3 research outputs found

    On the effects of the fix geometric constraint in 2D profiles on the reusability of parametric 3D CAD models

    Get PDF
    [EN] In order to be reusable, history-based feature-based parametric CAD models must reliably allow for modifications while maintaining their original design intent. In this paper, we demonstrate that relations that fix the location of geometric entities relative to the reference system produce inflexible profiles that reduce model reusability. We present the results of an experiment where novice students and expert CAD users performed a series of modifications in different versions of the same 2D profile, each defined with an increasingly higher number of fix geometric constraints. Results show that the amount of fix constraints in a 2D profile correlates with the time required to complete reusability tasks, i.e., the higher the number of fix constraints in a 2D profile, the less flexible and adaptable the profile becomes to changes. In addition, a pilot software tool to automatically track this type of constraints was developed and tested. Results suggest that the detection of fix constraint overuse may result in a new metric to assess poor quality models with low reusability. The tool provides immediate feedback for preventing high semantic level quality errors, and assistance to CAD users. Finally, suggestions are introduced on how to convert fix constraints in 2D profiles into a negative metric of 3D model quality.The authors would like to thank Raquel Plumed for her support in the statistical analysis. This work has been partially funded by Grant UJI-A02017-15 (Universitat Jaume I) and DPI201784526-R (MINECO/AEI/FEDER, UE), project CAL-MBE. The authors also wish to thank the editor and reviewers for their valuable comments and suggestions that helped us improve the quality of the paper.González-Lluch, C.; Company, P.; Contero, M.; Pérez Lopez, DC.; Camba, JD. (2019). On the effects of the fix geometric constraint in 2D profiles on the reusability of parametric 3D CAD models. International Journal of Technology and Design Education. 29(4):821-841. https://doi.org/10.1007/s10798-018-9458-zS821841294Ait-Aoudia, S., & Foufou, S. (2010). A 2D geometric constraint solver using a graph reduction method. Advances in Engineering Software, 41(10), 1187–1194. https://doi.org/10.1016/j.advengsoft.2010.07.008 .Ault, H. K. (1999). Using geometric constraints to capture design intent. Journal for Geometry and Graphics, 3(1), 39–45.Ault, H. K. (2004). Over-constrained, under-constrained or just right? Goldilocks evaluates DOF of sketched profiles. Paper presented at American Society for Engineering Education, 59th annual midyear meeting past, present and future? Williamsburg, November 21–23.Ault, H. K., Bu, L., & Liu, K. (2014). Solid modeling strategies-analyzing student choices. Paper presented at proceedings of the 121st ASEE annual conference and exposition, Indianapolis, June 15–18.Ault, H. K., & Fraser, A. (2013). A comparison of manual vs. online grading for solid models. Paper presented at 120th ASEE annual conference and exposition, Atlanta, GA, June 23–26, 2013, Paper ID #7233.Barbero, B. R., Pedrosa, C. M., & Samperio, R. Z. (2016). Learning CAD at university through summaries of the rules of design intent. International Journal of Technology and Design Education. https://doi.org/10.1007/s10798-016-9358-z .Bodein, Y., Bertrand, R., & Caillaud, E. (2014). Explicit reference modeling methodology in parametric CAD system. Computers in Industry, 65(1), 136–147. https://doi.org/10.1016/j.compind.2013.08.004 .Bouma, W., Fudos, I., Hoffmann, C., Cai, J., & Paige, R. (1995). Geometric constraint solver. Computer-Aided Design, 27(6), 487–501. https://doi.org/10.1016/0010-4485(94)00013-4 .Briggs, J. C., Hepworth, A. I., Stone, B. R., Cobum, J. Q., Jensen, C. G., & Red, E. (2015). Integrated, synchronous multi-user design and analysis. Journal of Computing and Information Science in Engineering, 15(3), 031002. https://doi.org/10.1115/1.4029801 .Buckley, J., Seery, N., & Canty, D. (2017). Heuristics and CAD modelling: An examination of student behaviour during problem solving episodes within CAD modelling activities. International Journal of Technology and Design Education. https://doi.org/10.1007/s10798-017-9423-2 .Camba, J. D., & Contero, M. (2015). Assessing the impact of geometric design intent annotations on parametric model alteration activities. Computers in Industry, 71, 35–45. https://doi.org/10.1016/j.compind.2015.03.006 .Camba, J. D., Contero, M., & Company, P. (2016). Parametric CAD modeling: An analysis of strategies for design reusability. Computer-Aided