The document provides an overview of statistical process control (SPC). It discusses the history and need for SPC, describing how it helps ensure processes operate efficiently to reduce waste. Key aspects of SPC covered include variation and its causes, control charts, histograms, and calculating metrics like Cp and Cpk. Control charts graph process data over time to determine if a process is stable or experiencing assignable causes of variation. Histograms depict the distribution of process data. SPC enables analyzing, maintaining, and improving processes through monitoring and addressing sources of variation.

1. Statistical Process Control
Presented by
Hardil Shah

2. Table of Content
• Introduction
• History
• Need of SPC
• Variation and its Causes
• Control Chart
• Histogram
• Advantages of SPC

3. Introduction
• Statistical process control (SPC) is a method of measuring and
controlling quality by monitoring mfg. process.
• Quality data collected in form of product or process,
measurements or reading .
• SPC is an effective method to drive a continuous
improvement. By monitoring and control a process we can
assure that it operates at its fullest potential.

4. History
• SPC is not new to industry. In 1924 a man at bell laboratory
develop the control chart and concept that a process could
be in statistical control
• SPC gained wide uses during WW2 by the military in
ammunitions and weapon facilities .

5. Need of SPC
•Manufacturing companies facing ever
increasing competition at the same time raw
material cost continue to increase.
•There are the factors that the most of the
company can not control. Therefore company
must control on the thing what they can
control like: their process. Company must
strive for continuous improvement in quality,
efficiency ,and cost reduction.
•SPC is implemented to move a company from
detection based quality control to prevention
based quality control.
1
100
10
Prevention
cost
Detection
cost
Failure cost

6. Objectives for implementation of SPC
• Analyze the process
i. Attribute data: The data that can not be measured comes
under attribute data. Examples: CV, Roughness etc…
ii. Variable Data: all measurable data comes under variable
data. Example: Temperature, weight etc…
• Maintain the process
– To maintain the process we have to detect the problem intervals.
• Improve the process
– We should take Preventive Actions.

7. Variation and its causes
• There is no two things in this world that are completely alike to
each other. Those differences are known as variation.
• There are two main causes of variation:
(i) Common Causes: The cause which present always in process
are known as common cause. (85% of Total cause) Examples:-
Slight variation in temperature from set point.
(ii) Special Causes: The cause which comes in process as random
manner are known as special causes.(15% of Total cause)
Examples: change of raw m/t , change in method, etc…

8. Control Chart
Control Chart: The control chart is a graph used to study how a
process changes over time. Data are plotted in time order.
Control charts, also known as Shewhart charts or process-behavior
charts, are a statistical process control tool used to determine if a
manufacturing or business process is in a state control

9. Measurement of Central Tendency and Dispersion
• There are three ways in which Central tendency of numbers
can be measured
• These are the 3M’s
1. Mean
2. Mode
3. Median

10. Measurement of Dispersion
1. Range(R)
2. Standard deviation

11. Cp
• We are offend require to compare the
o/p of stable process with process
specification and make a statement
about how well the process meets the
specification. To do this we compare the
nature variability of stable process with
a process specification limit.
• Process where almost all the
measurements fall inside specification
limits is a capable process
• This can be represented pictorially
below.

12. Cpk
• Cpk measures how close you are to target and how consistent
you are to around your average.

13. Example of Cpk
i. this indicates lower Cpk , whereas Cp will
be high .
ii. Cpk will be lower but Cp will be high.
But Both will be negative as they cross
the specification limit
iii. This is ideal condition. Cp = Cpk
≥1.33

14. Calculation

15. Moving Range chart
• Step 1 : MR1 = 𝑋0 − 𝑋1
MR2= 𝑋1 − 𝑋2
• Step 2 : Calculate the mean of all MR data
MR Bar =
𝑴𝑹 𝟏
+𝑴𝑹 𝟐
+⋯+𝑴𝑹𝒏
𝒏
• Step 3: Calculate the UCL for Moving range
UCL = MR bar x D4 ; D4 = 3.27 (Constant, from standard)

