12 research outputs found

    Extraction of generative processes from B-Rep shapes and application to idealization transformations

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    International audienceA construction tree is a set of shape generation processes commonly produced with CAD modelers during a design process of B-Rep objects. However, a construction tree does not bring all the desired properties in many configurations: dimension modifications, idealization processes, etc. Generating a non trivial set of generative processes, possibly forming a construction graph, can significantly improve the adequacy of some of these generative processes to meet user's application needs. This paper proposes to extract generative processes from a given B-rep shape as a high-level shape description. To evaluate the usefulness of this description, finite element analyses (FEA) and particularly idealizations are the applications selected to evaluate the adequacy of additive generative processes. Non trivial construction trees containing generic extrusion and revolution primitives behave like well established CSG trees. Advantageously, the proposed approach is primitive-based, which ensures that any generative process of the construction graph does preserve the realizability of the corresponding volume. In the context of FEA, connections between idealized primitives of a construction graph can be efficiently performed using their interfaces. Consequently, generative processes of a construction graph become a high-level object structure that can be tailored to idealizations of primitives and robust connections between them

    Automated feature recognition system for supporting engineering activities downstream of conceptual design.

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    Transfer of information between CAD models and downstream manufacturing process planning software typically involves redundant user interaction. Many existing tools are process-centric and unsuited for selection of a "best process" in the context of existing concurrent engineering design tools. A computer based Feature-Recognition (FR) process is developed to extract critical manufacturing features from engineering product CAD models. FR technology is used for automating the extraction of data from CAD product models and uses wire-frame geometry extracted from an IGES neutral file format. Existing hint-based feature recognition techniques have been extended to encompass a broader range of manufacturing domains than typical in the literature, by utilizing a combination of algorithms, each successful at a limited range of features. Use of wire-frame models simplifies product geometry and has the potential to support rapid manufacturing shape evaluation at the conceptual design stage. Native CAD files are converted to IGES neutral files to provide geometry data marshalling to remove variations in user modelling practice, and to provide a consistent starting point for FR operations. Wire-frame models are investigated to reduce computer resources compared to surface and solid models, and provide a means to recover intellectual property in terms of manufacturing design intent from legacy and contemporary product models. Geometric ambiguity in regard to what is ?solid? and what is not has plagued wire-frame FR development in the past. A new application of crossing number theory (CNT) has been developed to solve the wire-frame ambiguity problem for a range of test parts. The CNT approach works satisfactorily for products where all faces of the product can be recovered and is tested using a variety of mechanical engineering parts. Platform independent tools like Extensible Mark-up Language are used to capture data from the FR application and provide a means to separate FR and decision support applications. Separate applications are composed of reusable software modules that may be combined as required. Combining rule-based and case-based reasoning provides decision support to the manufacturing application as a means of rejecting unsuitable processes on functional and economic grounds while retaining verifiable decision pathways to satisfy industry regulators

    Automated Parting Methodologies for Injection Moulds

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    Ph.DDOCTOR OF PHILOSOPH

    Análisis de fabricabilidad de piezas conformadas por moldeo por inyección de polvos

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    Una de las primeras etapas en el Ciclo de Desarrollo Producto-Proceso es el Diseño Conceptual del producto. El Diseño Conceptual define el concepto físico del producto, estableciendo los principios para el ejercicio de su función e identificando sus geometrías características. Un diseño puede ser difícil de fabricar, originando defectos y parámetros inadecuados durante el proceso de fabricación que dan lugar a la necesidad de cambios en ingenieria que, a su vez, aumentan el tiempo de puesta en el mercado. Disponer de una herramienta de asesoramiento automático capaz de mostrar la influencia del diseño en la fabricabilidad de la pieza en un tiempo reducido resulta esencial en el Diseño Conceptual. Con una metodología de este tipo, se ofrece la posibilidad de estimar la calidad final de la pieza y su funcionalidad incluso antes de que se proceda con su fabricación. Una herramienta de asesoramiento que relaciona el diseño del producto con su fabricabilidad debe estar basada en el conocimiento de los procesos que rigen las etapas del proceso de fabricación. Relacionar la geometría del producto con su fabricabilidad utilizando dicho conocimiento permite estimar la viabilidad del producto antes de ser fabricado, mejorando el diseño del producto y evitando los costosos cambios de ingeniería que son necesarios cuando se detectan problemas en la fase de producción. En los procesos de conformado por inyección unos de los aspectos más importantes de la fabricabilidad son la posibilidad de moldeo/desmoldeo, un llenado completo y uniforme y una distribución de espesores uniforme o con cambios suaves. Todos estos aspectos están claramente relacionados con la geometría de la pieza. En esta Tesis Doctoral se detallan las bases para el desarrollo de una herramienta capaz de estimar de forma automática e integrada la fabricabilidad de una pieza conformada por el Moldeo por Inyección de Polvos (MIP). El MIP es un proceso de conformado que incluye la etapa de inyección por loPetrovic, V. (2008). Análisis de fabricabilidad de piezas conformadas por moldeo por inyección de polvos [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/2284Palanci

    Manufacturing Feature Recognition With 2D Convolutional Neural Networks

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    Feature recognition is a critical sub-discipline of CAD/CAM that focuses on the design and implementation of algorithms for automated identification of manufacturing features. The development of feature recognition methods has been active for more than two decades for academic research. However, in this domain, there are still many drawbacks that hinder its practical applications, such as lack of robustness, inability to learn, limited domain of features, and computational complexity. The most critical one is the difficulty of recognizing interacting features, which arises from the fact that feature interactions change the boundaries that are indispensable for characterizing a feature. This research presents a feature recognition method based on 2D convolutional neural networks (CNNs). First, a novel feature representation scheme based on heat kernel signature is developed. Heat Kernel Signature (HKS) is a concise and efficient pointwise shape descriptor. It can present both the topology and geometry characteristics of a 3D model. Besides informative and unambiguity, it also has advantages like robustness of topology and geometry variations, translation, rotation and scale invariance. To be inputted into CNNs, CAD models are discretized by tessellation. Then, its heat persistence map is transformed into 2D histograms by the percentage similarity clustering and node embedding techniques. A large dataset of CAD models is built by randomly sampling for training the CNN models and validating the idea. The dataset includes ten different types of isolated v features and fifteen pairs of interacting features. The results of recognizing isolated features have shown that our method has better performance than any existing ANN based approaches. Our feature recognition framework offers the advantages of learning and generalization. It is independent of feature selection and could be extended to various features without any need to redesign the algorithm. The results of recognizing interacting features indicate that the HKS feature representation scheme is effective in handling the boundary loss caused by feature interactions. The state-of-the-art performance of interacting features recognition has been improved

    Intégration des caractéristiques de cycle de vie dans la phase de conception

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    Data base representation of life cycle design features -- Product analysis design based on life cycle features
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