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A framework for formalizing science based composites manufacturing practice

University of British Columbia

Advanced composites are materials growing in importance. In recent years, all major aerospace original equipment manufacturers (OEMs) have invested significantly in this technology, and its use in automotive, alternative energy and industrial applications is rapidly growing. Increases in product size and production scaling, given radically larger and more complex structures and the sheer volume of composites manufacturing, are leading to challenging problems concerning manufacturing risk, such as increasing development time frames and program costs. The use of manufacturing science to address these problems has always been a rational and promising strategy with most research efforts focusing on automation to improve production efficiencies, the development of multiphysics based models exercised in manufacturing simulation software, and the promise of production ‘big data’ analytics given improvements in sensor technologies and machine based learning algorithms. However, it is no longer sufficient to keep adding to this science base without explicitly addressing how manufacturing practice should be changed. In this thesis, qualitative research analysis of two industrial small and medium sized enterprises (SMEs) based in Western Canada is first performed to investigate the use of the composites manufacturing science base to manage technological and market uncertainty, and how the needs and receptor capabilities of OEMs and SMEs differ. Next, a manufacturing outcomes taxonomy explicitly linking the science–technology–practice levels of activity and a hierarchical knowledge model (Equipment–Tool–Part–Material factory ontology) that defines a common nomenclature for organizing composites manufacturing domain knowledge are introduced. A series of high-level manufacturing scenarios are presented to demonstrate this developed framework. Finally, case studies based on the thermal analysis of thick thermoset composites data sets using manufacturing simulation are presented. These case studies represent a starting point for how science based approaches can be used to directly support manufacturing decisions at all stages of the development design cycle. This work represents efforts to introduce a new translational research strategy aimed at both the composites manufacturing research community and the composites industry. Its focus is to encourage the systematic use of composites manufacturing science to transform manufacturing practice, and to support the effective management of increasing manufacturing risk.

Text

2018-10-15

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/67567

Materials Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/