A count of the number of defects is often used to monitor the quality of a production process. When defects rarely occur in a process, it is often desirable to monitor the time between the occurrence of each defect rather than a count of the number of defects. An exponential distribution often provides a useful model of the time between defects. Phase I control charts for exponentially distributed processes are discussed. Methods for computing the control limits are given and the overall Type I error rates of these charts are evaluated
The last 20 years have seen an increasing emphasis on statistical process control as a practical app...
Because the in-control distribution and parameters are generally unknown, control limits have to be ...
This dissertation deals with the applications of exponential smoothing to control charts with some c...
Quality is an extremely important feature for satisfying customers and winning market shares nowaday...
In this paper, a two stage control chart for monitoring the defective rate of high-yield processes i...
International audienceIn this paper, we present a number-between-events (NBE) control chart for moni...
Manufacturing with optimal quality standards is underpinned to the high reliability of its equipment...
This study proposes a procedure for an on-line process control system to monitor the average number ...
International audienceIn this paper, we study the performance properties of the phase II exponential...
A number of processes to which statistical control is applied are subject to various effects that ca...
Statistical Process Monitoring (SPM) provides statistical tools and techniques to understand process...
An increasing number of applications in the chemical industry involve measuring nonconforming items,...
Control chart is the most important statistical tool to manage the business processes. It is a graph...
In conventional statistical process control, a conforming process is usually assumed to be stable wi...
One way that a process may be said to be "out-of-control" is when a cyclical pattern exists in the o...
The last 20 years have seen an increasing emphasis on statistical process control as a practical app...
Because the in-control distribution and parameters are generally unknown, control limits have to be ...
This dissertation deals with the applications of exponential smoothing to control charts with some c...
Quality is an extremely important feature for satisfying customers and winning market shares nowaday...
In this paper, a two stage control chart for monitoring the defective rate of high-yield processes i...
International audienceIn this paper, we present a number-between-events (NBE) control chart for moni...
Manufacturing with optimal quality standards is underpinned to the high reliability of its equipment...
This study proposes a procedure for an on-line process control system to monitor the average number ...
International audienceIn this paper, we study the performance properties of the phase II exponential...
A number of processes to which statistical control is applied are subject to various effects that ca...
Statistical Process Monitoring (SPM) provides statistical tools and techniques to understand process...
An increasing number of applications in the chemical industry involve measuring nonconforming items,...
Control chart is the most important statistical tool to manage the business processes. It is a graph...
In conventional statistical process control, a conforming process is usually assumed to be stable wi...
One way that a process may be said to be "out-of-control" is when a cyclical pattern exists in the o...
The last 20 years have seen an increasing emphasis on statistical process control as a practical app...
Because the in-control distribution and parameters are generally unknown, control limits have to be ...
This dissertation deals with the applications of exponential smoothing to control charts with some c...