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Morphological analysis for product design
JCAD 498
COMPUTER-AIDED DESIGN Computer-Aided Design 32 (2000) 377–388 www.elsevier.com/locate/cad
Morphological analysis for product design M. Belaziz a, A. Bouras a, J.M. Brun b,* a
Laboratoire LIGIM, Bat 710-Universite´ Lyon 1, 43 Bd du 11 Novembre 1918, 69622 Villeurbanne, France b LIM/XAOlab, ESIL-Universite´ Aix-Marseille 2, Case 925, 13288 Marseille cedex 9, France Accepted 2 September 1999
Abstract Analysis plays a significant role during product design. Thanks to computational tools; it contributes highly in product optimisation while decreasing design cost and time. For analysis applications, the adaptation of the product geometry is required and consists of producing an idealised model out of a product solid one. This paper presents a form of features based tool to aid the integration of analysis during the design process. It allows producing an analysis model out of a part solid model. This tool is based on a morphological analysis of the solid model followed by a twophase process: simplification and idealisation. The tool provides an easy way to make computer-aided design model modifications implied by the analysis results; thanks to features parameterisation and a reconstruction process. Both allow us to create a solid model on the basis of the idealised one, by using parameterised reconstruction operators. 䉷 2000 Published by Elsevier Science Ltd. All rights reserved. Keywords: Geometric models; Feature; Simplification; Feature edition; Idealisation; Reconstruction
1. Introduction The emergence of product modelling techniques based on features has quickly demonstrated their potential. They enable the creation of attractive design environments since they facilitate geometric interpretations related to designed functions, performance evaluation, manufacturing process planning and other engineering tasks. In such systems, strong coupling between part’s geometry and semantics is formalised as features, which makes it possible for engineers to associate attributes and knowledge to the designed product’s geometry. This type of modelling, when combined with the concurrent engineering approach, enables different actors to perform concurrently their tasks in the product lifecycle. Many engineering applications can use features. Engineers usually think of a part in terms of functions to be fulfilled and design forms representing functionally significant entities; and they aim to define a manufacturable product. Geometry embeds morphological and topological properties which are closely related to the designed functions and to the manufacturing plans, but which are not to be confused with any of them. Thanks to computational tools, analysis enables designers * Corresponding author. Tel.: ⫹ 33-491-82-80-30; fax: ⫹ 33-491-8285-11. E-mail address: [email protected] (J.M. Brun).
to dimension the functionally optimal values of the manufactured product parameters, and to decrease design cost and time when fast analysis cycles are available. The use of features can aid such fast analysis cycles through the generation of meaningful input data for analysis applications. In most cases, the full details of the designed part are not meaningful for the analysis, while a model that idealises the geometry depending upon the analysis tools is often needed. This involves the simplification of the detailed geometry to produce a simplified model through detail removal and, whenever it is needed, a geometry idealisation by dimension reduction from “solid” 3D to “surfacic” or “linear” 3D (2D or 1D idealisations). Various types of analysis applications might be applied to a product during its design, for example stress analysis, tolerance, and electromagnetism. Each one is performed by a specialist who has his own product’s perception and uses his own knowledge and techniques to work out the analysis. This variety of perceptions induces idealisation aspects that depend on the application contexts. Furthermore, in the same application’s context, and for the same object, an analyst can use separate idealised models depending on the analysis conditions and loads. In each case, the analyst has to cope with the idealisation problem: “how to convert the object manufacturing geometry into an analysis one”. The reverse side of the problem arises when one has to reflect analysis results on the part geometry. The CAD
0010-4485/00/$ - see front matter 䉷 2000 Published by Elsevier Science Ltd. All rights reserved. PII: S0010-448 5(00)00019-1
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model must stay consistent with the analysis model, which is modified according to the analysis; this is incredibly time consuming and becomes the practical bottleneck in the design optimisation process. These concerns are particularly true in the early phase of the design process, since one has to make frequent gross evaluations to fix design decisions and to validate the product architecture. Ongoing research efforts on idealisation yield to a range of approaches. Some approaches attempt to generate the analysis model by using the skeleton computed by Medial Axis/Surfaces Transform [1,2], which is closely related to Voronoi Diagrams and Delaunay Triangulations. These approaches have the advantage to produce generic results for dimension reduction. However, they are somewhat inappropriate when one wants to relate shape abstractions or simplifications to analysis semantics and they require an artificial adaptation process to remove unneeded branches [3], related to needed simplifications. To relate idealisation to analysis semantics, some researchers attempt to generate an appropriate model, thanks to expert systems [4]. This involves that the knowledge base must capture all experimental and heuristic knowledge used by expert analysts when taking idealisation decisions, then to relate it to the part geometry (which can be made easier by a previous morphological analysis). In another approach [5], the attempt had been mainly based on retrieving midsurfaces from a solid model to generate the analysis one. This approach is a first step to overcome the inconsistencies found in the skeleton approach but it mixes the idealisation problem with the morphological analysis one, which makes the global problem more difficult. Practically, this approach is limited by the forms that can be processed particularly roundings, fillets and chamfers. We present here a feature-based tool to aid the integration of analysis during the design process. It allows producing an analysis model out of a part solid model. This tool is based on a morphological analysis of the solid model followed by a two-phase process: simplification and idealisation. Then it is possible to walk back from the idealised model to a solid one, reflecting modifications implied by the analysis results, through a parameterised reconstruction process.
2. Features and design The form feature concept, originally defined for manufacturing purpose [6], is a basic tool in a product-modelling environment, as it couples geometric details with their meaning in an application context. Thus, each actor in the product life cycle has his own descriptive language based on form features. Moreover, one may see the product model as an overlapping of several feature-based models, in which each model relates to one actor’s viewpoint in the product life cycle.
Historically, feature-based models have been created by two main approaches: feature-based design and feature recognition. The first approach, widely studied [7–9], uses libraries of features that can either be generic and global, or specific to the manufacturing context. More recent works on feature-based design deal with practical implementation problems related to constraint-based techniques and can be found in other papers [10–12]. The second one, feature recognition, has also been widely studied since the pioneering work of Kyprianou [13]. These studies fall into four distinct approaches: grammar-based [13], rule-based [14], graph-based [15,16], convex hull decomposition [17–19]. Most of this research deals with a limited set of isolated features. However, two important problems in feature recognition remain: they are the capability to recognise interacting features and the multiple interpretations of a part as different sets of features. More recent works classified as cell-based decomposition [20–22] and trace- or hint-based approach [23–25], have attempted to deal with these problems, but features are still identified according to one specific viewpoint (generally machining). Depending on the application context, however, different feature descriptions of a part are needed [26,27]. Therefore, the sole design-by-feature approach is not sufficient. Form features should be recognised from the solid model of the part, and conversion between different descriptions should be available. Such conversions must be automatic, since they would be exercised frequently in order to maintain the consistency of each description along with the changes made by the different actors [28–30]. We present, hereunder, the basic concepts of the morphological analyser as well as the feature taxonomy. 3. Morphological analysis In this process, an object is considered as an initial gross shape that has been progressively altered through the introduction of form features. The corresponding strategy is to reconstruct the gross shape step by step, after each detection of an alteration by a form feature [31,32]. In a first stage, the system operates a face classification according to their related surfaces, and generates several sets of faces corresponding to planar, cylindric, conic and toric faces and finally free form ones. In a second stage, these basic sets are used by the recognition procedure to generate the shape features. The morphological analysis is based on the following concepts: • The analysed model is seen as the result of morphological operations or modifications, similar to one phase in a process planning (which transforms the stock from an initial state to the final state, through a sequence of intermediate states).
