• DocumentCode
    1515802
  • Title

    Assemblability based on maximum likelihood configuration of tolerances

  • Author

    Sanderson, Arthur C.

  • Author_Institution
    Nat. Sci. Found., Arlington, VA, USA
  • Volume
    15
  • Issue
    3
  • fYear
    1999
  • fDate
    6/1/1999 12:00:00 AM
  • Firstpage
    568
  • Lastpage
    572
  • Abstract
    An assembly is defined by a configuration of parts of known geometries subject to tolerances in the pose, dimensions, and mating relations among part features. Using a tolerance model based on matrix transforms and Gaussian models of geometric variations, the pose and dimensional tolerance models are considered as a priori models of the assembly with nominal and variational components for both position and orientation. The mating relations are regarded as linear relational constraints, also with nominal and variational components. With this formulation, estimation of the configuration of parts may be posed as a maximum likelihood problem and solved by a Kalman filter algorithm. The resulting maximum likelihood configuration of the assembly may be used to evaluate the required deviation from nominal and the assemblability as defined by the maximum likelihood clearance from constraints. In addition, application of the technique to intermediate subassemblies may be used to evaluate assemblability of specific steps and discriminate among alternative assembly sequence plans
  • Keywords
    Gaussian distribution; Kalman filters; assembly planning; design for manufacture; filtering theory; matrix algebra; maximum likelihood estimation; Gaussian models; Kalman filter algorithm; assemblability; dimensional tolerance model; geometric variations; intermediate subassemblies; linear relational constraints; mating relations; matrix transforms; maximum likelihood tolerance configuration; pose tolerance model; tolerance model; variational components; ANSI standards; Assembly; Fixtures; Information geometry; Manufacturing; Maximum likelihood estimation; Product design; Solid modeling; Stability; Uncertainty;
  • fLanguage
    English
  • Journal_Title
    Robotics and Automation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1042-296X
  • Type

    jour

  • DOI
    10.1109/70.768188
  • Filename
    768188