Hand lay-up of complex geometries-prediction, capture and feedback

Dennis M Crowley, Michael P Elkington, Carwyn Ward, Kevin D Potter

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

1 Citation (Scopus)
367 Downloads (Pure)


This paper presents a process improvement framework built on previous research activities at the University of Bristol. The work focusses on hand lay-up and seeks to reduce variability, improve productivity and increase manufacturability of future designs. The framework is based on a double-loop learning model which incorporates prediction, capture and feedback. The predictive method employed uses a kinematic drape model as part of an expert system. The expert is needed to translate the model outputs into a more realistic set of drape instructions. The lay-up is captured by video analysis and quality data captured using an on-line tool. This data is then fed back to the user to facilitate decision making.
Original languageEnglish
Title of host publicationInternational SAMPE Technical Conference
PublisherSociety for the Advancement of Material and Process Engineering
Number of pages16
ISBN (Print)9781934551233
Publication statusPublished - 26 May 2016
EventSAMPE Long Beach 2016 Conference and Exhibition - Long Beach, United States
Duration: 23 May 201626 May 2016


ConferenceSAMPE Long Beach 2016 Conference and Exhibition
Country/TerritoryUnited States
CityLong Beach


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