Series on Quality, Reliability and Engineering

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Traditional Shewhart-type control charts ignore the skewness of the plotted statistic. Omsionally, the skewness is too large to be ignored, and in such cases the classical Shewhart chart ceases to deliver satisfactory performance. In this paper, we develop a general framework for constructing Shewhart-like control charts for attributes based on fitting a quantile function that preserves all first three moments of the plotted statistic. Furthermore, these moments enter explicitly into the formulae for calculating the limits. To enhance the accuracy of these limits the value of the skewness measure used in the calculations is inflated by 44%. This inflation rate delivers accurate control limits for diversely-shaped attribute distributions like the binomial: the Poisson, the geometric and th'e negative binomial. A new control chart for the M / M / S queueing model is developed and its performance evaluated.

Response Modeling Methodology (RMM) is a new empirical modeling methodology, recently developed. In this paper, a new structured procedure to compare relational models, in terms of goodness-of-fit and stability, is developed and applied to evaluate three types of models:  Those obtained by TableCurve2D (a dedicated software for relational modeling), acceptable models recommended by DIPPR (a widely used database for constant and temperature-dependent physical properties), and models derived by RMM. For four pure substances (oxygen, argon, nitrogen, and water), model comparison had been conducted on 14 temperature-dependent physical and thermodynamic properties. Summary tables of ranking the various models are provided. Detailed results are reported in this paper for water. The three variations of the RMM model (two-, three- and four-parameter models) compare favorably with others, both in terms of goodness-of-fit and stability. The unique desirable properties of RMM models are discussed.