INTELLIGENT MONITORING SYSTEMS IN MANUFACTURING: CURRENT STATE AND FUTURE PERSPECTIVES

Oladiran Kayode Olajiga, Emmanuel Chigozie Ani, Kehinde Andrew Olu-lawal, Danny Jose Portillo Montero, Adeniyi Kehinde Adeleke
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Abstract

Intelligent Monitoring Systems (IMS) have emerged as indispensable tools in modern manufacturing, offering real-time insights into production processes, equipment performance, and quality control. This review provides an overview of the current state and future prospects of IMS in manufacturing environments.  The current state of IMS in manufacturing involves the integration of advanced technologies such as Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), and Big Data analytics. These systems collect vast amounts of data from sensors, machines, and production lines, enabling real-time monitoring and analysis of various parameters. By employing AI and ML algorithms, IMS can identify patterns, predict anomalies, and optimize production processes, leading to increased efficiency, reduced downtime, and improved product quality. IMS play a crucial role in predictive maintenance, where they can anticipate equipment failures before they occur, thereby minimizing unplanned downtime and maintenance costs. Moreover, IMS facilitate condition-based monitoring, allowing manufacturers to monitor the health and performance of machinery in real-time and schedule maintenance activities accordingly, optimizing resource allocation and prolonging equipment lifespan. Furthermore, IMS contribute to quality control by continuously monitoring production processes and detecting deviations from desired specifications. By leveraging AI-driven algorithms, IMS can automatically adjust process parameters to maintain product quality standards and minimize defects, thereby enhancing overall product reliability and customer satisfaction. Looking ahead, the future perspectives of IMS in manufacturing are promising, with advancements in areas such as edge computing, robotics, and augmented reality poised to revolutionize manufacturing operations further. Edge computing enables data processing and analysis to occur closer to the data source, reducing latency and enhancing real-time decision-making capabilities. Robotics integration with IMS facilitates autonomous manufacturing processes, while augmented reality technologies provide intuitive interfaces for operators to interact with IMS data in real-time.  IMS represent a transformative technology in manufacturing, offering unprecedented levels of visibility, control, and optimization. As technology continues to evolve, IMS are poised to play an increasingly vital role in shaping the future of manufacturing, driving efficiency, productivity, and innovation.. Keywords: Monitoring, System, Intelligent, Manufacturing, Review, Perspectives.
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制造业智能监控系统:现状与未来展望
智能监控系统(IMS)已成为现代制造业中不可或缺的工具,可实时洞察生产流程、设备性能和质量控制。本综述概述了 IMS 在制造环境中的现状和未来前景。 制造业 IMS 的现状涉及物联网 (IoT)、人工智能 (AI)、机器学习 (ML) 和大数据分析等先进技术的集成。这些系统从传感器、机器和生产线上收集大量数据,实现对各种参数的实时监控和分析。通过采用人工智能和 ML 算法,IMS 可以识别模式、预测异常并优化生产流程,从而提高效率、减少停机时间并提高产品质量。IMS 在预测性维护方面发挥着至关重要的作用,它们可以在设备故障发生前进行预测,从而最大限度地减少计划外停机时间和维护成本。此外,IMS 还可促进基于状态的监控,使制造商能够实时监控机器的健康状况和性能,并据此安排维护活动,从而优化资源分配,延长设备使用寿命。此外,IMS 还能持续监控生产流程,检测与预期规格的偏差,从而促进质量控制。通过利用人工智能驱动的算法,IMS 可以自动调整工艺参数,以保持产品质量标准并最大限度地减少缺陷,从而提高产品的整体可靠性和客户满意度。展望未来,IMS 在制造业中的应用前景广阔,边缘计算、机器人技术和增强现实技术等领域的进步将进一步彻底改变制造业的运营。边缘计算可使数据处理和分析更接近数据源,从而减少延迟并提高实时决策能力。与 IMS 集成的机器人技术促进了自主制造流程,而增强现实技术则为操作员提供了与 IMS 数据实时交互的直观界面。 IMS 是制造业的一项变革性技术,可提供前所未有的可视性、控制和优化水平。随着技术的不断发展,IMS 将在塑造制造业的未来、推动效率、生产力和创新方面发挥越来越重要的作用。关键字监控 系统 智能 制造 评论 展望
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