TQM Resources Sdn. Bhd. ( X) 9, Solok Trengganu, 10460, Penang, Malaysia.

Transcription

1 TM Resources Sdn. Bhd. ( X) 6 Sigma Green Belt Training Introduction. An important component to ensure success of Six Sigma uality Implementation is to have team members who can support the work of the Black Belts. Green Belts are people work directly with the black belts but do not have the same level of training or responsibility to the project as the black belts. Given the nature of the tasks Green Belts most often execute, these individuals should receive training which focus on the Define, Measure, and Analyze phases of the Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control). Contents: 1. Practical application of statistical concepts learned is afforded through case studies, hands on exercises & assigned projects. This will need minimum 3 days training on Statistics. 2. Application of DMAIC (Define, Measure, Analyze, Improve, Control) and data collection to support the selection and completion of a project. This needs 1 day training. 3. Selected Training such as: a. Design of Experiments b. Variance Analysis & ANOVA. c. SPC. Note : The above list of training can be tailored to meet your needs and also modified the necessary training. Please let us know the needed module and we will provide the necessary details for your further understanding an review. Detailed contents: Define Phase Day 1- Day 2 Introduction of Six Sigma Basics of Six Sigma Meaning and definition of Six Sigma History and Implementation of Six Sigma Problem Solving Model Y = f(x) Customer, Employee and Business relationship and voice Roles and Responsibilities of Employees in Six Sigma activities Deliverable of Lean Six Sigma Project.

2 TM Resources Sdn. Bhd. ( X) Fundamental of Six Sigma Process definition CT definition and set up Pareto Analysis of production problems and failures Cost of uality definition and computation Six Sigma Metric such as DPMO, FTY< RTY Cycle Time and their derivation Determine project scope and boundaries Must define problem statement Projected annualized savings Project metrics, Baseline and Entitlement (target saving per project) Project deliverables Lean organization Understanding and history of Lean Relationship between Lean and Six Sigma Production Waste and 5S introduction Measure Phase Day 3 Day 6 Definition of Process Cause and effect analysis Process Mapping, SIPOC, Value Stream Map X-Y Relationship/Diagram Failure Mode Effect Analysis (FMEA) Brief explanation on FMEA principle and techniques Summarize the definitions, concepts, application options and relationships with other tools Basic statistics Describe mean, median, quartiles, mode, standard deviation, range from the data analysis Define variability in a process Work with variability (graphically and numerically) Normality Test Check data normal or non normal Normal Probability Plots Graphical Analysis

3 TM Resources Sdn. Bhd. ( X) Measurement System Analysis Precision and Accuracy Bias, Linearity, and Stability Understand that Measurement is a Process Compare Measurement System Variability to Process Variability Identify and quantify the sources of Measurement Variability- Repeatability and Reproducibility Variable and attribute MSA Discover opportunities for Measurement System and Total Process Variability improvement Process Capability Study Understand the need for Process Capability study uantify Process Capability (long and short term) Capability Analysis Process Stability Capability computation for Attribute and Discrete Data Process Monitoring techniques Analyze Phase Day 7 Day 9 Overview and Brief introduction on Probability Distribution (type and plotting with Minitab) Basic nature of data Discrete Probability Distributions Discrete Uniform Distribution Binomial Distribution Continuous Probability Distributions Continuous Uniform Distribution Normal or Gaussian Distribution Exponential Distribution Sample size selection Interval of Estimation Central Limit Theorem Hypotheses testing (Variables & Discrete) Concept and Goals of Hypothesis testing α and β risk Significance: Practical and Statistical Understanding Apply various tests such as 1 sample Z test, 1 sample T test, 2 samples T test, 1 proportion Test, 2 proportions Test to compare different populations.

4 TM Resources Sdn. Bhd. ( X) Non-Normal Data Hypothesis Testing Mann-Whitney test Kruskal-Wallis test Friedman test Wilcoxon test Mood s Median test ANOVA (Analysis of Variance) What is ANOVA? What is the Sum of Squares? Calculate the test statistic Epsilon Squared ANOVA by example Contingency Table Chi-Square contingency table analysis Correlations & Regression Correlation Create Scatter Plots Perform simple Linear Regression Coefficient of Correlation (R, R 2 and adjusted R 2 ) Regression diagnostics Improve Phase Day 10 Day 11 Linear Regression. Correlation study Regression equation y=ax+b Residual Analysis Multiple Regression Multiple Linear Regresssion Non linear regression Confidence and prediction interval Residual Analysis Transformation of data. Introduction to DOE (Design of Experiment) What is DOE To optimize the process variables DOE Planning

5 TM Resources Sdn. Bhd. ( X) Full Factorial Describe a full factorial experiment Define what it meant by factors & levels and explain the notation used for a full factorial experiment design Explain main effects and interactions Set up and Analyze full factorial experiment using Minitab 2 K Factorial Design Why do we need to use 2 k factorial experiments? 2 k Vocabulary & Terminology Steps for DOE Analysis 2 k Standard Order Designs Calculating main effects Calculating interactions Adding Center Points Adding Blocking 2 k Example and Exercise (with Minitab and other related software) Control Phase Day 12 Day 14 Introduction to Control Implementation of 5S Kanban Application on production control Introduction to process monitors and controls Introduction to current management tools and philosophies Determine the effects of the informal system SPC 1 (Variable Charts) Introduction to SPC Why we need Statistical Process Control Implementation and Theory Control Charts for continuous data X-bar and R charts Subgrouping and frequency Control Chart interpretation Reaction to Out-of-Control Situations Other Shewhart charts for continuous data Control Charts for discrete data P, NP, C, and U charts SPC 2 (Attribute Charts) Attribute Terminology Discrete or Attribute types of data Defect and Defective

6 TM Resources Sdn. Bhd. ( X) Error proofing Explain the value of error proofing Concept and Implementation of Poka Yoke. Describe situations where error proofing is needed Implement error- proofed systems Maintaining the Gains Understand why 5S Workplace Organization is a key factor in maintaining success Application of Control Plan and Response Plan to overcome problems Cost Benefit Analysis for the project implementation. Learn techniques for building organizational memory to make improvements permanent Who Should Attend This workshop is designed for six sigma improvement team members, supervisors and other executives who will be conducting Six Sigma projects in the lower complexity than the Black Belt projects.