Quality Tools and Topics
Learning Objectives
At the end of this module, you will be able to:
• Describe how quality is essential to Lean in
achieving customer satisfaction
• Use basic quality tools
Quality Tools and Topics V7.5 - Slide 2
© 2012 Massachusetts Institute of Technology
Why Do We Care About Quality?
Hidden Costs of Non-Conformance
= 2 to 3 Times Measured Costs
Direct Measured Costs:
• Scrap/rework
• Service calls
• Warranties/concessions
Courtesy of Richard Lewis II. Used with permission.
Indirect/Hidden Costs:
• Excess inventory
• Overtime
• Non-value added steps
• Queues and delays
• Reputation/image
Quality Tools and Topics V7.5 - Slide 3
© 2012 Massachusetts Institute of Technology
Problems with Inspection
Based Quality Control
•
•
Inspection does not add
value to the customer – it
simply screens or detects
(most of the time) defective
products from leaving the
factory.
Inspection is subject to
multiple errors
• Inspector skill and attention
• Measurement capability
• Environment (Human Factors)
Quality Tools and Topics V7.5 - Slide 4
© 2012 Massachusetts Institute of Technology
Inspection Exercise
This exercise will be in two 30 second sessions
Task: Find all of the fs or Fs on a page of text
• Take out the Inspection Exercise from the
student folder and turn it face down.
• On “GO”, circle all the fs or Fs you find
• On “STOP”, and turn over your sheet and pass
the sheet to the person on your right.
• On “GO”, mark Xs all the other fs or Fs you find
• On “STOP”, count up the number of fs and Fs
that are circled and the number with Xs.
Quality Tools and Topics V7.5 - Slide 5
© 2012 Massachusetts Institute of Technology
Impact of Inspector Efficiency
on Escaped Quality
Quality Tools and Topics V7.5 - Slide 6
© 2012 Massachusetts Institute of Technology
Total Quality Management
Lean Product
Development/
Lean
Healthcare
Lean Supply
Chain
7 Quality
Tools
VSMA
Total Quality Management (TQM) and Lean are related
Ref: Ritzman, L. P. and Krajewski, L.J., Foundations of Operations Management, Prentice Hall, Upper Saddle River NJ,
2003
Quality Tools and Topics V7.5 - Slide 7
© 2012 Massachusetts Institute of Technology
•
•
•
•
•
•
•
Flow Charts
The Seven Basic
Quality Tools
Cause and Effect Diagrams
Check Sheets
Histograms
Pareto Charts
Scatter Diagrams
Control Charts
Six Sigma Basics Module
Photo by Earll Murman
Cause & effect diagram from a
factory floor A3 at New Balance.
Quality Tools and Topics V7.5 - Slide 8
© 2012 Massachusetts Institute of Technology
Flow Charts
• Flow Chart examples
• Process maps
• S/W program flow
• Medical algorithms
Photo by Earll Murman
Process map for pre lean treatment of Acute
Myocardial Infarction (aka heart attack)
• Why are Flow Charts a quality tool?
•
•
•
•
Visual description improves comprehension
Helps assure process steps are done in the right
sequence
Ties outputs to inputs
Assists with data collection
Quality Tools and Topics V7.5 - Slide 9
© 2012 Massachusetts Institute of Technology
Cause and Effect Diagram
Also called Ishikawa or Fishbone diagram
Measurements
Personnel
Materials
Suggested
major
categories
Primary Cause
Secondary
Cause
Primary Cause
Methods
Environment
Machines
Effect or
problem
A root
cause
analysis
tool, often
supported
by 5 Whys
Quality Tools and Topics V7.5 - Slide 10
© 2012 Massachusetts Institute of Technology
Example Cause and Effect
Diagram
Source: Institute for Healthcare Improvement, Cause and Effect Diagram (IHI Tool).
Courtesy of Institute for Healthcare Improvement. Used with permission.
Quality Tools and Topics V7.5 - Slide 11
© 2012 Massachusetts Institute of Technology
Check Sheets
A structured tool for collecting data
A purely hypothetical example!
Quality Tools and Topics V7.5 - Slide 12
© 2012 Massachusetts Institute of Technology
Histograms
Inspection Results
8
7
7
6
6
Frequency
Shows
• Frequency of
occurrence
• Frequency distribution:
normal, random, …
5
4
4
6
4
3
2
1
2
1
0
18
21
24
27
30
33
36
Number of "F's"
Useful to see
• The spread of a distribution
• Changes over time
• Quantitative inputs/outputs
• Comparison to customer requirements
Quality Tools and Topics V7.5 - Slide 13
© 2012 Massachusetts Institute of Technology
M&M Exercise
What product attribute does the Mars Company control
variation of to deliver a quality to its customers?
•
•
•
•
Open your bag of M&Ms – don’t eat them yet!
Count the number of M&Ms in your bag by color.
Fill in your data on the Check Sheet for your table.
Contribute table data when asked by instructor.
Modification of an exercise suggested by Raytheon Corporation
Image: Wikimedia. Public Domain.
