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## STAT QUALITY ASSURN

by: Janiya Herzog

31

0

5

# STAT QUALITY ASSURN I E 361

Janiya Herzog
ISU
GPA 3.85

Stephen Vardeman

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COURSE
PROF.
Stephen Vardeman
TYPE
Class Notes
PAGES
5
WORDS
KARMA
25 ?

## Popular in Industrial Engineering

This 5 page Class Notes was uploaded by Janiya Herzog on Sunday September 27, 2015. The Class Notes belongs to I E 361 at Iowa State University taught by Stephen Vardeman in Fall. Since its upload, it has received 31 views. For similar materials see /class/214508/i-e-361-iowa-state-university in Industrial Engineering at Iowa State University.

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Date Created: 09/27/15
IE 361 Module 13 Control Charts for Counts quotAttributes Data Profs Stephen B Vardeman and Max D Morris Reading Section 33 Statistical Quality Assurance Methods for Engineers In this module we discuss the Shewhart control charts for so called quotfraction nonconforming and quotmean nonconformities per unit contexts These are the Shewhart p and np charts and the Shewhart u and c charts These tools are easy enough to explain and use but are typically really NOT very effective in modern applications where acceptable nonconformity rates are so small as to be stated in quotparts per million p Charts and np Charts The scenario under which a p chart or np chart is potentially appropriate is one where periodically groups of n items or outcomes from a process are 2 looked at and X the number of outcomes among the n that are quotnonconformingquot is observed This is illustrated in the cartoon in Figure 1 where dark balls represent nonconforming outcomes II Items or Process Outcomes Figure 1 Cartoon Representing 71 Process Outcomes X of Which are Non conforming In this kind of circumstance the notation 13 the sample fraction nonconforming n is standard and 0 control charts for 13 are called p charts 0 control charts for X 2 n13 are called np charts lfthe process producing itemsoutcomes is physically stable a reasonable prob ability model for X met in Stat 231 is the binomial mp

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