Exercises that will help you use the tools in the real world:

• Create flowcharts, histograms, scatter diagrams, Pareto charts, Cause-and-effect diagrams (Ishikawa), check sheets.
• Perform a Monte Carlo analysis, set up a QRAM and SWOT diagram for risk analysis.
• Set up basic AHP for decision analysis
• Create a decision tree chart

• Create management planning charts including: Affinity diagrams, interrelationship digraphs, tree diagrams, prioritization matrices, matrix diagrams, Process decision program charts (PDPC), activity network diagrams

• DOE/ANOVA exercise
• Create a basic QFD
• Perform a basic probability analysis and a conditional probability analysis using Bayesian formulas – conditional probability

• Create an FMEA process - calculate the Risk Priority Number

• Create all SPC charts including:  X-Bar, X-Bar R, X-Bar S, ImR and XmR (Individuals and moving range), median, p, np, c and u

• Create process performance charts including: DPU (Defects per unit), RTY (Rolled Throughput Yield), COPQ (Cost of Poor Quality), and DPMO (Defects per Million Opportunities)

• Create all process distributions including : Normalized Distribution, Uniform, Exponential, F-distribution, Chi-Square, Student’s ‘ t’, Binomial Distribution  (pdf and cdf), Poisson, and Hypergeometric

• A class project where you can put it all together!

• Calculate process performance using DPU (Defects per unit), RTY (Rolled Throughput Yield), COPQ (Cost of Poor Quality), and DPMO (Defects per Million Opportunity)
• Failure Mode and Effects Analysis (FMEA) – calculate the Risk Priority Number

• Use Team dynamics tools such as Brainstorming, multi-voting, nominal group technique, Delphi, etc.
• Understand team evolution: forming, storming, norming and performing.
• Understand team conflict and how to resolve issues
• Roles and responsibilities of Six Sigma teams including white belt, green belt, black belt, master black belt, champion, executive, coach, facilitator, team member, sponsor process owner, etc.

 Measure

• Utilize process modeling to create process maps, flow charts, cause-and-effect diagrams (Ishikawa), The Customer-Supplier model (SIPOC)
• Basic statistics – utilize and distinguish between enumerative (Descriptive) and Analytical (Inferential) statistical processes
• Basic probability including conditional probability (Bayesian analysis)
• Classify data and measurement scales: nominal, ordinal, interval and ratio,
• Utilize data collection methods such as check sheets, coded data, etc.
• Assure data accuracy utilizing random sampling, stratified sampling, sample homogeneity, etc
• Utilize descriptive statistics to define and compute measures of central tendency such as the PDF (Probability density function) and CDF (Cumulative distribution function).
• Utilize graphical tools for interpreting charts such as the stem-an-leaf plot, box-and-whisker plot, run charts, Pareto charts, scatter diagrams, histograms, etc.
• Understanding and utilize probability distributions:

Continuous Distributions

·         Normalized Distribution

·         Uniform

·         Exponential

·         F-distribution

·         Chi-Square

·         Student’s ‘ t’

Discrete Distributions

·         Binomial Distribution  (pdf and cdf)

·         Uniform

·         Poisson

·         Hypergeometric

• Measurement systems analysis tools: GR&R (Gage  R&R ) measure correlation, bias, linearity, precision/Tolerance
• Calculate process capability performance using the process capability indices C_p, C_pk, and process performance indices P_p, P_pk and C_pm, as well as short term and long term process capability as it relates to the 1.5 sigma shift.

Analyze

• Utilize and interpret multi-vari studies: know the difference between positional, cyclical and temporal variation
• Utilize correlation coefficient and regression analysis models to recognize the difference between correlation and causation and measure the statistical significance (p -value )
• Utilize and interpret the paired-comparison test
• Determine appropriate sample sizes

• Understand and utilize hypothesis testing: Type I and Type II errors, significance level and power.
• Plot and interpret one-way ANOVA
• Utilize and interpret chi-square to determine statistical significance

Improve and Control

• Basic DOE (Design of Experiments): dependant and independent variables, factors and levels, response, treatment, error, repetition and replication. Interpret main effects and interaction plots
• SPC charting: create, utilize and interpret the following control charts: X-Bar, X-Bar R, X-Bar S, ImR and XmR (Individuals and moving range), median, p, np, c and u