Basics of Statistical Process Control. It Contains Variation, Variability, Control Charts, Process Capability, Process Capability indices.

1. Statistical
Process Control
A Seminar By
Tushar Prakash Naiknaware
M.Pharmacy
(Quality Assurance)
Roll No. QA 14
Under the Guidance of
Prof. Mukesh Patil Sir
Shri. D.D Vispute College Of Pharmacy & Research Center
2020-2021
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2. Content
1. Introduction to SPC
2. Process Variability
2.1 Causes of Variation
2.2 Variation Management
3. Process Control
3.1 Process Control using Variables
3.2 Process Control using Attributes
4. Process Capability
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3. 1. Introduction to SPC
What is meant by Statistical Process Control?
Statistical process control (SPC) is defined by the American
Society for Quality as “the application of statistical techniques to
control a process.”
SPC tools and procedures can help you monitor process behavior,
discover issues in internal systems, and find solutions for
production issues.
SPC is also useful in demonstrating that a process is capable of
consistently delivering what the customer wants.
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4. The SPC is made up of three terms :
• Statistics - the science of collecting, analyzing, presenting, and
interpreting data.
• Process - the transformation of a set of inputs, which can
include materials, actions, methods and operations into desired
outputs, in the form of products, information, services or –
generally – results.
• Control - the power to direct, or an accepted comparison
model in an experiment, or a device used for regulation.
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5. 2. Process Variability
What is meant by Variability/Variation?
• Variability in statistics refers to the difference being exhibited
by data points within a data set, as related to each other or as
related to the mean.
• Process variability is the variation that occurs during the
manufacturing process and occurs in all manufacturing
processes.
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6. 2.1 Causes of Variation
Basically, the type of variation is based on it’s causes and is divided
into two categories:
1. Common cause variation: inherent in the process.
2. Special cause variation: due to real changes.
Common cause variation-
• Inherent to a system, random, always present and hence predictable
within statistical limits.
• Eliminate inherent variability (noise) is difficult
• When only common causes of variations are present in a process,
the process is considered to be ‘stable’, ‘in statistical control’ or ‘in
control’.
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7. Special cause variation-
• Exterior to a system, non-random, not always present (intermittent).
• Can cause changes in the output level, such as a spike, shift, drift, or non-
random distribution of the output.
• When special causes of variation are present, variation will be excessive
and the process is classified as ‘unstable’, ‘out of statistical control’ or
beyond the expected random variations.
Sources of Variation
• People - Every person is different
• Materials - Each piece of material/item/tool is unique
• Methods - Signatures for example
• Measurement - Samples from certain areas etc can bias results
• Environment - The effect of seasonality on hospital admissions
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8. 2.2 Variation Management
• We need to get the ‘big picture’, and see the context of the
data/information.
• This is best achieved by plotting a run chart, which will show
whether or not the process has or is changing over time.
• The purpose of a control chart is to detect change in the
performance of a process.
Ideally these should be used together to detect:
 Changes in absolute level (centering/accuracy).
 Changes in variability (spread/precision).
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9. Measures of accuracy or centering
• Mean (or arithmetic average)
• Median
• Mode
Following Diagram Shows a Comparison between Mean, Median
and Mode
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10. Measures of precision or spread
• Range
The range is the difference between the highest and the lowest observations
and is the simplest possible measure of scatter.
• Standard Deviation
The standard deviation takes all the data into account and is a measure of the
‘deviation’of the values from the mean.
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11. Formula For Standard Deviation of a Sample in a entire population is given by
The Normal Distribution
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12. 3. Process Control
What is meant by Process Control?
• Process control is the ability to monitor and adjust a process to
give a desired output.
• It is the active changing of the process based on the results of
process monitoring.
• Process Control is mostly done by using two methods-
 Process control using variables
 Process control by attributes
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13. • Control charts are designed to be used by
operators for Process Control.
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14. 3.1 Process Control using
Variables
• X-MR chart
• X-bar R Chart
• X-bar S Chart
X-MR chart
• An individuals and moving range (X-MR) chart is a pair of control charts
for processes with a subgroup size of one.
• Used to determine if a process is stable and predictable, it creates a
picture of how the system changes over time.
• The individual (X) chart displays individual measurements. The
moving range (MR) chart shows variability between one data point
and the next.
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16. X-bar R Chart
• An X-bar and R (range) chart is a pair of control charts used with processes
that have a subgroup size of two or more.
