V.B. Ghute Dept. of Statistics, Solapur University, Solapur, (MS), India [email protected]; +91 9881372729 ______________________________________________________________________________________________ Abstract Nonparametric or distribution-free control chart is useful in statistical process control when the underlying process distribution is unknown or is not likely to be normal. In...

Because of the networking technologies progress made, and the collaboration theories developed, the relationship of suppliers and buyers is changed to a collaborative one nowadays. The performance of each member in a supply chain will affect the market competitiveness of the chain. Therefore, how to choose an appropriate collaborative partner becomes an important issue for the initiator of the ...

For signalling alarms sooner when the dispersion of a multivariate process is “increased”, a multivariate control chart for Phase II process monitoring is proposed as a supplementary tool to the usual monitoring schemes designed for detecting general changes in the covariance matrix. The proposed chart is constructed based on the one-sided likelihood ratio test (LRT) for testing the hypothesis ...

In some real applications of Statistical Process Control it is necessary to design a control chart to not detect small process shifts, but keeping a good performance to detect moderate and large shifts in the quality. In this work we develop a new quality control chart, the synthetic T control chart, which can be designed to cope with this objective. A multi-objective optimization is carried ou...

While the assumption of normality is required for the validity ofmost of the available control charts for jointmonitoring of unknown location and scale parameters, we propose and study a distribution-free Shewhart-type chart based on the Cucconi statistic, called the Shewhart-Cucconi (SC) chart. We also propose a follow-up diagnostic procedure useful to determine the type of shift the process m...

In this paper, we propose a nonparametric CUSUM control chart for detecting a range of shifts in the location parameters based on previous research. This control chart is dynamically adaptive, ranks method-based nonparametric and self-starting; it can monitor various sizes of shifts in difference distributions simultaneously; and it can be used to monitor processes at the start-up stages. This ...

The scientific literature is abundant regarding control charts in multivariate environments for numerical and mixed data; however, there are few publications qualitative data. Qualitative variables provide valuable information on processes various industrial, productive, technological, health contexts. Social no exception. There multiple nominal ordinal categorical used economics, psychology, l...

Multivariate quality control charts show some advantages to monitor several variables in comparison with the simultaneous use of univariate charts, nevertheless, there are some disadvantages. The main problem is how to interpret the out-ofcontrol signal of a multivariate chart. For example, in the case of control charts designed to monitor the mean vector, the chart signals showing that it must...

Mukherjee and Chakraborti 1 proposed a single distribution-free (nonparametric) Shewhart-type chart based on the Lepage 2 statistic for simultaneously monitoring both the location and the scale parameters of a continuous distribution when both of these parameters are unknown. In the present work, we consider a single distribution-free CUSUM chart, based on the Lepage 2 statistic, referred to as...