Lean Six Sigma Green Belt Advanced

Understand the evolution of Six Sigma from quality leaders such as Juran, Deming, Shewhart, Ishikawa, and others.

Understand the evolution of Six Sigma from quality leaders such as Juran, Deming, Shewhart, Ishikawa, and others.

Recognize key business drivers (profit, market share, customer satisfaction, efficiency, product differentiation) for all types of organizations. Understand how key metrics and scorecards are developed and how they impact the entire organization.

To describe about the project selection process including knowing when to use six sigma improvement methodology (DMAIC) as well as to know how project goals are linked with organization goals.

Use value stream mapping to identify value-added processes and steps or processes that produce waste, including excess inventory, unused space, test inspection, rework, transportation, and storage.

Use value stream mapping to identify value-added processes and steps or processes that produce waste, including excess inventory, unused space, test inspection, rework, transportation, and storage.

Identify value-added processes and steps or processes that produce waste, including excess inventory, unused space, test inspection, rework, transportation, and storage.

Describe lean concepts such as the theory of constraints, value chain, flow, and perfection.

Describe the project selection process and what factors should be considered in deciding whether to use the Six Sigma DMAIC methodology or another problem-solving process.

Describe the project selection process and what factors should be considered in deciding whether to use the Six Sigma DMAIC methodology or another problem-solving process.

Define and describe process components and boundaries. Recognize how processes cross various functional areas and the challenges that result in process improvement efforts.

Understand various types of benchmarking, including competitive, collaborative, and best practices.

Identify the process owners and other stakeholders in a project.  Identify process input and output variables and evaluate their relationships using the supplier, input, process, output, customer (SIPOC) model.

Collect feedback from customers using surveys, focus groups, interviews, and various forms of observation.

Identify the critical to quality elements using the CTQ tree concept

Use quality function deployment (QFD) to translate customer requirements statements into product features, performance measures, or opportunities for improvement.

Define and describe elements of a project charter and develop a problem statement that includes baseline data or current status to be improved and the project’s goals

Define phase steps

Define and describe elements of a project charter and develop a problem statement that includes baseline data or current status to be improved and the project’s goals.

Help define the scope of the project using process maps, Pareto charts, and other quality tools.

Use Gantt charts, critical path method (CPM), and program evaluation and review technique (PERT) charts to plan projects and monitor their progress.

Identify and help develop appropriate presentation tools (storyboards, spreadsheet summary of results) for phase reviews and management updates.

Objectives of this lecture: to learn to define and describe the stages of team evolution such as storming, norming, performing, and defining the six sigma roles and responsibilities.

Understand the responsibilities of 6 major six sigma roles.

Learn and understand various management and planning tools.

Learn and understand various management and planning tools.

Learn and understand various management and planning tools.

Learn and understand various management and planning tools.

Objectives of this lecture: define and describe FMEA, describing the purpose and use of scale criteria and calculating the Risk Priority Number (RPN).

Calculate process performance metrics such as defects per unit (DPU), rolled throughput yield (RTY), cost of poor quality (CoPQ), defects per million opportunities (DPMO).

Calculate process performance metrics such as defects per unit (DPU), rolled throughput yield (RTY), cost of poor quality (CoPQ), defects per million opportunities (DPMO).

Calculate process performance metrics such as defects per unit (DPU), rolled throughput yield (RTY), cost of poor quality (CoPQ), defects per million opportunities (DPMO).

Develop process maps and review written procedures, work instructions, and flowcharts to identify any gaps or areas of the process that are misaligned.

Develop process maps and review written procedures, work instructions, and flowcharts to identify any gaps or areas of the process that are misaligned.

Develop process maps and review written procedures, work instructions, and flowcharts to identify any gaps or areas of the process that are misaligned.

Objectives of this lecture: to learn to define central limit theorem and sampling distribution of means.

Develop process maps and review written procedures, work instructions, and flowcharts to identify any gaps or areas of the process that are misaligned.

Objectives of this lecture: to identify and classify continuous data and discrete data, measurement scales such as ratio, interval, nominal and ordinal scales and data collection methods.

Recording of one of the live sessions by faculty, explaining about the basic statistics.  Helpful for more insights.

Understand the difference between a population parameter and sample statistic.

Identify and use basic probability concepts: independent events, mutually exclusive events, multiplication rules, permutations, and combinations.

Identify and use basic probability concepts: independent events, mutually exclusive events, multiplication rules, permutations, and combinations.

Identify and classify continuous (variables) and discrete (attributes) data. Describe and define nominal, ordinal, interval, and ratio measurement scales.

Define and apply various sampling methods (random and stratified) and data collection methods

Define, calculate, and interpret measures of dispersion and central tendency. Develop and interpret frequency distributions and cumulative frequency distributions.

Recording of one of the live sessions.  Will help you to understand basics like mean, variance and standard deviation.

Define, calculate, and interpret measures of dispersion and central tendency. Develop and interpret frequency distributions and cumulative frequency distributions.

