A scheme for balanced monitoring and accurate diagnosis of bivariate process mean shifts
Monitoring and diagnosis of mean shifts in manufacturing processes become more challenging when involving two or more correlated variables. Unfortunately, most of the existing multivariate statistical process control schemes are only effective in rapid detection but suffer high false alarm. Th...
Saved in:
Main Author: | Masood, Ibrahim |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2012
|
Subjects: | |
Online Access: | http://eprints.uthm.edu.my/2539/1/24p%20IBRAHIM%20MASOOD.pdf http://eprints.uthm.edu.my/2539/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Synergistic artificial neural network scheme for monitoring and diagnosis of multivariate process variation in mean shifts
by: Marian, Mohd Fairuz
Published: (2014) -
Study of artificial neural network scheme application in manufacturing industry for monitoring-diagnosis bivariate process variation
by: Majid, Mariam
Published: (2014) -
Diagnosis of bivariate process variation using an integrated mspc-ann scheme
by: Masood, Ibrahim, et al.
Published: (2016) -
Control chart pattern recognition using small window size for identifying bivariate process mean shifts
by: Kasmin, A., et al.
Published: (2021) -
SPC charting procedure for monitoring of small and large shifts in process mean
by: Masood, Ibrahim
Published: (2004)