1. Roberto lopez LSSMBB Roberto.lopez@bomconsulting.net DMAIC project template

2. 6 sigma steps (DMAIC) Define Measure Analyze Improve Control Define your business problem Measure your process (Y) performance Find the root causes (X’s) of the problem Improve, implement new solution Deliver Y performance over time

3. Description of the problem (what? where? since when? based on which data? Based on which facts?) Voice Of Customer (Customer perception) Internal perception Competitors benchmark 1 Pb Statement Business Problem Develop Goal statement/opportunity or objective in clear, concise, measurable terms Demonstrate alignment of the project with the company/business strategy 2 Goal Statement Define

4. Why to do the project? What if project not done? Financial Business Case Business Case 3 Business Case Define

5. Green Belt/Black Belt role: Team members/role: Black Belt: Master Black Belt: VP Quality / Quality Manager: Manager: Key stakeholders from Business team: Customers: Others: 4 Project scope Project: in scope DMAIC Dates: Gantt Project: out of scope Project charter 5 Team 6 Planning Define

6. 7 (SIPOC) Process map & CTQ’s process as felt by the customer Input Output Supplier = My Company DefinitionSpecificationPerformance limit targets CTQ* Step 2Step 1Step 3 measurement *Critical To Quality My Customer Define

7. M-step 1: Selected CTQs Selected Project CTQ(s): Discrete/continuous CTQ? CTQ Operational Definition(s): What is it (measurement starting point and end point) ? How to measure it? What is a defect? If applicable to your CTQ, LSL* contractual value or limit defined by customer: If applicable to your CTQ USL* contractual value or limit defined by customer: M-step 2: Define Performance standard Measure CTQ details *LSL Lower Specification Limit *USL Upper Specification Limit

8. M-step 3: Measurement System Analysis Measurement system analysis Data Collection plan for Repeatability & Reproductibility study: Data sample size = Date of data collection: Where data have been collected? How data have been collected? How many operators?How many repeats per operator? Gage R&R study – Continuous data: -Tolerance (USL-LSL): -Short method (yes/no): -Gage R&R as %contribution:Gage R&R as %tolerance: Nb of distinct categories: Gage R&R study – discrete data: If we have a Known sample (a reference), then how was built the known sample? Conclusion/decision taken (evidence that the measurement of our CTQ is reliable): Measure Gauge R&R

9. M-step 4: Baseline current (As Is) process capability CTQ data collection plan Data sample size = Date of data collection: Where data have been collected? How data have been collected? Will you take the opportunity to collect obvious X’s when collecting your CTQ measurements? If yes, which X’s: Display an extract of the data collected: Measure CTQ data collection plan

10. Continuous CTQ Sample size= Short term data or Long term data? Histogram with Normality test result and descriptive statistics: Type of the distribution (normal, other): Trend represented by its ( , median, Q1, Q3, other): Variability represented by its (  P95, Q1/Q3, other) : PROCESS CAPABILITY MEASURE: NORMAL Distribution Observed DPMO= Potential DPMO= Z LT = Z ST (Z LT +1.5)= Conclusion Problem with trend, variability or both? M-step 4: Baseline current (As Is) process capability Photography of current performance Measure Non NORMAL Distribution Observed DPMO= Equivalent Z LT = Equivalent Z ST (Z LT +1.5)=

11. Discrete CTQ Sample size: Short term data or Long term data? Process capability Yield (%)= %defects= DPMO= Opportunities per unit= DPU= Equivalent Z LT= Equivalent Z ST (Z LT +1.5)= 95% confidence interval on DPMO: Measure Photography of current performance M-step 4: Baseline current (As Is) process capability

12. Continuous CTQ Normal probability plot: Conclusion (can we detect a true process and an unstable process?): All type of CTQ Stability over time/Run chart: Conclusion: Pb of technology (short term common causes)? Pb of control (long term shift due to special causes)? Both pbs? A-step 5: As Is process Graph Analysis Analyze Graph analysis

