391
Views
18
CrossRef citations to date
0
Altmetric
Original Article

Experimental determination and control of prepreg tack for automated manufacture

, &
Pages 363-368 | Received 17 Jun 2010, Accepted 17 Jun 2010, Published online: 12 Nov 2013
 

Abstract

The automated tape laying (ATL) process has been examined and found to be sensitive to tack and stiffness properties of the prepreg material being laid. A comparison of existing aerospace and newly developed ATL prepreg tapes has revealed significant differences in tack response to temperature and feedrate. Examination of constituent resin rheology has found that tack, and the two observed failure modes, are somewhat dependent upon viscoelastic stiffness. Observation of temperature and feedrate response revealed a time–temperature superposition relationship. The Williams–Landel–Ferry equation was utilised to make predictions of the temperature response based on the feedrate response. Tack levels were stabilised over the feedrate range by making temperature adjustments. Results from the peel test, where mould conditions at lay-up were recreated, were found transferable to the ATL, where a suitable lay-up feedrate under ambient conditions was predicted.

This work was conducted as part of the AIRPOWER project which is focused on the development of materials and rapid production methods for large scale rotor blades for the wind energy industry. The authors would like to thank all the industrial partners, particularly Hexcel for prepreg materials, BAE systems for use of ATL equipment and Solent composites for mould supply. Cofunding of the project is provided by the UK Technology Strategy Board for which the consortium is grateful.

Notes

This paper is part of a special issue on Latest developments in research on composite materials

Log in via your institution

Log in to Taylor & Francis Online

There are no offers available at the current time.

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.