Mereotopological assembly joint information representation for collaborative product design

  • Authors:

  • Kyoung-Yun Kim;Hyungjeong Yang;Dong-Won Kim

  • Affiliations:

  • Department of Industrial and Manufacturing Engineering, Wayne State University, Detroit, MI 48202, USA;School of Electronics and Computer Engineering, Chonnam National University, Gwangjusi, South Korea;Department of Industrial and Information Systems Engineering, The Research Center of Industrial Technology, Chonbuk National University, Jeonjusi, South Korea

  • Venue:
  • Robotics and Computer-Integrated Manufacturing
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper we discuss an ontology-based representation method for differentiating assembly joints in collaborative and intelligent product design. As design becomes increasingly knowledge-intensive, intelligent, and collaborative, the need becomes more critical for computational frameworks that enable product development by effectively supporting the formal representation, capture, retrieval, and reuse of product knowledge. Joints are a key aspect of assembly models that are often ambiguous when model sharing takes place. Although various joints may have similar geometries and topologies, the physical implications of the selected joining processes may vary significantly. It is possible to attach notes and annotations to geometric entities in order to distinguish joints; however, such textual information does not readily prepare the model for downstream activities, such as simulation and analysis. As an illustration, analysts must read and interpret the annotations in order to develop the appropriate boundary conditions. In this work, we present an assembly design ontology that explicitly represents assembly constraints, including joining constraints, and infers any remaining implicit ones. By relating concepts through ontology technology rather than just defining data syntax, assembly and joining concepts can be captured in their entirety or extended as necessary. By using the knowledge captured by the ontology, similar looking joints can be differentiated. For this research, we used a mereotopology, which is a region-based theory for parts, and the Semantic Web Rule Language (SWRL) to represent the difference of joints and to define assembly design terms and their relationships. We also used SWRL so that the joining rules can be reasoned to differentiate assembly joints. Finally, by using an ontology, various geometrically and topologically similar joints are successfully differentiated in a standard and machine-interpretable manner.