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Six Sigma is Possible with R

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These slides were presented at the Use R! 2011 Conference, held in the University of Warwick (Coventry) in August 2011. It was one of the presentations of the Lightning Talks session.

These slides were presented at the Use R! 2011 Conference, held in the University of Warwick (Coventry) in August 2011. It was one of the presentations of the Lightning Talks session.

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  • 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 2011The 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

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