scholarly journals Evaluation of Variable Parameter MCV Control Chart in Downward Process Shifts

2021 ◽  
Vol 16 ◽  
pp. 479-485
Author(s):  
Xinying Chew
Keyword(s):  
Process Monitoring ◽  
Coefficient Of Variation ◽  
Variable Parameter ◽  
Industrial Process ◽  
Average Time To Signal ◽  
Related Quality ◽  
Mean And Variance ◽  
Research Gap ◽  
Highly Correlated ◽  
Almost All

Previous studies revealed that the coefficient of variation (CV) is important in ensuring process quality, especially for monitoring a process where its process mean and variance are highly correlated. The fact that almost all industrial process monitoring involves a minimum of two or more related quality characteristics being monitored simultaneously. The existing adaptive charts for monitoring the multivariate CV are focused on detecting upward process shifts. The downward process monitoring is crucial since it shows process improvement. Very little research works are available on the downward adaptive multivariate CV chart. This makes it difficult for the quality engineer who wishes to implement the adaptive multivariate CV chart on the downward process monitoring. Therefore, this paper filled the research gap by proposing a downward variable parameter chart for the multivariate coefficient of variation. The performance measures of the proposed charts are derived based on the Markov-chain approach. Numerical comparisons between the proposed and existing charts have been made, in terms of the average time to signal criterion. The findings reveal that the proposed charts outperform the existing charts for detecting small and moderate downward process shifts

scholarly journals An Optimal Adaptive Variable Sample Size Scheme for the Multivariate Coefficient of Variation

2021 ◽  
Vol 9 (3) ◽  
pp. 681-693
Author(s):  
KHAI WAH KHAW ◽  
XINYING CHEW ◽  
MING HA LEE ◽  
WAI CHUNG YEONG
Keyword(s):  
Sample Size ◽  
Process Monitoring ◽  
Coefficient Of Variation ◽  
Markov Chain Model ◽  
Average Run Length ◽  
Industrial Process ◽  
Salient Feature ◽  
Numerical Comparison ◽  
Chain Model ◽  
Run Length

Development of an efficient process monitoring system has always received great attention. Previous studies revealed that the coefficient of variation (CV) is important in ensuring process quality, especially for monitoring a process where its process mean and variance are highly correlated. The fact that almost all industrial process monitoring involves a minimum of two or more related quality characteristics being monitored simultaneously, this paper incorporates the salient feature of the adaptive sample size VSS scheme into the standard multivariate CV (MCV) chart, called the VSS MCV chart. A Markov chain model is developed for the derivation of the chart’s performance measures, i.e the average run length (ARL), the standard deviation of the run length (SDRL), the average sample size (ASS), the average number of observations to signal (ANOS) and the expected average run length (EARL). The numerical comparison shows that the proposed chart prevails over the existing standard MCV chart for detecting small and moderate upward and downward MCV shifts.

Industrial process monitoring by synthetic view

2007 ◽  
Author(s):  
Antonio Dourado ◽  
Paulo Barbeiro ◽  
Edgar Ferreira ◽  
Jorge Henriques ◽  
Maria Antonio ◽  
...  
Keyword(s):  
Process Monitoring ◽  
Industrial Process ◽  
Synthetic View

Methyl mercury in the dutch rhine delta

1994 ◽  
Vol 30 (10) ◽  
pp. 213-219 ◽  
Author(s):  
Hendrik Pieters ◽  
Victor Geuke
Keyword(s):  
Suspended Matter ◽  
Methyl Mercury ◽  
Mercury Contamination ◽  
Benthic Organisms ◽  
Considerable Decrease ◽  
Continuous Sedimentation ◽  
Highly Correlated ◽  
High Level ◽  
Almost All

Samples of yellow eel from various locations in the Dutch Rhine area have been analyzed for trend monitoring of mercury since 1977. In the western Rhine delta mercury levels in eels have hardly changed since the seventies, whereas in the eastern part of the Dutch Rhine area a considerable decrease of mercury concentrations in eel has occurred. Because of continuous sedimentation of contaminated suspended matter transported from upstream regions, accumulation rates and concentrations of mercury in eel in the western Rhine delta remained at a relatively high level. Analyses of methyl mercury in biota have been performed to elucidate the role of methyl mercury in the mercury contamination of the Dutch Rhine ecosystem. Low percentages of methyl mercury were observed in zooplankton (3 to 35%). In benthic organisms (mussels) percentages of methyl mercury ranged from 30 to 57%, while in fish species and liver of aquatic top predator birds almost all the mercury was present in the form of methyl mercury (> 80%). During the period 1970-1990 mercury concentrations of suspended matter in the eastern Rhine delta have drastically decreased. These concentrations seemed to be highly correlated with mercury concentrations of eel (R = 0.84). The consequences of this relation are discussed.

Distributed dictionary learning for industrial process monitoring with big data

2021 ◽  
Author(s):  
Keke Huang ◽  
Ke Wei ◽  
Yonggang Li ◽  
Chunhua Yang
Keyword(s):  
Big Data ◽  
Process Monitoring ◽  
Dictionary Learning ◽  
Industrial Process

Mobility Support and Service Discovery for Industrial Process Monitoring

2017 ◽  
pp. 57-85
Author(s):  
Tuan Dang ◽  
Pascale Minet ◽  
Patrick Bellot ◽  
Christophe Mozzati ◽  
Erwan Livolant
Keyword(s):  
Process Monitoring ◽  
Service Discovery ◽  
Industrial Process ◽  
Mobility Support

scholarly journals STATISTICAL STUDIES ON PROTEIN POLYMORPHISM IN NATURAL POPULATIONS II. GENE DIFFERENTIATION BETWEEN POPULATIONS

Genetics ◽  
1978 ◽  
Vol 88 (2) ◽  
pp. 367-390
Author(s):  
Ranajit Chakraborty ◽  
Paul A Fuerst ◽  
Masatoshi Nei
Keyword(s):  
Genetic Differentiation ◽  
Natural Populations ◽  
Drift Theory ◽  
Alternative Hypotheses ◽  
Mean And Variance ◽  
Statistical Studies ◽  
Different Populations ◽  
Using Data ◽  
Almost All ◽  
Good Agreement

ABSTRACT With the aim of testing the validity of the mutation-drift hypothesis, we examined the pattern of genetic differentiation between populations by using data from Drosophila, fishes, reptiles, and mammals. The observed relationship between genetic identity and correlation of heterozygosities of different populations or species was generally in good agreement with the theoretical expectations from the mutation-drift theory, when the variation in mutation rate among loci was taken into account. In some species of Drosophila, however, the correlation was unduly high. The relationship between the mean and variance of genetic distance was also in good agreement with the theoretical prediction in almost all organisms. We noted that both the distribution of heterozygosity within species and the pattern of genetic differentiation between species can be explained by the same set of genetic parameters in each group of organisms. Alternative hypotheses for explaining these observations are discussed.

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