ADD jeff wu's epic textbook
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@ -2451,6 +2451,18 @@ CONCLUSIONS: We developed a simplified, semi-closed system for the initial selec
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publisher = {Wiley},
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}
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@Book{Wu2009,
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author = {Wu, Hamada},
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publisher = {John Wiley \& Sons},
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title = {Experiments 2e},
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year = {2009},
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isbn = {0471699462},
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month = jul,
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ean = {9780471699460},
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pagetotal = {756},
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url = {https://www.ebook.de/de/product/8324352/wu\_hamada\_experiments\_2e.html},
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}
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@Comment{jabref-meta: databaseType:bibtex;}
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@Comment{jabref-meta: grouping:
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@ -1033,10 +1033,10 @@ described\cite{Budagian2004}.
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The \gls{dms} system has a number of parameters that can be optimized, and a
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\gls{doe} is an ideal framework to test multiple parameters simultaneously. The
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goal of \gls{doe} is to answer a data-driven question with the least number of
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resources. It was developed in many non-biological industries throughout the
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\nth{20} century such as the automotive and semiconductor industries where
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engineers needed to minimize downtime and resource consumption on full-scale
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production lines.
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resources\cite{Wu2009}. It was developed in many non-biological industries
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throughout the \nth{20} century such as the automotive and semiconductor
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industries where engineers needed to minimize downtime and resource consumption
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on full-scale production lines.
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At its core, a \gls{doe} is simply a matrix of conditions to test where each row
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is usually called a `run' and corresponds to one experimental unit to which the
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@ -1055,7 +1055,6 @@ possible. While there are many types of \glspl{doe} depending on the nature
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of the parameters and the goal of the experimenter, they all share common
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principles:
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% BACKGROUND cite wu hamada... because I feel like it
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\begin{description}
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\item [randomization --] The order in which the runs are performed should
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ideally be as random as possible. This is to mitigate against any confounding
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