Design of experiments (DOE) should be used during which of the following processes?
A. Perform Quality Assurance
B. Total Quality Management
C. Perform Quality Control
D. Plan Quality Management
Correct Answer: D
Explanation/Reference:
Explanation:
Process: 8.1 Plan Quality Management
Definition: The process of identifying quality requirements and/or standards for the project and its deliverables, and documenting how the project will demonstrate compliance with relevant quality requirements and/or standards.
Key Benefit: The key benefit of this process is that it provides guidance and direction on how quality will be managed and validated throughout the project.
Inputs
1.Project management plan
2.Stakeholder register
3.Risk register
4.Requirements documentation
5.Enterprise environmental factors
6.Organizational process assets
Tools & Techniques
1.Cost-benefit analysis
2.Cost of quality
3.Seven basic quality tools
4.Benchmarking
5.Design of experiments
6.Statistical sampling
7.Additional quality planning tools
8.Meetings
Outputs
1.Quality management plan
2.Process improvement plan
3.Quality metrics
4.Quality checklists
5.Project documents updates
8.1.2.5 Design of Experiments
Design of experiments (DOE) is a statistical method for identifying which factors may influence specific variables of a product or process under development or in production. DOE may be used during the Plan Quality Management process to determine the number and type of tests and their impact on cost of quality.
DOE also plays a role in optimizing products or processes. DOE is used to reduce the sensitivity of product performance to sources of variations caused by environmental or manufacturing differences. One important aspect of this technique is that it provides a statistical framework for systematically changing all of the important factors, rather than changing the factors one at a time. Analysis of the experimental data should provide the optimal conditions for the product or process, highlight the factors that influence the results, and reveal the presence of interactions and synergy among the factors. For example, automotive designers use this technique to determine which combination of suspension and tires will produce the most desirable ride characteristics at a reasonable cost.
Explanation/Reference:
Explanation:
Process: 8.1 Plan Quality Management
Definition: The process of identifying quality requirements and/or standards for the project and its deliverables, and documenting how the project will demonstrate compliance with relevant quality requirements and/or standards.
Key Benefit: The key benefit of this process is that it provides guidance and direction on how quality will be managed and validated throughout the project.
Inputs
1.Project management plan
2.Stakeholder register
3.Risk register
4.Requirements documentation
5.Enterprise environmental factors
6.Organizational process assets
Tools & Techniques
1.Cost-benefit analysis
2.Cost of quality
3.Seven basic quality tools
4.Benchmarking
5.Design of experiments
6.Statistical sampling
7.Additional quality planning tools
8.Meetings
Outputs
1.Quality management plan
2.Process improvement plan
3.Quality metrics
4.Quality checklists
5.Project documents updates
8.1.2.5 Design of Experiments
Design of experiments (DOE) is a statistical method for identifying which factors may influence specific variables of a product or process under development or in production. DOE may be used during the Plan Quality Management process to determine the number and type of tests and their impact on cost of quality.
DOE also plays a role in optimizing products or processes. DOE is used to reduce the sensitivity of product performance to sources of variations caused by environmental or manufacturing differences. One important aspect of this technique is that it provides a statistical framework for systematically changing all of the important factors, rather than changing the factors one at a time. Analysis of the experimental data should provide the optimal conditions for the product or process, highlight the factors that influence the results, and reveal the presence of interactions and synergy among the factors. For example, automotive designers use this technique to determine which combination of suspension and tires will produce the most desirable ride characteristics at a reasonable cost.
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