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Fig. 1. Morphological features types.
• The modifications between the stock and the next state of the model are a set of modifiers of stock’s geometric components, which create new geometric components. • The morphological features of the same phase do not interact, thus they can be positioned with reference to the modified entity in the reconstructed stock. The interactions will exist only between morphological features that belong to two different phases. • The modifications can be additive (protrusions) or negative (depressions). • The modifications can be global or local, thus they are associated to limited sets of modified vertices, edges and faces.
4. Classification of morphological features The morphological features are classified according to the modified geometric entities (Fig. 1) into: • elementary morphological features: (a) Vertex modification (Fig. 1a); (b) Edge modification (Fig. 1a); (c) Face’s interior modification; the feature can be a protrusion or a depression (Fig. 1b); (d) Modification of the contour of faces sharing a vertex (Fig. 1c); (e) Modification of the contour of two faces inside their common edge (Fig. 1d);
(f) Modification of the contour of two faces along their common edge (Fig. 1e); (g) Modification of the contour of two faces tied by a set of split faces (Fig. 1f).All the features presented in Fig. 1(c–g) are classified into two classes, depending on the complexity of their generating contour. The simple contours can be circular or rectangular (with chamfered or rounded corners), and the complex ones require a 2D analysis which corresponds to the 3D morphological analysis. (h) Modification of a set of faces according to a given direction or distance; this is the case of tapered and offset faces, which are a set of modified faces depending on an angularity relation according to a given direction or distance. ◦ Composite morphological features: The composite features are defined as bi-modifiers that are composed of two elementary modifications, like a feature that modifies the inner side of one face and the contour of two faces by their common edge. ◦ Interacting morphological features: The interacting features are defined as features that have one or several geometric entities modified by other features. ◦ Characteristic relationships: These relationships are geometric constraints connecting morphological features. They are applied on the features’ axis, or on the modified edges and faces. The main constraints used are parallelism, collinearity, perpendicularity, coaxiality and coplanarity.
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Fig. 2. Features extraction examples.
The morphological analysis consists of three steps: 1. to detect all the characteristic modifications in the final model; 2. to re-constitute the previous model, on which these modifications were made by extraction of the related modifiers; 3. to code these modifiers. This analysis can be considered as a B-Rep to CSG conversion—but a new one—in which the CSG operators are defined as a set of shape modifiers, instead of Boolean operators.
The finite number of the shape features classes and the hierarchical description ensure the generality of the proposed extraction method and the definition of a morphological language. This extraction strategy has a big advantage (it reduces the shape complexity in removing progressively the features’ interactions) and a side effect (it simplifies the object shape). Some results of feature extraction on a sample object (speed reduction casing) are shown in Fig. 2, where Fig. 2(a) represents the initial solid model, Fig. 2(b) the object after edge modifiers extraction and Fig. 2(c) the object after face interior modifiers extraction. One can remark that
Fig. 3. Tool components.
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Fig. 4. Simplification example.
edge’s modifiers removal is subject to dimension’s ratio conditions (radius of modifier over edge length) that prevent to remove the rounding of the radiating plates.
5. Design and morphological analysis The overall structure of the tool is shown in Fig. 3. The Form Feature model can be obtained in two ways. When the part geometry exists and is fully defined in a geometric solid model, the morphological feature analyser is used to map the solid model to the Form Feature model of Fig. 3. The second way is used when the part geometry is not yet
defined. In such a case, the user can construct a feature description using an interactive feature editor. Note that in both cases, the feature model is maintained in an unevaluated feature hierarchical modifier model, where leaves represent features and nodes modifying operations (Fig. 4). One can remark that the nature of these operations (related to addition or subtraction of material) is coded in the parameters of the modifiers, which are uniformly noted as additions to the original “stock” model. This additive or subtractive nature would be coded in the tree nodes for Boolean CSG instead. Then, the analysis model generation is conducted through a two-phase process:
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Fig. 5. Idealisation mapping rules.
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Fig. 6. Idealisation examples.
• A simplification phase, which tends to clean out any non relevant feature from the feature model for analysis purposes. • An idealisation phase, which construct idealised 3D, 2D, 1D or 0D geometric entities according to the analysis process used. These idealised entities are defined according to the original features found in the simplified model and the analysis can be achieved on the idealised model. The analysis begins with the selection of the analysis method, which implies generally the choice of both the mesh element type and the material properties. Based on this selection, the analyst proceeds to a mesh generation, which subdivides the idealised geometry into finite elements. Traditionally, loads and boundary conditions are applied to FEM entities, i.e. nodes and elements boundaries. Then, the analyst submits the model to the selected FEA solver and analyses the results through post processing. Based on this analysis, some modifications of the idealised geometry may be needed. They can be either parameter modification or idealised features addition. Then the analyst loops back to analysis until completion of these refinements. In the traditional approach, the geometry modifications are done on the CAD–CAM model, which slows down considerably the analysis process and prevents to loop back as often as desired. In our approach, the modifications are done on the idealised feature model, with the feature’s editor, which is more convenient for the analysis process.
However, at the end of the analysis process, one has to restore consistency of the CAD–CAM model according to the analysed model. This is done by an automatic reconstruction of the CAD–CAM model with the feature reconstruction module. 5.1. Simplification The original design geometry is generally too detailed and complicated for analysis purposes. In such cases, the analyst works out the detailed design model to produce a more simple mesh computationally less expensive to solve. Doing so, he cleans out the CAD model from the features considered as not pertinent for the analysis application. The morphological analyser described above, provides all the features of the object model and produces an abstracted feature tree, plus the B-Rep of a “stock”. This abstracted feature tree describes the modifications of the stock’s B-Rep to which the features are attached. With such a tree, the simplification task can be achieved at a level directly compatible with the analysis semantics, which is much easier than to simplify objects with a standard geometric editor. To this end, an interactive feature editor associated to the hierarchical tree has been implemented. In the example of Fig. 4, the four extracted holes are considered pertinent for the analysis since they are positioned close to the border and that the loads applied include critical torsion effects. They are thus included in the analysis model. The other features are not deleted, but remain abstracted
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• a shape factor including roundings, thickness and aspect ratio.
