6-Sigma Program & Concepts Overview

6s 6-Sigma Program& Concepts Overview Control Project Phases: Presenters: P. Pfaff H. Myrie K. Barker Improve Analyze Measure

6s Meet Larry. Larry is a golfer. His play is, shall we say, erratic? He wants to play more consistently.

6-Sigma Example - Measure Phase Larry’s Golf Game • What is the output of Larry’s game? Specification: Larry wants to shoot between 80 and 100 this season, with a target average score of 90.

6-Sigma Example - Measure Phase Cpk = -0.05 !!! • What is his process capability? • How does this relate to his ZLT (Long Term) and ZST (Short Term)? • ZLT = (Cpk x 3) = -0.15 s Process • ZST = (Cp x 3) = 5.64 s Process* *(Best Process Cp - Sources of Variation Eliminated) • Goal: Reduce the variation and move the average in Larry’s game. Cp = 1.88

6-Sigma Example - Measure Phase Larry is Here 3.0 • How do we determine the opportunity for improvement for Larry’s Game? Improve Control Control (Zshift) 1.5 Goal ZST = 5.64 ZLT = -0.15 ZSHIFT = 5.79 (ZSHIFT = ZST - ZLT) Improve Skills 0 0 3.0 6.0 Technology/Skills (ZST) • This means: • Just by improving his control, Larry can achieve a 5.5 sigma game. • If he wants a 6 sigma game he will also have to improve his skills.

Larry’s Golf Game 1 0 0 1 0 0 0 8 0 t n u o C 5 0 0 4 0 2 0 0 0 t r g o n S h o t T y p e h o S L 7 7 7 4 7 0 C o u n t P e r c e n t 6 2 . 3 3 7 . 7 6 2 . 3 1 0 0 . 0 C u m % 6-Sigma Example - Measure Phase Let’s analyze his game by breaking down his score. Where is the biggest opportunity in his overall game? He takes more shots in his short game (62.3%).

Larry’s Short Game 8 0 0 1 0 0 7 0 0 8 0 6 0 0 t 5 0 0 n u 4 0 0 o C 4 0 3 0 0 2 0 0 2 0 1 0 0 0 0 s s p t t i S h o t T y p e u h P C C o u n t 5 2 0 2 5 7 P e r c e n t 6 6 . 9 3 3 . 1 C u m % 6 6 . 9 1 0 0 . 0 6-Sigma Example - Measure Phase Let’s continue analyzing his game by breaking it down further. Where is the biggest opportunity in his short game? He takes more shots in his putting game (66.9%).

6-Sigma Example - Measure Phase Cause & Effect Diagram - Larry’s Putting Game Measurement Material Larry Putting Score Environment Methods Machine • What are the causes of variation in Larry’s Putting Game?

6-Sigma Example - Analyze Phase Cause & Effect Diagram - Larry’s Putting Game Measurement Material Larry >Cheat at Counting > Can’t Remember > Pencil has an eraser > Grass Type >Number of Drinks > Eye Glasses Prescription Updated > Properly Rested Putting Score > Golf Course > Green Condition > Time of Day > Weather > Playing Partners > Betting of Hole > Putting Style - Stance -Grip - Swing > Reading the Green >Putter Type > Ball Type > Shoes > Glove Environment Methods Machine • What are the causes of variation in Larry’s Putting Game?

6-Sigma Example - Analyze Phase Is putting really a significant source of variation in the overall golf score? ScatterPlot/Fitted Line Regression 1 3 0 Yes!!! 1 2 0 e 1 1 0 r o c S Y = 3 3 . 1 2 8 4 + 1 . 6 7 5 4 6 X 1 0 0 R-Squared = 0.906 9 0 The R-Squared value says that 90.6% of the variation in the Overall Score is directly related to the putting game. 3 5 4 0 4 5 5 0 P u t t s

6-Sigma Example - Analyze Phase Let’s figure out what is causing the variation in his putting game. . . What did Larry do differently during this time frame?

