Journal of Quality Technology · 2001 · 160 citations · 7 references
EngineeringMeasurementControl ChartsAccuracy And PrecisionSystem MeasurementCalibrationUncertainty QuantificationSystems EngineeringSignificant Measurement ErrorInstrumentationStatisticsQuantitative ManagementProcess MeasurementReliabilityProcess MonitoringQuality Control ApplicationsMeasurement ErrorPerformance MonitoringProcess ControlBusinessMeasurement System
Measurement error is common in quality control, reduces the power of X̄ and S₂ charts to detect shifts, and multiple measurement techniques exist, with one typically providing the greatest power per measurement. The study investigates how measurement error affects X̄ and S₂ chart performance, explores when multiple measurements per subgroup improve detection, proposes a cost‑based sampling plan, and examines a model where error variance grows linearly with the process mean. The authors employ a linear covariate in X̄ and S₂ charts, analyze multiple measurements per item, develop a cost model for optimal sampling, and study a model with mean‑dependent error variance. Measurement error leads to a loss of power in detecting shifts in the process mean or variance.
Significant measurement error often exists in quality control applications. Measurement error is known to result in reduced power to detect a given change in the mean or variance of a quality characteristic. There are often several available measurement techniques, among which one yields the greatest power per measurement to detect process shifts. The effect of measurement error on the performance of X̄ and S2 charts using a linear covariate is investigated. One of the effects of measurement error is a loss of power in detecting parameter shifts in the underlying process variable. In the presence of measurement error, it may be desirable to take multiple measurements for each of the items in a subgroup. Conditions under which multiple measurements are desirable are identified, and a cost model is suggested for selection of an optimal sampling plan. A model involving measurement error variance that is a linearly increasing function of the process mean is also investigated.
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