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  3. Mathematik, Informatik und Statistik - Open Access LMU - Teil 01/03 Podcast
  4. Screening Procedures to Identify Robust Product or Process Designs Using Fractional Factorial Experiments
In many quality improvement experiments, there are one or more
``control'' factors that can be modified to determine a final
product design or manufacturing process, and one or more
``environmental'' (or `` noise'') factors that vary under field or
manufacturing conditions. In many applications, the product design
or process design is considered seriously flawed if its performance
is poor for any level of the environmental factor. For example, if
a particular prosthetic heart valve design has poor fluid flow
characteristics for certain flow rates, then a manufacturer will
not want to put this design into production. Thus this paper
considers cases when it is appropriate to measure a product's
quality to be its {\em worst} performance over the levels of the
environmental factor. We consider the frequently occurring case of
combined-array experiments and extend the subset selection
methodology of Gupta (1956, 1965) to provide statistical screening
procedures to identify product designs that maximize the worst case
performance of the design over the environmental conditions for
such experiments. A case study is provided to illustrate the
proposed procedures.

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