Fig. 7. Reconstruction operators.
features, considered as modifiers of this model, and can be simplified, idealised or instantiated at will, depending on the analysis results. One may, for example, either idealise this simplified model as a plate or complete it by the addition of a simplified boss, leaving the hole and/or the roundings in an abstracted form. 5.2. Idealisation This step adapts the simplified geometry to a given analysis application, which requires the building of new geometric supports, depending on the solver used. These are generally a collection of 1D, 2D and 3D geometric elements. In stress analysis, for example, the following supports can be used: beam, plate, shell, lumped mass and solid [4]. Idealisation decisions are made according to two main factors: • an analysis factor including: analysis type and conditions (loads or boundary conditions);
The implemented editor allows the analyst to idealise any element of the resulting tree (features and stock) in different ways, according to different analysis interpretations. Each feature can have different idealisations depending on its dimensions and the analysis context. A box, for example, can be idealised as a beam or a plate, according to its aspect ratios, its loads, and the analysis type. The user can specify the idealisation type for each abstract feature contained in the analysed model. This analysed model, in its abstract form, is instantiated to create a geometric model ready for FEM/FEA. Such an analysis model leaves some form features in an abstracted state (simplification) or an idealised one, reducing the geometry from 3D to 2D or 1D. Each idealised feature is defined by its positional and dimensional parameters, according to the corresponding abstract feature. Dimensional reduction, required in idealisation, leads to the disappearance of some geometric and topologic information. In the example of Fig. 5(d), the edges modified by roundings in the solid model do not exist in the idealised one. Consequently, the rounding features become orphans and could not be attached to the idealised model, which becomes incomplete. Hence, to maintain consistency between the simplified feature model and the idealised one, we have established correlation rules to map the topologic entities of the object’s simplified geometry to those of the idealised one. This allows the propagation of the features attachment from the simplified feature model to the idealised one. These rules aim to replace the geometric and topologic information of the modified 3D entities by properties that are added to the idealised entities. The rules are presented in Fig. 5(a) and described below: • 3D to 2D: a volume is mapped to one face, which has tow sides (upper and lower). Each side corresponds to one of the pair of the thickness faces. Then, features modifying the pair faces become modifiers of the two sides of the corresponding face (Fig. 5(b)). • 2D to 1D: a face is mapped to one edge. The latter has also two sides, which correspond to the lateral edges of the original face. Hence, a feature attached to this face becomes attached to corresponding edge (Fig. 5(c)). • 1D to 0D: an edge is mapped to a vertex, which has two sides representing the original edge vertices. The features modifying the original edge become modifiers of the corresponding vertex (Fig. 5(d)). Fig. 6 shows some idealisation examples for the speed reduction casing. In this figure, fins are idealised as thin plates in Fig. 6(a)–(d), base’s holes are idealised as axes in Fig. 6(b), whereas in Fig. 6(c) and (d) the base is idealised as a plate and the holes are reduced to circles in Fig. 6(c) and to their centres in Fig. 6(d).
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Fig. 8. Example of a parametric reconstruction operator.
After the idealisation step, the feature editor makes it also possible for the user to manipulate the resulting elements. In object Fig. 6(e), the idealised fins are removed from the idealised object Fig. 6(d). One may interpret such idealisations as resulting from thermal analysis in Fig. 6(a)–(d) or from stress analysis in Fig. 6(e), provided that the strain of the upper part of the casing remains negligible. 5.3. Reconstruction The reconstruction allows the creation of a solid model from the modified stock and the modifying form features coded in the form feature model tree. It corresponds to the Boolean engines of standard geometric modellers evaluating the B-Rep defined by a CSG. For this purpose, we have developed parameterised B-Rep modification operators, which modify the topology and the morphology of the original solid model. These operators are based on Euler operators [33] and can be considered as Euler macro-operators; they are illustrated in Fig. 7 and their list is: • RFV (具Vertex典): Reconstruct Face from a modified Vertex. • RFE (具Edge典): Reconstruct Face from a modified Edge. • RBF (具Face典): Reconstruct Boss from a modified Face. • RHF (具Face典): Reconstruct blind Hole from a modified Face. • RHFS (具Faces典): Reconstruct through Hole from modified FaceS. Each operator is associated to a modifier class. Hence, the same operator can be used to reconstruct form features, which produce the same topology and present different
morphologies. Fig. 8 shows an example, where the RFE operator is used to reconstruct a chamfer of a angle and D offset, or a rounding of radius R1 or R2. 6. Applications to the design process The design process is generally split into separate phases: preliminary design, detailed design, manufacturing design. Going back and forth from design to analysis is particularly frequent during the preliminary design; it is also essential to the detailed design optimisation subphases. If idealisation is an important topic in design optimisation, it is prominently important in preliminary design as design loops between performance analysis and functional design are frequent and do not need high precision results. Preliminary design is essentially functional and is free of detailed geometry; consequently, the model simplification phase is frequently irrelevant. Conversely, preliminary design would use abstract modelling techniques through functional features synthesis and would generate as little geometry as possible. A morphological description, corresponding to a functional feature description, with a variable level of geometric instantiation can be the way to use the tools proposed here. 6.1. Feature model creation When the part geometry does not exist, users can create a feature description using the feature editor interface. This editor allows users to construct a model in terms of functional elements, each of them having a particular significance for the design.
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Fig. 9. Feature model creation.
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To create a feature, they can instantiate the corresponding class among the feature class hierarchy. Each class is defined by a set of parameters necessary to its instantiation and its geometry generation. The global process of creation is sequential, and features newly added are considered as modifiers of previously created ones. These dependencies are represented in a hierarchical features tree. This creation process is illustrated by the example shown in Fig. 9. The geometry to which the hierarchical features tree corresponds can be generated with the reconstruction module, which represents an evaluation of the tree. This task is conducted using reconstruction operators which allow for any feature to be reconstructed with the appropriate values of its parameters. This leads to the creation of low-level geometric entities such as faces, edges and vertices, and to storing them in a Boundary Representation model.
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analysis”. Such an analysis is not yet available, so the complex contours are coded as a 2D “stock” and are not parameterised. This is considered as a natural extension of the 3D morphological analysis, which can be realised without any theoretical difficulty, but the work is yet to be done. The direct link between the idealised model and the FEM tools is not realised, so our approach was not tested “live” in preliminary design processes. This is probably the most important task to achieve, in order to pass from a simulation of design process to a real experimentation. The Form Feature Editor needs some improvements to handle conveniently industrial models, which are difficult to manipulate in the scope of a simple screen. To do so, form features can be grouped in logical sets of macro-features, generating shapes of a higher level of signification than elementary features. Globally, one has to pass from a feasibility proof to a working prototype.
6.2. Preliminary design Feature based modelling still needs to be extended in the early creative stages of the design, the phase where designers are more concerned by function and overall structure of the designed product than by detailed geometry [34]. At these stages, designers know the required functionality of the device but they have no idea about its implementation and appearance. First, designers determine the functions that the design should perform corresponding to the functional design. Then, they determine how functions can be realised by physical entities and the constraints involved by functional requirements. This leads to create a model with functional features in an abstract form. The form features editor can be used to create this model. Next, designers should be able to evaluate the created model to check that all expected functions occur. For that purpose, simulations using analysis processes are performed. This requires model idealisation, which can be conducted by the tool simplification and idealisation process. On the basis of the simulation, designers could modify the model to enhance the product until the functional requirements are reached. This implies features parameters’ modifications and addition or suppression of features. The form features editor is best suited to perform this task, thanks to features parameterisation and instantiation. Then, they proceed into the detailed definition of the product by generating the corresponding geometry, which can be done with the reconstruction module. 6.3. Limitations and future work In the processes described above, some limitations still exist. As noted in the classification of morphological features section, the complex contours would “require a 2D analysis, which corresponds to the 3D morphological
7. Conclusion This paper describes a tool for linking analysis and CAD systems using a form feature-based approach. This tool is based on a morphological analysis of the product model followed by a two-phase process: simplification and idealisation. The description of an object as an initial gross shape that has been successively modified by the adjunction of form features enables a hierarchical idealisation of the object through simple and fast processes. The use of reconstruction operators makes it possible to recreate a solid model on the basis of the idealised model. The reconstruction operators are parameterised, so the recreated model integrates the parameters’ modifications implied by the analysis results. This scheme presents interesting capabilities to link analysis applications to design and manufacturing, and to parameterise efficiently design models as well.
