Page 62 - Six Sigma Advanced Tools for Black Belts and Master Black Belts
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                                   The IDOV Roadmap                           47
      for showing that C pk is greater than say, C pk0 − , where C pk0 is the true value, is given
      by
                    2
            (Z α + Z β ) (9C 2  + 2)
                         pk0
        n =                    .
                   18  2
      The above approximation works well for large n(>50) and C pk0 >1, as it is based on
      an asymptotic result for C pk .
        A consolidated table summarizing the DFSS tools and their respective purposes is
      given in Table 4.3. For a seasoned Black Belt who is conversant with DMAIC tools,
      acquiring three additional tools, namely, QFD, design for reliability, and Monte Carlo


      Table 4.3 Six Sigma tools and their objectives in DFSS.

               Quality tools                       Purpose
      Identify     Project management tools such as Gantt     To develop a project charter
                charts and critical path analysis      To identify customers
                Voice of customers                     To translate customers’wants into

                QFD; FMEA, Benchmarking; Stakeholder  product design requirements;

                analysis; leverage chart; Pareto charts  requirements into specifications
                                                     and to perform gap analysis
      Design      Brainstorming; affinity diagram; reality     To formulate design concepts
                trees                                  To brainstorm conceptual design
                TRIZ (theory of inventive problem    To get measurement systems

                solving); cause-and-effect analysis  ready for design evaluation
                  Gage R&R                             To evaluate design options
                  Statistical thinking; t-, F-test, ANOVA     To identify KPOVs and KPIVs
                  Screening experiments                To evaluate design sensitivity to
                  Robust design                      environment changes
                  Response surface method, multiple     To develop transfer functions
                regression

      Optimize     Monte Carlo simulation              To perform statistical tolerancing
                  Capability analysis                  To analyze and optimize
                  Design for reliability             capability measures
                  Two-level fractional factorials      To develop reliability metrics and
                  DFSS score card                    to conduct accelerated testing
                                                       To demonstrate feasibility and
                                                     conduct sensitivity analysis
                                                       To review current design
                                                     achievement

      Validate     Sample size determination           To conduct confirmatory runs
                  Statistical process control          To design control plan and
                  Poka-yoke(mistake proofing)        develop control charting tools
                                                       To error proof design and
                                                     processes
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