A virtual prototyping environment for a robust design of an injection moulding process

被引:7
作者
Berti, Guido [1 ]
Monti, Manuel [1 ]
机构
[1] Univ Padua, DTG, I-36100 Vicenza, Italy
关键词
Injection moulding process; Finite Element Method; Response Surface Methodology; Robust design; Stochastic simulations; OPTIMIZATION;
D O I
10.1016/j.compchemeng.2013.04.005
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper proposes a new approach that enables a robust optimisation of the injection moulding process, based on the integration of numerical simulations, Response Surface Methodology and stochastic simulations in a type of integrated environment known as a virtual prototyping environment (VPE). The principal aim of the proposed approach is to include in the numerical setup of injection moulding the effects of fluctuations of process parameters. To clarify the proposed methodology, the paper details its application to the injection moulding process for the production of an engine cover. The moulded part presents some critical tolerances on different dimensions because of sealing and assembly requirements and the application of the VPE makes it possible to perform a robust setup taking into account the process fluctuations. The numerical prediction was confirmed by real production measurements on small pre-production runs performed adopting the moulding window explored in the virtual setup. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:159 / 169
页数:11
相关论文
共 12 条
[1]   Identification of process disturbance using SPC/EPC and neural networks [J].
Chiu, CC ;
Shao, YJE ;
Lee, TS ;
Lee, KM .
JOURNAL OF INTELLIGENT MANUFACTURING, 2003, 14 (3-4) :379-388
[2]  
Erguo L., 2002, COMPUT CHEM ENG, V26, P1253
[3]   Integrating artificial intelligence into on-line statistical process control [J].
Guh, RS .
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2003, 19 (01) :1-20
[4]  
Kini S., 2005, ADV TECHN PLAST 2005, P107
[5]   Cylindrical tube optimization using response surface method based on stochastic process [J].
Lee, SH ;
Kim, HY ;
Oh, SI .
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2002, 130 :490-496
[6]  
Montgomery D., 2010, Design and Analysis of Experiments
[7]  
Montgomery D.C., 2009, Engineering statistics
[8]   Comparison of the warpage optimization in the plastic injection molding using ANOVA, neural network model and genetic algorithm [J].
Ozcelik, B ;
Erzurumlu, T .
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2006, 171 (03) :437-445
[9]   Combination of finite element and reliability methods in nonlinear fracture mechanics [J].
Pendola, M ;
Mohamed, A ;
Lemaire, M ;
Hornet, P .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2000, 70 (01) :15-27
[10]  
Rowlands H, 2000, QUAL RELIAB ENG INT, V16, P91, DOI 10.1002/(SICI)1099-1638(200003/04)16:2<91::AID-QRE307>3.0.CO