ANALYSIS OF THE INTELLIGENT MONITORING SYSTEM FOR INDUSTRIAL QUALITY CONTROL USING ARTIFICIAL INTELLIGENCE AND STATISTICAL INFERENCES
DOI:
https://doi.org/10.31510/infa.v22i2.2361Keywords:
Intelligent Monitoring System, Quality Control, Artificial Intelligence, IoTAbstract
With the intensification of the digitalization of industrial processes and the high demand for efficiency and traceability, the use of advanced technologies capable of raising quality standards in production becomes indispensable. The Intelligent Monitoring System for Quality Control (SMICQ) emerges as a strategic alternative by integrating Artificial Intelligence, the Internet of Things (IoT), and predictive statistical methods. This need becomes even more evident in light of the increasing complexity production and the pressure to reduce failures, waste, and operational costs. The ability to monitor variables in real time strengthens process reliability and ensures greater compliance with quality standards and competitiveness on a large scale. This study was developed based on practical evidence and a bibliographic survey in the field, bringing together contributions from scientific research, technical reports, and already consolidated industrial applications. Throughout the article, aspects such as the operation of SMICQ, its advantages compared to traditional inspection methods, as well as the impacts of its adoption in the context of Industry 4.0, are discussed. In this way, the research highlights role of SMICQ as a technological solution, emphasizing its strategic potential in the digital transformation of industry and in the construction of more autonomous, precise, and sustainable production processes.
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