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Engineering and manufacturing industries

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A graphical exploration of SPC

Article Abstract:

A X bar chart analyzes the probability structure of standard rules, which are used for identifying out-of control processes. Statistical process control (SPC) is an efficient tool for improving processes and provides information by using a small amount of data. The higher the out of control a process is, the more is the non-negative number in order to maintain stability. The mean of the X bar plotted in the chart acts as a standard against which the values of standard practices are measured. The characteristics of normal distributions are discussed.

Author: Hoyer, Robert W., Ellis, Wayne C.
Publisher: American Society for Quality Control, Inc.
Publication Name: Quality Progress
Subject: Engineering and manufacturing industries
ISSN: 0033-524X
Year: 1996
Models, Usage, Graphic methods

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The probability structure of rules for interpreting control charts

Article Abstract:

Information present in control charts for statistical process control (SPC) is interpreted by quality professionals using seven rules defining specific statistics whose occurrence indicates a special reason for variation in process control. The sensitivity of the rules in indicating an out of control process is high if their probability in controled processes is low. The rules have low probabilities for both symmetrical and skewed process output distribution. Methods to determine the probability of the rules and effective use of SPC are discussed.

Author: Hoyer, Robert W., Ellis, Wayne C.
Publisher: American Society for Quality Control, Inc.
Publication Name: Quality Progress
Subject: Engineering and manufacturing industries
ISSN: 0033-524X
Year: 1996
Probabilities, Probability theory

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Another look at "A graphical exploration of SPC."(Statistical Process Control)(response to Robert W. Hoyer and Wayne C. Ellis, Quality Progress, p. 65, May 1996 and p. 57, June 1996)

Article Abstract:

Robert W. Hoyer and Wayne C. Ellis are unfamiliar with Shewhart's basis for the control chart in the graphical exploration of Statistical Process Control. A probabilistic model which is a rough evaluation of control chart tests is incorrectly implied to be the operation of a control chart. The ability of control limits of plus or minus four-sigma to give more sensitive tests than the traditional three-sigma limits is incorrect.

Author: Nelson, Lloyd S.
Publisher: American Society for Quality Control, Inc.
Publication Name: Quality Progress
Subject: Engineering and manufacturing industries
ISSN: 0033-524X
Year: 1996

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Subjects list: Analysis, Quality control, Statistical process control, Reports, Quality control charts
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