16. What is control limits and how to find out control limits?
• Control limits: Control limits, also known as natural process limits, are horizontal
lines drawn on a statistical process control chart, usually at a distance of ±3
standard deviations of the plotted statistic from the statistic's mean.
• Standard Deviation: Standard deviation (SD, also represented by the Greek letter
sigma σor the Latin letter s) is a measure that is used to quantify the amount of
variation or dispersion of a set of values around mean. A low standard deviation
indicates that the data points tend to be close to the mean (also called the
expected value) of the set, while a high standard deviation indicates that the data
points are spread out over a wider range of values.
σ= 𝒊=𝟏
𝒏 𝑿𝒊
−x̅ 𝟐
𝒏−𝟏
X bar Chart

17. x̅ Chart
• Step 1 : Find out the mean value of given data
x̅ = 𝑖
𝑛
𝑥𝑖
𝑛
; 𝑖 = 1,2,3 … , 𝑛
x̅=
𝑥1+𝑥2+𝑥3+⋯+𝑥𝑛
𝑛
x̅= 0.057233 (from given data)

18. x̅ bar chart
• Step 2 : Subtract the mean value from the original value
i.e. (X- x̅)
• Step 3: make square of step 2
• Step 4: make sumassion of all the value
• Step 5: divide the step 4 by (n-1) ; n= number of data
• Step 6: make square root of step 5

19. x̅ chart
• Lower Control limit:
LCL= x̅ - 3σ
• Upper Control Limit:
UCL = x̅ + 3σ

20. Calculation of Cp and Cpk
• As USL is not specified in this data So Cp will be Infinity

21. Moving range chart
0
0.0005
0.001
0.0015
0.002
0.0025
0.003
0.0035
0.004
0.0045
0.005
MR BAR CHART
MR BAR CHART
UCL

22. X bar Chart
0.048
0.05
0.052
0.054
0.056
0.058
0.06
0.062
H6L118G-0168
H6L118G-0169
H6L118G-0170
H6L118G-0171
H6L118G-0172
H6L118G-0173
H6L118G-0174
H6L118G-0175
H6L118G-0176
H6L118G-0177
H6L118G-0178
H6L118G-0179
H6L118G-0180
H6L118G-0181
H6L118G-0182
H6L118G-0183
H6L118G-0184
H6L118G-0185
H6L118G-0186
H6L118G-0187
H6L118G-0188
H6L118G-0189
H6L118G-0190
H6L118G-0191
H6L118G-0192
H6L118G-0193
H6L118G-0194
H6L118G-0195
H6L118G-0196
H6L118G-0197
UCL0.0607
LCL0.053564
INCREASE DIAMETER
INCREASE…
LCL
UCL
LSL
LSL
CL
• The control chars tool would indicates that a
process is out of control if either one of
these is true:
1. Nine consecutive points are on one side of
the average.
2. These are six consecutive points, points ,
increasing or decreasing.
3. There are 14 consecutive points that
alternate up or down.
4. TWO points, out of three consecutive
points, are on the same side of the
average in ZONE A or beyond.
5. Four points, out of five consecutive points,
are on the same side of the average in
ZONE B or Beyond.
6. These are fifteen consecutive points
within Zone C.
7. These are eight points in a row in ZONE B
or beyond.

23. Histogram
• A diagram consisting of rectangles whose area is proportional
to the frequency of a variable and whose width is equal to
the class interval.
• Histograms depict the central tendency or mean of the data,
and its variation or spread. A histogram also shows the range
of measurements, which defines the process capability. A
histogram can show characteristics of the process being
measured.

24. Histogram

25. Advantages of SPC
• This helps to ensure that the process operates efficiently,
producing more specification-conforming products with less
waste (rework or scrap)
• An advantage of SPC over other methods of quality control, such
as "inspection", is that it emphasizes early detection and
prevention of problems, rather than the correction of problems
after they have occurred.
• SPC can lead to a reduction in the time required to produce the
product. SPC makes it less likely the finished product will need to
be reworked or scrapped.

26. References
1. https://www.winspc.com/what-is-spc/spc-tools/
2. https://www.itl.nist.gov/div898/handbook/pmc/section1/p
mc16.htm
3. https://quality-one.com/spc/
4. https://en.wikipedia.org/wiki/Statistical_process_control

27. THANK YOU