Why/When is Taguchi Method Appropriate? A new tip Every Friday Friday, 3rd August 2001

V a r i a n c e R e d u c t i o n Factor Effects Taguchi Method 1 st Priority : V a r i a n c e R e d u c t i o n 2 nd Priority : Factor Effects (next 4 slides) New Tip #16 Friday, 3 rd August 2001

(a) Variance R e d u c t i o n USE (a) Variance R e d u c t i o n : USE Factor-Effect Plot for S/N Ratio : Select ‘dominant’ Control Factor (and their Levels) such that “variance” is minimized Taguchi Method Variance R e d u c t i o n Factor Effects 1 st Priority : Variance R e d u c t i o n 2 nd Priority : Factor Effects Symbols :   A1C3D2 A1 A2 A3 B1 B2 B3 C1 C2 C3 D1 D2 D3 S / N RATIO  Neutral Factor (b) “USE (b) “put” the “mean-on-target” : USE Factor-Effect Plot for Mean : Select one of the ‘neutral’ Control Factors as the “adjustment factor” A1C3D2 A1 A2 A3 B1 B2 B3 C1 C2 C3 D1 D2 D3 Mean  Adjustment Factor

S/N Ratio (Objective Function) Taguchi methods are experimental statistical methods to optimize a given process technology with respect to an objective function defined as Taguchi Method Variance R e d u c t i o n 1 st Priority : Variance R e d u c t i o n Symbols :    = =  useful  Harmful Mean Square Variance The Ideal Value of the S/N Ratio is  (infinity). Since the ideal value of the Ratio is  (infinity),  the primary importance is shifted to “reduction in Variance” to 0 (zero) secondary  making “improving mean” a secondary objective (as in conventional approach)

NoIsE (a) Variance is, in fact, reduced in presence of NoIsE “ROBUST” and thus the product/process becomes “ROBUST” (b) Identify an “adjustment factor” that has little or no effect on the variance but has a large effect on the mean  use the ‘adjustment factor’ to “put” the “mean-on-target” Taguchi Method Variance R e d u c t i o n and 1 st Priority : Variance R e d u c t i o n and “put” the “mean-on-target” Symbols :  

(a) Factor-Effect Plot for S/N Ratio : Select ‘dominant’ Control Factor (and their Levels) such that “variance” is minimized Taguchi Method Variance R e d u c t i o n Factor Effects 1 st Priority : Variance R e d u c t i o n 2 nd Priority : Factor Effects Symbols :   A1C3D2 A1 A2 A3 B1 B2 B3 C1 C2 C3 D1 D2 D3 Mean  A1C3D2 A1 A2 A3 B1 B2 B3 C1 C2 C3 D1 D2 D3 S / N RATIO  Neutral Factor (b) Factor-Effect Plot for Mean : A, C, D Levels are selected from S/N ratio plot Select one of the ‘neutral’ Control Factors as the “adjustment factor”  use this ‘adjustment factor’ to “put” the “mean-on-target” Adjustment Factor Do not select from this plot

More Tips Links below 16.Taguchi Method V a r i a n c e R e d u c t i o n Factor Effects 1 st Priority : V a r i a n c e R e d u c t i o n 2 nd Priority : Factor Effects “inner” “outer” 15. “inner” L9 array with “outer” L4 and L9 NoIsE arrays 14.Taguchi Method “inner” “outer” “inner” L18 array with “outer” L4 and L9 NoIsE arrays not 13.Taguchi Method Why/When is Taguchi Method not Appropriate? Friday, 3rd Aug 2001 Friday, 27 th July 2001 Friday, 20 th July 2001 Friday, 13 th July 2001 Tips 12, 11, 10 

More Tips Links below 12.Taguchi Method “inner” “outer” “inner” L8 array with “outer” L4 and L9 NoIsE arrays 11.Taguchi Method ALL Life-stages Useful at ALL Life-stages of a Process or Product 10.Taguchi Method “centering”“fine tuning” Performs Process “centering” or “fine tuning” Friday, 6 th July 2001 Friday, 29 th June 2001 Friday, 22 nd June 2001 Tips 9, 8, 7 

More Tips Links below NoIsE Tolerance Design 9.Taguchi Method Identifies the “right” NoIsE factor(s) for Tolerance Design 8.Taguchi Method Finds best settings to optimize TWO quality characteristics Simultaneously 7. Taguchi Method When to select a ‘Larger’ OA to perform “Factorial Experiments” Friday, 15 th June 2001 Friday, 8 th June 2001 Friday, 1 st June 2001 Tips 6, 5, 4 

More Tips Links below 6.Taguchi Method Using Orthogonal Arrays for Generating Balanced Combinations of NoIsE Factors approaching IDEAL value 5.Taguchi Method Signal-to-Noise Ratio for Quality Characteristics approaching IDEAL value 4. Taguchi Method improves " quality “ at all the life stages the design stage itself at the design stage itself Friday, 25 th May 2001 Friday, 18 th May 2001 Friday, 11 th May 2001 Tips 3, 2, 1 

More Tips Links below Concurrent Engineering 3.Taguchi Method Appropriate for Concurrent Engineering 2.Taguchi Method can study Interaction Noise Factors Control Factors between Noise Factors and Control Factors Signal-to-Noise Ratios Log form 1.Taguchi’s Signal-to-Noise Ratios are in Log form Friday, 4 th May 2001 Friday, 27 th April 2001 Friday, 6 th April 2001

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