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Taguchi Methods: Benefits, Impacts, Mathematics, Statistics and Applications

Teruo Mori, PhD
Teruo Mori, PhD
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Shih-Chung Tsai, PhD
Shih-Chung Tsai, PhD
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ASME Press
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Data goes missing when test samples fall, experimental data is recorded incorrectly, measurements are incorrect, samples don't match factor level settings, or when there is no measurable quantity for the output responses, etc. In some cases, the test samples are made appropriately but the testing equipment does not function correctly (for example, there is a driving motor malfunction or a copy machine does not work as intended). In some reliability or durability tests, the output response data is not obtained because the samples don't yield under the loads within the test duration.

If samples are correctly made and the data...

15.1 Missing Data
15.2 Replacement Values for Missing Data
15.3 Comparison Between Approximation Methods Based on Main-Effect Plots and Orthogonal Polynomials
15.4 Iterative Approximations When There are Multiple Missing Values
15.5 Quantification of Missing Data Caused by Various Test Disruptions
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