Design of Experiments
Learn Design of Experiments (DOE)
Design of Experiments (DOE) is a statistical methodology that can be used for general problem-solving, improving or optimizing product designs and manufacturing processes. The Design of Experiments training course begins with the fundamentals of experimental design methods and continues with advanced concepts and principles in the application of DOE for the reliability engineer.
Software used
You will use ReliaSoft Weibull++ software and other ReliaSoft products with hands-on practice and through case studies to learn experiment design concepts and analysis methods.
Design of Experiments (DOE) is a statistical methodology that can be used for general problem-solving, improving or optimizing product designs and manufacturing processes. The Design of Experiments training course begins with the fundamentals of experimental design methods and continues with advanced concepts and principles in the application of DOE for the reliability engineer.
Software used
You will use ReliaSoft Weibull++ software and other ReliaSoft products with hands-on practice and through case studies to learn experiment design concepts and analysis methods.
Learning objectives
- Understand what a DOE is and how to create, execute and interpret the results
- Design experiments that are effective for studying the factors that may affect a product or process
- Analyze experimental results to identify the significant factors and evaluate ways to improve and optimize the design
- Go beyond traditional DOE techniques to apply the proper analysis treatment for the response information that is often of interest to reliability engineers — product lifetime data
Topics included
- Introduction to Design of Experiments (DOE)
- Full factorial designs
- Two level fractional factorial designs
- Robust engineering designs
- Response surface methodology
- Reliability DOE
Who should attend
The Design of Experiments course is for product, process or maintenance professionals that have a need to conduct experimental studies as part of their design, development or improvement efforts to understand critical factors using the most efficient and effective analytical methods.