1. Engineering Experimentation Functional Types of Experiments

2. Determining Material Properties • Viscosity • Density • Heat Capacity • Strength • Etc.

3. Component Parameters and Performance Indices • Process Unit Components • Sensors • Controls • Etc.

4. System Parameters & Performance • Assemblies of Components • Unit Operations • Blocks of Unit Operations • Production Process

5. Evaluate and Improve Theoretical Models • Always looking for better models • Process Simulation • Evaluating models to determine limits, risks in accepting data • Somewhat the class of experiments we often do in CHEN3820 and 4860 (Evaluate)

6. Product and/or Process Improvement • Statistical designed experiments most appropriate (“DOE” or “DOX”) • Ongoing process/product monitoring through Statistical Process Control (SPC) techniques • These two work in tandem as technical part of modern management systems • Will be our focus from here out

7. Exploratory Experimentation • “Basic Research” • Determine nature of newly discovered or previously unexplained physical phenomena • Creative Process; less focused than others

8. Acceptance Testing • Used to verify that equipment or product meets criteria: • Performance standards • Health & Safety standards • If acceptable, complete purchase

9. Physical Model Analogues • Computer Simulation becoming better but still place for model testing • Scale up: • bench scale • pilot scale • production scale • Flow testing in a wind tunnel for example: • Testing vs. model

10. Accelerated Testing • Testing to replicate aging in reasonable amount of time • Automated repeated operation of components • Temperature swings, etc

11. Educational • Teach and learn using experimental systems • Demonstrations • “Hands on” learning • False starts, delays, mistakes, misconceptions part of real processes and trouble shooting

12. Educational Lab Projects • Define problem • Plan of attack • Design system • Build apparatus • Test apparatus • Debug apparatus • Iterate

13. Most Important • Plan, plan, plan • Consider information you need and plan experiment that will get you that info. • Plan and practice technique to minimize systematic errors • Anticipate the unexpected • Know your equipment