Predicting Failure Rates in Low Usage Gray and Ductile Iron Castings

Predicting Failure Rates in Low Usage Gray and Ductile Iron Castings
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Publisher :
Total Pages : 122
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ISBN-10 : OCLC:803980650
ISBN-13 :
Rating : 4/5 (50 Downloads)

Book Synopsis Predicting Failure Rates in Low Usage Gray and Ductile Iron Castings by : Stephen M. Lucas

Download or read book Predicting Failure Rates in Low Usage Gray and Ductile Iron Castings written by Stephen M. Lucas and published by . This book was released on 2011 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study determined the correlation between the failure rate of low-usage gray and ductile iron castings and the weight, annual usage, core usage, inspection procedures, type of sand used, and machining requirements of the castings. Weight was predicted to have a negative correlation, and annual usage a positive correlation. The use of cores with the casting pattern, necessity of downstream machining, use of green sand (without chemical bonding), and use of visual inspection procedures (opposed to non-destructive testing) were all measured as binary variables, and expected to increase the failure rate. Data for 302 castings supplied by 7 different suppliers to a heavy manufacturing company were used for regression analysis to determine which factors or combinations thereof affected the failure rate of castings. While weight was not determined to be a predictor of failure rate in this study, annual usage showed statistical significance in affecting the quality level as predicted, and each binomial measure were correlated as predicted. Specifically, the combination of decreased annual usage, use of cores, downstream machining requirements, use of green sand, and lack of non-destructive testing were determined to predict 84% of the failure rate at .01% confidence. Further, the data was separated by supplier and plotted for midpoint analysis to determine the amount of the failure rate that could be explained by differing supplier competence, which showed no evidence that the choice of supplier significantly affected the reliability of the model.


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