6-Sigma Example - Analyze Phase If he gave up drinking, does the number of drinks directly affect his putting? ScatterPlot/Fitted Line Regression 5 4 Yes!!! s 4 4 t t u P Y = 3 6 . 2 5 + 2 X R-Squared = 0.872 3 4 The R-Squared value says that 87.2% of the variation in Putting is directly related to the number of drinks he had. 0 1 2 3 4 5 6 D r i n k s

6-Sigma Example - Analyze Phase Conclusions • Larry should putt, or drink, but not both! • If Larry gives up drinking while golfing he will have addressed 87.2% of the variation in his putting game. • By bringing his putting game under control he will achieve a 5-sigma game. • To achieve a 6-sigma game we will have to do further investigations.

6-Sigma Example - Improve Phase Cause & Effect Diagram - Larry’s Putting Game Measurement Material Larry >Cheat at Counting > Can’t Remember > Pencil has an eraser > Grass Type >NUMBER OF DRINKS > Eye Glasses Prescription Updated > Properly Rested Putting Score > Golf Course > Green Condition > Time of Day > Weather > Playing Partners > Betting of Hole > Putting Style - Stance -Grip - Swing > Reading the Green >Putter Type > Ball Type > Shoes > Glove Environment Methods Machine • Last time we determined drinks was a significant X. • What other sources also drive the Putting Score?

6-Sigma Example - Improve Phase In order to improve his game above the 5-sigma level he has to improve his skills. • What skills does he need to improve? • After talking with Larry and the Golf Pro we • have concluded that there are three areas • that would most likely improve his putting • game. They are the putter type, stance • and grip during putting. • The Golf Pro wants to sell him the latest • high tech/high $$ putter (Big Bubba). • What does Larry have to do?

6-Sigma Example - Improve Phase • Larry was not sure, so he consulted with his trustworthy Black Belt, who uses data to help make decisions. • They then set up a Designed Set of Experiments with the following settings:

6-Sigma Example - Improve Phase This is the Experiment Matrix that they decided to run! This is a 23 DOE, which has eight conditions to test.

6-Sigma Example - Improve Phase This is the Experiment Matrix after we randomized the order that they will run! Randomization is done to detect the effect of other non-controlled variables.

6-Sigma Example - Improve Phase We ran the experiments and these are the results. p = .003 Interaction Plots for Putting Score Main Effects Plot for Putting Score 1 1 - 1 1 1 40 38 36 34 32 Open Stance Open Stance p = .026 p = .873 p = .037 Stance - 1 - 1 Putting Score Close Stance 40 38 36 34 32 Close Stance - 1 40 38 36 34 32 - 1 1 Old Reliable 1 Putter Type Big Bubba Old Reliable - 1 1 Big Bubba 1 Open Interlock Stance Putter Type Open Open Grip Grip Close Interlock Big Bubba Old Reliable The Closed Stance with the Interlocked Grip gives Larry the Lowest Score! (Verified statistically.) Stance and Grip are significant factors. (Verified statistically.)

6-Sigma Example - Improve Phase DOE Conclusions • The high $$ putter made no difference!! • The interaction between Closed Stance and Interlocked Grip gives Larry the lowest score! • Just using the interlocked grip or closed stance by themselves will not achieve the lowest putting score.

6-Sigma Example - Improve Phase So, What is Larry’s Improvement Plan? • Give up drinking . . . on the golf course!! • Continue to use “Old Reliable” putter, since the DOE showed that the “Big Bubba” made no difference. • Always use an interlocking grip and a closed stance when he putts. • Implement these improvements and collect some data! Play some golf!

