Constraint-Aided Conceptual Design (Engineering Research by Barry A. O'Sullivan

By Barry A. O'Sullivan

A name within the “Engineering examine sequence” Constraint-Aided Conceptual Design is anxious with that section of product improvement in which the dressmaker takes a specification for the product and generates many huge suggestions to accomplish the outcome. This helpful e-book deals a computational reasoning resolution in response to the idea of constraint filtering because the foundation of an interactive layout aid software to aid a human dressmaker operating within the conceptual part of layout. utilizing this interactive layout help software, the clothier should be assisted in developing versions of proposed schemes which fulfill a number of the constraints which are imposed at the layout.


  • Background
  • Theory
  • Implementation strategy
  • Illustration and validation
  • Conclusions
  • An review of Galileo
  • Generic layout concepts
  • An illustrative example
  • An business case study.

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Knowledge acquisition method for conceptual design based on value engineering and axiomatic design theory. Artificial Intelligence in Engineering, 1:187–202, 1996. 63. J. C. G. Rees. Decision support for conceptual bridge design. Artificial Intelligence in Engineering, 11:259–272, 1997. 64. M. Stacey, H. Sharp, M. Petre, G. Rzevski, and R. Buckland. A representation scheme to support conceptual design of mechatronic systems. In J. Gero and F. Sudweeks, editors, Artificial Intelligence in Design ’96, pages 583–602, Kluwer Academic Press, 1996.

Computer-aided Design, 30(1):19–27, 1998. 44. K. J. de Kraker. Feature Conversion for Concurrent Engineering. PhD thesis, Technische Universiteit Delft, 1997. 45. J. Pratt. Solid modelling and the interface between design and manufacturing. IEEE Computer Graphics and Applications, pages 52–59, 1984. 46. R. J. Pratt. A taxonomy of features for solid modelling. W. L. Encarnaça o, editors, Geometric Modelling for CAD Applications, pages 76–94. North-Holland, 1988. 47. J. Pabon, R. Young, and W. Keirouz.

4 The Pareto optimal set of solutions to a multiple objective optimization problem The point X is not dominated by any other solution since there is no solution better than it in terms of Objective 2. The point Y is not dominated by any other solution since there is no solution better than it in terms of both Objective 1 and Objective 2, simultaneously. The point Z is not dominated by any other solution since there is no solution better than it in terms of Objective 1. Two dominated solutions are shown in Fig.

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