Production data acquisition method and system based on stream processing technology

Abstract

The invention relates to the technical field of data acquisition. The invention particularly relates to a production data acquisition method and system based on a stream processing technology. Firstly, relevant data information is collected through a workshop production data collection layer and a workshop detection data collection layer, production information, detection data and maintenance datarelated to a product are firstly stored for an MES system to read and graphically display, then a data flow is processed in real time through an operation data processing layer, and finally a production workshop field state and an operation data processing result are displayed on an acquisition data application layer. The method provided by the invention is more suitable for a current actual workshop application situation, and can carry out operations such as production mistake prevention and data acquisition in real time under the condition of not influencing actual production; workshop production field assembly information, test information, package information and maintenance information collected by equipment can be directly obtained from an existing data system, the obtaining methodis simple, and the operability of the method 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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