TY - JOUR
T1 - Multiresponse Parameter Optimization for the Composite Tape Winding Process Based on GRA and RSM
AU - Hong, Qi
AU - Shi, Yaoyao
N1 - Publisher Copyright:
© 2020 Qi Hong and Yaoyao Shi.
PY - 2020/7
Y1 - 2020/7
N2 - Composite tape winding is an important forming process of composite materials, which can ensure good performance of composite products. Selection and control of key process parameters in the winding process have a great influence on the properties of products, such as void content and residual stress of products. Through experimental analysis, the residual stress and void content of the composite products are not the minimum when the prepreg winding process is carried out by using the empirical process parameters. To solve this multiobjective optimization problem, experiments were conducted using the Box-Behnken design. The multiobjective optimization problem is converted to a single-objective problem using grey relational analysis (GRA). Principal component analysis (PCA) is used to quantify the relative contributions of residual stress and void content. Regression analysis of grey relational grade (GRG) based on the experimental data was used to develop a second-order GRG prediction model. The winding process parameters were optimized with response surface methodology (RSM), and the winding experiments were carried out with these parameters. The experimental results show that the best combination of process parameters yields the best GRG results with better void content and residual stress.
AB - Composite tape winding is an important forming process of composite materials, which can ensure good performance of composite products. Selection and control of key process parameters in the winding process have a great influence on the properties of products, such as void content and residual stress of products. Through experimental analysis, the residual stress and void content of the composite products are not the minimum when the prepreg winding process is carried out by using the empirical process parameters. To solve this multiobjective optimization problem, experiments were conducted using the Box-Behnken design. The multiobjective optimization problem is converted to a single-objective problem using grey relational analysis (GRA). Principal component analysis (PCA) is used to quantify the relative contributions of residual stress and void content. Regression analysis of grey relational grade (GRG) based on the experimental data was used to develop a second-order GRG prediction model. The winding process parameters were optimized with response surface methodology (RSM), and the winding experiments were carried out with these parameters. The experimental results show that the best combination of process parameters yields the best GRG results with better void content and residual stress.
UR - http://www.scopus.com/inward/record.url?scp=85090969478&partnerID=8YFLogxK
U2 - 10.1155/2020/2515014
DO - 10.1155/2020/2515014
M3 - 文章
AN - SCOPUS:85090969478
SN - 1024-123X
VL - 2020
JO - Mathematical Problems in Engineering
JF - Mathematical Problems in Engineering
M1 - 2515014
ER -