Six Sigma: Define and Measure

This module introduces the fundamentals of Six Sigma methodology and the DMAIC process improvement cycle, covering the cost of quality, the difference between defects and defectives, and how to calculate process yield including DPMO (Defects Per Million Opportunities)

This module focuses on understanding customer expectations using the Kano Model for quality characteristics categorization, and teaches how to initiate a Six Sigma project by defining the problem and creating a Project Charter

This module covers essential probability distributions used in quality engineering, including Binomial, Poisson, and Exponential distributions, along with descriptive statistics for effective project result communication

This module explores the characteristics of the Normal Distribution, the use of Standard Normal for probability calculations, and the Central Limit Theorem's application in sampling theory

This module covers various process mapping techniques including SIPOC and Value Stream Mapping, and teaches how to identify Critical-to-Quality characteristics for Six Sigma projects

This module teaches the fundamentals of Measurement Theory and Sampling Plans, including precision, accuracy, linearity, bias, stability, and Gage Repeatability & Reproducibility

This module introduces Process Capability and the metrics CP/CPK for establishing baseline process performance measurements

This module covers Tolerance Design and risk assessment using Failure Mode and Effects Analysis (FMEA), concluding with a comprehensive review of the Six Sigma Roadmap