NDLI: Reliability estimation of washing machine spider assembly via classification

Content Provider	Springer Nature Link
Author	Gorguluarslan, Recep Kim, Eui Soo Choi, Seung Kyum Choi, Hae Jin
Copyright Year	2014
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.
Starting Page	1581
Ending Page	1591
Page Count	11
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	72
Issue Number	9-12
e-ISSN	14333015
Language	English
Publisher	Springer London
Publisher Date	2014-03-28
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Probabilistic neural network Latin hypercube sampling Front loading washing machine Reliability Industrial and Production Engineering Production/Logistics/Supply Chain Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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