Fault detection in a ball mill circuit using principal component analysis
Pedro Henrique Trindade Dias Cabral; Leonardo Junior Fernandes Campos; André Luiz Alvarenga Santos; Douglas Batista Mazzinghy
Abstract
Quality engineering is a fundamental aspect of production systems that require minimal variability. However, the large number of variables analyzed in industrial processes and the correlation between them requires a more robust technique such as Principal Component Analysis (PCA) for process monitoring. The aim of this work was to develop a fault detection system, using the R programming language, based on PCA in order to improve the quality of products in a milling circuit and facilitate decision-making. The developed algorithm was validated using the Benchmark Tenessee case study, whose maximum deviations were less than 5%. Applying this algorithm to a real case study made it possible to detect a pulp box overflow fault, with very low T2 (0.012) and Q (0.026) values for the non-detection rate (TND).
Keywords
Referências
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Submetido em:
22/01/2025
Aceito em:
22/04/2025
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