11/4/2022 0 Comments Xbar control chart![]() Multiple-attribute decision making problems based on SVTNH methods were studied by Jana et al. Multi-criteria decision making process based on some single-valued neutrosophic Dombi power aggregation operators was developed by Jana and Pal. Multi-criteria decision making approach based on SVTrN Dombi aggregation functions proposed by Jana et al. Trapezoidal neutrosophic aggregation operators and their application to the multi-attribute decision-making process are given by Jana et al. A robust single-valued neutrosophic soft aggregation operator in multi-criteria decision-making was developed by Jana and Pal. Shewhart S-control chart for process variability monitoring using the neutrosophic statistics was presented by Khan et al. A control chart based upon gamma-distributed quality characteristic under the neutrosophic statistics was developed by Aslam et al. Dispersion control charts using the neutrosophic statistical interval method were presented by Aslam et al. Control charts for failure-censored reliability tests under the neutrosophic environment were presented by Aslam et al. Sampling plans using regression estimators for the neutrosophic statistics through the neutrosophic optimization solution were presented by Aslam and AL-Marshadi. Sampling plan under the neutrosophic process loss consideration was developed by Aslam. The engineering rock mass using the joint roughness coefficient under the neutrosophic statistics for scale effect and anisotropy environment were analyzed by Chen et al. Neutrosophic logic was introduced by Smarandache. Neutrosophic statistics has attracted the attention of several SPC experts during the last few years due to its nice properties of analyzing the vague, incomplete, imprecise, unclear and uncrispy data from numerous practical, real-world and everyday circumstances. Fuzzy logic is the special case of neutrosophic logic. Control charts under fuzzy theory for the univariate case and multivariate case were developed by Fernández. An attribute sampling plan under the multiple dependent state sampling for the fuzzy environment was designed by Afshari and Sadeghpour Gildeh. The X-bar chart using the fuzzy theorem for non-crispy data using the triangular fuzzy membership function was developed by Panthong and Pongpullponsak. A hybrid fuzzy adaptive control chart was developed to enhance the performance of the Shewhart control chart using fuzzified sensitivity criteria by Zarandi et al. A methodology for developing a quantitative control chart for nonprecise observations was given by Gülbay and Kahraman. Fuzzy set theory can be used to develop the control chart for quality assurance of the industrial product when the observations are collected from linguistic terms. Several procedures have been proposed to develop fuzzy control charts since the inception of fuzzy set theory by Zadeh. The fuzzy control charts are inevitable to deal with uncertain, vague, incomplete or data collected on human subjectivity. The fuzzy approach provides the perfect means of dealing with human subjectivity by modeling uncertainty which is neither stochastic nor random. Ambiguous and unclear data are well represented by the fuzzy logic which provides a systemic base by using algorithms of defuzzification methods. The fuzzy approach is very common in the control chart literature due to its efficient capability of handling vague data. Further literature on proposed approaches for quick detection of unusual changes can be consulted. ![]() The combination of exponentially distributed quality characteristics with the MDS has been shown as an efficient monitoring technique for the mean of the production process. The MDS sampling in combination with the double control limits can be used for the efficient monitoring of the production process. The multiple dependent state (MDS) sampling technique combined with a fixed deferred state sampling scheme for the correct decision of lot sentencing was promoted by Wortham and Baker. Several modifications by SPC researchers have been proposed by mixing and combining the design structures of monitoring techniques. The Statistical Process Control (SPC) experts are struggling hard to devise a robust control chart technique for the efficient monitoring of the process but in vain to launch a universal control chart methodology. #XBAR CONTROL CHART SOFTWARE#Control charts have been used extensively in a variety of areas like manufacturing processes, goods and services providing companies, health care enterprises, nuclear engineering, Software industry, education, analytical laboratories, etc. ![]()
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