Proposed Double Sampling Variable Sampling Interval Coefficient of Variation Chart for Manufacturing

Abstract

The aim of this study is to develop a new control chart, known as the double sampling variable sampling interval coefficient of variation (DS VSI CV) chart for an improved monitoring of the process CV. Process monitoring in manufacturing usually requires the process mean or standard deviation to be controlled. Nevertheless, for many quality characteristics, their standard deviations change with their means. Under this situation, a coefficient of variation control chart is adopted to monitor the process. The double sampling scheme improves the Shewhart scheme in the detection of small and medium shifts. Also, varying the sampling interval can significantly improve a chart’s sensitivity to identify process shifts. In this paper, the design of the double sampling chart by adopting a variable sampling interval scheme is suggested for controlling the coefficient of variation. Results are presented in the tables for the DS VSI CV chart. The DS VSI CV chart is compared with the DS CV, variable parameter coefficient of variation (VP CV), and exponentially weighted moving average coefficient of variation (EWMA CV) charts. From the comparison, the DS VSI CV chart surpasses the DS CV and VP CV charts in the detection of all sizes of shifts using the out-of-control average time to signal measure. Meanwhile, the EWMA CV chart beats the DS VSI CV chart for the sample size,  and very small shift , for all in control CV,  values. For the out-of-control standard deviation of the time to signal criterion, the DS VSI CV chart overtakes the DS CV and VP CV charts for all (n₀, , ) combinations. An example is provided to illustrate the application of the DS VSI CV chart to help quality engineers implement the proposed chart to monitor their manufacturing processes. This study contributes to a more effective scheme for the process CV, through the developed DS VSI CV chart that surpasses the existing CV charts’ ability in detecting shifts in the process CV, making it a great tool in facilitating timely interventions to maintain process quality and efficiency.