Method and system for establishing product process quality prediction model based on site data

A technology for field data and quality prediction, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as low accuracy and no data analysis, and achieve the effect of avoiding singleness and preventing output

Active Publication Date: 2016-09-21
CHINA TOBACCO SHANDONG IND
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AI Technical Summary

Problems solved by technology

[0004] At present, the prediction of the product process quality of cigarette equipment is only based on manual judgment based on the change trend of cigarette quality and experience, which is relatively subjective, without analysis based on relevant data, and the accuracy is not high

Method used

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  • Method and system for establishing product process quality prediction model based on site data
  • Method and system for establishing product process quality prediction model based on site data
  • Method and system for establishing product process quality prediction model based on site data

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Embodiment Construction

[0047] The present invention is described in detail below in conjunction with accompanying drawing:

[0048] Such as figure 1 As shown, the establishment method of the product process quality prediction model based on field data includes the following steps:

[0049] Step 1. Organize data of various on-site equipment through data analysis software; Step 2. Use neural network method to predict product quality; Step 3. Formulate management strategies based on the prediction results combined with equipment fault trees.

[0050] The sorting of all kinds of on-site equipment data includes the following sub-steps: Step 11, use data analysis software to read the cigarette equipment on-site data stored in the database; Sort all kinds of data in chronological order; step 14, sort out all kinds of data in units of 15 minutes, the least common multiple of each other's collection cycle, and the data of equipment output, elimination, and shutdown are among the maximum and minimum values ​...

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Abstract

The invention discloses a method and a system for establishing a product process quality prediction model. The method comprises the following steps of: acquiring site data of cigarette equipment and storing the acquired data to a database; processing the site data of the cigarette equipment, wherein the site data of the cigarette equipment include shutdown data, deletion data, yield data and product quality data of a cigarette making machine; establishing a product process quality neural network prediction model; establishing an equipment fault tree; inputting real-time data of the cigarette equipment to the product process quality neural network prediction model to obtain prediction product quality data, and controlling the cigarette equipment in combination with the equipment fault tree. According to the method and the system for establishing the product process quality prediction model based on the site data, the singleness of a data statistical analysis method can be avoided; the data of the cigarette equipment are effectively combined, a data comprehensive analysis model is established, the product quality in the next period of time is predicted, defective products are prevented from being produced, the product quality-oriented equipment management is guided.

Description

technical field [0001] The invention relates to the field of establishing data models in the tobacco industry, in particular to a method and system for establishing a product process quality prediction model based on field data. Background technique [0002] In recent years, the industrial automation of cigarette enterprises has made considerable progress, and systems such as bottom-level data acquisition, centralized control, and status monitoring have been established. The management has also established a large number of application systems. There are a large number of industrial automation systems and application systems in these Equipment data resources, but the level of data management and data value mining in equipment management is not high, resulting in the waste of a large amount of data resources, which cannot effectively support lean management. [0003] On-site data of cigarette equipment mainly includes downtime data, reject data, output data and product qualit...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
CPCG06F30/367
Inventor 马万强程继忠郭红广马俊吴艳丽宋磊张东生
Owner CHINA TOBACCO SHANDONG IND
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