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DISCOVER . LEARN . EMPOWER
TOPIC OF PRESENTATION
Control Charts
University School of Business
(MBA)
SUBJECT NAME: Operations & Quality Management
SUBJECT CODE: 21BAT632
Simmi Dhyani
INTRODUCTION TO OPERATIONS MANAGEMENT
Control Charts
originally developed by
Walter A. Shewhart
Control Charts
The control chart is a statistical quality
control tool used in the monitoring variation
in the characteristics of
a product or service
Control Charts
The control chart focuses on the time
dimension and the nature of the
variability in the system.
Control Charts
The control chart may be used to study
past performance and/or to evaluate
present conditions.
Control Charts
Data collected from a control chart may
form the basis for process
improvement.
Control Charts
Levine, Prentic-Hall
Control Charts
• UCL = Process Average + 3 Standard Deviations
• LCL = Process Average - 3 Standard Deviations
Process Average
UCL
LCL
X
+ 3
- 3
TIME
Levine, Prentice-Hall
0
20
40
60
1 3 5 7 9 11
X
Time
0
20
40
60
1 3 5 7 9 11
X
Time
• Graph of sample data plotted over time
Assignable
Cause Variation
Random
Variation
Process
Average 
Mean
Control Charts
UCL
LCL
Levine, Prentice-Hall
Control Charts
X X
X
Common Cause Variation: no
points outside control limit
Special Cause Variation: two
points outside control limit
Downward Pattern: no
points outside control limit;
however, eight or more
points in trend
Control Charts
•Attribute charts
•Variables charts
Control Charts
Charts may
be used for
categorical
variables.
[i.e.: attributes]
Control Charts
Whenever a character of interest is
measured on a nominative or an interval,
ie: categorical, scale…an attributes control
chart is used to monitor a process.
Control Charts
•Attributes Control Charts
counts [c-chart]
proportion [p-charts]
Control Charts
•Attributes Control Charts
when sample size are not constant
and/or are unknown
use counts charts
[c-charts]
Control Charts
c Chart for num_defect
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
11.0
12.0
13.0
14.0
15.0
16.0
17.0
18.0
19.0
20.0
0
4
8
12
16
20
c
Centerline = 10.00
UCL = 19.49
LCL = 0.51
Control Charts
•Attributes Control Charts
when sample size are constant and are known
use proportion charts
[p-charts]
Control Charts
p Chart for defects/100
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
11.0
12.0
13.0
14.0
15.0
16.0
17.0
18.0
19.0
20.0
21.0
22.0
23.0
24.0
25.0
26.0
27.0
28.0
29.0
30.0
0
0.03
0.06
0.09
0.12
0.15
p
Centerline = 0.04
UCL = 0.10
LCL = 0.00
Control Charts
Charts may
be used for
interval or
ratio data [i.e.:
variables ]
Control Charts
Whenever a character of interest is
measured on an interval or a ratio scale, a
variables control chart is used to monitor
a process.
Control Charts
•Variables Control Charts
Mean and Range charts
[x-bar & R charts]
Control Charts
Variables control charts are typically used
used in pairs.
…… one chart monitors process average while
the other monitors the variation in a process.
Control Charts
p Chart for defects/100
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
11.0
12.0
13.0
14.0
15.0
16.0
17.0
18.0
19.0
20.0
21.0
22.0
23.0
24.0
25.0
26.0
27.0
28.0
29.0
30.0
0
0.03
0.06
0.09
0.12
0.15
p
Centerline = 0.04
UCL = 0.10
LCL = 0.00
X-bar Chart for observa
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
11.0
12.0
13.0
14.0
15.0
16.0
17.0
18.0
19.0
20.0
21.0
22.0
23.0
24.0
25.0
190
194
198
202
206
210
214
X-bar
Centerline = 203.98
UCL = 208.21
LCL = 199.75
Control Charts
Range Chart for observa
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
11.0
12.0
13.0
14.0
15.0
16.0
17.0
18.0
19.0
20.0
21.0
22.0
23.0
24.0
25.0
0
3
6
9
12
15
Range
Centerline = 5.80
UCL = 13.24
LCL = 0.00
Control Charts
In conclusion:
the control chart is a means of monitoring
variation in the characteristics of
a product or service
Control Charts
Know the
assumptions …
let the
computer do
the hard work.
References
TEXT BOOKS
• B. Mahadevan, 2007. Operations Management Theory and Practice, Pearson Education, Second Impression 2007. ISBN:
8177585649
• Dale H. Besterfiled, et at., 2006. Total Quality Management, Pearson Education Asia, Third Edition, Indian Reprint 2006.
ISBN: 978-81-317-3227-4
REFERENCE BOOKS
• R1 William J. Stevenson, 2018. Operations Management Mc Graw Hill Publications, 13th Edition ISBN: 9781259667473
• R2 James R. Evans and William M. Lindsay, 2012. “The Management and Control of Quality”, Cengage Learning, 8th
Edition, First Indian Edition, 2012. ISBN: 978032482706
• R3 Janakiraman. B and Gopal. R. K., 2006. “Total Quality Management-Text and Cases”, Prentice Hall (India) Pvt. Ltd., 2006.
