Introduction to Statistical Quality Control, Fifth Edition

By William H. Woodall. 2005

577 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/1c1cbcad9ebf9263a032918d6933d58f6ccd39a3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

Citations in the corpus

Investigating the effects of innovation and employee performance on the relationship between total quality management practices and firm performance: An empirical study of Turkish firms (2010, methodology): “Tan (2005), Nair (2006), Choi and Eboch (1998), Rungtusanatham et al.”
Control Charts for Simultaneous Monitoring of Unknown Mean and Variance of Normally Distributed Processes (2013, methodology): “His email address is amitmukh2@yahoo.co.in. been popular tools for use in statistical process control (Montgomery (2005)).”
Nonparametric CUSUM and EWMA Control Charts for Detecting Mean Shifts (2010, methodology): “The details of parametric CUSUM and EWMA charts design can be found in Montgomery (2005), Woodall and Adams (1993), and Lucas and Saccucci (1990). 3.”
Directional MEWMA Schemes for Multistage Process Monitoring and Diagnosis (2008, methodology): “This charting scheme follows an idea similar to the group Shewhart charts in Montgomery (2004) but is more sensitive to small and moderate shifts.”
Effect of the Amount of Phase I Data on the Phase II Performance of S2 and S Control Charts (2015, methodology): “With m = 25 or 30 phase I samples of size n = 4 or 5—a usual recommendation in textbooks and SPC guides (see, for instance, Montgomery (2012), subsection 6.”
Optimal Design of a CUSUM Chart for a Mean Shift of Unknown Size (2010, methodology): “In this paper, Siegmund’s approximation is used due to its simplicity and effectiveness (Montgomery (2004)).”
The Use of Control Charts in Health-Care and Public-Health Surveillance (2006, methodology): “The geometric chart methods are yet to be included in popular textbooks, such as Montgomery (2005), however, or in software such as MINITAB.”
CUSUM Monitoring of First-Order Integer-Valued Autoregressive Processes of Poisson Counts (2009, methodology): “Here we devise the CUSUM control charts (Page (1954)) due to their sensitivity in detecting small shifts.”
Control Charts for Poisson Count Data with Varying Sample Sizes (2010, methodology): “Often Lu = 3, resulting in the usual three-sigma limits (Montgomery (2009)).”
EWMA Control Charts for Monitoring Optimal Portfolio Weights (2007, result): “The difference chart based on the multivariate EWMA statistic (MEWMA Dif) provides the worst results.”
GA: A Package for Genetic Algorithms in R (2013, background): “An introduction to acceptance sampling is contained in the textbook by Montgomery (2009), while a monograph devoted to the argument is Schilling and Neubauer (2009).”
Some Current Directions in the Theory and Application of Statistical Process Monitoring (2014, methodology): “For a description of this approach, see Montgomery and Woodall (2008). Within the DMAIC process, process monitoring plays a large role. It is useful in the measure phase to assess current performance and to monitor the performance of measurement systems. It is also useful in the control phase to mon”
Distribution-free monitoring of univariate processes (2011, methodology): “See, e.g., Hawkins and Olwell (1998), Montgomery (2009), Woodall (2000), and Yeh et al. (2004) for related discussion.”
Phase I Distribution-Free Analysis of Univariate Data (2013, methodology): “Despite its crucial importance, a general discussion of Phase I analysis can be found in a few SPC textbooks (see, e.g., Montgomery (2005)).”