✅Module-1: SIX SIGMA AND THE ORGANIZATION
Value of Six Sigma: Recognize why organizations use Six Sigma, History of Six Sigma. Juran, Deming, Shewhart, Ishikawa’s philosophy of Quality
Organizational goals and Six Sigma projects: Describe how Lean Six Sigma projects influence the organization as a whole.
Organizational drivers and metrics: Profit, market share, customer satisfaction, efficiency, product differentiation. Balanced Scorecard.
Lean Principles in the Organization
Value chain, flow, 7 wastes, and 3Ms
Design for Six Sigma (DFSS): Distinguish between DMADV (define, measure, analyze, design, verify) and IDOV (identify, design, optimize, verify), and recognize how they align with DMAIC.
✅Module-2: DEFINE PHASE
Project Identification: Project Selection Process, Stakeholder analysis, Voice of Customer, Voice of Business, Cost of Poor Quality, CTQ Tree, Project Charter, SIPOC.
Team Management: Communication Plan, Team stages and dynamics, Team roles and responsibilities, Brainstorming, NGT, Multi-voting
Management & Planning Tools: affinity diagrams, interrelationship diagrams, tree diagrams, prioritization matrices, matrix diagrams, process decision program charts (PDPC), and activity network diagrams
✅Module-3: MEASURE PHASE
Basic Statistics: Basic statistical terms, Central limit theorem, Descriptive & Inferential statistics, Statistical Distributions, Central Limit Theorem
Probability: Identify and use basic probability concepts: independent events, mutually exclusive events, multiplication rules, permutations, and combinations
Process Characteristics: Process flow metrics, Process analysis tools
Data Collection: Types of data, Measurement scales, Sampling, Data collection plans, and methods
Measurement system analysis (MSA): Bias, Linearity, Stability, Gage R&R, P/T Ratio
Process Capability: Cp, Cpk, Pp, Ppk, DPMO, PPM, Process performance vs. specification, Short-term and long-term capability
✅Module-4: ANALYZE PHASE
Measuring and Modeling Relationships Between Variables: The correlation coefficient, Linear regression
Hypothesis Testing: Terminology, Statistical vs. practical significance, Sample size, Tests for means, variances, and proportions, Analysis of variance (ANOVA), Goodness-of-fit (chi-square) tests
Failure Mode and Effects Analysis (FMEA): PFMEA and DFMEA
Other Analysis Tools: Why-Why Analysis, Root Cause Analysis, Waste Analysis
✅Module-5: IMPROVE PHASE
Design of Experiments:
Basic terms, Main effect, and Interaction effect plots.
Lean Tools for Waste Elimination:
5S Kanban, Standard work, Continuous flow, Kaizen, SMED, Pilot & Implementation
✅Module-6: CONTROL PHASE
Statistical Process Control (SPC) Basics:
Objectives, Selection of variables, Rational subgrouping, Control chart selection, and Control chart analysis.
Other Controls: Control plan, TPM, Poka Yoke, Visual controls.
Documentation: Lessons learned, Training for process owners and staff, Ongoing evaluation
