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Six Sigma is Possible with R
                                    And Even Better


                                        Emilio Lopez
                      Department of Statistics and Operations Research
                            Rey Juan Carlos University (Madrid)


                University of Warwick, August 2011



The R User Conference 2011 - Lightning Talk                              1/15
The DMAIC Cycle




 The R User Conference 2011 - Lightning Talk   2/15
The Scientific Method




   http://electroncafe.wordpress.com/2011/
       05/04/scientific-process-rage/
 The R User Conference 2011 - Lightning Talk   3/15
The Scientific Method & Six Sigma

                        DMAIC Cycle              Scientific Method
                                               Ask a question
                             Define
                                               Do some background
                            Measure            research

                                               Construct a hypothesis
                            Analyze
                                               Test the hypothesis
                                               with an experiment
                            Improve
                                               Analyze the data and
                                               draw conclusions
                             Control
                                               Communicate results



 The R User Conference 2011 - Lightning Talk                            4/15
The key to success
                     Science is organized knowledge.
                                               Herbert Spencer
 Six Sigma is a quality paradigm which translates the
 complicated scientific terminology into a simple way
 to apply the scientific method within every
 organization.




 The R User Conference 2011 - Lightning Talk               5/15
Six Sigma Software




 The R User Conference 2011 - Lightning Talk   6/15
Six Sigma Software




 The R User Conference 2011 - Lightning Talk   7/15
R Challenges
 Why Not
          Six Sigma uses Statistics.
          Six Sigma is based in the Scientific Method.
          Six Sigma should use R!.

 Outstanding advantages
          Every Statistical Tool even in base installation
          Extending possibilities
          Powerful graphics



 The R User Conference 2011 - Lightning Talk             8/15
Packages

        qcc Shewhart quality control charts for
            continuous, attribute and count data
     IQCC Builds statistical control charts with
            exact limits for univariate and
            multivariate cases.
 qualityTools This is a package for teaching
            statistical methods in the field of Quality
            Science [. . . ] The focus is on teaching
            [. . . ]
 SixSigma Our effort for spreading the R thinking
            along Six Sigma practitioners.
 The R User Conference 2011 - Lightning Talk        9/15
Six Sigma with R - Springer Use R! Series

                                               Features
                                                  Title:
                                                  Six Sigma with R
                                                  Due 2012
                                                  350 pages approx.
                                                  Wide background
                                                  scope
                                                  Examples, a Case
                                                  Study and practices


 The R User Conference 2011 - Lightning Talk                      10/15
Process Map
                                             Six Sigma Process Map
                                                  operators
                             INPUTS
                                                  tools
                                X                 raw material
                                                  facilities

                    INSPECTION                        ASSEMBLY                           TEST                      LABELING
                       sheets                           sheets                         helicopter                  helicopter
                         ...
                    INPUTS




                                                  INPUTS




                                                                              INPUTS




                                                                                                          INPUTS
                  Param.(x): width NC          Param.(x): operator C        Param.(x): operator C       Param.(x): operator C
                              operator C                   cut P                        throw P                     label P
                              Measure pattern P            fix P                        discard P       Featur.(y): label
                              discard P                    rotor.width C                environment N
                  Featur.(y): ok                           rotor.length C   Featur.(y): time
                                                           paperclip C
                                                           tape C
                                               Featur.(y): weight




                   LEGEND
                                                                                        helicopter
                   (C)ontrollable                                                                                  OUTPUTS
                   (Cr)itical
                   (N)oise
                                                                                                                      Y
                   (P)rocedure


                                                           Paper Helicopter Project



 The R User Conference 2011 - Lightning Talk                                                                                    11/15
Gage R&R
                                                                                                   Six Sigma Gage R&R Study
                                                   Components of Variation                                                                                       Var by Part

                                                                                                                                       1.8
                                                                                                                                                                                          q
           80                                                                                                                                                                             q
                                                                                                                                                                                          q
                                                                                                                                                                                          q
                                                                                                                                                                                          q
                                                                                                                                       1.6
           60
                                                                                                                                                                        q
                                                                                                                                                                                          q
 Percent




                                                                                                                                       1.4




                                                                                                                                 var
           40                                                                                                                                  q
                                                                                                                                               q
                                                                                                                                               q
                                                                                                                                               q                                          q
                                                                                                                                                                        q
                                                                                                                                       1.2
           20                                                                                                                                                           q
                                                                                                                                                                        q
                                                                                                                                                                        q
                                                                                                                                               q                        q
                                                                                                                                       1.0                              q
           0
                                                                                                                                               q
                           G.R&R                    Repeat                      Reprod               Part2Part
                                                                                                                                             prot #1                  prot #2           prot #3
                                        %Contribution                       %Study Var

                                                     R Chart by appraiser                                                                                      Var by appraiser

