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Experimental Design

Experimental Design. Fr. Clinic II. Planning. Begins with carefully considering what the objectives (or goals)are How do our filters work? Which filter is best? Performance Cost Ease of Use Durability…. Variables.

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Experimental Design

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  1. Experimental Design Fr. Clinic II

  2. Planning • Begins with carefully considering what the objectives (or goals)are • How do our filters work? • Which filter is best? • Performance • Cost • Ease of Use • Durability…

  3. Variables • Process variables include both inputs and outputs - i.e. factors and responses • The selection of these variables is best done as a team effort

  4. Terms • Factor • Something that can be varied, e.g.,temperature, pressure, material … • Response • the results • Level • Each variable can be “set” to or measured at different levels • Run • How many times each unique combinations of factors and levels will be tested

  5. What are our factors? • How do filters work? • Could be the membrane/porous filter, the activated carbon, the viral guard… • Comparative Assessment • We have one factor, the portable water filters themselves!

  6. Water are our possible responses? • Removal of contaminants • Produced water quality • Cost • Ease of use • …

  7. Experimental Design • Choosing an experimental design depends on the objectives of the experiment and the number of factors to be investigated.

  8. Experimental Design Objectives • Comparative objective • 1 or several factors under investigation • primary goal to make conclusion about 1 important factor • in the presence of, and/or in spite of the other factors • Screening objective • select or screen out few important main effects from many lesser important ones • Response Surface (method) objective • estimate response to multiple factors • find improved or optimal process settings, troubleshoot process problems and weak points, or make a product or process more robust against external and non-controllable influences.

  9. Experimental Designs • Completely Randomized Designs • Comparative objective, 1 factor • Randomized Block Designs • Comparative objective, multiple factors • Full or fractional factorial • Screening objective, multiple factors • Many more!…

  10. Completely Randomized Designs • One factor, with multiple levels of interest • For example – effect of temperature on a chemical reaction • three levels, two runs each gives 90 unique orders to conduct experiment (e.g., T1, T1, T2, T2, T3, T3;…) • In a completely randomized design, you would randomly select the order of runs

  11. Randomized Block Designs • One factor or variable is of primary interest. However, there are also several other nuisance factor variables • Nuisance variables are those which may affect the measured result, but are not considered of primary interest. • For example: specific operator who prepared the treatment, the time of day the experiment was run, and the room temperature. • All experiments have nuisance factors.

  12. Randomized Block Designs (cont.) • Blocking • Run every level of the primary factor with the nuisance factor(s) held the same • Minimizes total # of runs • Random • Run with nuisance factors selected randomly. • More runs may be required • Likely to get more variability (error) in results • May be able to block some nuisance factors, but not all

  13. Randomized Block Design Example • Engineers at semiconductor manufacturing facility want to test effect of 4 different wafer implant material dosages using 3 runs for each level • The nuisance factor is "furnace run", since it is known that each furnace run differs from the last and impacts many process parameters • Block: run all 4x3=12 wafers in the same furnace run • Completely Random: randomly select order and and include each run each on a different furnace run

  14. Full Factorial • Run all combinations of factors and levels. • For example: A basic experimental design is one with all input factors set at two levels each • These levels are called ‘high’ and ‘low’ or ‘+1’ and‘-1’ respectively. • A design with all possible high/low combinations of all the input factors is called a “full factorial design in two levels”

  15. Fractional Factorial • A factorial experiment in which only an adequately chosen fraction of the treatment combinations required for the complete factorial experiment is selected to be run

  16. What should we do? • For our competitive assessment, we have one factor – portable water filters • The levels are the different filters • What are our nuisance factors? • Properties of pond water? • Day of experiment? • Operators of experiment? • ???

  17. Competitive Assessment Experiment • We will run a randomized block design • However, we may only be able to do one run per level • We’ll try to block as many of the nuisance factors as possible • There are some that we won’t be able to block or randomize

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