This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
SPC in Filtration for Non-normal Distribution
Technical Paper
1999-01-0009
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
The validity of many statistical methods, including statistical process control (SPC) rests on the assumption that the probability distribution is nearly normal. The assumption of normal distribution of variables is not critical in the construction of a confidence interval; however, it is important in constructing a tolerance interval to include a specified proportion of the population. The application of SPC to an industrial process whose variables cannot be described by a normal distribution can be a major source of error and frustration. An assumption of normal distribution for some filter performance characteristics can be unrealistic and these characteristics cannot be adequately described by a normal distribution.
A transformation of data can improve the agreement with normality and can greatly extend the range of validity to statistical methods. This paper examines some transformation methods, which can be applied to non-normal distribution.
Filter performance characteristics represent variables, which could be non-normal. This paper highlights some issues of non-normal distribution of filter performance data and addresses methods that make SPC applicable to non-normal distribution of efficiency data.
Authors
Citation
Ptak, T. and Nichols, J., "SPC in Filtration for Non-normal Distribution," SAE Technical Paper 1999-01-0009, 1999, https://doi.org/10.4271/1999-01-0009.Also In
References
- Deming W. E. Out of the Crisis Center for Advanced Engineering Study MIT Cambridge, Mass. 1986
- Statistical Process Control Chrysler Corp., Ford Motor Co., and General Motors Corp. 1992
- Pearson K. Philos. Trans. A. 186 1895
- Johnson N. L. “System of Frequency Curves Generated by Methods of Translation” Biometrika 36 1949
- Shapiro S. S. Gross A. J. Statistical Modeling Techniques Marcel Dekker New York 1981
- Slifker J. F. Shapiro S. S. “The Johnson System: Selection and Parameter Estimation” Technometrics 22 1980
- Shapiro S. S. Wilk M. B. “An Analysis of Variance Test for Normality” Biometrika 52 1965
- Kohler H. Statistics for Business and Economics Scott, Foresman and Co. Glenview, IL 1985
- Jacobs D. C. “Watch out for Nonnormal Distributions” Chemical Engineering Progress Nov. 1990
- Clements J. A. “Process Capability calculations for Non-normal Distributions” Quality Progress Sept. 1989
- Gruska G. F. Mirhani K. Iamberson L. R. Non Normal Data Analysis St. Clair Shores, MI 1989
- Wadsworth H. M. Handbook of Statistical Methods for Engineers and Scientists McGraw-Hill Publishing Co. 1990