Product quality control method based on integration learning

A product quality and control method technology, applied in the direction of manufacturing computing systems, resources, instruments, etc., can solve problems such as difficult to find parameter connections and lack of versatility, and achieve the effects of reducing resource utilization, good accuracy, and high computing performance

Inactive Publication Date: 2018-11-06
SOUTH CHINA UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Traditional product quality control analysis is more about analyzing the influence of parameters themselves on quality indicators one by one. However, such analysis is difficult to find the intrinsic relationship between parameters, and it is not universal

Method used

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  • Product quality control method based on integration learning
  • Product quality control method based on integration learning
  • Product quality control method based on integration learning

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Embodiment

[0051] This embodiment takes product quality control in the injection molding industry as the research object, based on 1) predicting the key quality indicators (yield rate) of products under different schedules in the production process; 2) recommending the optimal preset values ​​of the process parameters in the production process, In order to obtain better key quality indicators, two methods are used to conduct applied research on the quality control of injection products. Use big data technology and machine learning methods to find abnormalities in the production process and improve product quality control.

[0052] Such as figure 1 As shown, the implementation of the integrated learning-based product quality control method includes two aspects: 1) predict the key quality indicators (yield rate) of products under different schedules in the production process; 2) optimize the process parameters in the production process The default value is recommended to obtain better key qua...

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Abstract

The present invention discloses a product quality control method based on integration learning. For prediction of product key quality indexes (yield) in different progresses in a production flow, themethod comprises the following steps of: (1) data analysis based on injection molding data; (2) feature engineering analysis and construction; (3) model design based on integration learning; (4) unbalance processing of data; and (5) multi-model fusion processing scheme. For recommendation of the optimal preset value of process parameters in the production process, the method comprises the following steps of: (6) whole process adjustable parameter recommendation; and (7) for un-adjustable parameters of a special process, recommendation of process adjustable parameters. The product quality control method is suitable for the processing unbalance data in the industrial data to break through a traditional product quality control single parameter analysis mode, and constructs and excavates internal feature relations between parameters through the feature engineering of the machine learning to discover the abnormality of the production process and improve the product quality control.

Description

Technical field [0001] The invention relates to the technical field of data mining, in particular to a product quality control method based on integrated learning. Background technique [0002] Machine learning is currently an important research field of artificial intelligence applications, and its development is very active, and integrated learning is a popular research direction in machine learning. "Made in China 2025" proposes to use the in-depth integration of informatization and industrialization to lead and drive the development of the entire manufacturing industry and transform the manufacturing industry to Industry 4.0. However, because the networking and intelligence of injection molding machinery have just started, the industry’s informatization service level is low, and industry resources lack a unified plan, resulting in higher overall labor costs, lower informatization levels, and product added value in plastic-related industries. Inferior issues have severely res...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/04G06K9/62G06F17/50
CPCG06Q10/06395G06Q50/04G06F2119/18G06F30/17G06F30/20G06F18/24Y02P90/30
Inventor 傅予力李凯鑫张勰吴宗泽张莉婷
Owner SOUTH CHINA UNIV OF TECH
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