Design of experiments, followed by numeric and graphical optimization, is frequently used by engineers to optimize a process, and to define a design space or operating window. It is critical to understand the boundaries of this operating window – if you choose a specific set of operating conditions close to the boundary, what is the likelihood that normal process variation will cause the resulting characteristic to be out of spec? To ensure critical quality characteristics are meeting their specifications, uncertainty (variability) must be accounted for in defining the boundaries of the design space. We present a method of accounting for uncertainty via confidence intervals and tolerance intervals. These intervals will allow engineers to present a more meaningful design space, one in which they have confidence that the results will be reliable. A “tableting” process is used to illustrate the method.
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