Multivariate control charts are essential tools in multivariate statistical process control. In real applications, when a multivariate process shifts, it occurs in either location or scale. Several methods have been proposed recently to monitor the covariance matrix. Most of these methods use rational subgroups and are used to detect large shifts. In this paper, we propose a new accumulative me...

Process monitoring refers to the task of detecting abnormal process operations resulting from the shift in the mean and/or the variance of one or more process variables. To successfully operate any process it is important to detect and diagnose any process upsets, equipment failures or other events that may have significant impact on energy consumption and productivity. In most manufacturing pr...

In some statistical process monitoring applications, quality of a process or product is described by more than one ordinal factors called ordinal multivariate process. To show the relationship between these factors, an ordinal contingency table is used and modeled with ordinal log-linear model. In this paper, a new control charts based on ordinal-normal statistic is developed to monitor the ord...

in this project creep feed grinding process of gas turbine blade root is investigated with the aim of consistant and controlable production. inthispaper, effectiveness of creep feed grinding process prometers suchas wheel speed, workpiece speed, grind depth and dresser speed are investigated. this investigation include their interaction on thelob of gas torbine blade root, as amajor cause of a ...

Simultaneously monitoring two or more quality characteristics depends on the development of more specific statistical tools to detect, identify and analyze the major causes of variability that affect the behavior of the production process. The multivariate control charts represent one of these emerging statistical techniques successfully used to monitor simultaneously several correlated charact...

The global steel industry is striving to improve product quality through excellence in operation. To support this, significant investments have been made in upgrading instrumentation, data acquisition and computing infrastructures. The expectation is that with more process and product data readily available, useful information and better process knowledge can be gained in a timely fashion. The ...

An extremely important issue in quality management is monitoring and diagnosing processes, and, subsequently, supervising them using so-called control charts. In typical production charts with constant parameters are commonly used, such as x-R, x-s, CUSUM, EWMA others, which, most cases, effective tools for process stability evaluation. Charts considered untypical (in statistical control) those...

In this paper, first the available single charting methods, which have been proposed to detect simultaneous shifts in a single process mean and variance, are reviewed. Then, by designing proper simulation studies these methods are evaluated in terms of in-control and out-ofcontrol average run length criteria (ARL). The results of these simulation experiments show that the EWMA and EWMS methods ...