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Diagnosis method of enterprise production status based on cloud fusion and digital twin technology

A diagnostic method and twinning technology, applied in data processing applications, image data processing, text database query, etc., can solve problems such as not fully utilizing cloud services and backward technology

Active Publication Date: 2022-06-21
ZHEJIANG UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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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  • Diagnosis method of enterprise production status based on cloud fusion and digital twin technology
  • Diagnosis method of enterprise production status based on cloud fusion and digital twin technology
  • Diagnosis method of enterprise production status based on cloud fusion and digital twin technology

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Embodiment Construction

[0050] The technical solutions of the present invention are further described below with reference to the accompanying drawings.

[0051] 1. This method is applied to the diagnosis process of the production status of a manufacturing and assembly enterprise that produces instruments. First, the production resources and operating data in the production process of the enterprise are divided. Among them, the production resources of enterprises include factors related to the whole life cycle of products, such as workshop area, equipment types, equipment quantity, logistics routes, enterprise employees, warehousing and other data. Enterprise operation data includes data such as production capacity, number of products in process, production process, workshop layout, and production plan. Data can be collected by:

[0052] a. Field research. Special personnel are responsible for conducting field research on staff scheduling, production rhythm, and smoothness of logistics routes at th...

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Abstract

The diagnosis method of enterprise production status based on cloud integration and digital twin technology includes: Step 1. Divide the production resources and operation data in the production process of the enterprise; Realize virtualization or digitalization of physical workshops to form twin workshops; Step 3. Use artificial intelligence technology and digital twin technology to predict the data of the production factors of the twin workshops; Step 4. Diagnose and improve the system; Step 5. Monitoring system for enterprise production Monitor the risks existing in the system; step 6. Use cloud fusion technology to realize real-time interactive connection between the cloud service platform on the cloud side and the physical entity workshop on the end side, and feed back the data obtained on the cloud side, optimization plans and other characteristics to the The physical entity workshop satisfies the adaptation mechanism of each entity in the physical entity workshop. The invention can improve the production efficiency of the enterprise, improve the production status of the enterprise, and improve the output quality of products.

Description

technical field [0001] The invention relates to a method for diagnosing production status of an enterprise. Background technique [0002] Digital twin is an emerging intelligent technology that integrates physical, virtual data and the hub connecting the two to form a new method technology or system. Based on the digital twin technology, the 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 performed on the information-based platform. The physical entities in the operation control. 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 to achieve improve...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/04H04L67/51G06T17/00G06N3/04G06F30/27G06F16/33G06F16/31H04L67/1097
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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