Cost-optimal multistage sampling plans in statistical quality control

1995 ◽  
Vol 41 (3) ◽  
pp. 359-380
Author(s):  
Ingolf Terveer
Keyword(s):  
Quality Control ◽  
Statistical Quality Control ◽  
Sampling Plans ◽  
Statistical Quality ◽  
Multistage Sampling

Integrating Human Factors Models into Statistical Quality Control

1976 ◽  
Vol 20 (1) ◽  
pp. 1-5 ◽  
Author(s):  
C. G. Drury
Keyword(s):  
Quality Control ◽  
Operating Characteristic ◽  
Statistical Quality Control ◽  
Control Field ◽  
Sampling Plans ◽  
Statistical Quality ◽  
Input Quality ◽  
Human Inspection

Recent progress in the Statistical Quality Control field has led to the design of Sampling plans which do not assume perfect inspection. Simple methods now exist for analyzing the effect of inspector error on the operating characteristic (OC) curve of a plan and further for re-designing the plan so that a predetermined OC curve is obtained. However, the usual assumption made about human inspection error is that it is constant. Many studies show that Type 1 and Type 2 inspector error change systematically with many variables such as input quality, complexity of item inspected, type of fault, standards, individual differences, etc. This paper develops a methodology for including an explicit human inspector model into the sampling plan design. A particular model integrating visual search and decision making (proposed earlier by the author) is used to demonstrate the feasibility of including explicit human inspector data in the design process. The applications of this model to single and double sampling plans are discussed, together with evidence for the validity of the model under laboratory and field conditions.

Integrating Human Factors Models into Statistical Quality Control

1978 ◽  
Vol 20 (5) ◽  
pp. 561-572 ◽  
Author(s):  
Colin G. Drury
Keyword(s):  
Quality Control ◽  
Operating Characteristic ◽  
Statistical Quality Control ◽  
Control Field ◽  
Sampling Plans ◽  
Statistical Quality ◽  
Input Quality ◽  
Human Inspection

Recent progress in the statistical quality control field has led to the design of sampling plans which do not assume perfect inspection. Simple methods now exist for analyzing the effect of inspector error on the operating characteristic (OC) curve of a plan and further for redesigning the plan so that a predetermined OC curve is obtained. However, the usual assumption made about human inspection error is that it is constant. Many studies show that Type 1 and Type 2 inspector errors change systematically with many variables such as input quality, complexity of item inspected, type of fault, standards, individual differences, etc. This paper develops a methodology for including an explicit human inspector model into the sampling plan design. A particular model integrating visual search and decision making (proposed earlier by the author) is used to demonstrate the feasibility of including explicit human inspector data in the design process. The applications of this model to single and double sampling plans are discussed, together with evidence for the validity of the model under laboratory and field conditions.

Statistical Quality Control of HIV-1 ELISA Test Performance

1994 ◽  
Vol 89 (428) ◽  
pp. 1200-1208 ◽  
Author(s):  
R. C. Gentleman ◽  
M. S. Hamada ◽  
D. E. Matthews ◽  
A. R. Wilson
Keyword(s):  
Quality Control ◽  
Test Performance ◽  
Elisa Test ◽  
Statistical Quality Control ◽  
Statistical Quality ◽  
Hiv 1

Inspection Efficiency

1945 ◽  
Vol 152 (1) ◽  
pp. 69-75
Author(s):  
J. C. Edwards ◽  
W. A. Bennett
Keyword(s):  
Quality Control ◽  
Personnel Selection ◽  
Statistical Quality Control ◽  
Statistical Quality ◽  
Time And Motion Study ◽  
Time And Motion ◽  
Motion Study

The purpose of the paper is to outline the numerous directions in which improvements can be sought in engineering inspection. It shows how direct improvements in efficiency can be effected by carefully planned methods of recording results, including the use of statistical quality control, by adopting the principles of time and motion study in the planning of flow of work through inspection, and in the design of gauging fixtures and the arrangement of gauges. The importance of correct personnel selection and organization is stressed, as is also the avoidance of duplication of inspection. The paper concludes by quoting figures showing the substantial reductions which have been achieved in the authors' company by a progressive application of the methods described over a period of several years.

Statistical Quality Control Using Excel

Technometrics ◽  
2000 ◽  
Vol 42 (2) ◽  
pp. 221
Author(s):  
Eric R. Ziegel ◽  
Steven M. Zimmerman ◽  
Marjorie L. Icenogle
Keyword(s):  
Quality Control ◽  
Statistical Quality Control ◽  
Statistical Quality
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