Integrating Machine Learning into Engineering: A Study on Intelligent Systems
Keywords:
Machine Learning, Engineering Systems, Intelligent Systems, Predictive Maintenance, Automation, System Integration, Supervised LearningAbstract
The revolutionary change has occurred in the several branches of engineering triggered by the rapid development of the machine learning (ML) technologies. This research discusses the introduction of the ML in engineering systems with the emphasis on the formation and implementation of smart systems. While analyzing current literature as well as a case study (practical one) related to predictive maintenance in industrial systems, this research reveals the potential of ML that can be used for increasing efficiency, reliability, and automation of engineering projects. The methodology integrates supervised learning models and system specific sensor data to come up with adaptive systems. Findings show positive improvement on the predictive accuracy and functioning of the operations. The paper winds up with a recommendation for further research in the system integration, ethical deployment, and scalable architectures.
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