1. Six sigma Orientation

3. What is Quality?

4. Evolution of Quality Historically Proactive Quality “ Create process that will produce less or no defects” Contemporary Reactive Quality Quality Checks (QC) - Taking the defectives out of what is produced

8. Path to Six Sigma Sigma levels and Defects per million opportunities (DPMO) 4 Sigma 6,210 Defects 2 Sigma 308,537 Defects 3 Sigma 66,807 Defects 5 Sigma 233 Defects 6 Sigma 3.4 Defects

9. What it means to be @ Six Sigma Example quoted from GE Book of Knowledge - copyright GE Is 99% (3.8  ) good enough? 99.99966% Good – At 6  20,000 lost mails per hour 7 lost mails per hour Unsafe drinking water almost 15 minutes each day One minute of unsafe drinking water every seven months 5,000 incorrect surgical operations per week 1.7 incorrect surgical operations per week 2 short or long landings at most major airports daily One short or long landing at major airports every five years 200,000 wrong drug prescriptions each year 68 wrong drug prescriptions each year

12. The GE model for process improvements The Growth of Six Sigma Define Measure Analyze Improve Control Combination of change management & statistical analysis

13. The Growth of Six Sigma

14. BPMS Business Process Management System DMAIC Six Sigma Improvement Methodology DMADOV Creating new process which will perform @ Six Sigma Three Methodologies of Six Sigma

15. BPMS Business Process Management System

17. The Methodology Define purpose of the process, its goal and its boundaries Identify Critical to Quality and Critical to process Visual representation of performance Map process steps, identify input/ output measures MSA, DCP, indicators and monitors Service excellence and process excellence The DMAIC cycle Define Process Mission Map Process VOC and VOP Build PMS Develop Dashboards Identify Improvement Opportunities

18. DMAIC Six Sigma Improvement Methodology

20. The Approach Practical Problem Statistical Problem Statistical Solution Practical Solution

21. D Define M Measure A Analyze I Improve C Control Identify and state the practical problem Validate the practical problem by collecting data Convert the practical problem to a statistical one, define statistical goal and identify potential statistical solution Confirm and test the statistical solution Convert the statistical solution to a practical solution Methodology

22. VoC - Who wants the project and why ? The scope of project / improvement Key team members / resources for the project Critical milestones and stakeholder review Budget allocation Define D Define M Measure A Analyze I Improve C Control

24. Understand statistical problem Baseline current process capability Define statistical improvement goal Identify drivers of variation (significant factors) Analyze D Define M Measure A Analyze I Improve C Control

30. Map improved process Pilot solution Identify operating tolerance on significant factors Improve D Define M Measure A Analyze I Improve C Control

31. Ensure measurement system reliability for significant factors Improved process capability Sustenance Plan - Is tool used to measure the input / process variables flawed ? - Do all operators interpret the tool reading in the same way ? - Statistical Process Control - Mistake Proofing - Control Plan Control D Define M Measure A Analyze I Improve C Control

33. Six Sigma Organization

34. Six Sigma - Three Dimensions Tools Organization Methodology Driven by customer needs Enabled by quality team. Led by Senior Mgmt Define Measure Analyze Improve Control Process Map Analysis Pareto Chart Process variation LSL USL Upper/Lower specification limits Regression • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •

37. Thank You