Environmental sampling plan for Kwajalein Atoll Lagoon: 2017 Kwajalein sampling event

2017 ◽  
Author(s):  
T. F. Hamilton
1990 ◽  
Vol 25 (12) ◽  
pp. 1259-1263
Author(s):  
Domenica Paoletti ◽  
Giuseppe Schirripa Spagnolo

Author(s):  
Pei Y. Tsai ◽  
Junedong Lee ◽  
Paul Ronsheim ◽  
Lindsay Burns ◽  
Richard Murphy ◽  
...  

Abstract A stringent sampling plan is developed to monitor and improve the quality of 300mm SOI (silicon on insulator) starting wafers procured from the suppliers. The ultimate goal is to obtain the defect free wafers for device fabrication and increase yield and circuit performance of the semiconductor integrated circuits. This paper presents various characterization techniques for QC monitor and examples of the typical defects attributed to wafer manufacturing processes.


2017 ◽  
Vol 34 (8) ◽  
pp. 1343-1351 ◽  
Author(s):  
Rosaiah K. ◽  
Srinivasa Rao Gadde ◽  
Kalyani K. ◽  
Sivakumar D.C.U.

Purpose The purpose of this paper is to develop a group acceptance sampling plan (GASP) for a resubmitted lot when the lifetime of a product follows odds exponential log logistic distribution introduced by Rao and Rao (2014). The parameters of the proposed plan such as minimum group size and acceptance number are determined for a pre-specified consumer’s risk, number of testers and the test termination time. The authors compare the proposed plan with the ordinary GASP, and the results are illustrated with live data example. Design/methodology/approach The parameters of the proposed plan such as minimum group size and acceptance number are determined for a pre-specified consumer’s risk, number of testers and the test termination time. Findings The authors determined the group size and acceptance number. Research limitations/implications No specific limitations. Practical implications This methodology can be applicable in industry to study quality control. Social implications This methodology can be applicable in health study. Originality/value The parameters of the proposed plan such as minimum group size and acceptance number are determined for a pre-specified consumer’s risk, number of testers and the test termination time.


2002 ◽  
Vol 85 (4) ◽  
pp. 925-932 ◽  
Author(s):  
Mark Vandeven ◽  
Thomas Whitaker ◽  
Andy Slate

Abstract Processed food manufacturers often use acceptance sampling plans to screen out lots with unacceptable levels of contamination from incoming raw material streams. Sampling plan designs are determined by specifying sample sizes, sample preparation methods, analytical test methods, and accept/reject criteria. Sampling plan performance can be indicated by plotting acceptance probability versus contamination level as an operating characteristic (OC) curve. In practice, actual plan performance depends on the level of contamination in the incoming lot stream. This level can vary considerably over time, among different crop varieties, and among locales. To better gauge plan performance, a method of coupling an OC curve and crop distributions is proposed. The method provides a precise probabilistic statement about risk and can be easily performed with commercial spreadsheet software.


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