A process performance index and its application to optimization of the rtm process
Resin transfer molding (RTM) is a promising manufacturing process for hig formance composite materials. However, the fact that RTM process design has traditionally been an expensive, time‐consuming trial‐and‐error procedure has p ited its wide application base. This paper proposes a solution to that...
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Veröffentlicht in: | Polymer composites 2001-10, Vol.22 (5), p.690-701 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Resin transfer molding (RTM) is a promising manufacturing process for hig formance composite materials. However, the fact that RTM process design has traditionally been an expensive, time‐consuming trial‐and‐error procedure has p ited its wide application base. This paper proposes a solution to that problem—a simulation‐based optimum process design scheme for RTM. This scheme ei engineers to determine the optimum locations of injection gates and vents so both process efficiency and high part quality can be ensured. Essential to this mum process design scheme is a process performance index, which is defined respect to the major factors influencing 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 optimized. All data is obtained by running an RTM simulation program, and th netic algorithm (GA) is employed to carry out the optimization procedure for design parameters. It is found that constant pressure optimization will yi process with a short flow path, whereas constant flow optimization will yield process with smooth and vent‐oriented flow pattern. Although there is no dry factor in the objective function, it is interesting to note that both constant pres and constant flow optimization procedures result in process designs with a mil mum probability of dry spot formation. This study finds that, in general, cons flow optimization should be employed if injection pressure is not a major cone otherwise, constant pressure optimization should be used. Two case studies presented to illustrate the efficacy of this approach. |
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ISSN: | 0272-8397 1548-0569 |
DOI: | 10.1002/pc.10571 |