Design, 74, 18–31. https://doi.org/10.1016/j.cad.2016.01.003 .Camba, J. D., Contero, M., & Company, P. (2017). CAD reusability and the role of modeling information in the MBE context. Model-based enterprise summit 2017. National Institute of Standards and Technology (NIST), Gaithersburg, MD, April 3–7. MBE17-020. https://www.nist.gov/file/361581 .Cheng, Z., & Ma, Y. (2017). A functional feature modeling method. Advanced Engineering Informatics, 33, 1–15. https://doi.org/10.1016/j.aei.2017.04.003 .Cheng, Z., Xie, Y., & Ma, Y. (2018). Graph centrality analysis of feature dependencies to unveil modeling intents. Computer-Aided Design and Applications. https://doi.org/10.1080/16864360.2018.1441236 .Chester, I. (2007). Teaching for CAD expertise. International Journal of Technology and Design Education, 17, 23–35. https://doi.org/10.1007/s10798-006-9015-z .Company, P., Contero, M., Otey, J., & Plumed, R. (2015). Approach for developing coordinated rubrics to convey quality criteria in CAD training. Computer-Aided Design, 63, 101–117. https://doi.org/10.1016/j.cad.2014.10.00 .Company, P., & González-Lluch, C. (2013). CAD 3D con SolidWorks ® Tomo I: Diseño básico. Publicacions de la Universitat Jaume I. (Colección Sapientia, Núm. 86). http://cad3dconsolidworks.uji.es .Contero, M., Company, P., Vila, C., & Aleixos, N. (2002). Product data quality and collaborative engineering. IEEE Computer Graphics Applications, 22(3), 32–42. https://doi.org/10.1109/MCG.2002.999786 .Dixon, B. M., & Dannenhoffer, J. F., III. (2014). Geometric sketch constraint solving with user feedback. Journal of Aerospace Information Systems, 11(5), 316–325. https://doi.org/10.2514/1.I010110 .Fudos, I., & Hoffmann, C. M. (1997). A graph-constructive approach to solving systems of geometric constraints. ACM Transactions on Graphics, 16(2), 179–216. https://doi.org/10.1145/248210.248223 .Ge, J. X., Chou, S. C., & Gao, X. S. (1999). Geometric constraint satisfaction using optimization methods. Computer-Aided Design, 31(14), 867–879. https://doi.org/10.1016/S0010-4485(99)00074-3 .González-Lluch, C., Company, P., Contero, M., Camba, J. D., & Colom, J. (2017a). A case study on the use of model quality testing tools for the assessment of MCAD models and drawings. International Journal of Engineering Education, 33(5), 1643–1653.González-Lluch, C., Company, P., Contero, M., Camba, J. D., & Plumed, R. (2017b). A survey on 3D CAD model quality assurance and testing tools. Computer-Aided Design, 83, 64–79. https://doi.org/10.1016/j.cad.2016.10.003 .Hamade, R. F. (2009). Profiling the desirable CAD trainee: Technical background, personality attributes, and learning preferences. Journal of Mechanical Design, 131(12), 121009–121019. https://doi.org/10.1115/1.4000455 .Hekman, K. A., & Gordon, M. T. (2013). Automated grading of first year student CAD work. Paper presented at the 120th ASEE annual conference and exposition 2013, Atlanta, GA, June 23–26. Paper ID #6379.Hepworth, A., Tew, K., Trent, M., Ricks, R., Jensen, C. G., & Red, E. R. (2014). Model consistency and conflict resolution with data preservation in multi-user computer aided design. Journal of Computing and Information Science in Engineering, 14(2), 021008. https://doi.org/10.1115/1.4026553 .Jackson, C., & Buxton, M. (2007). The design reuse benchmark report: Seizing the opportunity to shorten product development. Boston: Aberdeen Group.Joan-Arinyo, R., Soto-Riera, A., Vila-Marta, S., & Vilaplana-Pastó, J. (2003). Transforming an under-constrained geometric constraint problem into a well-constrained one. Paper presented at proceedings of ACM SM03, Seatle, June 16–20.Kirstukas, S. J. (2016). Development and evaluation of a computer program to assess student CAD models. Paper presented at ASEE annual conference and exposition, New Orleans, June 26.Kramer, G. (1991). Using degrees of freedom analysis to solve geometric constraint systems. Paper presented at proceedings of the first ACM symposium on solid modeling foundations and CAD/CAM applications 1991, Austin, June 05–07.Kwon, S., Kim, B. C., Mun, D., & Han, S. (2015). Graph-based simplification of feature-based three-dimensional computer-aided design models for preserving connectivity. Journal of Computing and Information Science in Engineering, 15(3), 031010. https://doi.org/10.1115/1.4030748 .Leea, J. Y., & Kimb, K. (1998). A 2-D geometric constraint solver using DOF-based graph reduction. Computer-Aided Design, 30(11), 883–896. https://doi.org/10.1016/S0010-4485(98)00045-1 .Mata Burgarolas, N. (1997). Solving incidence and tangency constraints in 2D. Technical report LSI-97-3R, Departament LiSI, Universitat Politècnica de