1. MEANING & SIGNIFICANCE OF
STATISTICAL PROCESS CONTROL
[SPC]
Presented by,
JAYA VARATHAN B
SANKARAN S
SARAVANAN J
THANGAVEL S

2. PRESENTATION OUTLINE
• History Of SPC
• Meaning &Significance Of SPC
• SPC in TQM
• SPC in Production
• SPC Process
• Variation-Natural&Assignable
• Using sample in SPC
• Control charts using SPC
• Applying SPC to services
• Advantages of SPC

3. HISTORY OF SPC
 Foundation for Statistical Process
Control was laid by Dr.Walter
Shewart
 In 1920s conducting research on
methods to improve quality and
lower costs .
 Concept of control with regard to
variation, and came up with
Statistical Process Control
Charts.
 Today,SPC is used in both
production & services all over the
world.

4. MEANING OF SPC
Method for achieving quality control in
manufacturing processes.
An optimisation philosophy concerned with
continuous process improvements, using a
collection of (statistical) tools for
– data and process analysis
– making inferences about process behaviour
– decision making
 It Employs control charts to detect whether
the process obeserved is under control or not.

5. SIGNIFICANCE OF SPC
Detecting error at inspection.
More uniform quality of production.
Reduces inspection costs.
Reduces no of rejects and saves the cost of
material.
Determining the capability of the
manufacturing process.
Once the process is stable, provides process
capability analysis with comparison to product
tolerance.

6. SPC IN TQM
SPC
– Using PDSA CYCLE .
– Tool for identifying problems
and make improvements.
– Contributes to the TQM goal
of continuous improvements.

7.  Variation is inherent in every process.
 Natural or common causes.
 Special or assignable causes.
 Four sources of variation - Process, materials,
operators & miscellaneous [ includes
heat,light,radiation and humidity].
 Provides a statistical signal when assignable
causes are present.
 Detect & eliminate assignable causes of
variation.
SPC IN PRODUCTIONSPC IN PRODUCTION

8. PROCESS IN SPC
Identify measurable atrributes of process
Identify defined process
Characterize natural variation of attributes
Is process
controlled ?
Identify
assignable causes
Track variation Removes
assignable cause
YES
NO

9. NATURAL VARIATION
Common causes
Inherent in a process
Cannot be eliminated
Like difference in operator ,machine vibration,
minor variation in raw materials ...etc;
Output measures follow a probability
distribution
For any distribution there is a measure of central
tendency and dispersion
If the distribution of outputs falls within

10. ASSIGNABLE VARIATION
Special causes
Larger in magnitude and easily traced
Can be eliminated only through improvements
in the system
Like difference among machines,process,
materials, relationship with one another....etc;
When assignable causes are present
Eliminate the bad causes
Incorporate the good causes

11. USING SAMPLES IN SPCUSING SAMPLES IN SPC
To measure the process, we take samples and
analyze the sample statistics following these steps
(a) Samples of the product, say five boxes of cereal
taken off the filling machine line, vary from each
other in weight
Frequency
Weight
#
## #
##
##
#
# # ## # ##
# # ## # ## # ##
Each of these represents
one sample of five boxes of
cereal

12. CONTROL CHARTS USING SPCCONTROL CHARTS USING SPC
Control charts, also known as Shewhart charts
(after Walter A. Shewhart) or process-behavior
charts, in statistical process control are tools used
to determine if a manufacturing or business
process is in a state of statistical control.

13. OBJECTIVES
Be able to explain how control charts relate to
assigned dimension and tolerance
State what value you get from control charts
Be able to name several ways that control
charts indicate that a process is “out of
control”

14. Normal Distribution
Defined by two parameters:
mean and standard deviation
Reminder:

15. , R AND S CHART
 Mean [avg] - Calculated by summing all of the
observations and dividing by the number of
observations.
 Range - Measure of the spread of the data, calculated
as highest value minus lowest value
 SD -Measure of the spread of a set of data from its
mean, abbreviated:
σ for a population , s for a sample
The standard deviation is the square root of the
variance.
X
X

16. What does the control chart look like?X
- First we measure a number of parts as they come off the
line.
- For eg we might measure 4 parts per hour for 20 hours.
Those 80 parts would give us an overall mean and standard
deviation that would define the control chart.
µ
µ+3σ
µ-3σ
Time

17. Q - How do you know a process is “out of control”?
A – When the data aren’t “normal”
“Out of Control” cues include
- Points outside of control limits (±3σ)
- 8 consecutive points on one side of center line
- 2 of 3 consecutive points outside the 2σ limits
- 4 of 5 points outside the 1 σ limits
- 7 consecutive points trending up or down

18. 2.50±0.05
Example:
Suppose we specify a dimension
and tolerance as shown.
X

19. µ+3σµ-3σ
2.552.45
Assigned Tolerances
Measured Variation
How does the control
chart relate to the tolerances?

20. Defect Prevention
When you see signs that the process is “out of
control” you can look for and fix the causes
before you make bad parts.
The control chart can help you distinguish
between “common cause” & “special cause”
problems.

23. Nature of defect is different in services
Service defect is a failure to meet customer
requirements
Monitor times, customer satisfaction
Applying SPC to Service

24. Applying SPC to Service
 Hospitals
 timeliness and quickness of care, staff responses to requests,
accuracy of lab tests, cleanliness, courtesy, accuracy of
paperwork, speed of admittance and checkouts
 Grocery Stores
 waiting time to check out, frequency of out-of-stock items,
quality of food items, cleanliness, customer complaints,
checkout register errors
 Airlines
 flight delays, lost luggage and luggage handling, waiting time
at ticket counters and check-in, agent and flight attendant
courtesy, accurate flight information, passenger cabin
cleanliness and maintenance

25. ADVANTAGES OF SPC
Improving product quality
Improving productivity
Streamlining process
Reducing wastage
Reducing emissions
Improving customer service, etc.