Evaluation of geometrical complexity of products based on the analysis of triangulated models

The results of study evaluation possibilities of geometric complexity of industrial products are presented in this article by analyzing of functional dependence of number of triangular faces on triangulation parameters. As the main parameter of the triangulation was considered maximum size of edges. The dependence study was carried out for basic geometric bodies, which revealed the general regression equation. Test of the regression equation on models of industrial products has confirmed put forward a scientific hypothesis on the evaluation possibility of geometric complexity of industrial products based on the analysis of this functional dependence

IMECE2002-DE-34419 PURSUING MECHANICAL PART FEATURE RECOGNITION THROUGH THE ISOLATION OF 3D FEATURES IN ORGANIC SHAPES

ABSTRACT The successful extraction of 3D features in mechanical parts has always been a challenging task and has yielded mixed results. Extracting features from organic shapes however is even more difficult. This is due to the fact that they are defined by both gradual and abrupt changes in surface curvature. The term curvature is explained in detail in section 4. Learning how to recognize organic shapes may give insights into better ways of performing feature recognition on mechanical parts. Determining the exact values of curvature, based on the underlying parameters can prove to be quite difficult. Curvature can be a good tool to identify features as most of the features are areas of slowly changing curvature bounded by sudden changes in curvature. The benefits of developing a generic algorithm that picks out curvature, and hence the organic features, are quite huge. This paper explains one approach taken to accomplish this task. This paper studies characteristics of the watershed algorith

Transform-based surface analysis and representation for CAD models

In most Computer-Aided Design (CAD) systems, the topological and geometrical information in a CAD model is usually represented by the edge-based data structure. With the emergence of concurrent engineering, such issues as product design, manufacturing, and process planning are considered simultaneously at the design stage. The need for the development of high-level models for completely documenting the geometry of a product and supporting manufacturing applications, such as automating the verification of a design for manufacturing (DIM) rules and generating process plans, becomes apparent;This dissertation has addressed the development of a generalized framework for high-level geometric representations of CAD models and form features to automate algorithmic search and retrieval of manufacturing information;A new wavelet-based ranking algorithm is developed to generate surface-based representations as input for the extraction of form features with non-planar surfaces in CAD models. The objective of using a wavelet-based shape analysis approach is to overcome the main limitation of the alternative feature extraction approaches, namely their restriction to planar surfaces or simple curved surfaces;A transform-invariant coding system for CAD models by multi-scale wavelet representations is also presented. The coding procedure is based on both the internal regions and external contours of topology entities---faces

Development of a manufacturability analysis system for reinforced plastics components.

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