Catalunya.Petrina, S. (2003). Two cultures of technical courses and discourses: The case of computer aided design. International Journal of Technology and Design Education, 13, 47–73.Race, P. (2001). The lecturers toolkit—A practical guide to learning, teaching and assessment. Great Britain: Glasgow.Red, E., French, D., Jensen, G., Walker, S. S., & Madsen, P. (2013). Emerging design methods and tools in collaborative product development. Journal of Computing and Information Science in Engineering, 13(3), 031001. https://doi.org/10.1115/1.4023917 .Robertson, B. F., Walther, J., & Radcliffe, D. (2007). Creativity and the use of CAD tools: Lessons for engineering design education from industry. Journal of Mechanical Design, 129(7), 753–760. https://doi.org/10.1115/1.2722329 .Stone, B., Salmon, J., Eves, K., Killian, M., Wright, L., Oldroyd, J., et al. (2017). A multi-user computer-aided design competition: Experimental findings and analysis of team-member dynamics. Journal of Computing and Information Science in Engineering, 17(3), 031003. https://doi.org/10.1115/1.4035674 .Summers, J. D., & Shah, J. J. (2010). Mechanical engineering design complexity metrics: Size, coupling, and solvability. Journal of Mechanical Design, 132(2), 21004–21015. https://doi.org/10.1115/1.4000759 .Szewczyk, J. (2003). Difficulties with the novices’ comprehension of the computer-aided design (CAD) interface: Understanding visual representations of CAD tools. Journal of Engineering Design, 14(2), 169–185. https://doi.org/10.1080/0954482031000091491

    Towards a better integration of modelers and black box constraint solvers within the Product Design Process

    Get PDF
    This paper presents a new way of interaction between modelers and solvers to support the Product Development Process (PDP). The proposed approach extends the functionalities and the power of the solvers by taking into account procedural constraints. A procedural constraint requires calling a procedure or a function of the modeler. This procedure performs a series of actions and geometric computations in a certain order. The modeler calls the solver for solving a main problem, the solver calls the modeler’s procedures, and similarly procedures of the modeler can call the solver for solving sub-problems. The features, specificities, advantages and drawbacks of the proposed approach are presented and discussed. Several examples are also provided to illustrate this approach

    Direct tree decomposition of geometric constraint graphs

    Get PDF
    The evolution of constraint based geometric models is tightly tied to parametric and feature-based Computer-Aided Design (CAD) systems. Since the introduction of parametric design by Pro/Engineer in the 1980's, most major CAD systems adopted constraint based geometric models as a core technology. Constraint based geometric models allowed CAD systems to provide a more powerful data model while offering an intuitive user interface. Later on, the same models also found application to fields like linkage design, chemical modeling, computer vision and dynamic geometry. Constraint based geometric models are unevaluated models. A key problem related to constraint based geometric models is the geometric constraint based solving problem which, roughly speaking, can be stated as the problem of evaluating a constraint based model. Among the different approaches to geometric constraint solving, we are interested in graph-based Decomposition-Recombination solvers. In the graph-based constructive approach, the geometric problem is first translated into a graph whose vertices represent the set of geometric elements and whose edges are the constraints. Then the constraint problem is solved by decomposing the graph into a set of sub-problems, each sub-problem is recursively divided until reaching basic problems which are solved by a dedicated equational solver. The solution to the initial problem is computed by merging the solutions to the sub-problems. The approach used by DR-solvers has been particularly successful when the decomposition into subproblems and subsequent recombination of solutions to these subproblems can be described by a plan generated a priori, that is, a plan generated as a preprocessing step without actually solving the subsystems. The plan output by the DR-planner remains unchanged as numerical values of parameters change. Such a plan is known as a DR-plan and the unit in the solver that generates it is the DR-planner. In this setting, the DR-plan is then used to drive the actual solving process, that is, computing specific coordinates that properly place geometric objects with respect to each other. In