Development of a manufacturability analysis system for reinforced plastics components.

Marquez Robledo, Miguel A. (2001) Development of a manufacturability analysis system for reinforced plastics components. PhD thesis, Middlesex University.

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Abstract

This thesis describes the research and development of a systematic and consistent methodology to perform manufacturability analysis of Reinforced Plastic Parts (RPP). The proposed methodology evaluates the part model in the early stages of the product development process considering the capabilities and constraints of available manufacturing processes, materials and tooling required in standard RPP production. Critical Manufacturing Part Features (CMPF) are identified and the relationship between the model's geometrical information, the expert's geometric reasoning, and the knowledge about the involved manufacturing processes are clarified and set together in an efficient feature-rule-based manufacturability analysis system. The prototype system named 'FEBAMAPP', combines solid modelling (SM), automatic feature recognition (AFR), object oriented programming (OOP), and a rule-based system (RBS) in order to assess the manufacturability of the proposed design. The novelty of this research is based in the use of a Face Vector (FVector) concept to transform geometrical and topological information of the solid model into a suitable input data to be used in the Neural Network Feature Recognition System. Further novelty arises from the fact that this is the first attempt to use neural networks in the recognition of 3-D features in hollow parts including the presence of fillets along the edges of the part. The manufacturability evaluation can be performed considering different combinations of materials along with different manufacturing processes giving the designer the opportunity of selecting an appropriate combination for any specific application. Promising results have been obtained during the test of the system, where 100 % recognition of trained features with 90% confidence has been achieved. Also, good results have been obtained in the recognition of non-trained features such as the Cross-Slot feature, which is recognised as a Slot feature. After automatic feature recognition, Manufacturability Analysis is focused on internal and external characteristics of the model's features, where potential manufacturing difficulties are identified and feedback in terms of design suggestions is then used to advise the design process and improve the overall manufacturability of the part. This manufacturability evaluation in terms of internal and external characteristics of the features has proved to be efficient in detecting detailed design errors that can be costly in further manufacturing stages in the product development process.

Item Type:Thesis (PhD)
Additional Information:

A thesis submitted to Middlesex University in partial fulfilment of the requirements for the degree of Doctor of Philosophy.

Research Areas:Masters and Doctorates > Theses
Middlesex University Schools and Centres > School of Science and Technology > Science & Technology
ID Code:6555
Deposited On:27 Sep 2010 13:46
Last Modified:20 Jul 2014 12:20

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