Process Improvement Webinar
Learn how to use the seven tools of quality and the normal curve
to control processes
By: Merwan Mehta, Ph. D.
Central Theme of Webinar
• Overview of the seven basic tools of quality
• Using the normal curve to control processes
• Utilizing statistics to control processes
Predictive Maintenance Technologies 2
The Seven Tools of Quality
1. Ishikawa (fishbone) diagram
2. Check sheets
3. Control charts
4. Histograms
5. Pareto charts
6. Scatter diagrams
7. Flowcharts
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Ishikawa (Fishbone) Diagram
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Machine Material Measurement
Method People Environment
Rejects
Variation Wear
Calibration
Standards
Enhance
Suppliers
Error
SQC
Motivation
Training
Humidity
Temperature
Check Lists
http://geoffmcdonald.com/atul-gawande-checklist-manifesto/
XmR Control Chart Using Excel
X Chart
mR Chart
Histograms Using Excel
Pareto Chart Using Excel
Scatter Plots Using Excel
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Activity 1
Activity 2
Activity 3
Activity 6
Activity 4
Activity 5 Activity 8
Activity 9
Activity 10
Activity 7
Employee A
Swim-lanes
Flow Chart with Swim Lanes
Document
the process
Employee B
Manager
Employee C
Process Mapping
Customer service rep
Enter in system
Visit customer For evaluation
Approve for Quoting?
Create Report
Notify CSR & FM
N Y Create Report
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2
3
4 5 5
6 Notify CSR & FM
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Notify Customer
7 Notify Customer
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FILE 8 Credit Good?
N Y 9
Notify Engineer
10 Notify CSR
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Custom Design?
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Y
Create Design
Send to Engineer
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12
Check Design
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Create BOM 15
Price Components
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Final Quote
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Approve Quote
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Notify Customer
FILE
Order entry clerk
Receive request
Customer service manager
Finance manager
Engineer
Draft person
Purchasing agent
Engineering manager
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N
Documents
the process
Metrics are
absent
The Normal Curve
Minimum Mean Maximum
Source: Adapted from Certified Six Sigma Green Belt Primer. Quality Council of Indiana, April 2006.
• The histogram will closely trace the normal curve • Most data points are near the centerline or the mean. • Centerline divides the curve into two symmetrical halves • Some points approach the minimum and maximum values • Very few points are outside the bell-shaped curve
Possibilities for Two Dice Total appearing
on dice Possible Combinations of Dice
Total # of
possibilities
2 1
1
1
3 1 2
2
2 1
4 1 2 3
3
3 2 1
5 1 2 3 4
4
4 3 2 1
6 1 2 3 4 5
5
5 4 3 2 1
7 1 2 3 4 5 6
6 6 5 4 3 2 1
8 2 3 4 5 6
5
6 5 4 3 2
9 3 4 5 6
4
6 5 4 3
10 4 5 6
3
6 5 4
11 5 6
2
6 5
12 6
1
6
Possibilities for Three Dice
# Possibilities
0
5
10
15
20
25
30
35
# Possibilities 1 3 6 10 15 18 25 27 30 25 21 15 10 6 3 1
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
The Empirical Rule
0.13% 2.14%
13.60%
34.13%
-3S -2S -1S X +1S +2S +3S
95.46%
99.73%
68.26%
13.60%
34.13%
2.14%
0.13%
-∞ +∞
Empirical Rule
Our Process
• Mean = 124.9 days
• SD for Mean = 5 days
• UCL for Mean = 139.8 days
• LCL for Mean = 110.0 days
• Based on the Empirical Rule, only 0.26% of the time the “time for the process” will be outside the control limits
Our Process
• Question: What % of the projects will be completed between 110 to 120 days?
X1 = 110 X2 = 120
Normal Curve
Mean = 124.9 days
SD = 5 days
Group Exercise
• What % of the projects will be completed between 100 to 105 days?
• Work in groups of 2 or 3
Designing a Process
• What will we have to do if we want to make sure that 99.7% of the time a project is done in 100 to 120 days?
• LCL = 100 days
• UCL = 120 days
Limits Based on Probability
• If we are able to bring the mean for the process to 100 days and the standard deviation to 3 days, what are the limits between which 60% of the time projects will get done?
Group Question
• The project process with mean of 110 days and standard deviation of 4 days will have 75% of projects completed between _____ days to _____ days!
110 days
Probability = 75%
____
____
Group Question
• If the process drifted to make mean = 138 and the SD changed to 6.5 days, what percentage of the time the project time will be outside the specification limits?
• Work in groups of 2 or 3
Goal of Statistical Presentation in the Conference
• How to structure any process to take advantage of statistical knowledge
• How to create metrics for processes based the normal curve
• How to create control charts based on the normal curve
• How to predict future process behavior based on the normal curve
Predictive Maintenance Technologies 23
Lean and Six Sigma Conference 2013
• For engineers by engineers
• Your organization's success = your success
• Latest innovations and techniques
• Industry and research professionals
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• CEO & founder: consulting and software solutions
• High mix manufacturers improve profitability
• Manufacturing executive at Alcoa & Siemens
• Three degrees from the MIT
• Chairman of NSF’s Small Business Innovation Research Advisory Committee
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• VP of process management for Macy’s
• Six Sigma strategic direction and implementation
• Certified master black belt
• 31-year career in industrial engineering, quality assurance and operations with Lockheed Martin, NCR Corp. and Macy’s
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• Former director of the CIM Systems Research Center
• Research interests:
– Global new product development
– Model-based enterprises
– Global supply networks integration
• Book: Integrated Process Design & Development
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