Alina Bianca POP, Aurel - Mihail ȚÎȚU


In this study, the factors affecting the surface roughness of machined 7136 aluminum components were investigated. Principal component analysis (PCA) was used to assess the quality criteria and it was found that the first component explained most of the variation in the data. Surface roughness and cutting conditions were significantly related to the first component, while axial depth of cut and feed per tooth were mostly related to the second component. The first three components combined explained 90.995% of the variance. These findings suggest that surface roughness is significantly influenced by cutting conditions. The study demonstrates that PCA is a useful tool for analyzing large data sets to identify key factors influencing surface roughness.

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