Statistical quality control relates heavily on the goodness of control chart limits. The more accurate those limits are, the more likely are to detect whether a process is in control. Various procedures have been developed to compute good control limits. This paper proposes construction of Range chart by considering a Pareto distribution of IV kind. The cumulative distribution function of sample range from their distribution is derived. The percentiles of the distribution of range are worked out and are used to construct the control limits. The performance of the control chart is compared with that of gamma based control chart. Interval estimation for the scale parameter is also worked out
Control limits are one of the main elements of control charts. Generally speaking, a control chart i...
In this manuscript, a control chart is designed when the quality characteristic of interest follows ...
Standard control charts with control limits determined by the mean and standard error of the mean ar...
A variable quality characteristic is assumed to follow the new weibull-Pareto distribution. Based on...
In this paper, robust control charts for percentiles based on location-scale family of distributions...
Lifetime percentile is an important indicator of product reliability. However, the sampling distribu...
The most commonly used techniques in statistical process control are parametric, and thus require as...
This paper presents a statistical analysis control chart for nonconforming units in quality control....
The probability of a false alarm rate (type I risk) in Shewhart control charts based on a normal dis...
Chapter Summary: Control charts for controlling the process mean are affected by changes in the proc...
This article presents simpler alternative formulae and procedures of implementation to deal with the...
The study proposes control limits for X and charts using Bayesian framework assuming the normality o...
Control chart is a powerful technique that can be of immense use in an industrial process in many wa...
An attribute control chart is developed in this manuscript for the Pareto distribution of second kin...
Because the in-control distribution and parameters are generally unknown, control limits have to be ...
Control limits are one of the main elements of control charts. Generally speaking, a control chart i...
In this manuscript, a control chart is designed when the quality characteristic of interest follows ...
Standard control charts with control limits determined by the mean and standard error of the mean ar...
A variable quality characteristic is assumed to follow the new weibull-Pareto distribution. Based on...
In this paper, robust control charts for percentiles based on location-scale family of distributions...
Lifetime percentile is an important indicator of product reliability. However, the sampling distribu...
The most commonly used techniques in statistical process control are parametric, and thus require as...
This paper presents a statistical analysis control chart for nonconforming units in quality control....
The probability of a false alarm rate (type I risk) in Shewhart control charts based on a normal dis...
Chapter Summary: Control charts for controlling the process mean are affected by changes in the proc...
This article presents simpler alternative formulae and procedures of implementation to deal with the...
The study proposes control limits for X and charts using Bayesian framework assuming the normality o...
Control chart is a powerful technique that can be of immense use in an industrial process in many wa...
An attribute control chart is developed in this manuscript for the Pareto distribution of second kin...
Because the in-control distribution and parameters are generally unknown, control limits have to be ...
Control limits are one of the main elements of control charts. Generally speaking, a control chart i...
In this manuscript, a control chart is designed when the quality characteristic of interest follows ...
Standard control charts with control limits determined by the mean and standard error of the mean ar...