Acknowledgements The authors gratefully acknowledge CORETECH International for its contribution in providing the TRANS-3D software.
References [1] Armstrong CG, Sheehy DJ, Robinson DJ. Computing the medial surface of a solid from a domain delaunay triangulation. (EDS) Third Symposium on Solid Modeling and Applications, May 1995. p. 201–12. [2] Reddy JM, Turkiyyah GM. Computation of 3d skeletons using a generalised delaunay triangulation technique. Computer-Aided Design 1995;27(9):677–94.
388
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[3] Armstrong CG. Modelling requirements for finite-element analysis. Computer-Aided Design 1994;26:573–8. [4] Prabhakar V, Dabke P, Sheppard S. Using features to support finite element idealizations. Computer in Engineering ASME 1994;1:183– 93. [5] Rezayat M. Midsurface abstraction from 3d solid models: general theory and applications. Computer-Aided Design 1996;28(11):905– 15. [6] Pratt MJ, Wilson PR. Requirements for support of form features in a solid modelling system. CAM-I Report R-85-ASPP-01, June 1985. [7] Cunningham JJ, Dixon JR. Designing with features: the origin of features, ASME computers in engineering, San Francisco, USA, July/August. 1988. p. 237–43. [8] Rossignac JR. Issues on feature based editing and interrogation of solid models. Computer and Graphics 1990;14(2):149–72. [9] Shah JJ. Conceptual development of form features and feature modelers, Research in engineering design, vol. 2. New York: Springer, 1991. p. 93–108. [10] Hoffmann CM, Juan R. Erep—an editable, high-level representation for geometric design and analysis. In: Wilson PR, Wozny MJ, Pratt MJ, editors. Geometric and product modeling, Amsterdam: Elsevier, 1993. p. 129–64. [11] Chen X, Hoffmann CM. Design compilation of feature-based and constraint-based CAD, Solid modeling’95, Salt Lake City, UT1995. p. 13–9. [12] Middledicth A, Reade C. A kernel for geometric features, Solid modeling’97, Atlanta, GA1997. p. 13–9. [13] Kyprianou LK. Shape classification in computer-aided design. PhD thesis, University of Cambridge, UK, July 1980. [14] Henderson MR, Anderson DC. Computer recognition and extraction of form features: a CAD/CAM link. Computers in Industry 1984;5:329–39. [15] Falcidieno B, Giannini F. In: Marechaled G, editor. Extraction and organisation of form features into a structured boundary model, EUROGRAPHICS’87Amsterdam: Elsevier, 1987. p. 249–59. [16] Joshi S, Chang TC. Graph-based heuristics for recognition of machined features from a 3D solid model. Computer-Aided Design 1988;20(2):58–66. [17] Woo TC. Feature extraction by volume decomposition. CAD/CAM technology in mechanical engineering, Cambridge, MA, 1982. p. 76– 94. [18] Ferreira JC, Hinduja S. Convex hull-based feature-recognition method for 2.5D components. Computer-Aided Design 1990;22(1):41–9. [19] Kim YS. Recognition of form features using convex decomposition. Computer-Aided Design 1992;24(9):461–76. [20] Shen Y, Shah JJ, Shirur A. Determination of machining volumes from extensible sets of design features. In: Shah J, Nau D, Mantyla M, editors. Advances in feature-based manufacturing, Amsterdam: Elsevier, 1994. p. 129–57. [21] Tseng Y, Joshi SB. Recognizing multiple interpretations of interacting machining features. Computer-Aided Design 1994;26(9):667–88. [22] Sakurai H, Dave P. Volume decomposition and feature recognition. Part II. Curved objects . Computer-Aided Design 1996;28(7):519–37. [23] Vandenbrande JH, Requicha AAG. Geometric computation for the recognition of spatially interacting machining features. In: Shah J, Nau D, Mantyla M, editors. Advances in feature-based manufacturing, Amsterdam: Elsevier, 1994. [24] Regli WC. Geometric algorithms for recognition of features from solid models. PhD thesis, Computer Science Department, University of Maryland, Maryland, 1995. [25] Han JJ. 3D geometric reasoning algorithms for features recognition. PhD thesis, Computer Science Department, University of Southern California, Southern California, 1996. [26] Shah JJ. Feature transformations between application-specific feature spaces. Computer-Aided Engineering Journal 1988;5/6:247–55. [27] Bronsvoort WF, Jansen FW. Feature modelling and conversion: key
[28]
[29] [30] [31]
[32] [33] [34]
concepts to concurrent engineering. Computers in Industry 1993;21:61–86. Kraker KJ, Dohmen M, Bronsvoort WF. Multiple-way feature conversion to support concurrent engineering, Solid modeling’95, Salt Lake City, UT1995. p. 105–14. Kraker KJ, Dohmen M, Bronsvoort WF. Maintaining multiple views in feature modeling, Solid modeling’97, Atlanta, GA1997. p. 123–30. Suh YS, Wozny MJ. Interactive feature extraction for a form feature conversion system, Solid modeling’97, Atlanta, GA1997. p. 111–22. Brun JM. From characteristic shapes to form features. IFIP international conference on feature modeling and recognition. In Advanced CAD/CAM Systems, Valenciennes, 1994. p. 315–26. Brun JM, Tehari A, Bouras A. Extraction multi-vue des formes caracteristiques. Journal of CAD/CAM and CG 1997;12(1/2):17–32. Mantyla M. An introduction to solid modeling. Computer Science Press, 1988. Mantyla M, Shah J. Parametric and feature-based CAD/CAM: concepts, techniques, and applications. New York: Wiley, 1995.
Mohamed Belaziz is a PhD student in Computer Science at Claude Bernard University. He received his master diploma (Diploˆme d’Etudes Approfondies) in Computer Science from Claude Bernard University of Lyon and his Diploma of Engineer in Computer Science from The National Institute of Computer Science (INI) of Algiers. His research interests are in geometric modelling, feature modelling and model idealisation.
Jean Marc Brun is currently Professor of Computer Science at ESIL (Ecole Superieure d’Ingenieurs de Luminy) and Director of XAOlab at the University Aix-Marseille. He received the Degree of “Docteur d’Etat” (State Doctor) at Paris University in 1969 for his thesis on “Steady and unsteady motion of airfoils in supersonic flows”. He derived the EUCLID Project 1970 to 1979 at CNRS, then was a founder of Datavision in 1979 (Matra Datavision in 1980). In 1988, he founded Coretech International, and was Professor in Lyon University from 1991 to 1998. In 1999, he joined Aix-Marseille University to found XAOlab a joint venture between University and Industry. During the 1970s, his research activities turned on fluid mechanics to geometric modeling and image synthesis applied to CAD/CAM systems.
Abdelaziz Bouras is an associate professor of Computer Science, and Head of the Technical Modeling Group at Claude Bernard University of Lyon, France. He was in 1998 at the Manufacturing Engineering Laboratory (MEL) of National Institute of Standards and Technology (NIST) as a Guest Researcher. He received his PhD in Computer Science from Claude Bernard University in 1992 and his Engineer Diploma in Mechanical Engineering in 1987 from The National Institute of Mechanical Engineering (INGM) of Boumerdas, Algeria. His research interests are in solid and feature based modeling, collaborative design, and data exchange.
