Control charts are useful tools to monitor signs of assignable cause(s) that results in poor quality products and services, especially in engineering applications. By convention, control charts detect shifts in the mean (µ) and standard deviation (σ). However, certain processes do not have a consistent µ and σ. For such processes, conventional charts will result in dubious conclusions. This motivated the development of charts monitoring the relationship between σ and µ instead, through the coefficient of variation (γ). The side sensitive synthetic chart was recently proposed to monitor γ. However, it is designed based on statistical considerations, i.e., by minimizing the expected number of samples required to detect a specific shift, while concurrently satisfying constraints in the false alarms. The weakness in this design is that it ignores the cost of the chart, which is important for most practical applications. Thus, we will propose economic and economic-statistical designs for the side sensitive synthetic γ chart, in which the former ignores statistical performance, while the latter incorporates statistical constraints. A Scicoslab program is developed to implement these two designs. The impact of various cost and process parameters are also studied.

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W. C. Yeong, Z. L. Chong, K. W. Khaw, and P. S. Ng, “Economic and economic-statistical designs of the side sensitive synthetic coefficient of variation chart,” International Journal of Applied and Physical Sciences, vol. 8, pp. 7-14, 2022. Doi:  https://dx.doi.org/10.20469/ijaps.8.50002