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Blind Identification of Manufacturing Variation Patterns by Combining Source Separation Criteria

Summary: [This abstract is based on the authors' abstract.] Blind source separation has been used for identifying and eliminating root causes of manufacturing variation, but the performance and applicability of many of the criteria used in blind separation algorithms depend on conditions that are not known beforehand. A method is presented for automatically combining the different criteria in order to minimize the mean squared estimation error. The resulting algorithm is more effective and robust than competing methods of combining the criteria.

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  • Topics: Problem Solving
  • Keywords: Factor analysis, Variation, Manufacturing process, Multivariate quality control, Statistical process control (SPC), Principal components
  • Author: Shan, Xuemei; Apley, Daniel W.
  • Journal: Technometrics