COMPUTER-AIDED DESIGN Computer-Aided Design 32 (2000) 377–388 www.elsevier.com/locate/cad
Morphological analysis for product design M. Belaziz a, A. Bouras a, J.M. Brun b,* a
Laboratoire LIGIM, Bat 710-Universite´ Lyon 1, 43 Bd du 11 Novembre 1918, 69622 Villeurbanne, France b LIM/XAOlab, ESIL-Universite´ Aix-Marseille 2, Case 925, 13288 Marseille cedex 9, France Accepted 2 September 1999
Abstract Analysis plays a significant role during product design. Thanks to computational tools; it contributes highly in product optimisation while decreasing design cost and time. For analysis applications, the adaptation of the product geometry is required and consists of producing an idealised model out of a product solid one. This paper presents a form of features based tool to aid the integration of analysis during the design process. It allows producing an analysis model out of a part solid model. This tool is based on a morphological analysis of the solid model followed by a twophase process: simplification and idealisation. The tool provides an easy way to make computer-aided design model modifications implied by the analysis results; thanks to features parameterisation and a reconstruction process. Both allow us to create a solid model on the basis of the idealised one, by using parameterised reconstruction operators. 䉷 2000 Published by Elsevier Science Ltd. All rights reserved. Keywords: Geometric models; Feature; Simplification; Feature edition; Idealisation; Reconstruction
1. Introduction The emergence of product modelling techniques based on features has quickly demonstrated their potential. They enable the creation of attractive design environments since they facilitate geometric interpretations related to designed functions, performance evaluation, manufacturing process planning and other engineering tasks. In such systems, strong coupling between part’s geometry and semantics is formalised as features, which makes it possible for engineers to associate attributes and knowledge to the designed product’s geometry. This type of modelling, when combined with the concurrent engineering approach, enables different actors to perform concurrently their tasks in the product lifecycle. Many engineering applications can use features. Engineers usually think of a part in terms of functions to be fulfilled and design forms representing functionally significant entities; and they aim to define a manufacturable product. Geometry embeds morphological and topological properties which are closely related to the designed functions and to the manufacturing plans, but which are not to be confused with any of them. Thanks to computational tools, analysis enables designers * Corresponding author. Tel.: ⫹ 33-491-82-80-30; fax: ⫹ 33-491-8285-11. E-mail address: [email protected] (J.M. Brun).
to dimension the functionally optimal values of the manufactured product parameters, and to decrease design cost and time when fast analysis cycles are available. The use of features can aid such fast analysis cycles through the generation of meaningful input data for analysis applications. In most cases, the full details of the designed part are not meaningful for the analysis, while a model that idealises the geometry depending upon the analysis tools is often needed. This involves the simplification of the detailed geometry to produce a simplified model through detail removal and, whenever it is needed, a geometry idealisation by dimension reduction from “solid” 3D to “surfacic” or “linear” 3D (2D or 1D idealisations). Various types of analysis applications might be applied to a product during its design, for example stress analysis, tolerance, and electromagnetism. Each one is performed by a specialist who has his own product’s perception and uses his own knowledge and techniques to work out the analysis. This variety of perceptions induces idealisation aspects that depend on the application contexts. Furthermore, in the same application’s context, and for the same object, an analyst can use separate idealised models depending on the analysis conditions and loads. In each case, the analyst has to cope with the idealisation problem: “how to convert the object manufacturing geometry into an analysis one”. The reverse side of the problem arises when one has to reflect analysis results on the part geometry. The CAD
0010-4485/00/$ - see front matter 䉷 2000 Published by Elsevier Science Ltd. All rights reserved. PII: S0010-448 5(00)00019-1
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model must stay consistent with the analysis model, which is modified according to the analysis; this is incredibly time consuming and becomes the practical bottleneck in the design optimisation process. These concerns are particularly true in the early phase of the design process, since one has to make frequent gross evaluations to fix design decisions and to validate the product architecture. Ongoing research efforts on idealisation yield to a range of approaches. Some approaches attempt to generate the analysis model by using the skeleton computed by Medial Axis/Surfaces Transform [1,2], which is closely related to Voronoi Diagrams and Delaunay Triangulations. These approaches have the advantage to produce generic results for dimension reduction. However, they are somewhat inappropriate when one wants to relate shape abstractions or simplifications to analysis semantics and they require an artificial adaptation process to remove unneeded branches [3], related to needed simplifications. To relate idealisation to analysis semantics, some researchers attempt to generate an appropriate model, thanks to expert systems [4]. This involves that the knowledge base must capture all experimental and heuristic knowledge used by expert analysts when taking idealisation decisions, then to relate it to the part geometry (which can be made easier by a previous morphological analysis). In another approach [5], the attempt had been mainly based on retrieving midsurfaces from a solid model to generate the analysis one. This approach is a first step to overcome the inconsistencies found in the skeleton approach but it mixes the idealisation problem with the morphological analysis one, which makes the global problem more difficult. Practically, this approach is limited by the forms that can be processed particularly roundings, fillets and chamfers. We present here a feature-based tool to aid the integration of analysis during the design process. It allows producing an analysis model out of a part solid model. This tool is based on a morphological analysis of the solid model followed by a two-phase process: simplification and idealisation. Then it is possible to walk back from the idealised model to a solid one, reflecting modifications implied by the analysis results, through a parameterised reconstruction process.
2. Features and design The form feature concept, originally defined for manufacturing purpose [6], is a basic tool in a product-modelling environment, as it couples geometric details with their meaning in an application context. Thus, each actor in the product life cycle has his own descriptive language based on form features. Moreover, one may see the product model as an overlapping of several feature-based models, in which each model relates to one actor’s viewpoint in the product life cycle.
Historically, feature-based models have been created by two main approaches: feature-based design and feature recognition. The first approach, widely studied [7–9], uses libraries of features that can either be generic and global, or specific to the manufacturing context. More recent works on feature-based design deal with practical implementation problems related to constraint-based techniques and can be found in other papers [10–12]. The second one, feature recognition, has also been widely studied since the pioneering work of Kyprianou [13]. These studies fall into four distinct approaches: grammar-based [13], rule-based [14], graph-based [15,16], convex hull decomposition [17–19]. Most of this research deals with a limited set of isolated features. However, two important problems in feature recognition remain: they are the capability to recognise interacting features and the multiple interpretations of a part as different sets of features. More recent works classified as cell-based decomposition [20–22] and trace- or hint-based approach [23–25], have attempted to deal with these problems, but features are still identified according to one specific viewpoint (generally machining). Depending on the application context, however, different feature descriptions of a part are needed [26,27]. Therefore, the sole design-by-feature approach is not sufficient. Form features should be recognised from the solid model of the part, and conversion between different descriptions should be available. Such conversions must be automatic, since they would be exercised frequently in order to maintain the consistency of each description along with the changes made by the different actors [28–30]. We present, hereunder, the basic concepts of the morphological analyser as well as the feature taxonomy. 3. Morphological analysis In this process, an object is considered as an initial gross shape that has been progressively altered through the introduction of form features. The corresponding strategy is to reconstruct the gross shape step by step, after each detection of an alteration by a form feature [31,32]. In a first stage, the system operates a face classification according to their related surfaces, and generates several sets of faces corresponding to planar, cylindric, conic and toric faces and finally free form ones. In a second stage, these basic sets are used by the recognition procedure to generate the shape features. The morphological analysis is based on the following concepts: • The analysed model is seen as the result of morphological operations or modifications, similar to one phase in a process planning (which transforms the stock from an initial state to the final state, through a sequence of intermediate states).
