Transcript I.5 Taguchi’s Philosophy - University of South Carolina

I.5 Taguchi’s Philosophy
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Some Important Aspects
Loss Functions
Exploiting Nonlinearities
Examples
Taguchi - Comments and Criticisms
Some Important Aspects
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Uses DOE to Make Rugged Products and
Processes
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DOE Is Used As a Tool “For Reducing the
Effects of Variation”
Traditional DOE Had “Focused More on
Optimizing Average Product Performance
Than on Considering the Effects of Variation”
Some Important Aspects
Loss Functions
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For Squared Error Loss,
Loss = Variance + (Bias)2
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Minimizing This Loss Involves
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Reducing Variation
Targeting The Process
Some Important Aspects
Loss Functions
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Minimizing This Loss
−May Involve Conflicting Goals
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You may not be able to simultaneously
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Optimally target the process and reduce
variation
Taguchi tries to resolve the conflict
through signal to noise performance
measures
Some Important Aspects
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Just Meeting
Specs
versus
Squared Error
Loss
Loss Functions
Squared Error Loss
LSL
Just Meeting Specifications Loss Function
LSL
Target
USL
Target
USL
Some Important Aspects
Loss Functions
Sony USA vs Sony JAPAN
Distribution of The Color Density in Television Sets
T arget Value is
Sony USA
Sony Japan
LSL
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USL
Some Important Aspects
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The competitive race is never ending
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Deming/Shewhart PDSA Cycle
Juran “Managerial Breakthrough”
Kaizen
Continual Improvement
Improvement Occurs When Variation Is
Reduced (Mostly Effected at The Product and
Process Design Stage)
Some Important Aspects
Reduce The Effects Of Variation!
How?
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“By Exploiting The Nonlinear Effects of Product
Parameters On The Performance
Characteristics”
 Use DOE
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To Search For Interactions Between Control Factors
and Noise Factors. If There Is An Interaction, It
May Be Useful For Mitigating The Effect Of The
Noise Factor
To Identify The Design Parameters That Have The
Most Effect On Product Performance.
Some Important Aspects
Example 3: Improving a Process
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Which Factors Affect
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Accuracy?
Precision?
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2
Some Important Aspects
Exploiting Nonlinearities
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To Understand This Concept Let’s
Consider an Example On Estimating
Angles
Some Important Aspects
Exploiting Nonlinearities - Other Examples
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INA Tile
Plasticity of Caramel
Electric Circuit
Some Important Aspects
Exploiting Nonlinearities
To Fix This Idea Let’s
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See How To Keep a Hubcap From Falling
Off!
Taguchi
Comments
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Developed A Comprehensive Model
of Quality Engineering
Quality Engineering Philosophy Is
Fundamentally Sound
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Exploiting Nonlinearities To Mitigate
Noise Factors Is Novel
Loss Functions
Taguchi
Criticisms
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There Is Room For Improvement In
His Methodology By The Use Of
More Sound Statistical Ideas
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Better Designs May Be Available
S/N Ratio Application May Be Better
Analyzed If Viewed As A Bivariate
Response (S,N) Problem
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S/N Can Mask Factor Effects
Ignores Sequential Experimentation
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EVOP and Response Surface Techniques
Adaptive design
Taguchi
Criticisms
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Traditional DOE Terminology and
Methodology Is Modified Which
Leads To Unnecessarily
Complications
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Linear Graphs rather than Alias
Structure for Choosing Designs
Taguchi
Criticisms
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The Term “Taguchi Methodology”*
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Is Objectionable
Ignores the Major Contribution of
Others to This Endeavor
Taguchi
Criticisms
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The Term “Taguchi Methodology”*
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”Taguchi himself has said that he does
not like the use of that term, which to
his embarrassment has been used by
others, ignorant of statistical history, to
include such tools as analysis of
variance, fractional factorials,
orthogonal arrays, and so forth.” Box
et al (1988)
Part I References
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G.E.P. Box, W.G. Hunter and J.S.Hunter (1978). Statistics
for Experimenters, John Wiley & Sons, N.Y.
G.E.P. Box, S. Bisgaard and C. Fung (1988). “An
Explanation and Critique of Taguchi's Contributions to
Quality Engineering,”University of Wisconsin Center for
Quality and Productivity Improvement, Report #28.
C. Daniel (1976). Applications of Statistics to Industrial
Experimentation, John Wiley & Sons, N.Y.
H. Karatsu (1988). TQC Wisdom of Japan, Productivity
Press, Cambridge, MA.
R. Snee (1990). Statistical Thinking and Its Contribution
to Total Quality, The American Statistician, 44, 116-121.