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Course Description

Data collection plays a very important role in Six Sigma projects. Continuous improvement teams gather and validate data or facts before they are able to act on business problems and opportunities. This one-day course is based on the Measure Phase of the DMAIC framework and is the third of six courses designed to prepare individuals to conduct continuous improvement work in their organizations. The purpose of this course is to help students familiarize themselves with the expectations, tools, concepts, and deliverables of the Six Sigma Measure Phase. Students will also explore different data collection methods as well as measurement systems and the statistical methods used in Six Sigma.

Course Details

By completion of this course, successful students will be able to:

  • Identify the types of statistical methods used in Lean Six Sigma projects
  • Describe the various data types and the difference between populations and samples
  • Explain common cause and special cause variations
  • Describe control charts for continuous and attribute data
  • Examine process capability, analysis and documentation tools, and explore how these tool are used within the measure phase and to understand customer requirements
  • Recognize high-level activities that can be used to improve process capability
  • Examine data types, measurement scales, and various sampling (random and stratified) and data collection methods
  • Employ basic probability concepts and describe various distributions as they apply to statistical process control and probability
  • Identify Measurement System Analysis (MSA) methods and quantify the impact of MSA variation on the precision of reported continuous and attribute data
  • Design, run, and interpret a measurement system study
  • Evaluate process performance metrics, process capability studies and their relationships

Notes

Students are strongly encouraged to take these courses in an order based on the DMAIC framework starting with PDS 243 Business Execution Systems; however, this is not required.

Prerequisites

None
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