This paper develops a model for the analysis and design of a CUSUM chart for monitoring the process mean in short production runs and proposes statistical measures of performance that are appropriate when the process is not operating indefinitely. The model can be used to evaluate the performance of the CUSUM scheme for any given set of chart parameters and thus allows comparisons with Shewhart...

Under estimated in-control parameters, the Phase II control chart performance is expected to vary among practitioners due to the use of different Phase I data sets. Accordingly, the typical measure of Phase II control chart performance, the average run length (ARL), becomes a random variable. In the literature, control charts with estimated parameters were assessed and the appropriate amounts o...

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 ...

Monitoring the coefficient of variation (CV) is a successful approach to Statistical Process Control when the process mean and standard deviation are not constant. In recent years the CV has been investigated by many researchers as the monitored statistic for several control charts. Viewed under this perspective, this paper presents a new efficient method to monitor the CV by means of Run Rules...

• We present a new adaptive sampling method for statistical quality control. In this method, called LSI (Laplace sampling intervals), we use the probability distribution function of the Laplace standard distribution to obtain the sampling instants, depending on a k parameter that allows control of sampling costs. Several algebraic expressions concerning the statistical properties of the LSI met...

This paper presents simpler alternative formulae and procedures of implementation to deal with the relative range statistic (moments, distribution and quantiles) used in the construction of range control charts for process dispersion monitoring. The Tippett’s integral formulae for sample relative range moments and distribution are revisited and simpler new alternative expressions are proposed t...

Western Electric (1956) and Nelson (1984) proposed rule sets to detect visually obvious process upsets on a control chart. Performance evaluation of these rules require simulating situations that correspond their intended detection purposes such as linear drift, cycling, seesaw sustained mean shifts. These non-random patterns become in the presence reduced variation. Contrary previous assessmen...