I.5 Taguchi’s Philosophy Some Important Aspects Loss Functions Exploiting Nonlinearities Examples Taguchi - Comments and Criticisms

Some Important Aspects Uses DOE to Make Rugged Products and Processes 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” Taguchi’s approach really focused on variation

Some Important Aspects Loss Functions For Squared Error Loss, Loss = Variance + (Bias)2 Minimizing This Loss Involves Reducing Variation Targeting The Process Loss functions are an old idea

Some Important Aspects Squared Error Loss Minimizing This Loss May Involve Conflicting Goals You may not be able to simultaneously Optimally target the process and reduce variation Taguchi tries to resolve the conflict through signal to noise performance measures Simultaneous goals are particularly difficult when optimize means “maximize”

Some Important Aspects Examples of Loss Functions Just Meeting Specs versus Squared Error Loss Specs are almost incidental for squared error loss.

Some Important Aspects Loss Functions Sony USA vs Sony JAPAN Sony Japan uses squared error loss; Sony USA uses notch loss

Some Important Aspects Quality Management The competitive race is never ending 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) Skim. Note that some slogans (which Deming abhorred) have a bad name: paradigm shift, interrupted equilibrium

Some Important Aspects Reduce The Effects Of Variation! How? “By Exploiting The Nonlinear Effects of Product Parameters On The Performance Characteristics” Use DOE 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. We will look at how variation propagates through a system. The first sub-bullet will be our focus.

Some Important Aspects Example 3: Improving a Process Which Factors Affect Accuracy? Precision? Skip (we’ve done this before)

Some Important Aspects Exploiting Nonlinearities To Understand This Concept Let’s Consider an Example On Estimating Angles Ladder Exercise in Minitab (Class Exercise 2). Show schematic (y=hsin(theta)) and review exercise.

Some Important Aspects Exploiting Nonlinearities - Other Examples Electric Circuit INA Tile Plasticity of Caramel Draw single resistor, then series/parallel resistors. The latter has A LOT less variability, but how reliable is it? Good simulation or hands-on exercise. INA Tile was an early Taguchi breakthrough. Draw graph, with X=Kiln heat profile (Uniform to Irregular), y=% shrinkage. Plasticity of caramel—show graphic on webpage.

Some Important Aspects Exploiting Nonlinearities To Fix This Idea Let’s See How To Keep a Hubcap From Falling Off! Webpage graphic. Stiffer clips are less forgiving. Softer clips can be made with more variation and still meet performance criteria.

Taguchi Comments Developed A Comprehensive Model of Quality Engineering Quality Engineering Philosophy Is Fundamentally Sound Exploiting Nonlinearities To Mitigate Noise Factors Is Novel Loss Functions Good contributions

Taguchi Criticisms There Is Room For Improvement In His Methodology By The Use Of More Sound Statistical Ideas Better Designs May Be Available S/N Ratio Application May Be Better Analyzed If Viewed As A Bivariate Response (S,N) Problem S/N Can Mask Factor Effects Ignores Sequential Experimentation EVOP and Response Surface Techniques Adaptive design Don’t explain all this yet. Squared error loss explains second bullet

Taguchi Criticisms of Terminology Traditional DOE Terminology and Methodology Is Modified Which Leads To Unnecessarily Complications Linear Graphs rather than Alias Structure for Choosing Designs Skim

Taguchi Criticisms of trademark The Term “Taguchi Methodology”* Is Objectionable Ignores the Major Contribution of Others to This Endeavor Skim

Taguchi Critique revisionism The Term “Taguchi Methodology”* ”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) Skim

Part I References G.E.P. Box, W.G. Hunter and J.S.Hunter (2005). Statistics for Experimenters, 2nd ed, 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.