Alternative definitions of Process Capability Indices (PCIs), based on different approaches, have been proposed in literature. Most of the research works related to Process Capability Indices assume no gauge measurement errors. However, in industrial applications, despite the use of highly advanced measuring instruments, account needs to be taken of gauge imprecision. The aim of this paper is f...

We present a model for representing stationary multivariate time series with arbitrary marginal distributions and autocorrelation structures and describe how to generate data quickly and accurately to drive computer simulations. The central idea is to transform a Gaussian vector autoregressive process into the desired multivariate time-series input process that we presume as having a VARTA (Vec...

A simple method is given to calculate the multivariate process capability index Cp * as defined by Taam et al. (1993) and discussed by Kotz & Johnson (1993). It is shown that using this index is equivalent to using the smallest univariate Cp -value to determine the capability of a process.

We investigate tests to detect general nonlinear behavior in a vector time series. The proposed tests are multivariate extensions of the univariate nonlinearity tests of Keenan (1985) and Tsay (1986). Simulation results show that, in general, the multivariate tests are more powerful than their univariate counterparts, especially for series having nonlinear structure that involves several compon...

process capability indices (pcis) can be used as an effective tool for measuring product quality and process performance. in classic quality control there are some limitations which prevent a deep and flexible analysis because of the crisp definition of pca‟s parameters. fuzzy set theory can be used to add more flexibility to process capability analyses. in this study, the fuzzy x ba and mrx ba...

Monitoring, control and improvement of quality are  important  for companies.  Process capability indices (PCIs) are tools widely used by the industries to determine  the quality of their products and the performance of their manufacturing processes. Classic versions of  these  indices were constructed for processes whose quality characteristics have  a  normal distribution. But, many of these ...

As one of important nonparametric regression method, support vector regression can achieve nonlinear capability by kernel trick. This paper discusses multivariate support vector regression when its regression function is restricted to be convex. This paper approximates this convex shape restriction with a series of linear matrix inequality constraints and transforms its training to a semidefini...