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Fig. 1. Morphological features types.
• The modifications between the stock and the next state of the model are a set of modifiers of stock’s geometric components, which create new geometric components. • The morphological features of the same phase do not interact, thus they can be positioned with reference to the modified entity in the reconstructed stock. The interactions will exist only between morphological features that belong to two different phases. • The modifications can be additive (protrusions) or negative (depressions). • The modifications can be global or local, thus they are associated to limited sets of modified vertices, edges and faces.
4. Classification of morphological features The morphological features are classified according to the modified geometric entities (Fig. 1) into: • elementary morphological features: (a) Vertex modification (Fig. 1a); (b) Edge modification (Fig. 1a); (c) Face’s interior modification; the feature can be a protrusion or a depression (Fig. 1b); (d) Modification of the contour of faces sharing a vertex (Fig. 1c); (e) Modification of the contour of two faces inside their common edge (Fig. 1d);
(f) Modification of the contour of two faces along their common edge (Fig. 1e); (g) Modification of the contour of two faces tied by a set of split faces (Fig. 1f).All the features presented in Fig. 1(c–g) are classified into two classes, depending on the complexity of their generating contour. The simple contours can be circular or rectangular (with chamfered or rounded corners), and the complex ones require a 2D analysis which corresponds to the 3D morphological analysis. (h) Modification of a set of faces according to a given direction or distance; this is the case of tapered and offset faces, which are a set of modified faces depending on an angularity relation according to a given direction or distance. ◦ Composite morphological features: The composite features are defined as bi-modifiers that are composed of two elementary modifications, like a feature that modifies the inner side of one face and the contour of two faces by their common edge. ◦ Interacting morphological features: The interacting features are defined as features that have one or several geometric entities modified by other features. ◦ Characteristic relationships: These relationships are geometric constraints connecting morphological features. They are applied on the features’ axis, or on the modified edges and faces. The main constraints used are parallelism, collinearity, perpendicularity, coaxiality and coplanarity.
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Fig. 2. Features extraction examples.
The morphological analysis consists of three steps: 1. to detect all the characteristic modifications in the final model; 2. to re-constitute the previous model, on which these modifications were made by extraction of the related modifiers; 3. to code these modifiers. This analysis can be considered as a B-Rep to CSG conversion—but a new one—in which the CSG operators are defined as a set of shape modifiers, instead of Boolean operators.
The finite number of the shape features classes and the hierarchical description ensure the generality of the proposed extraction method and the definition of a morphological language. This extraction strategy has a big advantage (it reduces the shape complexity in removing progressively the features’ interactions) and a side effect (it simplifies the object shape). Some results of feature extraction on a sample object (speed reduction casing) are shown in Fig. 2, where Fig. 2(a) represents the initial solid model, Fig. 2(b) the object after edge modifiers extraction and Fig. 2(c) the object after face interior modifiers extraction. One can remark that
Fig. 3. Tool components.
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Fig. 4. Simplification example.
edge’s modifiers removal is subject to dimension’s ratio conditions (radius of modifier over edge length) that prevent to remove the rounding of the radiating plates.
5. Design and morphological analysis The overall structure of the tool is shown in Fig. 3. The Form Feature model can be obtained in two ways. When the part geometry exists and is fully defined in a geometric solid model, the morphological feature analyser is used to map the solid model to the Form Feature model of Fig. 3. The second way is used when the part geometry is not yet
defined. In such a case, the user can construct a feature description using an interactive feature editor. Note that in both cases, the feature model is maintained in an unevaluated feature hierarchical modifier model, where leaves represent features and nodes modifying operations (Fig. 4). One can remark that the nature of these operations (related to addition or subtraction of material) is coded in the parameters of the modifiers, which are uniformly noted as additions to the original “stock” model. This additive or subtractive nature would be coded in the tree nodes for Boolean CSG instead. Then, the analysis model generation is conducted through a two-phase process:
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Fig. 5. Idealisation mapping rules.
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Fig. 6. Idealisation examples.
• A simplification phase, which tends to clean out any non relevant feature from the feature model for analysis purposes. • An idealisation phase, which construct idealised 3D, 2D, 1D or 0D geometric entities according to the analysis process used. These idealised entities are defined according to the original features found in the simplified model and the analysis can be achieved on the idealised model. The analysis begins with the selection of the analysis method, which implies generally the choice of both the mesh element type and the material properties. Based on this selection, the analyst proceeds to a mesh generation, which subdivides the idealised geometry into finite elements. Traditionally, loads and boundary conditions are applied to FEM entities, i.e. nodes and elements boundaries. Then, the analyst submits the model to the selected FEA solver and analyses the results through post processing. Based on this analysis, some modifications of the idealised geometry may be needed. They can be either parameter modification or idealised features addition. Then the analyst loops back to analysis until completion of these refinements. In the traditional approach, the geometry modifications are done on the CAD–CAM model, which slows down considerably the analysis process and prevents to loop back as often as desired. In our approach, the modifications are done on the idealised feature model, with the feature’s editor, which is more convenient for the analysis process.
However, at the end of the analysis process, one has to restore consistency of the CAD–CAM model according to the analysed model. This is done by an automatic reconstruction of the CAD–CAM model with the feature reconstruction module. 5.1. Simplification The original design geometry is generally too detailed and complicated for analysis purposes. In such cases, the analyst works out the detailed design model to produce a more simple mesh computationally less expensive to solve. Doing so, he cleans out the CAD model from the features considered as not pertinent for the analysis application. The morphological analyser described above, provides all the features of the object model and produces an abstracted feature tree, plus the B-Rep of a “stock”. This abstracted feature tree describes the modifications of the stock’s B-Rep to which the features are attached. With such a tree, the simplification task can be achieved at a level directly compatible with the analysis semantics, which is much easier than to simplify objects with a standard geometric editor. To this end, an interactive feature editor associated to the hierarchical tree has been implemented. In the example of Fig. 4, the four extracted holes are considered pertinent for the analysis since they are positioned close to the border and that the loads applied include critical torsion effects. They are thus included in the analysis model. The other features are not deleted, but remain abstracted
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• a shape factor including roundings, thickness and aspect ratio.
