Joint economic design of x and R charts under Weibull shock models

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Monitoring Process Mean and Variability with One Non-central Chi-square Chart (2004, background): “…studied for monitoring processes which might be subject to different types of assignable causes, including the assignable cause that shifts the process mean and increases variability (see Jones & Case, 1981; Saniga, 1989; Rahim, 1989; Costa, 1993, 1998; Rahim & Costa, 2000; Ohta et al., 2002).”
Economic design of X charts with variable parameters: The Markov chain approach (2001, background): “Costa and Rahim (2000), and Rahim and Costa (2000) studied the joint economic design of XÅ and R charts under non-Markovian shock models.”
A Single EWMA Chart for Monitoring Process Mean and Process Variance (2006, methodology): “The use of the non-central chi-square statistic to control the process mean and variance has also been considered by Costa and Rahim [8].”
Self-starting control chart for simultaneously monitoring process mean and variance (2010, methodology): “…that are designed for monitoring the mean and variability, respectively, such as the combination of Shewhart X (or X) and R (MR or S) charts (Rahim 1989, Saniga 1989, Costa 1993, Rahim and Costa 2000) and the combination of EWMA-type charts (Domangue and Patch 1991, Reynolds and Stumbos 2001).”