LSSG Green Belt Training

1. LSSG Green Belt Training Analyze: What are the Key Drivers for Breakthrough Performance?

2. Qualitative vs. Quantitative Analysis Qualitative: Goal - Identify and prioritize critical X’s Tools - Pareto Charts, C&E matrix/fishbone diagram, Brainstorming, Detailed As-Is process, Non-value add analysis, Benchmarking, FMEA Quantitative: Goal – Find Root Causes and Validate critical Xs. Tools - Hypothesis Testing Concepts, Multi-Vari Studies, Simple and Multiple Regression, ANOVA

3. Process Analysis Process • Any part of an organization that takes inputs and transforms them into outputs repeatedly Process Analysis • The ability to diagram a process, identify its flow, potential bottlenecks, and determine its capacity Process Flowchart • The use of a diagram to present the major elements of a process.

4. Example of a Process Flowchart

5. Process Analysis Definitions Cycle Time - The average time between successive completions of units Throughput Time - The total time it takes for a unit to move through the process from beginning to completion Throughput Rate - The inverse of cycle time, expressed as number of units per time period Capacity - The measure of output per unit of time when system is busy Utilization- The ratio of the time that a resource is actually active relative to the time that it is available for use Continuous Flow - A job performed in a steady flow with no wasted motion, no interruptions, and no waiting Work-In-Process - Any type of unfinished work waiting to be performed at a later time Bottleneck- The slowest operation in the process; defines cycle time and capacity of the process

6. A 20 min B 30 min 30 30 Process Analysis for Processes withoutBuffers What is the cycle time of this process? What is the throughput time of this process? What is the throughput rate of this process? Batch1: 0-20 20-50 B – Starved for 20 min Batch2: 20-40 50-80 A – Blocked for 10 min Batch3: 50-70 80-110 A – Blocked for 10 min

7. B 30 min A 20 min B 30 min A 20 min Batch1: 0-20 20-50 B – Starved for 20 min 30 30 Batch2: 20-40 50-80 A – Blocked for 10 min 30 30 Batch3: 50-70 80-110 A – Blocked for 10 min Batch1: 0-30 30-50 A – Starved for 30 min Batch2: 30-60 60-80 A – Starved for 10 min Batch3: 60-90 90-110 A – Starved for 10 min Process Analysis for Processes withoutBuffers

8. Stage 2 Stage 1 Average WIP = Lead Time (throughp ut time in WIP inven tory) Throughput Rate Buffer Little’s Law Throughput Time Throughput time in WIP How to reduce Lead (Throughput) Time?

9. Process Analysis with Buffers Example of Using Little’s Law Bake 100 meat loaves Baking time 60 minutes Bake 100 meat loaves Baking time 60 minutes CT= 30 min Individual Pack 100 meat loaves 48 min CT= 48 min

10. FMEA Template Severity – How serious is the failure to the process; to business results? (1 = minor, 2-3 = annoyance, 9-10 = very high/most severe) Detection = Likelihood that a defect will be detected by controls before the next (subsequent) process (1-2 = very high, 9 = very low, 10 = absolutely cannot detect) Occurrence = Frequency of failure mode (1 = remote, 9 = inevitable, 10 = certain)

11. Benchmarking Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 6 Internal Benchmarking Reverse Engineering Different Industry Process Benchmarking International Benchmarking Similar Industry Process Benchmarking Strategic Benchmarking Standardize internal best practices Study/ Incorporate best features of competitive products Study/ Incorporate best process practices Study/ Incorporate applicable best process practices Study other approaches to strategy development Leverage core competencies and trends Identify global strategies, customers, new partners, products, and processes

12. Problem Solving through Appreciative Inquiry Appreciative Inquiry extends the first step of the benchmarking process by focusing on the “best of what is” Source: David Cooperrider et all, Appreciative Inquiry

13. Statistics Roadmap for Analyze(Black Belt Topics) DMAIC Find out what is causing the problem ANALYZE ID and Confirm with Data VALIDATE ROOT CAUSES Is there really a relationship? What to compare? Amount of risk? Calculation and comparison to test statistics HYPOTHESIS TESTS Measured Data, E.g. time, length and weight Compare Proportions Count Data Etc… CONTINOUS DATA DISCRETE DATA Definitions: www.asq.org/sixsigma/terms/a.html

14. Hypothesis Testing Continuous Attribute Normal Non-Normal c2 Contingency Tables Variance Variance Means Medians Correlation Z-tests Levene’s Correlation c2 Same tests as Non-Normal Medians Sign Test t-tests F-test ANOVA Bartlett’s Wilcoxon Correlation Kruskal-Wallis Regression Mood’s Friedman’s Hypothesis Testing Roadmap

15. Testing of Means - Roadmap Comparing Means 3 or more Factors 2 Factors 1 Factor 1 Sample 2 Samples 2 or more samples s not known Indep- endent paired s known 1-sample Z-test 1-sample t-test 2-sample t-test Paired t-test One way ANOVA Two way ANOVA ANOVA GLM

16. Testing of Variation - Roadmap Comparing Variances 2 Sample More Than 2 Samples 1 Sample Test for Equal Variance 1 Variance 2 Variance Test Test Descriptive Statistics F- test Levene’s Test Bartlett’s Test Levene’s Test

17. Comparing Proportions 2 Sample More than 2 samples 1 Sample Chi-Square Test 1 Proportion 2 Proportion Z Test Z Test Testing of Proportions - Roadmap

18. Non-Parametric Tests Binominal (2 Levels) 3 or more Levels Independent Dependent Dependent Independent Mann-Whitney U (t-test analog) Wilcoxon/ Sign (Paired t-test analog) Kruskal-Wallis H /Mood’s Median Test (One-way ANOVA analog) Friedman Two-way ANOVA (Repeated measure ANOVA) Non-Parametric Testing Roadmap