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Multinomial acceptance sampling
Proceedings of the 1966 21st national conference on -, 1966Careless manufacture or assembly will yield an incidence of unsatisfactory output, the percentage of which will drop very rapidly when greater precautions are taken, but will not result in a perfect performance level, and indeed as that ideal is approached, the effort expense required to ensure higher quality rises inordinately for each small gain in ...
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Coal blending—with acceptance sampling
Computers & Operations Research, 1991Abstract This paper presents a blending problem with 1. (a) integer constraints on minimum usage and 2. (b) acceptance sampling with penalty function and rejection. A combination of a “core” integer programming analysis with supporting simulation of stochastic outcomes allows an orderly search for the preferred cost-risk combination.
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Credit to and in acceptance sampling
Statistica Neerlandica, 2006A simple method of controlling average outgoing quality is discussed. It is based on a straightforward definition of credit and proved to be valid under a quite tractable condition. The special case of acceptance sampling by attributes is studied in detail.
Baillie, D.H., Klaassen, C.A.J.
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IEEE Transactions on Reliability, 1972
This tutorial paper shows, via an example, how optimum sampling plans can be derived using Bayesian decision theory. Both nonsequential and sequential sampling plans are described. The Bayesian method is contrasted with classical methods. The salient difference between Bayesian and classical methods is that the Bayesian approach allows one formally to ...
Darrell R. Gimlin, Arthur M. Breipohl
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This tutorial paper shows, via an example, how optimum sampling plans can be derived using Bayesian decision theory. Both nonsequential and sequential sampling plans are described. The Bayesian method is contrasted with classical methods. The salient difference between Bayesian and classical methods is that the Bayesian approach allows one formally to ...
Darrell R. Gimlin, Arthur M. Breipohl
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Statistical Acceptance Sampling in a Competitive Environment
Operations Research, 1980This paper presents a model and its solution for a statistical acceptance sample inventory problem in a competitive environment. The model is based upon the theory of games and is applied to a nuclear material accounting example. A game is formulated between a diverter who might deliberately steal valuable nuclear material and a defender who must make
Melvin Dresher, Sidney Moglewer
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2020
Acceptance sampling is the application of hypothesis testing to the decision problem of either accepting a lot, or batch of units, or the process producing those units as “acceptable,” or “rejecting” it as “unacceptable.” Often the null hypothesis is stated in terms of the probability that a randomly selected unit is “unacceptable.” However, the ...
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Acceptance sampling is the application of hypothesis testing to the decision problem of either accepting a lot, or batch of units, or the process producing those units as “acceptable,” or “rejecting” it as “unacceptable.” Often the null hypothesis is stated in terms of the probability that a randomly selected unit is “unacceptable.” However, the ...
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Inspection and acceptance sampling
1996The purpose of acceptance sampling is to provide for the user some assurance that the risks associated with accepting a lot are within specified limits. To do so, it is necessary to specify these risks, state clearly how sample data will be collected and measured, and state for what purpose it will be used and how to reach some conclusion (such as ...
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Quality Engineering, 1999
[This abstract is based on the author's abstract.] A quick graphical method is presented for determining the optimal plan for acceptance sampling for attributes. The standard values for producer's and consumer's risk of a = 5% and b = 10%, respectiv..
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[This abstract is based on the author's abstract.] A quick graphical method is presented for determining the optimal plan for acceptance sampling for attributes. The standard values for producer's and consumer's risk of a = 5% and b = 10%, respectiv..
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