Quality Tools and Topics V7.5 - Slide 14
© 2012 Massachusetts Institute of Technology
Class Poll
What M&M attribute to you think Mars
Company uses quality principles to
control variation of?
• Total M&Ms in a bag?
• Color distribution?
• Something else
• I don’t know
Hold up the colored 3 x 5 card of your choice
Quality Tools and Topics V7.5 - Slide 15
© 2012 Massachusetts Institute of Technology
Pareto Chart of Preventable
Causes Leading to ED Admissions
Courtesy of Faten Mitchell, Quality Improvement Advisor, Health Quality Ontario. Used with permission.
Source: Faten Mitchell, Quality Improvement Advisor, Health Quality Ontario.
Quality Tools and Topics V7.5 - Slide 16
© 2012 Massachusetts Institute of Technology
Pareto Example - Discrepancies During
Satellite System Integration & Test
30%
Satellite Causes
26%
25%
24%
20%
Non-Satellite Causes
18%
15%
12%
10%
8%
6%
Unknown
Other
Software
Design
Test
Equipment
Operator/
Employee
3%
2%
Material
5%
No
Anomaly
% of Discrepancies
Root Cause of Discrepancies for 229 Satellites tested from 1970-1999
Root Cause Category
Source: Weigel A. and Warmkessel, J., “Seeing The Spacecraft Testing Value Stream”, LAI Executive Board Briefing, June 2000
Ref: Weigel, A., “Spacecraft System Level Test Discrepancies: Characterizing Distributions and Costs”, MIT SM Thesis, May 2000
Quality Tools and Topics V7.5 - Slide 17
© 2012 Massachusetts Institute of Technology
Scatter Diagrams
• Plots of (x,y) pairs of numerical data
• Can show whether a correlation exists
• Useful starting point for root cause analysis
Coordination vs. Performance - Hospitals
Relational Coordination
0.85
0.8
0.75
0.7
0.65
-0.4
-0.2
0
0.2
0.4
Patient Care Performance Index
Uncorrelated data
Correlated data
Quality Tools and Topics V7.5 - Slide 18
© 2012 Massachusetts Institute of Technology
Summing Up
• Inspection is an ineffective way to produce
•
•
•
•
high quality products and services
Total Quality Management and Lean Thinking
are closely related
Lean Thinking and TQM both utilized simple,
structured, quantitative and qualitative tools
to achieve quality
There are seven basic quality tools
But remember – capable people are the most
important factor in achieving quality
Quality Tools and Topics V7.5 - Slide 19
© 2012 Massachusetts Institute of Technology
An Example of Focus on Quality:
Floor Beams for Commercial Aircraft
Courtesy of Boeing. Used with permission.
747
Assembly Strategy
Tooling
Hard tools
28
Soft tools
2/part #
Major assembly steps
10
Assembly hrs
100%
Process capability
Cpk<1 (3.0 )
Number of shims
18
777
Toolless
0
1/part #
5
47%
Cpk>1.5 (4.5 )
0
Refs:J.P. Koonmen, “Implementing Precision Assembly Techniques in the Commercial Aircraft Industry”, Master’s thesis, MIT (1994),
Quality Tools and Topics V7.5 - Slide 20
and J.C.Hopps, “Lean Manufacturing Practices in the Defense Aircraft Industry”, Master’s Thesis, MIT (1994)
© 2012 Massachusetts Institute of Technology
Reading List
Deming, E., Out of Crisis, The MIT Press, Cambridge, MA, 2000
Hopp, W.J. and Spearman, M.L., Factory Physics, 3rd Edition,
McGraw-Hill/Irwin, 2007
Juran, J.M., Juran on Quality by Design, The Free Press, New
York, 1992
Nelson, E.C., Batalden, P.B., Godfrey, M. M., Quality By Design: A
Clinical Micosystems Approach, John Wiley and Sons, New York,
2007
Ritzman, L.P. and Krajewski, L.J., Foundations of Operations
Management, Prentice Hall, Upper Saddle Brook NJ, 2003
Tague, N.R., The Quality Tool Box, Second Edition, ASQ Quality
Press, 2004
Quality Tools and Topics V7.5 - Slide 21
© 2012 Massachusetts Institute of Technology
Acknowledgements
Contributors
•Dick Lewis – Rolls-Royce (ret.)
•Jose Macedo – Cal Poly, San Luis Obispo
•Hugh McManus – Metis Design
•Earll Murman – MIT
•Steve Shade – Purdue University
•Alexis Stanke – MIT
Collaborators
•Tom Callarman – Arizona State University
•Phil Farrington – University of Alabama in Huntsville
•Al Haggerty – MIT, Boeing (ret.)
•Jan Martinson – Boeing, IDS
•Faten Mitchell – Health Quality Ontario
•Bo Oppenheim – Loyola Marymount University
•Sue Siferd – ASU
•Barrett Thomas – University of Iowa
Quality Tools and Topics V7.5 - Slide 22
© 2012 Massachusetts Institute of Technology
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16.660J / ESD.62J / 16.853 Introduction to Lean Six Sigma Methods
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