Fig. 7. Reconstruction operators.
features, considered as modifiers of this model, and can be simplified, idealised or instantiated at will, depending on the analysis results. One may, for example, either idealise this simplified model as a plate or complete it by the addition of a simplified boss, leaving the hole and/or the roundings in an abstracted form. 5.2. Idealisation This step adapts the simplified geometry to a given analysis application, which requires the building of new geometric supports, depending on the solver used. These are generally a collection of 1D, 2D and 3D geometric elements. In stress analysis, for example, the following supports can be used: beam, plate, shell, lumped mass and solid [4]. Idealisation decisions are made according to two main factors: • an analysis factor including: analysis type and conditions (loads or boundary conditions);
The implemented editor allows the analyst to idealise any element of the resulting tree (features and stock) in different ways, according to different analysis interpretations. Each feature can have different idealisations depending on its dimensions and the analysis context. A box, for example, can be idealised as a beam or a plate, according to its aspect ratios, its loads, and the analysis type. The user can specify the idealisation type for each abstract feature contained in the analysed model. This analysed model, in its abstract form, is instantiated to create a geometric model ready for FEM/FEA. Such an analysis model leaves some form features in an abstracted state (simplification) or an idealised one, reducing the geometry from 3D to 2D or 1D. Each idealised feature is defined by its positional and dimensional parameters, according to the corresponding abstract feature. Dimensional reduction, required in idealisation, leads to the disappearance of some geometric and topologic information. In the example of Fig. 5(d), the edges modified by roundings in the solid model do not exist in the idealised one. Consequently, the rounding features become orphans and could not be attached to the idealised model, which becomes incomplete. Hence, to maintain consistency between the simplified feature model and the idealised one, we have established correlation rules to map the topologic entities of the object’s simplified geometry to those of the idealised one. This allows the propagation of the features attachment from the simplified feature model to the idealised one. These rules aim to replace the geometric and topologic information of the modified 3D entities by properties that are added to the idealised entities. The rules are presented in Fig. 5(a) and described below: • 3D to 2D: a volume is mapped to one face, which has tow sides (upper and lower). Each side corresponds to one of the pair of the thickness faces. Then, features modifying the pair faces become modifiers of the two sides of the corresponding face (Fig. 5(b)). • 2D to 1D: a face is mapped to one edge. The latter has also two sides, which correspond to the lateral edges of the original face. Hence, a feature attached to this face becomes attached to corresponding edge (Fig. 5(c)). • 1D to 0D: an edge is mapped to a vertex, which has two sides representing the original edge vertices. The features modifying the original edge become modifiers of the corresponding vertex (Fig. 5(d)). Fig. 6 shows some idealisation examples for the speed reduction casing. In this figure, fins are idealised as thin plates in Fig. 6(a)–(d), base’s holes are idealised as axes in Fig. 6(b), whereas in Fig. 6(c) and (d) the base is idealised as a plate and the holes are reduced to circles in Fig. 6(c) and to their centres in Fig. 6(d).
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Fig. 8. Example of a parametric reconstruction operator.
After the idealisation step, the feature editor makes it also possible for the user to manipulate the resulting elements. In object Fig. 6(e), the idealised fins are removed from the idealised object Fig. 6(d). One may interpret such idealisations as resulting from thermal analysis in Fig. 6(a)–(d) or from stress analysis in Fig. 6(e), provided that the strain of the upper part of the casing remains negligible. 5.3. Reconstruction The reconstruction allows the creation of a solid model from the modified stock and the modifying form features coded in the form feature model tree. It corresponds to the Boolean engines of standard geometric modellers evaluating the B-Rep defined by a CSG. For this purpose, we have developed parameterised B-Rep modification operators, which modify the topology and the morphology of the original solid model. These operators are based on Euler operators [33] and can be considered as Euler macro-operators; they are illustrated in Fig. 7 and their list is: • RFV (具Vertex典): Reconstruct Face from a modified Vertex. • RFE (具Edge典): Reconstruct Face from a modified Edge. • RBF (具Face典): Reconstruct Boss from a modified Face. • RHF (具Face典): Reconstruct blind Hole from a modified Face. • RHFS (具Faces典): Reconstruct through Hole from modified FaceS. Each operator is associated to a modifier class. Hence, the same operator can be used to reconstruct form features, which produce the same topology and present different
morphologies. Fig. 8 shows an example, where the RFE operator is used to reconstruct a chamfer of a angle and D offset, or a rounding of radius R1 or R2. 6. Applications to the design process The design process is generally split into separate phases: preliminary design, detailed design, manufacturing design. Going back and forth from design to analysis is particularly frequent during the preliminary design; it is also essential to the detailed design optimisation subphases. If idealisation is an important topic in design optimisation, it is prominently important in preliminary design as design loops between performance analysis and functional design are frequent and do not need high precision results. Preliminary design is essentially functional and is free of detailed geometry; consequently, the model simplification phase is frequently irrelevant. Conversely, preliminary design would use abstract modelling techniques through functional features synthesis and would generate as little geometry as possible. A morphological description, corresponding to a functional feature description, with a variable level of geometric instantiation can be the way to use the tools proposed here. 6.1. Feature model creation When the part geometry does not exist, users can create a feature description using the feature editor interface. This editor allows users to construct a model in terms of functional elements, each of them having a particular significance for the design.
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Fig. 9. Feature model creation.
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To create a feature, they can instantiate the corresponding class among the feature class hierarchy. Each class is defined by a set of parameters necessary to its instantiation and its geometry generation. The global process of creation is sequential, and features newly added are considered as modifiers of previously created ones. These dependencies are represented in a hierarchical features tree. This creation process is illustrated by the example shown in Fig. 9. The geometry to which the hierarchical features tree corresponds can be generated with the reconstruction module, which represents an evaluation of the tree. This task is conducted using reconstruction operators which allow for any feature to be reconstructed with the appropriate values of its parameters. This leads to the creation of low-level geometric entities such as faces, edges and vertices, and to storing them in a Boundary Representation model.
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analysis”. Such an analysis is not yet available, so the complex contours are coded as a 2D “stock” and are not parameterised. This is considered as a natural extension of the 3D morphological analysis, which can be realised without any theoretical difficulty, but the work is yet to be done. The direct link between the idealised model and the FEM tools is not realised, so our approach was not tested “live” in preliminary design processes. This is probably the most important task to achieve, in order to pass from a simulation of design process to a real experimentation. The Form Feature Editor needs some improvements to handle conveniently industrial models, which are difficult to manipulate in the scope of a simple screen. To do so, form features can be grouped in logical sets of macro-features, generating shapes of a higher level of signification than elementary features. Globally, one has to pass from a feasibility proof to a working prototype.
6.2. Preliminary design Feature based modelling still needs to be extended in the early creative stages of the design, the phase where designers are more concerned by function and overall structure of the designed product than by detailed geometry [34]. At these stages, designers know the required functionality of the device but they have no idea about its implementation and appearance. First, designers determine the functions that the design should perform corresponding to the functional design. Then, they determine how functions can be realised by physical entities and the constraints involved by functional requirements. This leads to create a model with functional features in an abstract form. The form features editor can be used to create this model. Next, designers should be able to evaluate the created model to check that all expected functions occur. For that purpose, simulations using analysis processes are performed. This requires model idealisation, which can be conducted by the tool simplification and idealisation process. On the basis of the simulation, designers could modify the model to enhance the product until the functional requirements are reached. This implies features parameters’ modifications and addition or suppression of features. The form features editor is best suited to perform this task, thanks to features parameterisation and instantiation. Then, they proceed into the detailed definition of the product by generating the corresponding geometry, which can be done with the reconstruction module. 6.3. Limitations and future work In the processes described above, some limitations still exist. As noted in the classification of morphological features section, the complex contours would “require a 2D analysis, which corresponds to the 3D morphological
7. Conclusion This paper describes a tool for linking analysis and CAD systems using a form feature-based approach. This tool is based on a morphological analysis of the product model followed by a two-phase process: simplification and idealisation. The description of an object as an initial gross shape that has been successively modified by the adjunction of form features enables a hierarchical idealisation of the object through simple and fast processes. The use of reconstruction operators makes it possible to recreate a solid model on the basis of the idealised model. The reconstruction operators are parameterised, so the recreated model integrates the parameters’ modifications implied by the analysis results. This scheme presents interesting capabilities to link analysis applications to design and manufacturing, and to parameterise efficiently design models as well.
