QUltima Lean Six Sigma Black Belt Course Contents

Key “take away”

  • Basic Statistics – 5 Steps and the significance of statistics in fundamental analysis using various distributions including hyper-geometric, bivariate, exponential, lognormal and weibull (Minitab based)
  • Introduction to Six Sigma – its history and present perspective
  • Key Steps in Problem Solving and advent of DMAIC, LEAN, DFSS.
  • Leadership – Leadership responsibilities, organizational road blocks, change management, complementing six sigma with other methodologies; and roles and responsibility for six sigma.
  • Organizational Performance Measures – Stakeholders, CTXs, benchmarking, balanced organizational objectives, financial measures of organizational success and project success.
  • Team Management – Team formation including team types & constraints; team roles, team member selections; and launching teams. Team Facilitation including team motivation, team stages, team communication, team dynamics, time management of teams, team decision making tools, management and planning tools; and team performance evaluation and awards.
  • Understanding Money – Financial Aspects of the organization and Six Sigma.
  • Project Management (Critical Path Method), Team Dynamics and Process Understanding
  • Define Phase – Voice of Customer including customer identification, customer feedback analysis and deciding customer requirements. Problem definition, Six Sigma Metric, base lining, time series analysis, improvement potential estimates, team selection, tracking project progress and basics of data analysis (data types, location, variation, distribution). Fundamentals of Value Stream and using it for project pipeline development.
  • Measure Phase – Data collection strategies, CLT, MSA, Metrology, measurement system for marketing, sales, engineering, research, technology etc., capability analysis (normal and non-normal both, including transformations), identification product /process variables using multiple methods, Using Waste Analysis for immediate improvements, high & level prioritization (Cause & Effect Matrix) of impacting variables
  • Analyze Phase – Detailed variable analysis using FMEA, Action planning for immediate gains, Data interpretation using various graphical analysis, correlation / regression, Hypothesis testing, goodness of fit, contingency tables, non-parametric tests avoiding analysis paralysis. Using appropriate sampling methods and sample size.
  • Improve Phase – Validating highest impacting variables, Design of Experiments (2k, Full Factorial), Optimal Solution Identification. SMED techniques for cycle time reduction, kaizen blitz, Theory of constraints, implementation plan and risk analysis.
  • Control Phase – Various Strategies of process control, Control Plan design, Training teams for new control plans, SPC, error proofing etc. Introducing Lean tools like standard work, 5S, TPM, Visual Management, Kanban etc. for better control. Project to Process Transition.
  • Sustain Results – managing lessons learned; training plan deployment; managing documentation; setting up systems for on-going evaluation.
  • Fundamentals of DFSS (Design for Six Sigma) – commonly used methodologies for DFSS, Design for X (DFX), robust design processes, strategic and tactical design tools.

Who Should Attend”

  • Must Certification for all aspiring career in Six Sigma (Green Belt / Black Belt / Master Black Belt)
  • Middle and Senior Management Team
  • Must for those heading functions of technology, research and engineering responsible for setting specification limits and design of new product / processes as basic requirement.
  • Quality Team, Management Representative and key people involved in improvement
  • For those who want to learn & use tools and certification is just a bi-product.

Day Wise Agenda

Module 1: DEFINE & PREPARE

Day 1

DATA ANALYSIS FUNDAMENTALS (Not needed if already a Yellow Belt or Green Belt)

  • Basic Statistics – 5 steps with the concept and application
  • Types of Data – Discrete (Nominal, Ordinal) and Continuous (Interval & Ratio)
  • Location / Central tendency of Data (Mean, Median, Mode)*
  • Spread of Data – Range, Variance, Standard Deviation & COV*
  • Shape of Data and Predictions – Histogram, Distributions, Normal Distribution, probability calculations*
  • Non-normal Distributions – Exponential, Gamma, Binomial, Poisson, Hyper-geometric, Lognormal, Weibull etc.
  • Introduction to Minitab* – a statistical software

Day 2

SIX SIGMA OVERVIEW (Not needed if already a Yellow Belt or Green Belt))

  • History of Quality and Need of Six Sigma, What is Six Sigma – Various approaches merging into concept
  • Cost of Quality
  • Futility of Inspection, Successful and not so successful stories of Six Sigma, Who ultimately gains by Six Sigma initiative.
  • Problem Solving Techniques, Developing an eye for Improvement Opportunities (Problems)
  • Various methodologies of Six Sigma (DFSS, DMAIC, LEAN) and understanding various steps in each.
  • Understanding Team Roles and challenges as member, Leader and facilitator

Day 3

LEADERSHIP QUALITIES FOR A BLACK BELT
Part 1

  • Enterprise Leadership Responsibilities – Responsibilities of executive leaders, role in six sigma deployment by providing resources, managing change, communication etc.
  • Organizational Road Blocks – impact of cultures, organization structure, resource priorities, management support etc. & techniques to overcome.
  • Change Management – techniques to understand and facilitate change
  • Team Formation – Types of teams (e.g., formal, informal, virtual, cross-functional, self-directed, etc.), and which one will work best under constraints.
  • Team Facilitation – team motivation, team stages, team communication, team dynamics, time management of teams, team decision making tools, management and planning tools; and team performance Evaluation and Award

