Supersparse overlay sampling plans: an evaluation of methods and algorithms for optimizing overlay quality control and metrology tool throughput

1999 ◽  
Author(s):  
Joseph C. Pellegrini ◽  
Ziad R. Hatab ◽  
Jeffrey M. Bush ◽  
Thomas R. Glass
Keyword(s):  
Quality Control ◽  
Sampling Plans ◽  
Evaluation Of Methods

Statistical Process and Quality Control

2000 ◽  
pp. 233-244
Keyword(s):  
Quality Control ◽  
Quality Improvement ◽  
Quality Management ◽  
Total Quality Management ◽  
Statistical Process Control ◽  
Control Charts ◽  
Statistical Testing ◽  
Total Quality ◽  
Statistical Process ◽  
Sampling Plans

Abstract This chapter provides an introduction to statistical process control and the concept of total quality management. It begins with a review of quality improvement efforts in the extrusion industry and the considerations involved in developing sampling plans and interpreting control charts. It then lays out the steps that would be followed in order to implement statistical testing for billet casting, die performance, or any other process or variable that impacts extrusion quality. The chapter concludes with an overview of the fundamentals of total quality management.

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.

Multivariate Sampling Plans in Quality Control: A Numerical Example

1983 ◽  
Vol R-32 (4) ◽  
pp. 359-365 ◽  
Author(s):  
L.F. Pau ◽  
C. Toghrai ◽  
C.H. Chen
Keyword(s):  
Quality Control ◽  
Sampling Plans ◽  
Numerical Example
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