Principal component analysis (PCA) is applied to particulate size distributions measured at receptor sites in two cleanrooms. The principal components are determined by evaluating the rotated component patterns. Each component is then assigned to a source by comparing the principal components to the particle size distributions emitted by the sources. Hence, sources of particulate contamination in the cleanrooms are determined. Particle volume concentration balances are used to quantitatively apportion the contaminant levels at the receptor sites to each source. PCA can thus be used to identify contaminant particle sources and to develop strategies for improvement of the cleanroom cleanliness class.
Principal Component Analysis for Particulate Source Resolution in Cleanrooms
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Yi Tian, Pratim Biswas, Sotiris Pratsinis, Walter Hsieh; Principal Component Analysis for Particulate Source Resolution in Cleanrooms. Journal of the IEST 1 November 1989; 32 (6): 22–27. doi: https://doi.org/10.17764/jiet.184.108.40.206877570h8086136
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