A production data acquisition method and system based on stream processing technology

Abstract

The present invention relates to the technical field of data acquisition, in particular to a production data acquisition method and system based on stream processing technology. Firstly, the relevant data information is collected through the workshop production data acquisition layer and the workshop inspection data acquisition layer, and the product-related production information, detection , The maintenance data is first stored for reading and graphical display by the MES system, and then the data flow is processed in real time through the operation data processing layer, and finally the on-site status of the production workshop and the processing results of the operation data are displayed to the data collection application layer; The inventive method is more suitable for the current actual workshop application situation, and can perform operations such as production error prevention and data collection in real time without affecting actual production; the assembly information, test information, packaging information and maintenance information of the workshop production site collected by equipment, It can be obtained directly from the existing data system, the method of obtaining is simple, and the operability of the method of the present invention is improved.

Description

technical field [0001] The invention relates to the technical field of data collection, in particular to a production data collection method and system based on stream processing technology. Background technique [0002] With the rapid rise of China's economic development, the industrial manufacturing industry has a direct impact on the country's economic development and social progress. Due to the complexity of the on-site environment of the production workshop and the diversity of product information, the enterprise's allocation of resources is unreasonable, resulting in waste of materials and economic losses. [0003] In recent years, with the development of sensor detection technology and the popularization of Internet of Things equipment, the operating data of the workshop production site has shown an "exponential" rise. For the workshop site, the real-time performance of the monitoring system is low and the scalability is not high. It is prone to delays or even crashe...

AI Technical Summary

Problems solved by technology

Due to the complexity of the on-site environment of the production workshop and the diversity of product information, the enterprise's allocation of resources is unreasonable, resulting in waste of materials and economic losses

[0003] In recent years, with the development of sensor detection technology and the popularization of Internet of Things equipment, the operating data of the workshop production site has shown an "exponential" rise. For the workshop site, the real-time performance of the monitoring system is low and the scalability is not high. It is prone to delays or even crashes, and the total amount and value of data increases and loses rapidly over time. Mining its value exceeds the computing power of traditional data processing, and cannot meet the real-time monitoring and management needs of workshop production. The abnormal status monitoring system of on-site operating data in the workshop brings challenges such as real-time processing of massive operating data streams, massive data storage, and real-time visual analysis of data.

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