                                                        prot #1   prot #2      prot #3
                                                                                                                                       1.8
                                                                                                                                               q                        q
                              op #1                               op #2                             op #3                                      q
           0.5                                                                                                                                                                            q
                                           q                                                                                                                            q
                                                                                                                                                                        q                 q
                                                                                                                                       1.6
           0.4                                                                                                                                                                            q
                   q                                                                                                                                                                      q
                                                                                                     q                                 1.4




                                                                                                                                 var
           0.3                                                                                                                                                          q
 var




                                                                                                                                                                        q
                                                                    q                                              q                           q
                                                                                                                                               q                        q                 q
                                                                                                                                                                        q
           0.2                                                                                                                         1.2
                                                                                           q                                                   q                        q                 q
                                                                                                                                               q
                                                                                 q                                                             q                                          q
           0.1
                                   q                      q                                                                            1.0                              q

                                                                                                                                               q
                 prot #1      prot #2    prot #3                                         prot #1   prot #2       prot #3
                                                                                                                                             op #1                    op #2              op #3
                                                                  part

                                                     x Chart by appraiser                                                                              Part*appraiser Interaction

                                                        prot #1   prot #2      prot #3
                                                                                                                                       1.7                                                 q
                              op #1                               op #2                             op #3
           1.7                                                                   q
                                                                                                                                       1.6                                                 q

           1.6                             q                                                                       q                   1.5
                                                                                                                                 var




           1.5                                                                                                                         1.4
 var




           1.4                                                                                                                                   q
                                                                                                                                       1.3
                                                          q                                                                                                              q
           1.3
                                                                                                     q                                 1.2
           1.2                                                                                                                                   q
                                                                                           q                                                                             q
           1.1                     q                                q                                                                  1.1       q
                   q
                                                                                                                                             prot #1                  prot #2           prot #3
                 prot #1      prot #2    prot #3                                         prot #1   prot #2       prot #3
                                                                                                                                                       op #1                    op #3
                                                                  part                                                                                 op #2




                                                                                                                       Helicopter Project




 The R User Conference 2011 - Lightning Talk                                                                                                                                                      12/15
Capability Analysis
                              Six Sigma Capability Analysis Study
                                    Histogram & Density                                Density Lines Legend
                                                        Target                                   Density ST
                                                                                                 Theoretical Dens. ST
                                                                                                 Density LT
                                                                                                 Theoretical Density LT


                           LSL                                     USL                      Specifications
                                                                                               LSL: 740
                                                                                             Target: 750
                                                                                               USL: 760



                                                                                    Short Term   Process Long Term
                      740           745             750     755        760
                                                                                     Mean: 749.7625 Mean: 752.8443
                                      Check Normality                                  SD: 2.1042     SD: 2.9577
                                                                                         n: 20          n: 40
                                                            Shapiro−Wilk Test           Zs: 3.14       Zs: 2.42
                                                    q
                                                            p−value: 0.07506                        DPMO:
                                                q
                                                                                    Short Term    Indices Long Term
                                           qq
                                       q qq
                                                            Lilliefors (K−S) Test      Cp: 1.5841          Pp: 1.1270
                                      qq
                                   qq
                                  qq
                                     q                       p−value: 0.2291            CI: [1.1,2.1]       CI: [0.9,1.4]
                                qq
                              qq
                          q
                      q                                                                Cpk: 1.5465         Ppk: 0.8065
                                                                                        CI: [1.1,2.1]       CI: [0.9,1.4]
                          Normality accepted when p−value > 0.05

                                                                 Winery Project



 The R User Conference 2011 - Lightning Talk                                                                                13/15
Open Platform for Quality Methodologies
 Open Platform for Quality Methodologies
          Improving the European Factory
          FP7 PPP Funding Scheme
          Looking for Partners

 Other Projects
 We are available for other projects that need
 partners in this area




 The R User Conference 2011 - Lightning Talk     14/15
Conclusion

 Thanks
 We hope we will be able to convince Six Sigma
 practitioners that not only is it possible with R, but
 it is BETTER with R.




                @emilopezcano | emilio.lopez@urjc.es

 The R User Conference 2011 - Lightning Talk           15/15

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Six Sigma is Possible with R

