ASTM E2587-07e1
(Practice)Standard Practice for Use of Control Charts in Statistical Process Control
Standard Practice for Use of Control Charts in Statistical Process Control
SIGNIFICANCE AND USE
This practice describes the use of control charts as a tool for use in statistical process control (SPC). Control charts were developed by Shewhart (1) in the 1920s and are still in wide use today. SPC is a branch of statistical quality control (2, 3), which also encompasses process capability analysis and acceptance sampling inspection. Process capability analysis, as described in Practice E2281, requires the use of SPC in some of its procedures. Acceptance sampling inspection, described in Practices E1994 and E2234, requires the use of SPC so as to minimize rejection.
Principles of SPC—A process may be defined as a set of interrelated activities that convert inputs into outputs. SPC uses various statistical methodologies to improve the quality of a process by reducing the variability of one or more of its outputs, for example, a quality characteristic of a product or service.
A certain amount of variability will exist in all process outputs regardless of how well the process is designed or maintained. A process operating with only this inherent variability is said to be in a state of statistical control, with its output variability subject only to chance, or common, causes.
Process upsets, said to be due to assignable, or special causes, are manifested by changes in the output level, such as a spike, shift, trend, or by changes in the variability of an output. The control chart is the basic analytical tool in SPC and is used to detect the occurrence of special causes operating on the process.
When the control chart signals the presence of a special cause, other SPC tools, such as flow charts, brainstorming, cause-and-effect diagrams, or Pareto analysis, described in various references (3-7), are used to identify the special cause. Special causes, when identified, are either eliminated or controlled. When special cause variation is eliminated, process variability is reduced to its inherent variability, and control charts then function as a process monitor. ...
SCOPE
1.1 This practice provides guidance for the use of control charts in statistical process control programs, which improve process quality through reducing variation and controlling the process to a particular target level or historical average.
1.2 Control charts are used to monitor product or process characteristics to determine whether or not a process is in a state of statistical control. When this state is attained, the true mean and the true standard deviation of that characteristic are constant.
1.3 This practice applies to variables data (characteristics measured on a continuous numerical scale) and to attributes data (characteristics measured as percentages, fractions, or counts of occurrences in a defined interval of time or space).
1.4 The system of units for this practice is not specified. Dimensional quantities in the practice are presented only as illustrations of calculation methods. The examples are not binding on products or test methods treated.
1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.
General Information
Standards Content (Sample)
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Designation:E2587–07
Standard Practice for
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Use of Control Charts in Statistical Process Control
This standard is issued under the fixed designation E2587; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (ϵ) indicates an editorial change since the last revision or reapproval.
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ϵ NOTE—Minor corrections were made editorially in February 2010.
1. Scope E1994 Practice for Use of Process Oriented AOQL and
LTPD Sampling Plans
1.1 This practice provides guidance for the use of control
E2234 Practice for Sampling a Stream of Product by
charts in statistical process control programs, which improve
Attributes Indexed by AQL
process quality through reducing variation and controlling the
E2281 Practice for Process and Measurement Capability
process to a particular target level or historical average.
Indices
1.2 Control charts are used to monitor product or process
characteristics to determine whether or not a process is in a
3. Terminology
state of statistical control. When this state is attained, the true
3.1 Definitions—See Terminology E456 for a more exten-
mean and the true standard deviation of that characteristic are
sive listing of statistical terms.
constant.
3.1.1 assignable cause, n—factor that contributes to varia-
1.3 This practice applies to variables data (characteristics
tion in a process or product output that is feasible to detect and
measured on a continuous numerical scale) and to attributes
identify (see special cause).
data (characteristics measured as percentages, fractions, or
3.1.1.1 Discussion—Many factors will contribute to varia-
counts of occurrences in a defined interval of time or space).
tion, but it may not be feasible (economically or otherwise) to
1.4 The system of units for this practice is not specified.
identify some of them.
Dimensional quantities in the practice are presented only as
3.1.2 attributes data, n—observed values or test results that
illustrations of calculation methods. The examples are not
indicate the presence or absence of specific characteristics or
binding on products or test methods treated.
counts of occurrences of events in time or space.
1.5 This standard does not purport to address all of the
3.1.3 average run length (ARL), n—the average number of
safety concerns, if any, associated with its use. It is the
times that a process will have been sampled and evaluated
responsibility of the user of this standard to establish appro-
before a shift in process level is signaled.
priate safety and health practices and determine the applica-
3.1.3.1 Discussion—A long ARL is desirable for a process
bility of regulatory limitations prior to use.
located at its specified level (so as to minimize calling for
2. Referenced Documents unneededinvestigationorcorrectiveaction)andashortARLis
2 desirable for a process shifted to some undesirable level (so
2.1 ASTM Standards:
that corrective action will be called for promptly).ARLcurves
E456 Terminology Relating to Quality and Statistics
are used to describe the relative quickness in detecting level
shifts of various control chart systems (see section 5.4). The
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This practice is under the jurisdiction ofASTM Committee E11 on Quality and
average number of units that will have been produced before a
Statistics and is the direct responsibility of Subcommittee E11.30 on Statistical
shift in level is signaled may also be of interest from an
Quality Control.
economic standpoint.
Current edition approved Oct. 1, 2007. Published November 2007. DOI:
10.1520/E2587-07E01.
3.1.4 c chart, n—control chart that monitors the count of
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For referenced ASTM standards, visit the ASTM website, www.astm.org, or
occurrencesofaneventinadefinedincrementoftimeorspace
contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
3.1.5 center line, n—line on a control chart depicting the
Standards volume information, refer to the standard’s Document Summary page on
average level of the statistic being monitored.
the ASTM website.
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E2587–07
3.1.6 chance cause, n—source of inherent random variation corrective action strategy used to bring the process back into a
in a process which is predictable within statistical limits (see state of statistical control.
common cause). 3.1.21 subgroup, n—set of observations on outputs sampled
from a process at a particular time.
3.1.6.1 Discussion—Chance causes may be unidentifiable,
3.1.22 uppercontrollimit(UCL),n—maximumvalueofthe
or may have known origins that are not easily controllable or
control
...
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