Diagnostic techniques for predictive maintenance of industrial rotating systems: a systematic review and its applicability in Ecuadorian industry
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Abstract
Industrial rotating systems, such as electric motors, pumps, compressors, and fans, are essential components in production processes. Failures in this equipment cause significant losses, both economic and operational, including reduced industrial productivity. Consequently, an effective strategy has emerged to anticipate failures and optimize management: predictive maintenance. Its purpose is to provide continuous monitoring of operating conditions. This study aims to analyze diagnostic techniques used for predictive maintenance in industrial rotating systems. The approach is based on vibration analysis, laser alignment, and bearing monitoring. A literature review of scientific publications related to these technologies was conducted for this study. The results show that vibration analysis is the most widely used technique for detecting imbalances, mechanical defects, and misalignments. Laser alignment improves operational efficiency, extending the lifespan of rotating components, and bearing monitoring significantly contributes to reducing critical failures. This finally makes it possible to identify opportunities and challenges for the implementation of these technologies in the Ecuadorian industry.
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