نتایج جستجو برای: fuzzy control charts suggested by rose
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Statistical process control (SPC) is an approach to evaluate processes whether they are in statistical control or not. For this aim, control charts are generally used. Since sample data may include uncertainties coming from measurement systems and environmental conditions, fuzzy numbers and/or linguistic variables can be used to capture these uncertainties. In this paper, one of the most popula...
Due to competition in the market, organization must have quality improvement program. Statistical quality control and especially control charts are proven quality improvement techniques. Control charts are based on the quality characteristics measurement in the course of time. There are some situations such as measurement error, sophisticated measurement instruments, costly skilled inspectors, ...
Control charts are widely used in industry as a tool to monitor process characteristics. Deviations from process targets can be detected based on the evidence of statistical significance. The control chart helps to take decisions such as the need for machine or technology replacement to monitor the process with categorical observations. Fuzzy logic is used to cram the uncertainty and vagueness ...
Control charts are widely used in industrial processes as well as in health sciences and particularly for monitoring the performance of cardiac surgeon or a group of surgeons based on the preoperative risk of patients. Since the preoperative risk is a vague and nonprecise variable and the anesthesiologists after checking how many risk factors a patient has, determine the risk of mortality befor...
Statistical control charts are useful tools in monitoring the state of a manufacturing process. Control charts are used to plot process data and compare it to the limits set for the process. Points plotting outside these limits indicate an out-of-control condition. Standard control charting procedures, however, are limited in that they cannot take into account the case when data is of a fuzzy n...
Fuzzy control charts are proposed to solve the problem that traditional cannot be applied fuzzy quality characteristics. First, characteristics converted representative statistics, which mode transformation, level midrange transformation and median transformation. Control designed based on Poisson distribution. Second, effects of different statistics analysed. Direct Charts avoid some informati...
a manufacturing process cannot be released to production until it has been proven to be stable. also, we cannot begin to talk about process capability until we have demonstrated stability in our process. this means that the process variation is the result of random causes only and all assignable or special causes have been removed. in complicated manufacturing processes, such as drilling proces...
Shewhart charts are the main tools for statistical process control. They are used for detecting assignable causes which affect quality of process output. From them, X and MR charts are two univariate control charts for monitoring mean and variation of measurable quality characteristics. The main drawbacks of these charts are: weakness of X chart against non-normal distribution of process data,...
Statistical Process Control (SPC) is used to monitor the process stability which ensures the predictability of the process. In 1920‟s Shewhart introduced the control chart techniques that are one of the most important techniques of quality control to detect if assignable causes exist. The widely used control chart techniques are R X and S X . These are called traditional variable control ch...
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