Key Technologies of Real-time Visualization System for Intelligent Manufacturing Equipment Operating State under IIOT Environment

Abstract

In the context of Industry 4.0, real-time fine-grained visualization and fault prediction of intelligent manufacturing equipment is critical for adopting optimal maintenance strategies to reduce total production cost and avoid unnecessary downtime and even casualties. Based on the analysis of the electrocardiogram (ECG) principle of intelligent manufacturing equipment, this paper
profoundly studies the key technologies of the Real-time Visualization System (RVS) of intelligent manufacturing equipment operating state. Firstly, the operating state of intelligent manufacturing equipment is the standard to determine the health condition of the equipment, so we define the tolerance value to make real-time judgment on the operating state of the equipment. Secondly, aiming at the outliers in the original data, an improved Rheinda criterion is proposed to eliminate the gross errors in the data. Thirdly, the Baseline value of the intelligent manufacturing equipment operation is the premise of judging the equipment running condition. The correlation analysis is carried out on the processed data, the Baseline model is established and the model robustness is tested. Finally, the robot of vehicle side welding line is taken as an application case to verify the reliability and effectiveness of the system, which provides a new method for monitoring the real-time fine-grained operation and active operation and maintenance of intelligent manufacturing equipment.