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Enterprise production status diagnosis method based on cloud fusion and digital twinning technology

A diagnostic method and twinning technology, applied in image data processing, data processing applications, text database query, etc., can solve the problems of insufficient use of cloud services and backward technology, and achieve the effect of breaking information islands

Active Publication Date: 2020-12-15
ZHEJIANG UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The existing enterprise production diagnosis methods have the defects of backward technology, not fully utilizing cloud services, and large delays in data interaction between the cloud side and the device side

Method used

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  • Enterprise production status diagnosis method based on cloud fusion and digital twinning technology
  • Enterprise production status diagnosis method based on cloud fusion and digital twinning technology
  • Enterprise production status diagnosis method based on cloud fusion and digital twinning technology

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Embodiment Construction

[0050] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings.

[0051] 1. Applying this method to the diagnosis process of the production status of a manufacturing and assembly enterprise that produces instruments and meters, firstly divide the production resources and operating data in the production process of the enterprise. Among them, enterprise production resources include factors related to the full life cycle of products, such as workshop area, equipment type, equipment quantity, logistics route, enterprise employees, warehousing and other data. Enterprise operation data includes production capacity, work in progress, production process, workshop layout, production plan and other data. Data can be collected through the following operations:

[0052] a. Field research. Special personnel are responsible for conducting on-the-spot research on employee scheduling, production rhythm, and smoothness of...

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Abstract

The invention discloses an enterprise production status diagnosis method based on cloud fusion and a digital twinning technology. The method comprises the following steps: 1, dividing production resources and operation data in an enterprise production process; 2, virtualizing or digitalizing a physical entity workshop through a certain mapping relationship and data obtained by predicting the twinsystem to form a twin workshop; 3, predicting the obtained data of the production elements of the twinning workshop by using an artificial intelligence technology and a digital twinning technology; 4,diagnosing and improving the system; 5, enabling the monitoring system to monitor risks existing in enterprise production; and 6, realizing real-time interactive connection between the cloud serviceplatform at the cloud side and the physical entity workshop at the end side by using a cloud fusion technology, and feeding back the characteristics of data, optimization schemes and the like obtainedat the cloud side to the physical entity workshop through twin workshop projection, thereby satisfying an adaptation mechanism of each entity in the physical entity workshop. The production efficiency of enterprises can be improved, the current production situation of the enterprises is improved, and the product output quality is improved.

Description

technical field [0001] The invention relates to a method for diagnosing the production status of an enterprise. Background technique [0002] Digital twin is an emerging intelligent technology, which is a new method technology or system that integrates entity, virtual data and the hub connecting the two. Based on digital twin technology, physical entities in reality can be virtualized, that is, the behavior of physical entities in reality can be simulated and simulated with the help of data, and real-time monitoring can be carried out on the information platform. Operational control of physical entities in . At the same time, through a certain feedback system and iterative optimization of performance, combined with the corresponding artificial intelligence technology, the simulated twin body data is fed back to the physical entity in real time, and the physical entity can perform self-optimization and self-learning according to the feedback data, so as to improve the physic...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/04H04L29/08G06T17/00G06N3/04G06F30/27G06F16/33G06F16/31
CPCG06Q10/04G06Q10/0631G06F30/27G06T17/00H04L67/1097G06F16/31G06F16/334G06Q50/04H04L67/51G06N3/045Y02P90/30
Inventor 王亚良范欣宇倪晨迪高康洪张敏
Owner ZHEJIANG UNIV OF TECH
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