Day 4

LEADERSHIP QUALITIES FOR A BLACK BELT
Part 2

  • Six Sigma Complements – understand other improvement initiatives and how six sigma complements with them especially Lean
  • Six Sigma Roles & Responsibilities – Deployment Leaders, Champions, MBB, BB, GB, YB etc.
    Organizational Financial Performance and Impact of Six Sigma Projects. Understanding Balance Sheet, Profit & Loss and Fund Flow.
  • Organizational Performance Measures – Stakeholders, CTXs, benchmarking, balanced organizational objectives, financial measures of organizational success and project success.
  • Project Management for Six Sigma Projects (Critical Path Method, Analysis and tracking)
  • Basic Process Management and important issues for Six Sigma Projects
  • Using VSM approach for focused project identification.

Day 5

DEFINE PHASE (Not needed if already a Yellow Belt or Green Belt)

  • Voice of Customers – segments of customer for project, customer feedback analysis, understanding customer requirements.
  • Six Sigma Metrics (Business, Primary, Negative consequence, Financial)
  • Scoping Down Tools (Macro Map, VSM, Tree Diagram, Pareto Analysis*)
  • Base lining the performance, Time series analysis* and target setting, Improvement potential estimates
  • Problem definition, objective statements, metric and milestone tracking

Module 2: MEASURE & INITIATING ANALYSE

Day 6

MEASURE PHASE – Part 1 (Not needed if already a Yellow Belt or Green Belt)

  • Metrology – Different type of measurement system in manufacturing, marketing, sales, engineering, research, technology etc.,
  • Data Collection Methods – Check sheets and other data sheets, development of data collection sheets using minitab*
  • Accuracy and Precision – definition and types, calibration and need for linkage to NPL. GRR and attribute agreement study introductions.
  • Measurement System Analysis (MSA) for variable data* –terms, definitions and class room exercise. Live
  • Exercise with data collection, calculation and improvement plans.

Day 7

MEASURE PHASE – Part 2 (Not needed if already a Yellow Belt or Green Belt)

  • Measurement System Analysis (MSA) for attribute data* –terms, definitions and class room exercise. Live Exercise with data collection, calculation and improvement plans
  • Process Specification and Control Limits – demystifying the confusions for both discrete and variable data.
  • Process Capability – Basic Definitions. Short term and long term capabilities. Differentiating capability from performance, (Cp, Zst, Cpk and Pp, Zlt, Ppk)*
  • Capability analysis and interpretation for improvement* for both normal and non-normal data.
  • Transformations for Capability Analysis.

Day 8

MEASURE PHASE – Part 3

  • Process Definition and its elements including performance and control measures. Differentiating leading / lagging and efficiency / effectiveness.
  • Process Management and related documents.
  • Identification product /process variables using Ishikawa Diagram, PFD diagnosis technique, KPIV / KPOV Matrix
  • Class exercise on Variable identification through Ishikawa diagram and PFD on standard template

Day 9

MEASURE PHASE – Part 4

  • 7 types of Wastes for immediate improvements. Class exercise for identifying waste. Hidden Factories for enabling process adherence.
  • High & level prioritization (Cause & Effect Matrix) of impacting variables. Using one and multiple Ys.
  • Project Management – Updating targets and revalidation of financials, project evaluation requirements, mile stone review, updating project tracker and report preparation till measure phase

Day 10

ANALYZE PHASE – PART 1 (Not needed if already a Yellow Belt or Green Belt)

  • Detailed variable analysis using FMEA, Design of severity, occurrence and detection scales
  • Action planning for immediate gains, Tips for small project selection and dividing among team
  • Class Exercise for Actual usage of FMEA on standard template.

Module 3: ANALYSE

Day 11

ANALYZE PHASE – PART 2

  • FMEA Review and clarifications for gaps in understanding (Clarity Module)
  • Sampling Methods – random sampling, stratified sampling, systematic sampling, etc. ensuring consideration of representative selection, homogeneity, bias, etc.
  • Data interpretation using various graphical analysis (box plots, main effect, scatter diagram, multivari charts etc.)*
  • Central Limit Theorem (CLT) along with its applications in measurement systems, control charts and hypothesis testing*
  • Confidence Intervals – concept, manual calculations and minitab based calculations, application of concept*. Distinguish from Prediction Intervals.

Day 12

ANALYZE PHASE – PART 3 (Not needed if already a Yellow Belt or Green Belt)

  • Correlation and Regression* – development of concept, manual and minitab based calculations, implementation of concept
  • Introduction to Hypothesis testing along with risks (alpha and beta)*.
  • Sample Size Calculations for different tests
  • Test of Means* – concept, calculations, understanding of p-value and comparison with α (risk understanding)
    • 1 sample Z,
    • 1 sample t,
    • 2 sample t,
    • Paired t &
    • ANOVA

Day 13

ANALYZE PHASE – PART 4

  • Test of Variations (1 Variance, 2 variance)*
  • Test of Proportions (1 Proportion, 2 Proportion and ANOM)*
  • Use and interpret multivariate tools such as principal components, factor analysis, discriminant analysis, multiple analysis of variance (MANOVA), etc., to investigate sources of variation
  • Analyze attributes data using logit, probit, logistic regression, etc., to investigate sources of variation.

