DOE Terminologies IE-432.

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Presentation transcript:

DOE Terminologies IE-432

Terminologies Controlled Experiment: a study where treatments are imposed on experimental units, in order to observe a response Factor: a variable that potentially affects the response ex. temperature, time, chemical composition, etc. Treatment: a combination of one or more factors Levels: the values a factor can take on Effect: how much a main factor or interaction between factors influences the mean response

Terminologies Design Space: range of values over which factors are to be varied Design Points: the values of the factors at which the experiment is conducted One design point = one treatment Usually, points are coded to more convenient values ex. 1 factor with 2 levels – levels coded as (-1) for low level and (+1) for high level Response : unknown; represents the mean response at any given level of the factors in the design space. Center Point: used to measure process stability/variability, as well as check for curvature of the response surface.

Replications Replicates NOT the same as repeated measurements Repeated measurements is when you take multiple measurements on the same unit. Replication is when you repeat your design a 2nd, 3rd, 4th, etc. time. Ex. Say you have a 22 design (2 factors, 4 runs) and want 3 replicates. Your experiment will have 3*22 = 12 runs. Replication will help give you more accurate effect estimates. Replicates should be run at the same time as your original design (to ensure all controlled conditions are the same). If that’s not possible, consider blocking

Blocking Grouping together experimental units that are similar to one another – the groups are called blocks Blocking “reduces known, but irrelevant sources of variation between units and thus allows greater precision” In Factorial Designs, blocks are confounded with higher order interactions. This means you don’t know if an observed relationship between a block and the response variable is due to the block itself, or due to the factor interaction. Assuming the higher order interactions are insignificant one can estimate the block effect.