Experimental design is the science of ensuring we get the most information from an experiment at the least cost. Well-chosen experimental designs maximize the amount of “information" that can be obtained for a given amount of experimental effort. This course will teach you how to design and implement experiments to receive the maximum amount of unbiased information regarding factors affecting a production process at the lowest cost.
This course is part of the Industrial Engineering Professional Skills Certificate Program. Learn more about IIE certificate programs and how you can save by paying in advance for all of the courses included in a program.
Class Schedule:
| Course ID | Course Dates | Location | Register |
| 1808 | Jan 21 - 22, 2014 | Norcross, GA | Register |
Overview:
This course will provide you with the framework for creating experimental designs that lay out a detailed experimental plan in advance of doing the experiment. In industrial settings, the primary goal is usually to extract the maximum amount of unbiased information regarding the factors affecting a production process from as few costly observations as possible. In general, every machine used in a production process allows its operators to adjust various settings, affecting the resultant quality of the product manufactured by the machine. Experimentation allows the engineer to adjust the settings of the machine in a systematic manner and to learn which factors have the greatest impact on the resultant quality. Using this information, the settings can be constantly improved until optimal quality is obtained.
Topic Highlights:
- ANOVA: One and two factor
- Completely randomized design and randomized block design
- Computer applications
| - Full and fractional factorial design
- Interaction and replications
- Single-factor design and two-factor design
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What You Will Learn:
- Analyze and interpret data that is generated in the experiment
- Design experiments to identify the optimum combination to minimize cost and increase quality and productivity
- Determine operating levels for key process factors
- Identify critical process characteristics