In the present work, a novel cloud-based remote and real time monitoring and control scheme has been developed for a manufacturing process named friction stir welding (FSW) to avoid occurrence of weld defects. This model acquires data from multiple sensors associated with the FSW machine and transmits them to the cloud. The signals are analyzed and processed in the cloud in real time through various signal processing and machine learning techniques. The model provides a feedback to the machine regarding the desired controlled parameters to achieve an improved weld quality. This is an example of Industry 4.0 where a manufacturing process can be controlled in real time from any location.

在当前的工作中，已经开发了一种新颖的基于云的远程实时监控方案，该方案用于名为摩擦搅拌焊接（FSW）的制造过程，以避免出现焊接缺陷。该模型从与FSW机器关联的多个传感器获取数据，并将其传输到云。通过各种信号处理和机器学习技术，可以在云中实时分析和处理信号。该模型向机器提供有关所需控制参数的反馈，以实现改善的焊接质量。这是工业4.0的示例，其中可以从任何位置实时控制制造过程。