نتایج جستجو برای: cumulative count of conforming charts
تعداد نتایج: 21171329 فیلتر نتایج به سال:
Control charts for monitoring of process variance are developed based on Shewhart, exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts for mean. In all these variance control charts, log transformation of the sample variance is used. The design procedure of this chart is complex and it is poorly understood by the industry. In this paper a EWMA chart for monito...
Control charts have been broadly used for monitoring the process mean and dispersion. Cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are memory control charts as they utilize the past information in setting up the control structure. This makes CUSUM and EWMA-type charts good at detecting small disturbances in the process. This article proposes two new mem...
Surveillance of resistant bacteria in a French Hospital in 2010-2015 using cumulative control charts
Precise identification of the time when a process has changed enables process engineers to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for a Poisson process in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step < /div> change, a linear trend and a known multip...
The current document describes the methodology adopted for finding the optimal thresholds for ‘cumulative sequence count' and 'overlap percentage' using ROC curves. For each of the four training data sets, i-rDNA program was executed using various pairs of thresholds for cumulative sequence count and overlap percentage. For each pair of thresholds, the True Positive Rate and the False Positive ...
Unlike a Shewhart chart, the exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts are memory control charts (also known as time weighted control charts) that are used for a quick detection of small shifts in the process mean. Control charts that combine information from present and past samples, like the EWMA and CUSUM charts have the ability to detect process changes ...
In many circumstances, the quality of a process or product is best characterized by a given mathematical function between a response variable and one or more explanatory variables that is typically referred to as profile. There are some investigations to monitor auto-correlated linear and nonlinear profiles in recent years. In the present paper, we use the linear mixed models to account autocor...
Knowing about the real time of a change in the parameter(s) of a statistical process would enable users to identify root causes more quickly and precisely. Due to the sensitivity and importance of reaching zero defects in high quality processes, to be aware of the change time would be so precious. In this paper, we consider the performance of the Maximum Likelihood Estimator in comparison with ...
Control charts are extensively used in processes and are very helpful in determining the special cause variations so that a timely action may be taken to eliminate them. One of the charting procedures is the Shewhart-type control charts, which are used mainly to detect large shifts. Two alternatives to the Shewhart-type control charts are the cumulative (CUSUM) control charts and the exponentia...
In the manufacture of metal fasteners in a progressive die operation, and other industrial situations, important quality dimensions cannot be measured on a continuous scale, and parts are classified into groups using a step gauge. This article proposes a version of exponentially weighted moving average (EWMA) control charts applicable to monitoring the grouped data for process shifts. The run l...
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