An Automated Data Analytics and Overall Equipment Effectiveness Visualization Technique for Assembly Line on Continuous Manufacturing System using Power BI

Thailand 4.0 model is established to develop a smart city with human-machine interaction to communicate to every station in the manufacturing process using sensor and visualization techniques. The automated approach for analyzing and visualizing the Overall Equipment Effectiveness (OEE) of the assembly line on the continuous manufacturing system using Power BI is introduced. The data cleansing and data transform process was applied to prepare the input data, and the Data Analysis Expressions (DAX) measurement is used to calculate the key features from timestamp and output table such as time duration of ‘RED’, ‘GREEN’, and ‘YELLOW’, count ‘NG’ status, and count ‘FG’ status. Once OEE and OEE Loss are calculated from the prepared data, the visualization of Modules I, II, and III are generated to demonstrate the cycle time, progress amount, and OEE and OEE loss. The visualization shows the relation between OEE and OEE loss and their components. The losses and abnormality signals can be detected from the graph and eliminated losses by the Kaizen process. It showed that the Performance Loss from the minor stop could be reduced by decreasing the waiting time from 2 Standard Cycle Time (StdCT) to 1 StdCT, the OEE is improved from 53.11% to 57.05%, and Performance is changed from 78.55% to 84.38%.