ASQ

Exclusive Content & Downloads from ASQ

c-charts, X-charts, and the Katz Family of Distributions

Summary: [This abstract is based on the author's abstract.] The c-chart is the principle method used to monitor the number of nonconformities in statistical process control. The conventional c-chart assumes that nonconformities in samples are well modeled by a Poisson distribution, but when that assumption is not met, the X-chart is often used as an alternative. The relative merits of the c-chart are compared to the X-chart for the Katz family of distributions relative to the Poisson distribution. Use of the X-chart can lead to significant improvements under certain circumstances, but both 3-sigma c- and X-charts fail to provide reliable information with a small in-control process mean when a downward mean shift occurs.

Anyone with a subscription, including Site and Enterprise members, can access this article.


Other Ways to Access content:

Join ASQ

Join ASQ as a Full member. Enjoy all the ASQ member benefits including access to many online articles.

Subscribe to Journal of Quality Technology

Access this and ALL OTHER Journal of Quality Technology online articles. You'll also receive the print version by mail.

  • Topics: Statistical Process Control (SPC)
  • Keywords: Average run length (ARL),Modified likelihood ratio principle,Poisson process,C chart (count chart),Statistical process control (SPC),X-bar charts,Robust design
  • Author: Fang, Yue
  • Journal: Journal of Quality Technology