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A new method in selective assembly for components with skewed distributions

Author

Listed:
  • S.M. Kannan
  • R. Sivasubramanian
  • V. Jayabalan

Abstract

A product consists of two or more components assembled together is an assembly. The quality of the product depends upon the quality of the assembly. The contributing quality characteristics of the mating parts play a major role. A good amount of research has been carried out to improve the quality of assembly using selective assembly, when the contributing quality characteristics confirms to normal distribution. However, in reality, the contributing quality characteristics of a component will have some skewness, which will make the models proposed by earlier researcher not suitable for practice. In this paper, a new method is proposed with component quality characteristics having skewness and selective assembly can be effectively used to meet the specification requirements without any surplus parts. The proposed method ensures that all the components of the mating part population is used and at the same time there is minimum variation in the assembly even there is skewness in the dimensional distribution of the mating parts. Genetic algorithm (GA) is used to find the number of components in selective group combinations for a given clearance variation.

Suggested Citation

  • S.M. Kannan & R. Sivasubramanian & V. Jayabalan, 2009. "A new method in selective assembly for components with skewed distributions," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 4(5/6), pages 569-589.
    • Handle: RePEc:ids:ijpqma:v:4:y:2009:i:5/6:p:569-589
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    Cited by:

    1. Lenin Nagarajan & Siva Kumar Mahalingam & Jayakrishna Kandasamy & Selvakumar Gurusamy, 2022. "A novel approach in selective assembly with an arbitrary distribution to minimize clearance variation using evolutionary algorithms: a comparative study," Journal of Intelligent Manufacturing, Springer, vol. 33(5), pages 1337-1354, June.

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