1. Quality Control and Improvement
Chapter 9
INTRODUCTION to Operation Management
4e, Schroeder
McGraw-Hill/Irwin
Copyright © 2008 by The McGraw-Hill Companies, Inc., All Rights Reserved.

2. Chapter Outline Design of Quality Control Systems
Process Quality Control
Attribute Control
Variables Control
Using Control Charts
Continuous Improvement
Six Sigma
Lean and Six Sigma
Quality Control and Improvement in Industry
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3. Chapter Emphasis Process definition Statistical quality control
Continuous improvement
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4. Design of Quality Control Systems
Break down production process into subprocesses and “internal customers.”
Identify “Critical points” where inspection or measurement should take place
Four steps in designing QC systems.
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5. Steps in Designing QC Systems
Identify critical points
Incoming materials & services
Work in process
Finished product or service
Decide on the type of measurement
variables
attribute
Decide on the amount of inspection to be used.
Decide who should do the inspection
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6. Types Of Measurement Attribute measurement Variables measurement
Product characteristic evaluated with a discrete choice:
Good/bad, yes/no
Variables measurement
Product characteristic that can be measured on a continuous scale:
Length, size, weight, height, time, velocity
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7. When the Inspector Finds a Defect…
Containment: Keep the defective items from getting to the customer
Correction: Find the cause of the defect and correct it.
Prevention: Prevent the cause from happening again.
Continuously improve the system.
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8. When the Inspector Finds a Defect e.g. Strap on backpack comes loose
Containment: pull the bad backpacks from the line.
Correction: sewing machine misaligned; fix it.
Prevention: why was it misaligned? Find out and change system to prevent it happening again.
Continuously monitor and improve system.
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9. Process Quality Control
Basic assumptions (tenets) of Process Quality Control:
Every process has random variation in it.
Production processes are not usually found in a state of control.
“State of Control”; what does it mean?
Unnecessary variation is eliminated.
Remaining variation is because of random causes.
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10. “It’s our job to drive the randomness out.”
--Bill James, statistician for the Boston Red Sox
Wall Street Journal, 20 June 2007, p. D7.
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11. Process Quality Control
Assignable (special) causes
Can be identified and corrected
Common causes
Occur randomly
Cannot be changed unless process is redesigned
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12. Process Control Chart (Figure 9.1)y
Time x
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13. Quality Control Chart (Figure 9.2)
Stop the process; look for assignable cause
Stop the process; look for assignable cause
Stop the process; look for assignable cause
Stop the process; look for assignable cause
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14. Attributes & Variables
Attributes are counts, such as the number (or proportion) of defects in a sample.
Variables are measures (mean & range or standard deviation) of critical characteristics in a sample.
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15. Formulas for SPC (3 Sigma)
p-Chart
x-Bar Chart
R-Chart
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16. Issues in Using Control Charts
Sample Size
large enough to detect defectives
variables can use smaller sample sizes
How often to sample?
Depends upon cost
Control limits vs. product specifications
Is the process capable of producing to specs?
Are the specifications appropriate?
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17. Continuous Improvement
Aim of continuous improvement is to reduce the variability of the product or process
Techniques for continuous improvement
Pareto analysis
Cause-and-effect (fish-bone) diagrams
Process capability indicies
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18. Pareto Analysis
Note: 40 percent of the items cause 78.6 percent of the defects
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19. Pareto Diagram (Figure 9.3)
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20. Cause-and-effect (Fish-bone, Ishikawa) diagram (Figure 9.4)
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21. Process Capability Index Examples (Figure 9.5)
frequency
process measure
process measure
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22. Computation of Cpk (Figure 9.6)
frequency
process measure
process measure
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23. Six-Sigma Quality
Pioneered by Motorola in 1988 (Juran claims credit for the idea).
3.4 defects per million
Sample size rules become unusable
Most process are 4 sigma, e.g. payroll, prescriptions, baggage handling, journal vouchers, restaurant bills.
Airline fatalities are 6.4 sigma
IRS tax advice is less than 2 sigma
Criticism: accepts 3.4 defects/million. Is not zero defects.
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24. Six Sigma Quality Process Improvement steps of Six Sigma (DMAIC):
Define
Measure
Analyze
Improve
Control
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25. Six Sigma Quality Six Sigma uses a project/team approach.
A process is selected for improvement
A cross-functional team is formed.
A six sigma ‘black belt’ is chosen to head the team.
The team uses the DMAIC method for finding root causes and improving the process.
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26. Lean and Six Sigma Are complementary approaches to improvement.
Lean seeks to eliminate waste.
Six sigma seeks to eliminate defects.
Six sigma organization is more formal and training intensive.
Six sigma is project focused; lean is more broad based.
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27. Quality Control and Improvement in Industry
75% use process control charts.
More use of variable (x-bar and R) charts than attribute (p) charts because of sample size requirements.
“The Seven Tools of Quality Control” (see Figure 9.7)
Quality control in the service industry (SERVQUAL)
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28. Quality Control and Improvement in Industry
The seven tools of quality control
Flowcharts
Pareto charts
Cause-and-effect diagrams
Run (trend) charts
Histograms
Control charts
Scatter diagrams
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29. Summary Design of Quality Control Systems Process Quality Control
Attribute Control
Variables Control
Using Control Charts
Continuous Improvement
Six Sigma
Lean and Six Sigma
Quality Control and Improvement in Industry
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30. End of Chapter Nine
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