Design of Experiments (DOE) has been one of the most powerful tools to evaluate and quantify contribution of various input factors on output or response. The technique was developed by Ronald Fisher for improving agricultural yield. Conventional experimentation is done with only one factor at a time (OFAT). In Statistically Designed Experiments (SDE), the idea is to minimize cost and efforts of the experimentation but still obtain maximum information about a process. Objective of DOE is ‘Test Less and learn More’.
Who could join?
The course is most appropriate for engineers and managers responsible for
• Process design and optimization
• Product Design and Development
• Quality Improvement
• Reliability Engineers
• Production Engineers
• Supplier Improvement
• Others responsible for improving performance
Training Agenda:
• Introduction and expectations of participants
• One Factor at a Time Approach to experimentation and its limitations
• Introduction to Designed Experiments
• 2-Factor 2-Level (22) Experiment and its analysis
• 2k experiments
o Calculation of main effects and interactions
o Plotting Main Effects and Interactions
• Examples of 2k Full Factorial Experiments
• Introduction to Fractional Factorial Experiments
o Resolution of Experiment
o Confounding or Aliasing
o Examples of Fractional Factorial Experiments
• Introduction to Robust Design
• Quiz