The prediction of process-induced deformation in a thermoplastic composite in support of manufacturing simulation

Peidong Han*, Joseph Butterfield, Saul Buchanan, Rauri McCool, Zhenyu Jiang, Mark Price, Adrian Murphy

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Digital manufacturing techniques can simulate complex assembly sequences using computer-aided design-based, as-designed' part forms, and their utility has been proven across several manufacturing sectors including the ship building, automotive and aerospace industries. However, the reality of working with actual parts and composite components, in particular, is that geometric variability arising from part forming or processing conditions can cause problems during assembly as the as-manufactured' form differs from the geometry used for any simulated build validation. In this work, a simulation strategy is presented for the study of the process-induced deformation behaviour of a 90 degrees, V-shaped angle. Test samples were thermoformed using pre-consolidated carbon fibre-reinforced polyphenylene sulphide, and the processing conditions were re-created in a virtual environment using the finite element method to determine finished component angles. A procedure was then developed for transferring predicted part forms from the finite element outputs to a digital manufacturing platform for the purpose of virtual assembly validation using more realistic part geometry. Ultimately, the outcomes from this work can be used to inform process condition choices, material configuration and tool design, so that the dimensional gap between as-designed' and as-manufactured' part forms can be reduced in the virtual environment.

Original languageEnglish
Pages (from-to)1417-1429
Number of pages13
JournalProceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
Issue number10
Publication statusPublished - Oct 2013


  • Thermoforming
  • composite part form prediction
  • digital manufacturing
  • simulation


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