An Industrial IoT Analysis System Based on Machining Data of Metal Materials

摘要

The purpose of this study is to use industrial IoT technology to collect machining data of machine tools, and then to develop a data analysis system based on metal materials. The system has several main functions, including data collection and storage, visualization, signal conversion and analysis, batch and trend detection. First, we analyzed the machining data in the time domain and observed the changes under different batch from the statistical analysis. However, machining parameters change with path planning, and frequency analysis is used here as the primary basis for judgment. In the experimental part, we via five batches of data to verify the effectiveness of the proposed technology. Among them, the proposed method successfully detects the breakpoint of the machining program and the value is 257, thereby completing the trend detection capability of the metal processing. The three axes have their appropriate indicators to follow, such as X-axis (standard deviation (#1) index), Y-axis (crest factor (#3), kurtosis (#3), skewness (#3) index), and the Z-axis (average (#1, #3), skewness (#1) index).