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There has been considerable interest recently in the application of parameter design methodology to make a system's performance robust over a wide range of input conditions. This has been referred to as robust design with dynamic characteristics. In this paper, we first review this overall strategy and its usefulness and then demonstrate the limitations of the data analysis methods recommended by Taguchi. We then propose two graphical methods, the sensitivity-standard deviation plot and the gamma-plot, for identifying suitable measures of dispersion that are valid more generally. These graphical methods are related to the mean-variance plot and the lambda-plot that have been found useful in analyzing data from static robust design studies. The implementation and the usefulness of the proposed graphical methods are illustrated through two examples including a real application on engine idling performance.
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Stored only when both papers are in the corpus — 66 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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