Statistical Design of Attribute Charts for Monitoring and Continuous Improvement When Count Levels Are Low

  • Erwin M. Saniga
  • Darwin J. Davis
  • James M. Lucas
Conference paper
Part of the Frontiers in Statistical Quality Control book series (FSQC, volume 7)


Consider the situation where an attribute chart is being used to monitor a process for special causes of variability and attempts at continuous improvement are being made. In certain cases where the count level is low no lower control limit will exist for standard Shewhart control charts.

Optimal methods for shift detection when attribute data is being used are traditional CUSUM methods but CUSUM methods have not enjoyed wide popularity when compared to Shewhart methods because they are difficult to apply and understand.

In this paper we show how one can design special CUSUMs that will enable the Shewhart attribute chart user to monitor decreases in the process parameter when count levels are small. These CUSUMs, like the Shewhart chart, are easy to understand, easy to use, and, with the application of the algorithm given in this paper, easy to design.

A comparison with traditional CUSUMs is given and a variety of example designs developed using this algorithm are presented.


Control Chart High Side CUSUM Chart Statistical Quality Control Lower Control Limit 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Erwin M. Saniga
    • 1
  • Darwin J. Davis
    • 1
  • James M. Lucas
    • 2
  1. 1.University of DelawareUSA
  2. 2.J. M. Lucas and AssociatesUSA

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