this thesis we develop a new DR-planner algorithm for graph-constructive two dimensional DR-solvers. This DR-planner is based on the tree-decomposition of a graph. The triangle- or tree-decomposition of a graph decomposes a graph into three subgraphs such that subgraphs pairwise share one vertex. Shared vertices are called hinges. The tree-decomposition of a geometric constraint graph is in some sense the construction plan that solves the corresponding problem. The DR-planner algorithm first transforms the input graph into a simpler, planar graph. After that, an specific planar embedding is computed for the transformed graph where hinges, if any, can be straightly found. In the work we proof the soundness of the new algorithm. We also show that the worst case time performance of the resthe number of vertices of the input graph. The resulting algorithm is easy to implement and is as efficient as other known solving algorithms.L'evolució de models geomètrics basats en restriccions està fortament lligada al sistemes de Disseny Assistit per Computador (CAD) paramètrics i als basats en el paradigma de disseny per mitjà de característiques. Des de la introducció del disseny paramètric per part de Pro/Engineer en els anys 80, la major part de sistemes CAD utilitzaren com a tecnologia de base els models geomètrics basats en restriccions. Els models geomètrics basats en restriccions permeteren als sistemes CAD proporcionar un model d'informació més ampli i alhora oferir una interfície d'usuari intuitiva. Posteriorment, els mateixos models s'aplicaren en camps com el disseny de mecanismes, el modelatge químic, la visió per computador i la geometria dinàmica. Els models geomètrics basats en restriccions són models no avaluats. Un problema clau relacionat amb el models de restriccions geomètriques és el problema de la resolució de restriccions geomètriques, que es resumeix com el problema d'avaluar un model basat en restriccions. Entre els diferents enfocs de resolució de restriccions geomètriques, tractem els solvers de Descomposició-Recombinació (DR-solvers) basats en graphs. En l'enfoc constructiu basat en grafs, el problema geomètric es trasllada en un pas inicial a un graf, on els vèrtexs del graf representen el conjunt d'elements geomètrics i on les arestes corresponen a les restriccions geomètriques entre els elements. A continuació el problema de restriccions es resol descomposant el graf en un conjunt de subproblemes, cadascun dels quals es divideix recursivament fins a obtenir problemes bàsics, que sovint són operacions geomètriques realitzables, per exemple, amb regle i compàs, i que es resolen per mitjà d'un solver numèric específic. Finalment, la solució del problema inicial s'obté recombinant les solucions dels subproblemes. L'enfoc utilitzat pels DR-solvers ha esdevingut especialment interessant quan la descomposició en subproblemes i la posterior recombinació de solucions d'aquests subproblemes es pot descriure com un pla de construcció generat a priori, és a dir, un pla generat com a pas de pre-procés sense necessitat de resoldre realment els subsistemes. El pla generat pel DR-planner esdevé inalterable encara que els valors numèrics dels paràmetres canviin. Aquest pla es coneix com a DR-plan i la unitat en el solver que el genera és l'anomenat DR-planner. En aquest context, el DR-plan s'utilitza com a eina del procés de resolució en curs, és a dir, permet calcular les coordenades específiques que correctament posicionen els elements geomètrics uns respecte els altres. En aquesta tesi desenvolupem un nou algoritme que és la base del DR-planner per a DR-solvers constructius basats en grafs en l'espai bidimensional. Aquest DR-planner es basa en la descomposició en arbre d'un graf. La descomposició en triangles o arbre de descomposició d'un graf es basa en descomposar un graf en tres subgrafs tals que comparteixen un vèrtex 2 a 2. El conjunt de vèrtexs compartits s'anomenen \emph{hinges}. La descomposició en arbre d'un graf de restriccions geomètriques equival, en cert sentit, a resoldre el problema de restriccions geomètriques. L'algoritme del DR-planner en primer lloc transforma el graf proporcionat en un graf més simple i planar. A continuació, es calcula el dibuix en el pla del graf transformat, on les hinges, si n'hi ha, es calculen de manera directa. En aquest treball demostrem la correctesa del nou algoritme. Finalment, proporcionem l'estudi de la complexitat temporal de l'algoritme en cas pitjor i demostrem que és quadràtica en el nombre de vèrtexs del graf proporcionat. L'algoritme resultant és senzill d'implementar i tan eficient com altres algoritmes de resolució concret
    corecore