sequence and each quality index was calculated, and then the grey relational grade was obtained by means of a comprehensive evaluation model which combined the analytic hierarchy process (AHP) with gray relational analysis (GRA) methods, the analysis of means was executed afterwards. Holding pressure of second stage was best significantly effective on the comprehensive quality index, followed by injection time. The optimal process parameters combination of the injection molding was injection time(1.2 s), holding pressure of first stage (120 MPa), holding pressure of second stage (t20 MPa), holding pressure of third stage(80 MPa). The feasibility of the proposed method was demonstrated by the project of mobile phone shell.
出处 《中国塑料》 CAS CSCD 北大核心 2015年第7期80-85,共6页 China Plastics
关键词 注射成型 层次分析法 灰色关联分析 injection molding analYtic hierarchy process gray relational analysis
  • 相关文献

参考文献8

  • 1程锦,谭建荣,余加红.基于TOPSIS的注塑工艺参数多目标稳健优化设计[J].机械工程学报,2011,47(6):27-32. 被引量:24
  • 2Shen Changyu, Wang Lixia, Li Qian. Optimization of In- jection Molding Process Parameters Using Combination of Artificial Neural Network and Genetic Algorithm Method [J]. Journal of Materials Processing Technology, 2007, 183(2/3) : 412-418. 被引量:1
  • 3Mehat Nik Mizamzul, Kamaruddin Shahrul. Multi-Re- sponse Optimization of Injection Moulding Processing Pa- rameters Using the Taguchi Method[J]. Polymer-Plastics Technology and Engineering, 2011. 50(15): 1519-1526. 被引量:1
  • 4Barghash Mahmoud A, Alkaabneh Faisal Alkhannan. Shrinkage and Warpage Detailed Analysis and Optimiza- tion for the Injection Molding Process Using Multistage Experimental Design[J]. Quality Engineering, 2014. 26 (3) : 319-334. 被引量:1
  • 5孙东川,杨立洪,钟拥军编著..管理的数量方法[M].北京:清华大学出版社,2005:390.
  • 6丁丽宏.基于改进的灰关联分析和层次分析法的边坡稳定性研究[J].岩土力学,2011,32(11):3437-3441. 被引量:87
  • 7Tzeng Chorng Jyh, Lin Yu Hsin, Yang, Yung Kuang Jeng, et al. Optimization of Turning Operations with Multiple Performance Characteristics Using the Taguchi Method and Grey Relational Analysis[J]. Journal of Materials Processing Technology, 2009. 209 ( 6 ) 2753-2759. 被引量:1
  • 8Yung-kuang yang, Jie-ren Shie, Rong-tai Yang, et al. Op- timization of Injection-Molding Process for Mechanical and Tribological Properties of Short Glass Fiber and Polytet- rafluoroethyiene Reinforced Polycarhonate Composites with Grey Relational Analysis: A Case Study[J]. Poly- rner-Plastics Technology and Engineering, 2006. 45 (7) : 769-777. 被引量:1

二级参考文献16

共引文献109

同被引文献94

引证文献11

二级引证文献79

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部