Machine learning method based on working conditions and related device

Abstract

The embodiment of the invention provides a working condition-based machine learning method and a related device, which are applied to electronic equipment. According to the method, material inspection data of a target working condition, production line working condition data of the target working condition and a working condition coding rule are obtained, a target code of the target working condition is determined according to the material inspection data, the production line working condition data and the working condition coding rule, and the target code is compared with a preset code of the target working condition; if the target working condition does not create the machine learning task, establishing a first machine learning task for the target working condition, and configuring a first machine training parameter for the first machine learning task; and inputting the first machine training parameters into a product parameter prediction model, performing machine training on the target working condition to obtain a plurality of first learning results, and determining a benchmark value from the plurality of first learning results. Thus, the accurate product parameter prediction model is obtained through machine training, the process optimization efficiency can be improved, and accurate product parameters can be obtained.

Description

technical field [0001] The application belongs to the technical field of production data processing, and in particular relates to a machine learning method and related devices based on working conditions. Background technique [0002] At present, the production process optimization of traditional chemical plants and process manufacturing enterprises relies on the accumulation of experience of front-line operators. This method makes process improvement difficult and takes a long time, and excellent experience cannot be shared or solidified and promoted. At the same time, the traditional experience lacks the support of big data and precise statistical analysis, and cannot meet the needs of current intelligent production. Contents of the invention [0003] The embodiment of the present application provides a working condition-based machine learning method and related devices in order to improve the efficiency of process optimization. [0004] In the first aspect, the embodim...

AI Technical Summary

Problems solved by technology

[0002] At present, the production process optimization of traditional chemical plants and process manufacturing enterprises relies on the accumulation of experience of front-line operators. This method makes process improvement difficult and takes a long time, and excellent experience cannot be shared and promoted.

At the same time, the traditional experience lacks the support of big data and precise statistical analysis, and cannot meet the needs of current intelligent production

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