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Journal ArticleDOI

Summary of Recent Work on Variables Acceptance Sampling with Emphasis on Non-normality

D. B. Owen
- 01 Nov 1969 - 
- Vol. 11, Iss: 4, pp 631-637
TLDR
In this paper, a sampling plan for truncated life tests based on the exponential, normal, lognormal, gamma, Weibull, etc., distributions is presented, as well as disbribution-free life test plans based on increasing or decreasing failure rate distributions.
Abstract
Acceptance sampling plans based on the normal distribution have been available since 1955 and before. Yet reports of potential users indicate a general lack of enthusiasm for their application. There is the uncertainty of the assumption of the normal distribution, but the difficulties users have encountered are attributable more to the translation from the standardized deviate to proportion defective than with the probabilities involved. Some possible ways of adjusting for this are discussed. Sampling plans for truncated life tests based on the exponential, normal, lognormal, gamma, Weibull, etc., distributions are also available, as are disbribution-free life test plans based on increasing or decreasing failure rate distributions. These are extremely useful and further extensions of these ideas are in the offing. For the normal distribution, plans have been devised which control each tail of the distribution to separate levels. These plans are useful in the very common situation where defectiveness measu...

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Citations
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Journal ArticleDOI

Non‐Normality and the Design of Control Charts for Averages*

TL;DR: The effects of non-normality, as measured by skewness and kurtosis, on the performance, and hence the design, of control charts for averages are examined and an alternative method of designing charts for averaging data with non-normal distributions is provided.
Journal ArticleDOI

MIL-STD-414 Sampling Procedures and Tables for Inspection by Variables for Percent Defective

TL;DR: In this paper, the MIL-STD-414 Sampling Procedures and Tables for Inspection by Variables for Percent Defective are presented. But they do not specify a set of test cases.
Journal ArticleDOI

Robustness of mean E(X) and R charts

TL;DR: In this article, the effect of nonnormality on E(X) and R charts is examined by comparing the probabilities that E( X and R lie outside their three standard deviation and two standard deviation control limits.
Journal ArticleDOI

Optimal acceptance sampling plans for log-location-scale lifetime models using average risks

TL;DR: The proposed approach extends the traditional sampling plans to those cases in which appreciable prior information on p exists, and also allows the analyst the flexibility to delimitate the range of p and to incorporate into the reliability analysis prior impartiality between the producer and the consumer.
References
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Journal ArticleDOI

Gamma Distribution in Acceptance Sampling Based on Life Tests

TL;DR: In this paper, the gamma distribution is assumed as a model for lifetime and the problem of acceptance sampling when the life test is truncated at a pre- assigned time is discussed.
Journal ArticleDOI

Sampling Plans for Inspection by Variables

TL;DR: In this paper, the authors performed a study under the sponsorship of the office of Naval Research (ONR) under the name of "Naval research under the patronage of Albert H. Bowker".
Journal ArticleDOI

Life Test Sampling Plans for Normal and Lognormal Distributions

TL;DR: In this paper, sampling plans for truncated life tests from the normal and lognormal distributions are obtained, and the operating characteristic functions of these plans are obtained and for a wide range of values of practical interest these functions are graphed in order to facilitate selection of an appropriate plan in a given situation.
Journal ArticleDOI

Two Theorems for Inferences about the Normal Distribution with Applications in Acceptance Sampling

TL;DR: In this article, two theorems are presented which are useful in making inferences about the univariate normal distribution, i.e., the expected value of the cumulative distribution function of the normal (0, 1) distribution, when the argument of this function is a linear combination of a normal and an independent chi random variable.