Abstract:In order to solve the problem that there are multi-source and uneven quality data in process-oriented workshop, which affect production control, the data classification and processing technology for multi-source data is proposed. Data processing is performed using a combination of data classification and sliding windows. First, a data model is established based on the characteristics of the production data, and the data is classified. It is mainly divided into three types: state data, switch data and logical data. Different types of data use different processing algorithms. As the same time, sliding windows are used to solve the difficult that different tasks have different requirements for data real-time and integrity. Finally, the data classification processing model is put into use in the actual production environment, which verifies the accuracy and real-time performance of the production data processing. The results show that by applying the processed data to production control, the control error rate is reduced to less than 1%.