Acknowledgements The authors gratefully acknowledge CORETECH International for its contribution in providing the TRANS-3D software.
References [1] Armstrong CG, Sheehy DJ, Robinson DJ. Computing the medial surface of a solid from a domain delaunay triangulation. (EDS) Third Symposium on Solid Modeling and Applications, May 1995. p. 201–12. [2] Reddy JM, Turkiyyah GM. Computation of 3d skeletons using a generalised delaunay triangulation technique. Computer-Aided Design 1995;27(9):677–94.
388
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[3] Armstrong CG. Modelling requirements for finite-element analysis. Computer-Aided Design 1994;26:573–8. [4] Prabhakar V, Dabke P, Sheppard S. Using features to support finite element idealizations. Computer in Engineering ASME 1994;1:183– 93. [5] Rezayat M. Midsurface abstraction from 3d solid models: general theory and applications. Computer-Aided Design 1996;28(11):905– 15. [6] Pratt MJ, Wilson PR. Requirements for support of form features in a solid modelling system. CAM-I Report R-85-ASPP-01, June 1985. [7] Cunningham JJ, Dixon JR. Designing with features: the origin of features, ASME computers in engineering, San Francisco, USA, July/August. 1988. p. 237–43. [8] Rossignac JR. Issues on feature based editing and interrogation of solid models. Computer and Graphics 1990;14(2):149–72. [9] Shah JJ. Conceptual development of form features and feature modelers, Research in engineering design, vol. 2. New York: Springer, 1991. p. 93–108. [10] Hoffmann CM, Juan R. Erep—an editable, high-level representation for geometric design and analysis. In: Wilson PR, Wozny MJ, Pratt MJ, editors. Geometric and product modeling, Amsterdam: Elsevier, 1993. p. 129–64. [11] Chen X, Hoffmann CM. Design compilation of feature-based and constraint-based CAD, Solid modeling’95, Salt Lake City, UT1995. p. 13–9. [12] Middledicth A, Reade C. A kernel for geometric features, Solid modeling’97, Atlanta, GA1997. p. 13–9. [13] Kyprianou LK. Shape classification in computer-aided design. PhD thesis, University of Cambridge, UK, July 1980. [14] Henderson MR, Anderson DC. Computer recognition and extraction of form features: a CAD/CAM link. Computers in Industry 1984;5:329–39. [15] Falcidieno B, Giannini F. In: Marechaled G, editor. Extraction and organisation of form features into a structured boundary model, EUROGRAPHICS’87Amsterdam: Elsevier, 1987. p. 249–59. [16] Joshi S, Chang TC. Graph-based heuristics for recognition of machined features from a 3D solid model. Computer-Aided Design 1988;20(2):58–66. [17] Woo TC. Feature extraction by volume decomposition. CAD/CAM technology in mechanical engineering, Cambridge, MA, 1982. p. 76– 94. [18] Ferreira JC, Hinduja S. Convex hull-based feature-recognition method for 2.5D components. Computer-Aided Design 1990;22(1):41–9. [19] Kim YS. Recognition of form features using convex decomposition. Computer-Aided Design 1992;24(9):461–76. [20] Shen Y, Shah JJ, Shirur A. Determination of machining volumes from extensible sets of design features. In: Shah J, Nau D, Mantyla M, editors. Advances in feature-based manufacturing, Amsterdam: Elsevier, 1994. p. 129–57. [21] Tseng Y, Joshi SB. Recognizing multiple interpretations of interacting machining features. Computer-Aided Design 1994;26(9):667–88. [22] Sakurai H, Dave P. Volume decomposition and feature recognition. Part II. Curved objects . Computer-Aided Design 1996;28(7):519–37. [23] Vandenbrande JH, Requicha AAG. Geometric computation for the recognition of spatially interacting machining features. In: Shah J, Nau D, Mantyla M, editors. Advances in feature-based manufacturing, Amsterdam: Elsevier, 1994. [24] Regli WC. Geometric algorithms for recognition of features from solid models. PhD thesis, Computer Science Department, University of Maryland, Maryland, 1995. [25] Han JJ. 3D geometric reasoning algorithms for features recognition. PhD thesis, Computer Science Department, University of Southern California, Southern California, 1996. [26] Shah JJ. Feature transformations between application-specific feature spaces. Computer-Aided Engineering Journal 1988;5/6:247–55. [27] Bronsvoort WF, Jansen FW. Feature modelling and conversion: key
[28]
[29] [30] [31]
[32] [33] [34]
concepts to concurrent engineering. Computers in Industry 1993;21:61–86. Kraker KJ, Dohmen M, Bronsvoort WF. Multiple-way feature conversion to support concurrent engineering, Solid modeling’95, Salt Lake City, UT1995. p. 105–14. Kraker KJ, Dohmen M, Bronsvoort WF. Maintaining multiple views in feature modeling, Solid modeling’97, Atlanta, GA1997. p. 123–30. Suh YS, Wozny MJ. Interactive feature extraction for a form feature conversion system, Solid modeling’97, Atlanta, GA1997. p. 111–22. Brun JM. From characteristic shapes to form features. IFIP international conference on feature modeling and recognition. In Advanced CAD/CAM Systems, Valenciennes, 1994. p. 315–26. Brun JM, Tehari A, Bouras A. Extraction multi-vue des formes caracteristiques. Journal of CAD/CAM and CG 1997;12(1/2):17–32. Mantyla M. An introduction to solid modeling. Computer Science Press, 1988. Mantyla M, Shah J. Parametric and feature-based CAD/CAM: concepts, techniques, and applications. New York: Wiley, 1995.
Mohamed Belaziz is a PhD student in Computer Science at Claude Bernard University. He received his master diploma (Diploˆme d’Etudes Approfondies) in Computer Science from Claude Bernard University of Lyon and his Diploma of Engineer in Computer Science from The National Institute of Computer Science (INI) of Algiers. His research interests are in geometric modelling, feature modelling and model idealisation.
Jean Marc Brun is currently Professor of Computer Science at ESIL (Ecole Superieure d’Ingenieurs de Luminy) and Director of XAOlab at the University Aix-Marseille. He received the Degree of “Docteur d’Etat” (State Doctor) at Paris University in 1969 for his thesis on “Steady and unsteady motion of airfoils in supersonic flows”. He derived the EUCLID Project 1970 to 1979 at CNRS, then was a founder of Datavision in 1979 (Matra Datavision in 1980). In 1988, he founded Coretech International, and was Professor in Lyon University from 1991 to 1998. In 1999, he joined Aix-Marseille University to found XAOlab a joint venture between University and Industry. During the 1970s, his research activities turned on fluid mechanics to geometric modeling and image synthesis applied to CAD/CAM systems.
Abdelaziz Bouras is an associate professor of Computer Science, and Head of the Technical Modeling Group at Claude Bernard University of Lyon, France. He was in 1998 at the Manufacturing Engineering Laboratory (MEL) of National Institute of Standards and Technology (NIST) as a Guest Researcher. He received his PhD in Computer Science from Claude Bernard University in 1992 and his Engineer Diploma in Mechanical Engineering in 1987 from The National Institute of Mechanical Engineering (INGM) of Boumerdas, Algeria. His research interests are in solid and feature based modeling, collaborative design, and data exchange.