Deriving Functional Properties of Components from the Analysis of Digital Mock-ups

International audienceDigital Mock-ups (DMUs) are widespread and form a common basis for product description. However, DMUs produced by industrial CAD systems essentially contain geometric models and their exploitation often requires new input data to derive various simulation models. In this work, analysis and reasoning approaches are developed to automatically enrich DMUs with functional and kinematic properties. Indeed, interfaces between components form a key starting point to analyze their behaviours under operational reference states. This is a first stage in a reasoning process to progressively identify mechanical, kinematic as well as functional properties of the components. The overall process relying on the interfaces between components addresses also the emerging needs of conventional representations of components in industrial DMUs. Inferred semantics add up to the pure geometric representation provided by a DMU, to allow for easier exploitation of the model in different phases of a Product Development Process (PDP)

Functional restructuring of CAD models for FEA purposes

International audienceDigital Mock-ups (DMUs) are widespread and stand as reference model for product description. However, DMUs produced by industrial CAD systems essentially contain geometric models and their exploitation often requires user's input data to derive finite element models (FEMs). Here, analysis and reasoning approaches are developed to automatically enrich DMUs with functional and kinematic properties. Indeed, geometric interfaces between components form a key starting point to analyse their behaviours under reference states. This is a first stage in a reasoning process to progressively identify mechanical, kinematic as well as functional properties of the components. Inferred semantics adds up to the pure geometric representation provided by a DMU and produce also geometrically structured components and assemblies. Functional information connected to a structured geometric model of a component significantly improves the preparation of FEMs and increases its robustness because idealizations can take place using components' functions and components' structure helps defining sub-domains of FEMs

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

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

Manufacturing Feature Recognition With 2D Convolutional Neural Networks

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

Integration of sketch-based ideation and 3D modeling with CAD systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis is concerned with the study of how sketch-based systems can be improved to enhance idea generation process in conceptual design stage. It is also concerned with achieving a kind of integration between sketch-based systems and CAD systems to complete the digitization of the design process as sketching phase is still not integrated with other phases due to the different nature of it and the incomplete digitization of sketching phase itself. Previous studies identified three main related issues: sketching process, sketch-based modeling, and the integration between the digitized design phases. Here, the thesis is motivated from the desire to improve sketch-based modeling to support idea generation process but unlike previous studies that only focused on the technical or drawing part of sketching, this thesis attempts to concentrate more on the mental part of the sketching process which play a key role in developing ideas in design. Another motivation of this thesis is to produce a kind of integration between sketch-based systems and CAD systems to enable 3D models produced by sketching to be edited in detailed design stage. As such, there are two main contributions have been addressed in this thesis. The first contribution is the presenting of a new approach in designing sketch-based systems that enable more support for idea generation by separating thinking and developing ideas from the 3D modeling process. This kind of separation allows designers to think freely and concentrate more on their ideas rather than 3D modeling. the second contribution is achieving a kind of integration between gesture-based systems and CAD systems by using an IGES file in exchanging data between systems and a new method to organize data within the file in an order that make it more understood by feature recognition embedded in commercial CAD systems.This study is funded by the Ministry of Higher Education of Egypt

The investigation of a method to generate conformal lattice structures for additive manufacturing

Additive manufacturing (AM) allows a geometric complexity in products not seen in conventional manufacturing. This geometric freedom facilitates the design and fabrication of conformal hierarchical structures. Entire parts or regions of a part can be populated with lattice structure, designed to exhibit properties that differ from the solid material used in fabrication. Current computer aided design (CAD) software used to design products is not suitable for the generation of lattice structure models. Although conceptually simple, the memory requirements to store a virtual CAD model of a lattice structure are prohibitively high. Conventional CAD software defines geometry through boundary representation (B-rep); shapes are described by the connectivity of faces, edges and vertices. While useful for representing accurate models of complex shape, the sheer quantity of individual surfaces required to represent each of the relatively simple individual struts that comprise a lattice structure ensure that memory limitations are soon reached. Additionally, the conventional data flow from CAD to manufactured part is arduous, involving several conversions between file formats. As well as a lengthy process, each conversion risks the generation of geometric errors that must be fixed before manufacture. A method was developed to specifically generate large arrays of lattice structures, based on a general voxel modelling method identified in the literature review. The method is much less sensitive to geometric complexity than conventional methods and thus facilitates the design of considerably more complex structures. The ability to grade structure designs across regions of a part (termed functional grading ) was also investigated, as well as a method to retain connectivity between boundary struts of a conformal structure. In addition, the method streamlines the data flow from design to manufacture: earlier steps of the data conversion process are bypassed entirely. The effect of the modelling method on surface roughness of parts produced was investigated, as voxel models define boundaries with discrete, stepped blocks. It was concluded that the effect of this stepping on surface roughness was minimal. This thesis concludes with suggestions for further work to improve the efficiency, capability and usability of the conformal structure method developed in this work

