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Civil-Comp Proceedings
ISSN 1759-3433 CCP: 81
PROCEEDINGS OF THE TENTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING Edited by: B.H.V. Topping
Paper 19
Optimizing the Design of an Attribute Double Sampling Plan T.M. Cheng and Y.L. Chen
Department of Construction Engineering, Chaoyang University of Technology, Taiwan, R.O.C. Full Bibliographic Reference for this paper
T.M. Cheng, Y.L. Chen, "Optimizing the Design of an Attribute Double Sampling Plan", in B.H.V. Topping, (Editor), "Proceedings of the Tenth International Conference on Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Stirlingshire, UK, Paper 19, 2005. doi:10.4203/ccp.81.19
Keywords: attribute double sampling plan, genetic algorithms, lot-by-lot acceptance sampling.
Summary
An acceptance-sampling (AS) plan is a statement of the sample size to be used
and the associated acceptance or rejection criteria for sentencing an individual lot.
There are different ways for classifying AS plans. One major classification is by
attributes and variables. Variables are quality characteristics that are measured on a
numerical scale and attributes are quality characteristics that are expressed on "go"
and "no-go" basis. Performing a variables sampling plan (VSP) requires basic
statistical knowledge such as the calculation of the standard deviation and the decision
parameter as well as checking the quality index table. In contrast to a VSP, the attributes
sampling plan (ASP) is easy to use and does not involve statistical calculation for
processing data. Construction inspectors usually do not have the statistical knowledge
necessary for data processing in a VSP [1]. Hence, an ASP plays an important role in the
design quality assurance specification in construction.
An ASP can be categorized as single or double sampling depending on the number of samples taken. In a single sampling plan, the decision to accept or reject a lot is based on one sample. However, in a double sampling plan, a second sample may be required before a lot can be be accepted or rejected. This depends on whether the first sample conforms or does not conform to the specified requirements. Otherwise, the second sample has to be taken before a decision is made. Since the sampling phase is divided into two stages, as a result, attribute double sampling plan (ADSP) usually (not always) uses a smaller sample size and is commonly used in designing quality assurance specification [1,2].
To properly design an ADSP, the users first have to focus on certain points on the
operation characteristics (OC) curve which plots the probability of accepting the lot
versus the lot fraction that is defective. These points include the AQL-
The smaller the total sample sizes, the less cost and time is required for the quality inspection
process. This is true both from the producer's and the consumer's point of view.
However, the trial-and-error method does not guarantee that the minimum sample
sizes can be reached. Moreover, infeasible solutions can be obtained if the fitting of the
OC curve is strictly limited by both the AQL- References
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