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Identifying important variation patterns is a key step to identifying root causes of process variability. This gives rise to a number of challenges. First, the variation patterns might be non-linear

Identifying important variation patterns is a key step to identifying root causes of process variability. This gives rise to a number of challenges. First, the variation patterns might be non-linear in the measured variables, while the existing research literature has focused on linear relationships. Second, it is important to remove noise from the dataset in order to visualize the true nature of the underlying patterns. Third, in addition to visualizing the pattern (preimage), it is also essential to understand the relevant features that define the process variation pattern.

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    Date Created
    • 2013
    Resource Type
  • Text
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    • Partial requirement for: Ph.D., Arizona State University, 2013
      Note type
      thesis
    • Includes bibliographical references (p. 111-113)
      Note type
      bibliography
    • Field of study: Industrial engineering

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    by Anshuman Sahu

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