A novel approach to recognize interacting features for manufacturability evaluation of prismatic parts with orthogonal features

  • Manish Kumar Gupta
  • Abinash Kumar SwainEmail author
  • Pramod Kumar Jain


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.


Feature recognition Volume subtraction Face adjacency matrix Manufacturability Geometrical complexity Technological complexity 


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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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • Manish Kumar Gupta
    • 1
  • Abinash Kumar Swain
    • 1
    Email author
  • Pramod Kumar Jain
    • 1
  1. 1.Department of Mechanical & Industrial EngineeringIndian Institute of TechnologyRoorkeeIndia

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