Day 14

ANALYZE PHASE – PART 5

  • Goodness-of-fit (chi square) tests – Define, select, and interpret the results of these tests.
  • Contingency tables – Select, develop, and use contingency tables to determine statistical significance
  • Nonparametric tests – Select, develop, and use various nonparametric tests, including Mood’s Median, Levene’s test, Kruskal-Wallis, Mann-Whitney, etc.
  • Conclusion – Decision tree for the appropriate tool and its application.

Day 15

ANALYZE PHASE – PART 6

  • ANOVA Basic definitions – response, factors, levels, within and between variations, error, SS, MS, F-distribution etc.
  • ANOVA – Analysis, understanding its table, interpreting analysis and concept application along with class exercise*
  • Project Management – Updating project metric, evaluation of initial savings, mile stone review, updating project tracker and report preparation till Analyze phase

Module 4: IMPROVE AND CONTROL

Day 16

IMPROVE PHASE – Part 1 (Not needed if already a Yellow Belt or Green Belt)

  • ANOVA Review and clarifications for gaps in understanding (Clarity Module)
  • DOE Basic Definitions – independent and dependent variables, factors and levels, response, treatment, error
  • DOE Principles – power and sample size, balance, repetition, replication, order, efficiency, randomization, blocking, interaction, confounding, resolution, etc.
  • Planning experiments – Plan, organize, and evaluate experiments by determining the objective, selecting factors, responses, and measurement methods, choosing the appropriate design, etc
  • One-factor experiments – Design and conduct completely randomized, randomized block, and Latin square designs, and evaluate their results.
  • Full Factorial Designs – Fundamentals of Full Factorial Design. General Liner Model and understanding how to Reduce Models by eliminating insignificant terms*

Day 17

IMPROVE PHASE – Part 2

  • 2k Full Factorial – Design, Analysis, writing equation, Optimization*
  • 2k Factorial with Centre Points and Blocking – Understanding Curvature and model modification for significant blocks.
  • 2k Fractional Factorial – Design, analyze, and interpret these types of experiments, and describe how confounding affects their use
  • Statapult Exercise (Part A)*
    • Understanding Statapult
    • Setting Up Measurement System for Y.
    • Defining variables and Blocks in Statapult
    • Doing Hypothesis tests and setting levels
    • Setting up “Design of Experiments (2k Fractional Factorial)”
    • Screen out insignificant Factors

Day 18

IMPROVE PHASE – Part 3

  • Statapult Exercise (Part B)*
    • Conduct Balance Experiments (2k for balance parameters)
    • Develop equation, run optimizer for target distance with minimum variation.
    • Tournament 1 – Capability of team members to hit target.
  • Multiple Regression* – simple and multiple linear regression models, multi-factor models, multiple binary logistic regression (Optional)
  • Response Surface Designs* – Central Composite and Box Behnken Designs
  • Best settings – pros and cons, future optimizations

Day 19

IMPROVE PHASE – Part 4

  • Solution identification and short listing
  • SMED (Single Minute Exchange of Die) technique for quick change over
  • Theory of Constraints and its applications
  • Project Management – Updating project metric & savings, mile stone review, updating project tracker and report preparation till Improve phase

CONTROL PHASE – Part 1

  • Various Strategies of process control – Type 1, Type 2, Type 2 – SPC, Type – 3, SOP, Warning. Choosing the right control for specific situations.
  • Control Plan design – 10 step methodology of developing control plan. Importance of decision rule
  • Control Plan Exercise – Developing Control Plan using standard template

Day 20

CONTROL PHASE – Part 2 (Not needed if already a Yellow Belt or Green Belt)

  • Statistical Process Control (SPC) – Introduction, sporadic or chronic causes, concept of control charts and choosing the appropriate one based on type of data and sample size.
  • Statistical Process Control (SPC) for Variable Data* – Rational sub-grouping, calculating control limits, test for assignable / special causes. Live exercise for identifying special causes.
  • Statistical Process Control (SPC) for Discrete Data* – Sampling, calculating control limits, test for assignable / special causes. Live exercise for identifying special causes.
  • Mistake Proofing – Techniques of developing Mistake Proof devices. Types of sensors.
  • Lean Tools for better control viz. standard work, 5S, TPM, Visual Management, Kanban etc.
  • Training process teams for new control plans, controls and other key changes
  • Sustain Results – managing lessons learned; training plan deployment; managing documentation; setting up systems for on-going evaluation, Project to Process Transition
  • Conclusion and next methodology called DFSS – commonly used methodologies for DFSS, Design for X (DFX), robust design processes, strategic and tactical design tools

Note –

  • * Indicates minitab is needed during training.
  • Only 10 days are needed for Black Belt Training, if already a Six Sigma Green Belt.

Prior Knowledge Requirement

  • Prior exposure to improvement projects of any kind is useful.
  • Six Sigma Yellow Belt / Green Belt Certification or equivalent knowledge helps.