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592   Chapter Sixteen

                                             0.20
                                     "C L
                               p L                  0.678
                                     ("f) 2 L  0.295
             Because

                                 ∂f

                         ("f) R       "R   0.948 
 0.5   0.474 A
                                 ∂R

                                 ∂f
                         ("f) L      "L   0.98.53 
 0.003   0.295 A
                                "L
             Therefore, reducing R is more cost-effective than reducing L. Then

                            req
               p
                      i   1 	 ∂x i 		 2
                       n

                                2

                             ∂f
                           2
                          p i
                                    i
                                        0.1667
                                                                    1.332
                     0.316 
 0. 899 
  0.25    0.6 78 
 9708.2 
 0 .0015  2




                                        2
                                                2
                          2
             Therefore, the new tolerance limits for R and L are
                   R   3C p pp R   R   3 
 1.333 
 1.332 
 0.316 
 0.25   0.42
                   L   3C p pp L   L   3 
 1.333 
 1.332 
 0.678 
 0.0015   0.0054 H
           16.5 Taguchi’s Loss Function and
           Safety Tolerance Design
           Dr. Taguchi developed a unique approach to tolerance design and tol-
           erance analysis. His tolerance design approach includes a cost-based
           tolerance design and allocation. The most important consideration in
           cost is the quality loss due to requirement deviation from the ideal
           requirement level.

           16.5.1 Customer tolerance and
           producer tolerance
           Nominal-the-best requirement. The quality loss can be expressed by the
           Taguchi quality loss function that we discussed in detail in Chap. 14.
           Figure 16.8 shows the quadratic curve for the quality loss function for
           the “nominal-the-best” case.
             The quality loss function can be expressed as follows:


                                          A 0
                                   L(y)       (y   T) 2               (16.29)
                                            2
                                            0
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