Improve Measure 6-Sigma Example - Improve Phase Has Larry improved? USL LSL Yes! How much? From Measure: Zlt = -0.15 DPMO = 820,000 Zst = 5.64 From Improve: Zlt = 4.23 DPMO = 12

6-Sigma Example - Improve Review Remember Larry’s Improve “Plan” . . . • Give up drinking . . . on the golf course!! • Use “Old Reliable” putter!! • Always use an interlocking grip and a closed stance when he putts!! . . . and the Results From Measure: Zlt = -0.15 DPMO = 820,000 Zst = 5.64 From Improve: Zlt = 4.23 DPMO = 12

6-Sigma Example - Control Phase Larry Needs a Control Plan • What’s a good plan to insure that Larry sustains the improvements he has made? • Are there risks that could cause Larry to lose his improvement? • If so, how should Larry address those risks associated with changing his golf game? • Can Larry come up with a realistic drinking objective and maintain his improvement?

6-Sigma Example - Control Phase So, What is Larry’s Control Plan? Mistake - proofing • Alternate drinking plan • Leave wallet in car - only take enough $ for 1 beer • Lock and key on partners’ beer coolers • Unlimited supply of “Near Beer” in Red Dog bottles (shhh - Don’t tell Larry) • Put a Label on “Old Reliable” putter where he always sees it when putting • “Interlock grip, close stance”

6-Sigma Example - Control Phase More of Larry’s Control Plan • SPC Control Chart • Use the mean +/- 3 sigma limits as calculated from the Improve Phase data • Continue Data Collection on Vital X’s • Larry to track drinks per round Okay, he’s got a plan. Is there any risk associated with it?

6-Sigma Example - Control Phase Risk Assessment • Identify the risk elements (schedule, cost, technical) • Assign ratings (high (3), med(2), low(1)) • Prioritize elements (probability & impact) • Identify Risk Abatement plans • Incorporate into Larry’s Control plan Giving up drinking is a risk! Need an Abatement Plan

6-Sigma Example - Control Phase Abatement Planning If he drinks moderately, can he maintain an improvement? ScatterPlot/Fitted Line Regression 5 4 s 4 4 t t u P Y = 3 6 . 2 5 + 2 X R-Squared = 0.872 Expected Outcome 3 4 The Linear Regression predicts that 1 - 2 drinks will add only a few putts. 0 1 2 3 4 5 6 D r i n k s Realistic Tolerance

6-Sigma Example - Control Phase Monitoring the SPC Chart 99! Out of Control! UCL = 96.91 LCL = 83.23 What happened here? Let’s look at the data!

6-Sigma Example - Control Phase Does Larry’s Control Plan Work? • How did Larry get four drinks? • Was this risk in the Risk Assessment / Abatement Plan? • Yes! • Is there an Abatement Plan? • Yes! • Then implement the Abatement Plan immediately. Score Drinks 89 1 91 1 88 1 90 2 99 4 91 2 88 0 89 1 90 2 93 2 91 1 “Stuff” happens - so we do Risk Assessment / Abatement!!

6-Sigma Example - Control Phase Did the Abatement Work? UCL Control Chart says Yes! LCL Capability Analysis says Yes! He has reached Zlt = 5.7 Sigma! (Zst at Measure was 5.64) Success!

Glossary of Terms • ZLT - Overall (Long Term) process capability, ZLTs process • ZST - Best (Short Term) process capability, ZSTs process • Zshift = ZLT - ZST • DPU - Defects Per Unit • DPO - Defects Per Opportunity • DPMO - Defects Per Million Opportunities • PPM - Parts Per Million • FTY - First Time Yield • Cp - Capability Index (best process capability) • Cpk - Actual Capability Index (measure of process shift) • CPU - Capability index for upper spec. limit • CPL - Capability index for lower spec. limit • CTQ - “Critical To Quality” characteristic • Gage R&R - Gage Repeatability & Reproducibility • QFD - Quality Functional Deployment • Sigma - is a measure of variability (standard deviation) • NPI/EDC - New Process Introduction/Engine Development Cycle

6-Sigma Program & Concepts Overview