Shift Detection Properties of Moving Centerline Control Chart Schemes

Christina M. Mastrangelo · Evelyn C. Brown

17 citations0/0 files storedJournal of Quality Technology

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Advanced Statistical Process Monitoring Fault Detection and Control Systems Management Systems and Quality Improvement

Abstract

In statistical process monitoring, violating the assumption of independent data results in a control chart that exhibits increased false alarms and trends on both sides of the centerline. Autocorrelation requires modification to traditional control chart techniques. This paper explores the shift detection capability of the moving centerline exponentially weighted moving average (MCEWMA) chart and recommends enhancements for quicker detection of small process upsets.

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1977Time Series Analysis: Forecasting and Control 1959Control Chart Tests Based on Geometric Moving Averages 1986The Exponentially Weighted Moving Average 1988Time-Series Modeling for Statistical Process Control 1991Some Statistical Process Control Methods for Autocorrelated Data 1997Introduction to Statistical Quality Control 1989Design of Exponentially Weighted Moving Average Schemes 1994Run-Length Distributions of Special-Cause Control Charts for Correlated Processes

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