This paper studies design schemes for the X control chart under non-normality. Different estimators of the standard deviation are considered and the effect of the estimator on the performance of the control chart under non-normality is investigated. Two situations are distinguished. In the first situation, the effect of non-normality on the X control chart is investigated by using the control l...

Control charts have been used effectively for years to monitor processes and detect abnormal behaviors. However, most control charts require a specific distribution to establish their control limits. The bootstrap method is a nonparametric technique that does not rely on the assumption of a parametric distribution of the observed data. Although the bootstrap technique has been used to develop u...

The reliability data is getting used to monitor and improve the quality of products or services. Nowadays, most of products or services are the results of processes with dependent stages referred to as multi-stage process. In these processes, the quality characteristics are affected by the quality characteristics in the previous stages, called as cascade property. In some cases, it is not possi...

usually, in monitoring schemes the nominal value of the process parameter is assumed known. however, this assumption is violated owing to costly sampling and lack of data particularly in healthcare systems. on the other hand, applying a fixed control limit for the risk-adjusted bernoulli chart causes to a variable in-control average run length performance for patient populations with dissimilar...

abstract. in recent years several studies have shown that  control charts with adaptive schemes or double sampling plans detect both small and moderate shifts in the process mean more quickly than the traditional shewhart  chart. in the classical double sampling  chart, the difference between two points were placed in the central region of first stage was not considered. in this study, a new co...

Abstract Even if large historical dataset could be available for monitoring key quality features of a process via multivariate control charts, previous knowledge may not enough to reliably identify or adopt unique model all the variables. When no specific parametric turns out appropriate, some alternative solutions should adopted and exploiting non‐parametric methods build chart appears reasona...

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...

in this paper we propose a simple non-parametric model for multiple crite-ria supplier selection problem. the proposed model does not generate a zeroweight for a certain criterion and ranks the suppliers without solving the modeln times (one linear programming (lp) for each supplier) and therefore allowsthe manager to get faster results. the methodology is illustrated using anexample.