Learn how to use selection matrices such as the criteria selection matrix and Pugh matrix. Learn to use the criteria selection matrix when evaluating and scoring based on a 1 to 10 scale, or a numerical scale. Learn how to use the Pugh matrix when alternatives are compared to baselines.
- Deciding which car to buy can be a gut-wrenching decision.…Some may value fuel economy,…off-road capability,…or storage capacity,…while others may want high speed performance…and creature comforts like air condition,…perforated leather seats.…When buying a car, you have to decide what criteria…should be used to make the best choice.…Which ones carry more weight.…And how does each alternative stack up against each other?…Similarly, in the improved phase of Six Sigma projects,…after the project team has generated…and developed solution alternatives,…to address proven access,…the next step is to evaluate and select…the best solution steps.…
Fortunately, there are tools and techniques…for such an evaluation,…including two very popular ones.…The Criteria Selection Matrix…and the Pugh Concept Selection Method.…Both are qualitative evaluation techniques…that use the collective expertise and experience…of subject matter experts.…So it's important to involve subject matter experts…and key management stakeholders in this evaluation.…
Dr. Richard Chua builds upon his Six Sigma Foundations and Learning Minitab courses, and covers an array of topics, including measurement system analysis, descriptive statistics, hypothesis testing, design of experiments, statistical process control, and more.
Lynda.com is a PMI Registered Education Provider. This course qualifies for professional development units (PDUs). To view the activity and PDU details for this course, click here.
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- Six Sigma and the organization
- Collecting the voice of the customer
- Project management basics
- Process maps
- Sampling in data collection
- Measurement system analysis
- Measuring performance using descriptive statistics
- Process performance measures
- Hypothesis testing
- Testing for means, variances, proportions, and independence
- Correlation and regression
- Using selection matrices
- Using failure modes and effects analysis
- Developing control plans
- Statistical process control