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

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

Manufacturing compliance analysis for architectural design: a knowledge-aided feature-based modeling framework

Given that achieving nominal (all dimensions are theoretically perfect) geometry is challenging during building construction, understanding and anticipating sources of geometric variation through tolerances modeling and allocation is critical. However, existing building modeling environments lack the ability to support coordinated, incremental and systematic specification of manufacturing and construction requirements. This issue becomes evident when adding multi-material systems produced off site by different vendors during building erection. Current practices to improve this situation include costly and time-consuming operations that challenge the relationship among the stakeholders of a project. As one means to overcome this issue, this research proposes the development of a knowledge-aided modeling framework that integrates a parametric CAD tool with a system modeling application to assess variability in building construction. The CAD tool provides robust geometric modeling capabilities, while System Modeling allows for the specification of feature-based manufacturing requirements aligned with construction standards and construction processes know-how. The system facilitates the identification of conflicting interactions between tolerances and manufacturing specifications of building material systems. The expected contributions of this project are the representation of manufacturing knowledge and tolerances interaction across off-site building subsystems to identify conflicting manufacturing requirements and minimize costly construction errors. The proposed approach will store and allocate manufacturing knowledge as Model-Based Systems Engineering (MBSE) design specifications for both single and multiple material systems. Also, as new techniques in building design and construction are beginning to overlap with engineering methods and standards (e.g. in-factory prefabrication), this project seeks to create collaborative scenarios between MBSE and Building Information Modeling (BIM) based on parametric, simultaneous, software integration to reduce human-to-data translation errors, improving model consistency among domains. Important sub-stages of this project include the comprehensive review of modeling and allocation of tolerances and geometric deviations in design, construction and engineering; an approach for model integration among System Engineering models, mathematical engines and BIM (CAD) models; and finally, a demonstration computational implementation of a System-level tolerances modeling and allocation approach.Ph.D

Análisis y procesado tecnológico del modelo sólido de una pieza para determinar sus elementos característicos de mecanizado

Una de las primeras etapas en la Planificación de Procesos asistida por ordenador, para procesos de mecanizado por arranque de material, consiste en identificar las zonas de material a eliminar en el bruto de partida para generar la pieza. El resultado es un conjunto de entidades llamadas: Elementos Característicos de Mecanizado, que tienen una clara relación con las operaciones de mecanizado. Al procedimiento de obtención automática de estas entidades se le denomina: reconocimiento automático de Elementos Característicos de Mecanizado (AFR, Automatic Feature Recognition), en el que partiendo del modelo 3D del bruto y de la pieza se establecen las entidades de trabajo adecuadas (Elementos Característicos de Mecanizado). Estas entidades contienen la información necesaria para poder llevar a cabo una Planificación de Procesos automática. A su vez, la información se va completando y ampliando a medida que se avanza en las etapas de la Planificación. En la Tesis se plantea el reconocimiento automático de Elementos Característicos de Mecanizado como una de las primeras etapas de la Planificación de Procesos, y que permite el enlace con el diseño asistido por ordenador. Este reconocimiento debe tener un planteamiento dinámico, ofreciendo distintas opciones. Su solución no debe ser una entrada estática, prefijada, para el resto de etapas de la Planificación. El proceso de reconocimiento está fuertemente influenciado por conceptos y decisiones de índole tecnológico (tipos de herramientas, movimientos característicos de los procesos, influencia del corte vinculado, ), que lo guían y que permiten obtener resultados válidos en la aplicación destino: el mecanizado. Atendiendo a este planteamiento, la Tesis ofrece una solución general y completa al proceso de reconocimiento automático de Elementos Característicos de Mecanizado, teniendo en cuenta a los llamados procesos convencionales (torneado, fresado, limado, rectificado, etc.). La solución propuesta no se restringe a piezasGutiérrez Rubert, SC. (2007). Análisis y procesado tecnológico del modelo sólido de una pieza para determinar sus elementos característicos de mecanizado [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/1963Palanci