Overview

This measuring and analyzing process performance training develops strong skills in defining, measuring, and analysing processes to enable accurate, data-driven improvement. You learn the Measure phase and key tools such as SIPOC, process maps, cause-and-effect analysis, Value Stream Mapping, and FMEA to identify risks and performance gaps. The course also covers Six Sigma statistics, Measurement System Analysis, and process capability techniques to assess variation, reliability, and short- and long-term performance, enabling confident, evidence-based improvement decisions. By the end of this course, you will be able to: - Apply Measure Phase Tools: Define, map, and analyse processes using SIPOC, process maps, and risk analysis tools - Use Six Sigma Statistics: Analyse data using basic metrics, charts, and distributions - Validate Measurement Systems: Assess data accuracy and reliability using MSA, Gage R&R, and attribute studies - Assess Process Capability: Evaluate process performance and variation to support improvement decisions No prior advanced statistical knowledge required; ideal for professionals looking to strengthen measurement, analysis, and data-driven improvement skills in Lean Six Sigma projects.

Syllabus

Process Definition

Explore the Six Sigma Measure phase to define, map, and analyse processes. Learn Measure phase objectives and tools to document processes effectively. Create cause-and-effect and fishbone diagrams, build process maps at multiple levels, and use SIPOC for end-to-end visibility. Apply Value Stream Maps, X-Y diagrams, and FMEA to identify risks, relationships, and performance gaps, enabling accurate measurement and data-driven improvement.

Six Sigma Statistics

Explore Six Sigma statistics to build a foundation in data and measurement. Learn data types, measurement scales, basic statistics, and measures of central tendency and dispersion. Use graphical analysis tools such as box plots and time series plots with practical Minitab demos. Understand normal and standard normal distributions, perform normality tests, and interpret results to support accurate, data-driven decisions.

Measurement System Analysis

Explore Measurement System Analysis to evaluate the accuracy and reliability of data in Six Sigma projects. Learn MSA fundamentals, measurement errors, and sources of variation. Assess repeatability, reproducibility, accuracy, bias, stability, and linearity. Perform MSA studies using Gage R&R and Attribute Agreement Analysis, with practical demonstrations for continuous and attribute data, to ensure measurement systems support valid analysis and confident decision-making.

Process Capability

Explore Process Capability to assess how well processes meet performance requirements. Learn process capability concepts, data types, and how to establish reliable performance baselines. Understand components of variation and process stability. Apply process capability indices and perform capability analysis using continuous and attribute data, including DPU, DPMO, and sigma levels. Evaluate short- and long-term process performance to drive data-driven improvement decisions.