PBDS production process big data analysis system
System functions:
Data collection: production equipment data collection, inspection equipment data collection, manual entry data collection, raw material use data collection.
Data storage: Data storage supports mass data storage, metadata storage, service data storage, and system monitoring data storage based on data space usage, reuse, and frequency.
Model building and training: Using the combination of mechanism and data analysis, using the data analysis model to modify the mechanism model, so as to establish the production process model; In view of the fact that the mechanism model is not available, the data analysis model is used for forecasting and quality prediction: real-time acquisition or simulation of input of production process equipment data, raw material use data and manual input data, and automatic prediction of the probability of various product defects.
Production process optimization: Using the obtained production process model, establish the operation optimization model, and use the evolutionary algorithm to obtain the optimal setpoint value of each operation variable for operation optimization.
System benefits:
Reduce R & D costs: It can simulate the ratio of raw materials and production process parameters, and directly predict the quality through the system to reduce the R & D cost of trial production.
Improve product quality: Through the system to provide suggested raw material ratio information and process parameters, constantly optimize and improve the production process, improve product quality.
The inspection is more targeted: the quality prediction data of each product can be understood during the inspection, and the inspection can be more targeted.