Define the central limit theorem and describe its significance in relation to confidence intervals, hypothesis testing, and control charts.

Construct and interpret diagrams and charts that are designed to communicate numerical analysis efficiently, including scatter diagrams, normal probability plots, histograms, stem-and-leaf plots, box-and-whisker plots.

Construct and interpret diagrams and charts that are designed to communicate numerical analysis efficiently, including scatter diagrams, normal probability plots, histograms, stem-and-leaf plots, box-and-whisker plots.

Construct and interpret diagrams and charts that are designed to communicate numerical analysis efficiently, including scatter diagrams, normal probability plots, histograms, stem-and-leaf plots, box-and-whisker plots.

Construct and interpret diagrams and charts that are designed to communicate numerical analysis efficiently, including scatter diagrams, normal probability plots, histograms, stem-and-leaf plots, box-and-whisker plots.

Explains how to graphically summarize a set of data with the help of Minita. You may download Minitab trail version from its official website for practice.

Understand Pareto analysis and identify the vital few contributors

Understand Pareto analysis and identify the vital few contributors

Define and describe various distributions as they apply to statistical process control and probability: normal, binomial, Poisson, chi-square, Student’s t, and F.

Define and describe various distributions as they apply to statistical process control and probability: normal, binomial, Poisson, chi-square, Student’s t, and F.

Define and describe various distributions as they apply to statistical process control and probability: normal, binomial, Poisson, chi-square, Student’s t, and F.

Define and describe various distributions as they apply to statistical process control and probability: normal, binomial, Poisson, chi-square, Student’s t, and F.

Understanding normal distribution in Minitab

Define and describe various distributions as they apply to statistical process control and probability: normal, binomial, Poisson, chi-square, Student’s t, and F.

Calculate, analyze, and interpret measurement system capability using gauge repeatability and reproducibility (GR&R) studies.

Define, describe, and conduct process capability studies, including identifying characteristics, specifications, and tolerances, and verifying stability and normality.

Define, describe, and conduct process capability studies, including identifying characteristics, specifications, and tolerances, and verifying stability and normality.

Describe the relationship between these types of indices. Define, select, and calculate process capability and process performance. Describe when Cpm measures can be used.

Describe the relationship between these types of indices. Define, select, and calculate process capability and process performance.

Process capability Minitab

Select appropriate sampling plans to create multi-vari study charts and interpret the results for positional, cyclical, and temporal variation.

Select appropriate sampling plans to create multi-vari study charts and interpret the results for positional, cyclical, and temporal variation.

Calculate the correlation coefficient and linear regression and interpret the results in terms of statistical significance (p-value). Use regression models for estimation and prediction.

Recording of live sessions - Correlation, regression in Minitab

Objectives of this lecture: to learn to define one way ANOVA, Chi-square test and interpreting the result.

Distinguish between statistical and practical significance. Determine appropriate sample sizes and develop tests for significance level, power, and type I and type II errors.

Conduct hypothesis tests to compare means, variances, and proportions (paired-comparison t-test, F-test, analysis of variance [ANOVA], chi-square) and interpret the results.

Conduct hypothesis tests to compare means, variances, and proportions (paired-comparison t-test, F-test, analysis of variance [ANOVA], chi-square) and interpret the results.

Conduct hypothesis tests to compare means, variances, and proportions (paired-comparison t-test, F-test, analysis of variance [ANOVA], chi-square) and interpret the results.

Conduct hypothesis tests to compare means, variances, and proportions (paired-comparison t-test, F-test, analysis of variance [ANOVA], chi square) and interpret the results.

Learn to define and describe basic Design of Experiment (DOE) terms and to interpret the main effects and interaction plots.

Define and describe terms such as independent and dependent variables, factors and levels, responses, treatments, errors, repetition.

Interpret main effects analysis and interaction plots.

Select and apply tools and techniques for eliminating or preventing waste, including pull systems, kanban, 5S, standard work, and poka-yoke.

Describe the theory and objectives of SPC, including measuring and monitoring process performance for both continuous and discrete data. Define and distinguish between common and special cause variation and how these conditions can be deduced from control chart analysis.

Describe the theory and objectives of SPC, including measuring and monitoring process performance for both continuous and discrete data. Define and distinguish between common and special cause variation and how these conditions can be deduced from control chart analysis.

Describe the theory and objectives of SPC, including measuring and monitoring process performance for both continuous and discrete data. Define and distinguish between common and special cause variation and how these conditions can be deduced from control chart analysis.

Identify, select, construct, and use control charts: X-R, X-s, individual and moving range (IMR or XMR), median, p, np, c, and u.

Identify, select, construct, and use control charts: X-R, X-s, individual and moving range (IMR or XMR), median, p, np, c, and u.

Identify, select, construct, and use control charts: X-R, X-s, individual and moving range (IMR or XMR), median, p, np, c, and u.

Define and distinguish between common and special cause variation and how these conditions can be deduced from control chart analysis.

Assist in developing and implementing a control plan to document and monitor the process and maintain the improvements.