Journal of Quality Technology · 2000 · 495 citations · 48 references
EngineeringProcess VariationControl ChartingSmart ManufacturingControl ChartsControl Chart PerformanceOperations ResearchUncertainty QuantificationAbstractstatistical Process ControlSystems EngineeringStatisticsQuantitative ManagementStatistical Quality ControlProcess MeasurementProcess MonitoringProcess AnalysisProbability TheoryStatistical Process ControlProcess ControlBusinessIndustrial Process Control
Statistical process control (SPC) methods are widely used to monitor and improve manufacturing processes, yet frequent disputes arise over their theory, application, and relevance. The paper aims to resolve key SPC controversies to improve communication between practitioners and researchers. The authors propose a resolution framework for SPC disagreements to enhance practitioner‑researcher communication. Author contact: bwoodall@vt.edu.
AbstractStatistical process control (SPC) methods are widely used to monitor and improve manufacturing processes and service operations. Disputes over the theory and application of these methods are frequent and often very intense. Some of the controversies and issues discussed are the relationship between hypothesis testing and control charting, the role of theory and the modeling of control chart performance, the relative merits of competing methods, the relevance of research on SPC and even the relevance of SPC itself. One purpose of the paper is to offer a resolution of some of these disagreements in order to improve the communication between practitioners and researchers.KeywordsAverage Run LengthControl ChartsCumulative Sum Control ChartsExponentially Weighted Moving Average Control Charts Additional informationNotes on contributorsWilliam H. WoodallDr. Woodall is a Professor in the Department of Statistics. He is a Fellow of ASQ. His e-mail address is bwoodall@vt.edu.
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