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Reliability estimation of washing machine spider assembly via classification

  • Recep Gorguluarslan
  • Eui-Soo KimEmail author
  • Seung-Kyum Choi
  • Hae-Jin Choi
ORIGINAL ARTICLE

Abstract

This paper presents a study on the reliability estimation of the spider assembly of the front loading washing machine. To achieve the analytical certification of the current design of the spider assembly of the washing machine, fatigue life test, finite element analysis, physical experimentation, and a classification processes were conducted. First, the conventional finite element analysis and fatigue life analysis were conducted and their simulation results have been validated by physical experiments in this research. The probability of failure is estimated by a classification process. Specifically, the probabilistic neural network classifier is incorporated into the simulation process to reduce the number of finite element analysis calculations while ensuring the prediction accuracy of the failure probability. Based on the estimated failure probability and other structural analysis results, the margin of the performance of the spider assembly is fully identified.

Keywords

Probabilistic neural network Latin hypercube sampling Front loading washing machine Reliability 

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Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  • Recep Gorguluarslan
    • 1
  • Eui-Soo Kim
    • 2
    Email author
  • Seung-Kyum Choi
    • 1
  • Hae-Jin Choi
    • 3
  1. 1.G.W. Woodruff School of Mechanical EngineeringGeorgia Institute of TechnologyAtlantaUSA
  2. 2.National Forensic ServiceSeoulSouth Korea
  3. 3.School of Mechanical EngineeringChung-Ang UniversitySeoulSouth Korea

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