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Multivariate Max-Chart
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Keoagile Thaga
Veröffentlicht/Copyright:
15. März 2010
Abstract
A single control chart called Multivariate Maximum Control Chart (Max-Mchart) is proposed in this article that is capable of monitoring the process, with the quality of an item being determined by several correlated quality characteristics. This scheme simultaneously monitors the process location and process spread using only one chart. The chart quickly detects both small and large shifts in the process parameters and indicates the parameter that has shifted. Compared with other recently proposed single multivariate control charts, this chart quickly detects small shifts in the process mean and is also simple to use, as it applies the well known Shewhart control charts procedures to compute the average run lengths.
Key words:: Noncentrality parameter; Shewhart type control chart; average run length; incontrol process
Published Online: 2010-03-15
Published in Print: 2006-April
© Heldermann Verlag
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Artikel in diesem Heft
- Transient Analysis of Multistage Degraded Systems with Partial Repairs of General Distribution Modeled by Erlang-k Distribution
- A Practical Procedure for Developing p-Charts
- Posterior Distribution and Loss Functions for Parameter Estimation in Weibull Processes
- Combined CUSUM–Shewhart Schemes for Binomial Data
- A Goodness of Fit Approach to NBURFR and NBARFR Classes
- Control Charts for the Log-Logistic Distribution
- Stability Index of Stochastic Processes: The Statistical Process Control Approach
- Multivariate Max-Chart
- An Optimization Methodology for Condition Based Minimal and Major Preventive Maintenance
- Multivariate Diagnostic Tests: A Review of Different Methods
- A Note on the Concept of Independence
Schlagwörter für diesen Artikel
Noncentrality parameter;
Shewhart type control chart;
average run length;
incontrol process
Artikel in diesem Heft
- Transient Analysis of Multistage Degraded Systems with Partial Repairs of General Distribution Modeled by Erlang-k Distribution
- A Practical Procedure for Developing p-Charts
- Posterior Distribution and Loss Functions for Parameter Estimation in Weibull Processes
- Combined CUSUM–Shewhart Schemes for Binomial Data
- A Goodness of Fit Approach to NBURFR and NBARFR Classes
- Control Charts for the Log-Logistic Distribution
- Stability Index of Stochastic Processes: The Statistical Process Control Approach
- Multivariate Max-Chart
- An Optimization Methodology for Condition Based Minimal and Major Preventive Maintenance
- Multivariate Diagnostic Tests: A Review of Different Methods
- A Note on the Concept of Independence
