A control chart is an important tool in statistical process monitoring that useful to monitor and improve production quality. In this article, attribute using repetitive sampling under a truncated life test proposed for the mean of product where lifetime follows Rayleigh distribution. The parameters limit coefficients are determined so in-control average run length (ARL) very close target ARL. ...

Nonparametric (distribution-free) control charts have been introduced in recent years when quality characteristics do not follow a specific distribution. When the sample selection is prohibitively expensive, we prefer ranked-set sampling over simple random because ranked set sampling-based outperform charts. In this study, proposed nonparametric homogeneously weighted moving average based on Wi...

background: taking visual acuity is an important part of an eye routine examination. this study was conducted to compare visual acuity measured using an iranian digital tumbling e chart with visual acuity measured using an italian digital tumbling e chart as a familiar foreign chart. materials and methods: this study was carried out on 200 participants (400 eyes; healthy n=40, glaucoma n=40, re...

multivariate control charts such as hotelling`s t^ 2 and x^ 2 are commonly used for monitoring several related quality characteristics. these control charts use correlation structure that exists between quality characteristics in an attempt to improve monitoring. the purpose of this article is to discuss some issues related to the g chart proposed by levinson et al. [9] for detecting shifts in ...

Control charts are effective tools for signal detection in both manufacturing processes and service processes. Much of the data in service industries comes from processes having nonnormal or unknown distributions. The commonly used Shewhart variable control charts, which depend heavily on the normality assumption, are not appropriately used here. In this paper, we propose a new asymmetric EWMA ...