过程(计算)
工业互联网
可视化
工业4.0
生产(经济)
互联网
物联网
制造工程
计算机科学
工业生产
制造业
工艺工程
系统工程
工业工程
机械工程
工程类
嵌入式系统
万维网
宏观经济学
凯恩斯经济学
政治学
经济
法学
操作系统
作者
Boon Xian Chai,Maheshi Gunaratne,Mohammad Ravandi,Jinze Wang,Tharun Dharmawickrema,Adriano Di Pietro,Jiong Jin,Dimitrios Georgakopoulos
出处
期刊:Sensors
[MDPI AG]
日期:2024-07-26
卷期号:24 (15): 4852-4852
被引量:24
摘要
Composite materials are increasingly important in making high-performance products. However, contemporary composites manufacturing processes still encounter significant challenges that range from inherent material stochasticity to manufacturing process variabilities. This paper proposes a novel smart Industrial Internet of Things framework, which is also referred to as an Artificial Intelligence of Things (AIoT) framework for composites manufacturing. This framework improves production performance through real-time process monitoring and AI-based forecasting. It comprises three main components: (i) an array of temperature, heat flux, dielectric, and flow sensors for data acquisition from production machines and products being made, (ii) an IoT-based platform for instantaneous sensor data integration and visualisation, and (iii) an AI-based model for production process forecasting. Via these components, the framework performs real-time production process monitoring, visualisation, and prediction of future process states. This paper also presents a proof-of-concept implementation of the framework and a real-world composites manufacturing case study that showcases its benefits.
科研通智能强力驱动
Strongly Powered by AbleSci AI