By Edward G. Schilling
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Additional resources for Acceptance Sampling in Quality Control, Second Edition (Statistics: Textbooks and Monographs)
Nelson for his continued interest and suggestions, and Dan J. Sommers and Professor Emil Jebe for their constructive comments and theoretical insight. Certainly, my appreciation goes to Dr. Donald P. Petarra, Dr. James R. Donnalley, and Dr. Pieter J. von Herrmann of the General Electric Lighting Research and Technical Services Operation for their encouragement and support throughout. I am indebted to the American Society for Quality Control, the American Society for Testing and Materials, the American Statistical Association, the Institute of Mathematical Statistics, the Philips Research Laboratories, the Royal Statistical Society, and Bell Laboratories for their permission to reprint a variety of material taken from their publications.
The sampling plan to be employed is to sample two items and accept the lot if no defectives are obtained. Reject if one or more are found. Thus, the sampling plan is n ¼ 2 and c ¼ 0, where n is the sample size and c represents the acceptance number or maximum number of defectives allowed in the sample for acceptance of the lot. If the items are removed from the shipping container one at a time, we may ask in how many different orders (permutations) the three items can be removed from the box. Suppose the serial numbers are the same except for the last digit which is 5, 7, and 8, respectively.
They are also used to isolate evidence of the nature of the ‘‘assignable cause’’ of an out of control point. These methods, covered in the literature of statistical quality control, should be utilized by qualiﬁed individuals to determine the fundamental causes of process shifts before evidence from control charts which are out of control is used in setting up an acceptance sampling plan. Instructions for constructing a control chart will be found in any basic text on quality control (Burr 2005).