A novel approach to recognize interacting features for manufacturability evaluation of prismatic parts with orthogonal features ORIGINAL ARTICLE First Online: 08 August 2019 Abstract
This paper describes a computer-aided tool for the quantitative evaluation of manufacturability of prismatic machining parts. A feature recognition approach, which uses volume subtraction and syntactic pattern recognition techniques, is proposed to identify machining features on a prismatic part from B-Rep data extracted from 3D model in STEP AP203 format. The methodology presented is also capable of identifying features in variety cases of feature interactions. The manufacturability of a part is expressed in terms of relative manufacturability indices of its constituting features. The present work considers the geometrical aspects of the designed product along with manufacturing issues at a very early stage of design. Geometrical and technological complexities of the design are established using several parameters such as feature intricacy, tool access direction, feature face orientation, feature accessibility, approach direction depth, feature neighborhood, feature hierarchy, parent and child feature complexities, tolerances, surface finish, and tooling complexities which affect the manufacturability of a feature on the part directly or indirectly. The best worst method (BWM) is used to assign weights to manufacturability parameters to reflect their relative importance. A case study is presented to show the capability of the system to generate sound indices that could make designs easier to manufacture without compromising on the functional requirements.
Keywords Feature recognition Volume subtraction Face adjacency matrix Manufacturability Geometrical complexity Technological complexity Notes Funding information
The authors received financial support from the Ministry of Human Resource Development, Government of India, to carry out the research work.
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Appendix 2. Sample calculations of the geometrical indices for sample part References
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