A process performance index and its application to optimization of the RTMprocess

Citation
Sl. Jiang et al., A process performance index and its application to optimization of the RTMprocess, POLYM COMP, 22(5), 2001, pp. 690-701
Citations number
12
Language
INGLESE
art.tipo
Article
Categorie Soggetti
Material Science & Engineering
Journal title
POLYMER COMPOSITES
ISSN journal
0272-8397 → ACNP
Volume
22
Issue
5
Year of publication
2001
Pages
690 - 701
Database
ISI
SICI code
0272-8397(200110)22:5<690:APPIAI>2.0.ZU;2-1
Abstract
Resin transfer molding (RTM) is a promising manufacturing process for high performance composite materials. However, the fact that RTM process design has traditionally been an expensive, time-consuming trial-and-error procedu re has prohibited its wide application base. This paper proposes a solution to that problem-a simulation-based optimum process design scheme for RTM. This scheme enables engineers to determine the optimum locations of injecti on gates and vents so that both process efficiency and high part quality ca n be ensured. Essential to this optimum process design scheme is a process performance index, which is defined with respect to the major factors influ encing RTM process efficiency and part quality. This index is then used as the objective function for the RTM process design optimization model. Gate and vent locations are the process design parameters to be optimized. All d ata is obtained by running an RTM simulation program, and the genetic algor ithm (GA) is employed to carry out the optimization procedure for the desig n parameters. It is found that constant pressure optimization will yield a process with a short flow path, whereas constant flow optimization will yie ld a process with smooth and vent-oriented flow pattern. Although there is no dry spot factor in the objective function, it is interesting to note tha t both constant pressure and constant flow optimization procedures result i n process designs with a minimum probability of dry spot formation. This st udy finds that, in general, constant flow optimization should be employed i f injection pressure is not a major concern; otherwise, constant pressure o ptimization should be used. Two case studies are presented to illustrate th e efficacy of this approach.