13. A-step 6: Define Performance Objectives of To Be process Improvement Goal Target (from benchmark) for: Trend: Variability: LT DPMO or LT %defects= Yield (%)= Z LT = Z ST =(Z LT +1.5)= Gap (Improvement – Actual) DPMO gap or Defect reduction factor: Z gap= 6 Sigma tools necessary to meet performance objectives: Ground fruit: Logic and Intuition Low hanging fruit: Basic tools (Process Map, CE/CNX fishbone diagram, SOP, FMEA, Pareto, Histogram, Box plot) Bulk of Fruit Process Characterization and Optimization Sweet Fruit: Transform the project into a DFSS project Analyze Set expected performance

14. A-step 7: Identify X’s (root causes) Process (AS IS) detail analysis: Detailed process map Conclusion CTQ Intermediate distribution plot (continuous CTQ only) Conclusion Standard Operation Procedures analysis: Exist: Are applied: Incitation to apply them exist: Training has been given to operators: Policy analysis: Exist Are applied Analyze Process analysis

15. List of potential significant X’s Label C/N/X on your fishbone, then rate every X impact vs implementation (table below) 1 2 3 4 Impact High Low Implementation Easy Hard Analyze Potential root causes A-step 7: Identify X’s (root causes)

16. Results of segmentation (continuous CTQ only) : (Box plots, Scatter plots, Distributions per X) Conclusion: Analyze Segmentation analysis A-step 7: Identify X’s (root causes)

17. Pareto chart of the CTQ categories: Conclusion: Pareto chart of the defect categories: Conclusion: FMEA: Conclusion: Analyze Pareto analysis A-step 7: Identify X’s (root causes)

18. Statistical Tests Performed Test X Factorsp value%contribution conclusion one sample or two sample T-test Annova one way Homogeneity of variance Chi square test Simple regression Non parametric data test ANOVA 2 ways GLM DOE screening Conclusion/Prioritized list of significant X’s: Financial benefits confirmation (Update your Business case): Analyze Hypothesis testing A-step 7: Identify X’s (root causes)

19. I-step 8: Screen potential causes. List improvement actions/projects List of Vital few Xs (screening DOE): Improvement action plan (Who What When): Improve Improvement actions

20. I13 X tolerance settings: I-step 9: Discover Variable relationships (if necessary) Transfer function: Proposed Solution: Optimal Settings Confirmation runs capability: I-step 10: Establish Operating Tolerances (if necessary) Improve Improved performance

21. Control Gage R&R on X’s C-step 11: Define and Validate Measurement System on X’s (if necessary) Control on one X (yes/no): If yes, X measurement system analysis: Data Collection plan for Repeatability & Reproductibility study: Data sample size = Date of data collection: Where data have been collected? How data have been collected? How many operators?How many repeats per operator? Gage R&R study – Continuous data: -Tolerance (USL-LSL): -Short method (yes/no): -Gage R&R as %contribution:Gage R&R as %tolerance: Nb of distinct categories: Gage R&R study – discrete data: If we have a Known sample (a reference), then how was built the known sample? Conclusion/decision taken (evidence that the measurement of our X is reliable):

22. C-step 12: Determine new Process Capability Process or Product new capability: Continuous CTQ: NORMAL Distribution Observed DPMO= Potential DPMO= ZLT = ZST (ZLT+1.5)= Discrete CTQ: Sample size:= Short term data or Long term data? Process capability Yield (%)= %defects= DPMO= Opportunities per unit= DPU= Equivalent ZLT= Equivalent ZST (ZLT+1.5)= 95% confidence interval on DPMO Statistical Confirmation of Improvement (by statistical test): Confirmation of improved performance Control Non NORMAL Distribution Observed DPMO= Equivalent Z LT = Equivalent Z ST (Z LT +1.5)=

23. C-step 13: Implement Process Control Control Charts (SPC) in place/review mechanisms: Mistake Proofing action taken: FMEA control actions in place: Process controls Control