A working condition-based machine learning method and related device

Abstract

Embodiments of the present application provide a working condition-based machine learning method and a related device, which are applied to electronic equipment. Method By obtaining the material inspection data of the target working condition, the production line working condition data and working condition coding rules of the target working condition, the target coding of the target working condition is determined according to the material inspection data, production line working condition data and working condition coding rules, and the The target code is compared with the preset code of the target working condition. If the target code is inconsistent with the preset code, and the target working condition does not create a machine learning task, the first machine learning task is established for the target working condition, which is the first machine learning task Configure the first machine training parameters; input the first machine training parameters into the product parameter prediction model, perform machine training on the target working condition, obtain multiple first learning results, and determine benchmark values ​​from the multiple first learning results. In this way, an accurate product parameter prediction model can be obtained through machine training, which can improve the efficiency of process optimization and obtain accurate product parameters.

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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