Control Charts for the Standard Mortality Ratio

Control charts for the standard mortality ratio.

Fuzzy rules for fuzzy $overline{X}$ and $R$ control charts

Statistical process control ($SPC$), an internationally recognized technique for improving product quality and productivity, has been widely employed in various industries. $SPC$ relies on the use of control charts to monitor a manufacturing process for identifying causes of process variation and signaling the necessity of corrective action for the process. Fuzzy data exist ubiquitously in the ...

An Evaluation of an Adaptive Generalized Likelihood Ratio Charts for Monitoring the Process Mean

When the objective is quick detection both small and large shifts in the process mean with normal distribution, the generalized likelihood ratio (GLR) control charts have better performance as compared to other control charts. Only the fixed parameters are used in Reynolds and Lou’s presented charts. According to the studies, using variable parameters, detect process shifts faster than fixed pa...

Application of Multivariate Control Charts for Condition Based Maintenance

Condition monitoring is the foundation of a condition based maintenance (CBM). To relate the information obtained from the condition monitoring to the actual state of the system, it is usually required a stochastic model. On the other hand, considering the interactions and similarities that exist between CBM and statistical process control (SPC), the integrated models for CBM and SPC have been ...

FUZZY CONTROL CHARTS FOR VARIABLE AND ATTRIBUTE QUALITY CHARACTERISTICS

This paper addresses the design of control charts for both variable ( x chart) andattribute (u and c charts) quality characteristics, when there is uncertainty about the processparameters or sample data. Derived control charts are more flexible than the strict crisp case, dueto the ability of encompassing the effects of vagueness in form of the degree of expert’spresumption. We extend the use o...