This paper introduces a new Bayesian control chart to compare two processes by monitoring the ratio of percentiles of two quality characteristics that are assumed to be independent Weibull distributed random variables with the same and stable shape parameter larger than one. The chart analyses the sampling data directly, instead of transforming them in order to comply with the usual normality assumption, as many charts do. A real application in the wood industry and a wide simulation illustrate the features of the chart and its performance, depending on the number of training data, the quality of prior information, and the magnitude of the shift
The frequentist Shewhart charts have proved valuable for the first stage of quality improvement in m...
Due to the proper performance of Bayesian control chart in detecting process shifts, it recently has...
This article develops a new design structure for S2-Chart, namely Bayesian variance chart, in Phase-...
This paper introduces a new Bayesian control chart to compare two processes by monitoring the ratio ...
This paper develops a Bayesian control chart for the percentiles of the Weibull distribution, when b...
In this paper we investigate the performance of semi-empirical Bayesian control charts to monitor th...
Purpose: This work proposes an innovative control chart of the Weibull percentiles using Bayesian es...
The general objective of the research study underlying this thesis was to develop innovative charts ...
The study proposes control limits for X and charts using Bayesian framework assuming the normality o...
Abstract: Shewhart control limits for individual observations are traditionally based on the average...
Multivariate control charts are valuable tools for multivariate statistical process control (MSPC) u...
An algorithm for detecting changes in the behaviour of a random variable based on the Bayes approach...
On-line Statistical Process Control (SPC) monitoring the ratio Z of two normal variables X and Y has...
Recently, there has been a growing interest among industrial practitioners and researchers for apply...
Recently, statistical profile monitoring methods have become efficient tools for monitoring the qual...
The frequentist Shewhart charts have proved valuable for the first stage of quality improvement in m...
Due to the proper performance of Bayesian control chart in detecting process shifts, it recently has...
This article develops a new design structure for S2-Chart, namely Bayesian variance chart, in Phase-...
This paper introduces a new Bayesian control chart to compare two processes by monitoring the ratio ...
This paper develops a Bayesian control chart for the percentiles of the Weibull distribution, when b...
In this paper we investigate the performance of semi-empirical Bayesian control charts to monitor th...
Purpose: This work proposes an innovative control chart of the Weibull percentiles using Bayesian es...
The general objective of the research study underlying this thesis was to develop innovative charts ...
The study proposes control limits for X and charts using Bayesian framework assuming the normality o...
Abstract: Shewhart control limits for individual observations are traditionally based on the average...
Multivariate control charts are valuable tools for multivariate statistical process control (MSPC) u...
An algorithm for detecting changes in the behaviour of a random variable based on the Bayes approach...
On-line Statistical Process Control (SPC) monitoring the ratio Z of two normal variables X and Y has...
Recently, there has been a growing interest among industrial practitioners and researchers for apply...
Recently, statistical profile monitoring methods have become efficient tools for monitoring the qual...
The frequentist Shewhart charts have proved valuable for the first stage of quality improvement in m...
Due to the proper performance of Bayesian control chart in detecting process shifts, it recently has...
This article develops a new design structure for S2-Chart, namely Bayesian variance chart, in Phase-...