DocumentCode :
3064467
Title :
Conditions for Gaussian long term manufacturing processes
Author :
Pieper, R.J. ; Satyala, Nikhil T.
Author_Institution :
Dept. of Electr. Eng., Univ. of Texas, Tyler, TX
fYear :
2009
fDate :
15-17 March 2009
Firstpage :
205
Lastpage :
208
Abstract :
The manufacturing community defines capability indices for manufacturing processes applicable time-wise for both long term and short term processes. The long term process distribution can be constructed from the consolidation of the data sets that was used to estimate the multiple short term distributions. There is a tendency for Gaussian distributed short-term processes to exhibit time sensitive random variation in the mean, while the short-term standard deviation remains unchanged. A mathematical model for construction of the long-term distribution from consolidation of short-term histograms will be discussed. Also, it can be shown the long term process will be Gaussian distributed if the mean for the short term processes is a random variable which is distributed Gaussian. A simple rule for predicting the long term (composite) variance is derived.
Keywords :
Gaussian distribution; manufacturing processes; process capability analysis; quality control; random processes; statistical analysis; Gaussian distributed short-term process; Gaussian long term manufacturing process condition; Gaussian probability density function; manufacturing community; manufacturing quality; process capability index; short-term histogram; time sensitive random variation; Histograms; Manufacturing processes; Mathematical model; Measurement standards; Probability density function; Process control; Random variables; Stochastic processes; Time varying systems; USA Councils; Process Control; Stochastic Processes; Time Varying Systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Theory, 2009. SSST 2009. 41st Southeastern Symposium on
Conference_Location :
Tullahoma, TN
ISSN :
0094-2898
Print_ISBN :
978-1-4244-3324-7
Electronic_ISBN :
0094-2898
Type :
conf
DOI :
10.1109/SSST.2009.4806810
Filename :
4806810
Link To Document :
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