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Intelligent manufacturing management system based on data mining

A technology for intelligent manufacturing and management systems, applied in manufacturing computing systems, image data processing, data processing applications, etc., and can solve problems such as operational difficulties, unsatisfactory product quality control, and low intelligence.

Pending Publication Date: 2021-07-20
CHONGQING CITY MANAGEMENT COLLEGE
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, in enterprises with a certain scale, various computer management software are usually used to assist management, such as enterprise resource planning (ERP), manufacturing execution system (MES), equipment management system (EMS), etc., but for the control of manufacturing quality There are few convenient systems. In industrial production, some defective products are often produced due to equipment reasons or manual reasons. In the past, due to the lack of data support, the cause of defects was only checked manually, and the efficiency of manual checking Low, difficult to operate, resulting in often unsatisfactory quality control of products
Although there are some intelligent systems that can detect and record quality defects, in the existing technology, most of the analysis relies on preset conditions for matching, the degree of intelligence is low, and there is a lack of in-depth analysis of the causes of quality problems. The reason for the poor accuracy

Method used

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  • Intelligent manufacturing management system based on data mining
  • Intelligent manufacturing management system based on data mining
  • Intelligent manufacturing management system based on data mining

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0042] Embodiment one is basically as attached figure 1 Shown: Including quality inspection module, production collection module, correlation analysis module, rectification plan module, staff training module.

[0043] The quality inspection module includes the image data visualization module, which takes product photos and extracts the features of the product, such as identifying the outline, color, shape, pattern, surface smoothness, etc. of the product. Through the image recognition algorithm, according to these input features , convert the picture information into text information, and find out the defective products according to the text information. The defective products are characterized by stains, defects, gaps, and leaks.

[0044] The production acquisition module collects the data of the industrial production line, including output, equipment operation, employee operation, product number, production time, etc.

[0045] The correlation analysis module combines the ch...

Embodiment 2

[0056] Embodiment two is basically as image 3 As shown, the difference from Embodiment 1 is that an operation and maintenance management module is also included.

[0057] Operation and maintenance management modules such as Figure 4 As shown, it includes the equipment traceability module, equipment definition module, equipment association module, scrapping planning module, and equipment purchase module. A series of adjustments are made for product defects caused by equipment.

[0058] The equipment traceability module traces back to which equipment produced the defective product based on the equipment operation status, product number, production time and other information collected by the production collection module, and can be traced back to the equipment that produced the defective product.

[0059] The equipment definition module collects various parameters of the equipment, such as current, voltage, amplitude, speed, pressure, pressure, integrity of parts, etc., and ju...

Embodiment 3

[0068] The difference between this embodiment and the third embodiment is that the scrapping planning module also includes a scrapping degree detection module.

[0069] The scrapping degree detection module judges the equipment failure level according to the equipment parameters. In this embodiment, there are 10 pieces of equipment to be scrapped, and the failure level is judged by the equipment speed. The slower the speed, the higher the failure level. The scrapping plan module is set every 3 days Carry out a scrapping, rank according to the fault level, from high to low, and scrap 2 devices each time. At the same time, order 10 corresponding equipment from the third-party supplier, and transfer two equipment from the third-party supplier one day before each scrapping.

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Abstract

The invention relates to the field of intelligent manufacturing management, and discloses an intelligent manufacturing management system based on data mining, which comprises a quality detection module, a production acquisition module, a correlation analysis module, an operation and maintenance management module, a rectification scheme module and an employee training module. The quality detection module detects product data and finds out defective products; the production acquisition module acquires various data on an industrial production line; the correlation analysis module combines and analyzes the product data and the industrial production line data to analyze whether the reason is a human reason or an equipment reason; and if the reason is human-caused, the problem is submitted to therectification scheme module to formulate aA corresponding rectification scheme; and if the rectification scheme is equipment-caused, the rectification scheme is handed over to the operation and maintenance management module to handle the equipment. According to the invention, the efficiency of product quality detection is improved, reasons of defective products are analyzed, hidden dangers of product defects are eliminated, and the yield of products is improved.

Description

technical field [0001] The invention relates to the field of intelligent management manufacturing, and specifically discloses an intelligent manufacturing management system based on data mining. Background technique [0002] With the increasingly fierce competition in the global market, the manufacturing industry is facing more stringent requirements in the fields of improving product quality, increasing production efficiency, reducing production costs and reducing resource consumption. Manufacturing companies take advantage of the continuous innovation of manufacturing technology and introduce emerging technologies such as the Internet of Things, big data, 3D printing, and cloud computing to achieve transparency, intelligence, and overall optimization of the production process to meet the above challenges. A new round of industrial revolution. [0003] At present, in enterprises with a certain scale, various computer management software are usually used to assist managemen...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/04G06T7/00
CPCG06Q10/06395G06Q50/04G06T7/0002Y02P90/30
Inventor 董引娣何娇王娟娟彭茂玲李顺琴梅青平
Owner CHONGQING CITY MANAGEMENT COLLEGE
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