• The X-bar chart shows how the mean or average changes over time and the
R chart shows how the range of the subgroups changes over time.
• It is also used to monitor the effects of process improvement theories.
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17. X-bar S Chart
• Used with processes that have a subgroup size of 11 or more,
X-bar and s charts show if the system is stable and predictable.
• Instead of using subgroup range to chart variability, these
charts use subgroup standard deviation. Because standard
deviation uses each individual reading to calculate variability,
it provides a more effective measure of the process spread.
• The sigma chart, on the bottom, shows how the data is spread
and used to study system variability.
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19. 3.2 Process Control using
Attributes
For Defects/non-conformities
• u-charts
• c-charts
For Defectives/non-conforming units
• np-charts
• p-charts
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20. u-charts
• A u-chart is an attributes control chart used with data collected in
subgroups of varying sizes.
• U-charts show how the process, measured by the number of
nonconformities per item or group of items, changes over time.
• U-charts are used to determine if the process is stable and predictable, as
well as to monitor the effects of process improvement theories.
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21. c-charts
• A c-chart is an attributes control chart used with data collected in subgroups
that are the same size.
• C-charts show how the process, measured by the number of
nonconformities per item or group of items, changes over time.
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22. np-charts
• An np-chart is an attributes control chart used with data collected in
subgroups that are the same size.
• The process attribute (or characteristic) is always described in a yes/no,
pass/fail, go/no go form.
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23. p-charts
• A p-chart is an attributes control chart used with data collected in
subgroups of varying sizes.
• Because the subgroup size can vary, it shows a proportion on
nonconforming items rather than the actual count.
• The process attribute (or characteristic) is always described in a yes/no,
pass/fail, go/no go form.
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24. 4. Process Capability
• Process Capability: It refers to the normal behavior of a
process when operating in a state of statistical control.
It also refers to the inherent ability of a process to similar
parts for a sustained period of time under a given set of
condition.
• Process Capability Indices: Process capability can be
expressed as percent nonconforming or in terms of the natural
spread related to the specification spread.
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25. Process Capability Indices
1. Cp
- A process capability index that indicates the process’ potential performance
by relating the natural process spread to the specification (tolerance)
spread.
2. Cpk(2-Sided Specification Limits)
- This is a process capability index that indicates the process actual
performance by accounting for a shift in the mean of the process toward
either the upper or lower specification limit.
Cpku=Cpk (Upper Specification Limit)
Cpkl=Cpk(Lower Specification Limit)
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26. 3. Capability Index for Attributes Data
a. No failures to meet specifications
b. With failures to meet specifications
4. Capability Index for use with Target Values, Cpm
Cpm is used when a target value other than the center of the specification
spread has been designated as desirable.
Where T is the process target value other than the center of the specification.
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27. References
1. John Oakland, Statistical Process Control, Sixth Edition,;
Elsevier:Butterworth-Heinemann; 2007, Page no.83-97;192-
207.
2. Process Variation – LabCE.com, Laboratory Continuing
Education
https://www.labce.com/spg737465_process_variation.aspx (accessed July 3, 2021)
3. Using Statistics to Measure & Analyze Process Variability in
Business – Video & Transcript, Study.com
https://study.com/academy/lesson/using-statistics-to-measure-analyze-process-variability-
in-business.html#:~:text=Lesson%20Summary-
,Process%20variability%20is%20the%20variation%20that%20occurs%20during%20the%
20manufacturing,is%20to%20reduce%20this%20variability (accessed July 3, 2021)
4. Daniel Y. Peng, Ph.D; Using Control Charts to Evaluate
Process Variability; U.S Food and Drug Administration.
http://pqri.org/wp-content/uploads/2015/09/02-Peng-Using-Control-Chart-to-Evaluate-
Process-Variability-Final.pdf (accessed July 3, 2021)
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28. 5. PQ Systems, Improve Your Quality, pqsystem.com
https://www.pqsystems.com/ (accessed July 4, 2021)
6. Symphony Technologies Planning, Design & Analysis;
Measuring Your Process Capability
http://www.symphonytech.com/articles/pdfs/processcapability.pdf (accessed July 4,
2021)
7. M. Suozzi, Process Capability Studies, Hughes Aircraft
Company, Tucson, Arizona, 27 November 1990.
https://elsmar.com/pdf_files/CPK.pdf (accessed July 4, 2021)
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