Building statistical models and scoring with UDFs

Author(s):  
Carlos Ordonez
Keyword(s):  
Author(s):  
C.K. Lakshminarayan ◽  
S. Pabbisetty ◽  
O. Adams ◽  
F. Pires ◽  
M. Thomas ◽  
...  

Abstract This paper deals with the basic concepts of Signature Analysis and the application of statistical models for its implementation. It develops a scheme for computing sample sizes when the failures are random. It also introduces statistical models that comprehend correlations among failures that fail due to the same failure mechanism. The idea of correlation is important because semiconductor chips are processed in batches. Also any risk assessment model should comprehend correlations over time. The statistical models developed will provide the required sample sizes for the Failure Analysis lab to state "We are A% confident that B% of future parts will fail due to the same signature." The paper provides tables and graphs for the evaluation of such a risk assessment. The implementation of Signature Analysis will achieve the dual objective of improved customer satisfaction and reduced cycle time. This paper will also highlight it's applicability as well as the essential elements that need to be in place for it to be effective. Different examples have been illustrated of how the concept is being used by Failure Analysis Operations (FA) and Customer Quality and Reliability Engineering groups.


2020 ◽  
pp. 71-76
Author(s):  
M.A. Levantsevich ◽  
E.V. Pilipchuk ◽  
N.N Maksimchenko ◽  
L.S. Belevskiy ◽  
R.R. Dema

Experimental-statistical models of the process of forming composite chromium coatings by electrodeformation cladding with a flexible tool are developed, which allow to determine the parameters of the regimes for obtaining coatings of the required thickness and roughness. Keywords electrodeformation cladding, flexible tool, coating, composite material, experiment planning, noncompositional plan, thickness, roughness. [email protected]


2009 ◽  
Vol 35 (2) ◽  
pp. 341-347 ◽  
Author(s):  
Jiu-Quan ZHANG ◽  
Ling-Xiao ZHANG ◽  
Ming-Hua ZHANG ◽  
Clarence WATSON

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