ISBN: 8120329953
Sources:
• https://sixsigmastudyguide.com/statistical-process-control-spc/
• www.uoh.edu.sa/facultymembers/en/M.AICHOUNI/Documents/QEM%20511/Chapter03-Control-Charts-2017.pdf
Video Link:
• https://www.youtube.com/watch?v=lOEqli-YV2I
28
Assessment Pattern
29
THANK YOU
30
For queries get in touch with me at: simmi.e12923@cumail.in

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Lecture-5 Control Charts-1.pptx

  • 1. DISCOVER . LEARN . EMPOWER TOPIC OF PRESENTATION Control Charts University School of Business (MBA) SUBJECT NAME: Operations & Quality Management SUBJECT CODE: 21BAT632 Simmi Dhyani
  • 3. Control Charts originally developed by Walter A. Shewhart
  • 4. Control Charts The control chart is a statistical quality control tool used in the monitoring variation in the characteristics of a product or service
  • 5. Control Charts The control chart focuses on the time dimension and the nature of the variability in the system.
  • 6. Control Charts The control chart may be used to study past performance and/or to evaluate present conditions.
  • 7. Control Charts Data collected from a control chart may form the basis for process improvement.
  • 9. Levine, Prentic-Hall Control Charts • UCL = Process Average + 3 Standard Deviations • LCL = Process Average - 3 Standard Deviations Process Average UCL LCL X + 3 - 3 TIME
  • 10. Levine, Prentice-Hall 0 20 40 60 1 3 5 7 9 11 X Time 0 20 40 60 1 3 5 7 9 11 X Time • Graph of sample data plotted over time Assignable Cause Variation Random Variation Process Average  Mean Control Charts UCL LCL
  • 11. Levine, Prentice-Hall Control Charts X X X Common Cause Variation: no points outside control limit Special Cause Variation: two points outside control limit Downward Pattern: no points outside control limit; however, eight or more points in trend
  • 13. Control Charts Charts may be used for categorical variables. [i.e.: attributes]
  • 14. Control Charts Whenever a character of interest is measured on a nominative or an interval, ie: categorical, scale…an attributes control chart is used to monitor a process.
  • 15. Control Charts •Attributes Control Charts counts [c-chart] proportion [p-charts]
  • 16. Control Charts •Attributes Control Charts when sample size are not constant and/or are unknown use counts charts [c-charts]
  • 17. Control Charts c Chart for num_defect 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 0 4 8 12 16 20 c Centerline = 10.00 UCL = 19.49 LCL = 0.51
  • 18. Control Charts •Attributes Control Charts when sample size are constant and are known use proportion charts [p-charts]
  • 19. Control Charts p Chart for defects/100 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 26.0 27.0 28.0 29.0 30.0 0 0.03 0.06 0.09 0.12 0.15 p Centerline = 0.04 UCL = 0.10 LCL = 0.00
  • 20. Control Charts Charts may be used for interval or ratio data [i.e.: variables ]
  • 21. Control Charts Whenever a character of interest is measured on an interval or a ratio scale, a variables control chart is used to monitor a process.
  • 22. Control Charts •Variables Control Charts Mean and Range charts [x-bar & R charts]
  • 23. Control Charts Variables control charts are typically used used in pairs. …… one chart monitors process average while the other monitors the variation in a process.
  • 24. Control Charts p Chart for defects/100 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 26.0 27.0 28.0 29.0 30.0 0 0.03 0.06 0.09 0.12 0.15 p Centerline = 0.04 UCL = 0.10 LCL = 0.00 X-bar Chart for observa 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 190 194 198 202 206 210 214 X-bar Centerline = 203.98 UCL = 208.21 LCL = 199.75
  • 25. Control Charts Range Chart for observa 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 0 3 6 9 12 15 Range Centerline = 5.80 UCL = 13.24 LCL = 0.00
  • 26. Control Charts In conclusion: the control chart is a means of monitoring variation in the characteristics of a product or service
  • 27. Control Charts Know the assumptions … let the computer do the hard work.
  • 28. References TEXT BOOKS • B. Mahadevan, 2007. Operations Management Theory and Practice, Pearson Education, Second Impression 2007. ISBN: 8177585649 • Dale H. Besterfiled, et at., 2006. Total Quality Management, Pearson Education Asia, Third Edition, Indian Reprint 2006. ISBN: 978-81-317-3227-4 REFERENCE BOOKS • R1 William J. Stevenson, 2018. Operations Management Mc Graw Hill Publications, 13th Edition ISBN: 9781259667473 • R2 James R. Evans and William M. Lindsay, 2012. “The Management and Control of Quality”, Cengage Learning, 8th Edition, First Indian Edition, 2012. ISBN: 978032482706 • R3 Janakiraman. B and Gopal. R. K., 2006. “Total Quality Management-Text and Cases”, Prentice Hall (India) Pvt. Ltd., 2006. ISBN: 8120329953 Sources: • https://sixsigmastudyguide.com/statistical-process-control-spc/ • www.uoh.edu.sa/facultymembers/en/M.AICHOUNI/Documents/QEM%20511/Chapter03-Control-Charts-2017.pdf Video Link: • https://www.youtube.com/watch?v=lOEqli-YV2I 28
  • 30. THANK YOU 30 For queries get in touch with me at: simmi.e12923@cumail.in