This course is to make individual understanding of the beauty of Design of Experiment methodology that can be effectively identified which process factors affect output to achieve optimization. It help to minimize the many variables changed in a planned manner in order to come out with the most optimal values for such variable thereby saving time and cost. Individual will experience setting up, running, and analysing the results of simple-to-intermediate complexity, Full Factorial and Partial Factorial experiments utilizing a hands-on computer tool that facilitates experimental design and data analysis. This course will also include the use of the Minitab™ software tool for analysing data.
Duration: 2 Days (16 Hours)
Course Content:
- Introduction to and preparation of DOE
- What is and why conduct DOE?
- Type of experiment
- Review basic statistical tools
- Planning for effective experiment
- Steps of DOE
- Concept of replication, randomization, blocking, center point
- Full Factorial
- 2K factorial
- DOE roadmap
- Factor, level and response
- Main, interaction, contour, surface and cube plot
- Case studying
- Factional Factorial
- Screening design
- Alias relationship
- Design resolution
- Saturated design
- Case studying
- DOE success factors