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.
|Title of host publication||International SAMPE Technical Conference|
|Publisher||Society for the Advancement of Material and Process Engineering|
|Number of pages||16|
|Publication status||Published - 26 May 2016|
|Event||SAMPE Long Beach 2016 Conference and Exhibition - Long Beach, United States|
Duration: 23 May 2016 → 26 May 2016
|Conference||SAMPE Long Beach 2016 Conference and Exhibition|
|Period||23/05/16 → 26/05/16|
Crowley, D. M., Elkington, M. P., Ward, C., & Potter, K. D. (2016). Hand lay-up of complex geometries-prediction, capture and feedback. In International SAMPE Technical Conference (Vol. 2016-January). Society for the Advancement of Material and Process Engineering.