  • 1. Six Sigma is Possible with R And Even Better Emilio Lopez Department of Statistics and Operations Research Rey Juan Carlos University (Madrid) University of Warwick, August 2011 The R User Conference 2011 - Lightning Talk 1/15
  • 2. The DMAIC Cycle The R User Conference 2011 - Lightning Talk 2/15
  • 3. The Scientific Method http://electroncafe.wordpress.com/2011/ 05/04/scientific-process-rage/ The R User Conference 2011 - Lightning Talk 3/15
  • 4. The Scientific Method & Six Sigma DMAIC Cycle Scientific Method Ask a question Define Do some background Measure research Construct a hypothesis Analyze Test the hypothesis with an experiment Improve Analyze the data and draw conclusions Control Communicate results The R User Conference 2011 - Lightning Talk 4/15
  • 5. The key to success Science is organized knowledge. Herbert Spencer Six Sigma is a quality paradigm which translates the complicated scientific terminology into a simple way to apply the scientific method within every organization. The R User Conference 2011 - Lightning Talk 5/15
  • 6. Six Sigma Software The R User Conference 2011 - Lightning Talk 6/15
  • 7. Six Sigma Software The R User Conference 2011 - Lightning Talk 7/15
  • 8. R Challenges Why Not Six Sigma uses Statistics. Six Sigma is based in the Scientific Method. Six Sigma should use R!. Outstanding advantages Every Statistical Tool even in base installation Extending possibilities Powerful graphics The R User Conference 2011 - Lightning Talk 8/15
  • 9. Packages qcc Shewhart quality control charts for continuous, attribute and count data IQCC Builds statistical control charts with exact limits for univariate and multivariate cases. qualityTools This is a package for teaching statistical methods in the field of Quality Science [. . . ] The focus is on teaching [. . . ] SixSigma Our effort for spreading the R thinking along Six Sigma practitioners. The R User Conference 2011 - Lightning Talk 9/15
  • 10. Six Sigma with R - Springer Use R! Series Features Title: Six Sigma with R Due 2012 350 pages approx. Wide background scope Examples, a Case Study and practices The R User Conference 2011 - Lightning Talk 10/15
  • 11. Process Map Six Sigma Process Map operators INPUTS tools X raw material facilities INSPECTION ASSEMBLY TEST LABELING sheets sheets helicopter helicopter ... INPUTS INPUTS INPUTS INPUTS Param.(x): width NC Param.(x): operator C Param.(x): operator C Param.(x): operator C operator C cut P throw P label P Measure pattern P fix P discard P Featur.(y): label discard P rotor.width C environment N Featur.(y): ok rotor.length C Featur.(y): time paperclip C tape C Featur.(y): weight LEGEND helicopter (C)ontrollable OUTPUTS (Cr)itical (N)oise Y (P)rocedure Paper Helicopter Project The R User Conference 2011 - Lightning Talk 11/15
  • 12. Gage R&R Six Sigma Gage R&R Study Components of Variation Var by Part 1.8 q 80 q q q q 1.6 60 q q Percent 1.4 var 40 q q q q q q 1.2 20 q q q q q 1.0 q 0 q G.R&R Repeat Reprod Part2Part prot #1 prot #2 prot #3 %Contribution %Study Var R Chart by appraiser Var by appraiser prot #1 prot #2 prot #3 1.8 q q op #1 op #2 op #3 q 0.5 q q q q q 1.6 0.4 q q q q 1.4 var 0.3 q var q q q q q q q q 0.2 1.2 q q q q q q q q 0.1 q q 1.0 q q prot #1 prot #2 prot #3 prot #1 prot #2 prot #3 op #1 op #2 op #3 part x Chart by appraiser Part*appraiser Interaction prot #1 prot #2 prot #3 1.7 q op #1 op #2 op #3 1.7 q 1.6 q 1.6 q q 1.5 var 1.5 1.4 var 1.4 q 1.3 q q 1.3 q 1.2 1.2 q q q 1.1 q q 1.1 q q prot #1 prot #2 prot #3 prot #1 prot #2 prot #3 prot #1 prot #2 prot #3 op #1 op #3 part op #2 Helicopter Project The R User Conference 2011 - Lightning Talk 12/15
  • 13. Capability Analysis Six Sigma Capability Analysis Study Histogram & Density Density Lines Legend Target Density ST Theoretical Dens. ST Density LT Theoretical Density LT LSL USL Specifications LSL: 740 Target: 750 USL: 760 Short Term Process Long Term 740 745 750 755 760 Mean: 749.7625 Mean: 752.8443 Check Normality SD: 2.1042 SD: 2.9577 n: 20 n: 40 Shapiro−Wilk Test Zs: 3.14 Zs: 2.42 q p−value: 0.07506 DPMO: q Short Term Indices Long Term qq q qq Lilliefors (K−S) Test Cp: 1.5841 Pp: 1.1270 qq qq qq q p−value: 0.2291 CI: [1.1,2.1] CI: [0.9,1.4] qq qq q q Cpk: 1.5465 Ppk: 0.8065 CI: [1.1,2.1] CI: [0.9,1.4] Normality accepted when p−value > 0.05 Winery Project The R User Conference 2011 - Lightning Talk 13/15
  • 14. Open Platform for Quality Methodologies Open Platform for Quality Methodologies Improving the European Factory FP7 PPP Funding Scheme Looking for Partners Other Projects We are available for other projects that need partners in this area The R User Conference 2011 - Lightning Talk 14/15
  • 15. Conclusion Thanks We hope we will be able to convince Six Sigma practitioners that not only is it possible with R, but it is BETTER with R. @emilopezcano | emilio.lopez@urjc.es The R User Conference 2011 - Lightning Talk 15/15