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GB/T 42127-2022: Intelligent manufacturing - Industrial data - Collection specification
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Intelligent manufacturing - Industrial data - Collection specification
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GB/T 42127-2022
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Basic data | Standard ID | GB/T 42127-2022 (GB/T42127-2022) | | Description (Translated English) | Intelligent manufacturing - Industrial data - Collection specification | | Sector / Industry | National Standard (Recommended) | | Classification of Chinese Standard | N10 | | Classification of International Standard | 25.040 | | Word Count Estimation | 10,128 | | Date of Issue | 2022-12-30 | | Date of Implementation | 2023-07-01 | | Issuing agency(ies) | State Administration for Market Regulation, China National Standardization Administration | GB/T 42127-2022: Intelligent manufacturing - Industrial data - Collection specification---This is a DRAFT version for illustration, not a final translation. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.) will be manually/carefully translated upon your order.
ICS 25.040
CCSN10
National Standards of People's Republic of China
Industrial Data Acquisition Specifications for Intelligent Manufacturing
Posted on 2022-12-30
2023-07-01 implementation
State Administration for Market Regulation
Released by the National Standardization Management Committee
table of contents
Preface I
Introduction II
1 Scope 1
2 Normative references 1
3 Terms, Definitions and Abbreviations 1
3.1 Terms and Definitions 1
3.2 Abbreviations 1
4 Data source and collection method 1
4.1 Industrial Data Sources 1
4.2 Industrial data collection method 2
5 Industrial Data Acquisition Requirements 2
5.1 General requirements 2
5.2 Data source requirements 3
5.3 Data Communication Protocol Requirements 3
5.4 Data Format Requirements 3
5.5 Data collection and monitoring requirements 3
Reference 5
foreword
This document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for Standardization Work Part 1.Structure and Drafting Rules for Standardization Documents"
drafting.
This document is proposed by China Machinery Industry Federation.
This document is under the jurisdiction of the National Industrial Process Measurement Control and Automation Standardization Technical Committee (SAC/TC124).
This document is drafted by. Shanghai Industrial Automation Instrument Research Institute Co., Ltd., Wuhan Marine Machinery Co., Ltd., Chongqing University of Posts and Telecommunications
Industrial Internet Research Institute, Xi'an Shaangu Power Co., Ltd., Machinery Industry Instrumentation Comprehensive Technology and Economic Research Institute, China Electronics
Technology Standardization Research Institute, Guangzhou Energy Testing Research Institute, Hunan University of Science and Technology, Zhejiang Supcon Automation Instrument Co., Ltd., Shanghai Intelligent Manufacturing
Functional Platform Co., Ltd., Siemens (China) Co., Ltd., Xi'an Shaangu Intelligent Information Technology Co., Ltd., Dongfeng Design and Research Institute Co., Ltd.
Division, Electric Power Planning General Institute Co., Ltd., Dongguan Institute of Technology, Xiamen Yudian Automation Technology Co., Ltd., Beijing Tiantuo Sifang Technology Co., Ltd.
Company, Shanghai Intelligent Manufacturing System Innovation Center Co., Ltd., Xinte Energy Co., Ltd., Shanghai Electric Appliance Research Institute (Group) Co., Ltd.
Division, Shanghai Advanced Research Institute of Chinese Academy of Sciences, Shenergy (Group) Co., Ltd., Ruili Group Ruian Auto Parts Co., Ltd., Hangzhou Woleizhi
Energy Technology Co., Ltd., Zhejiang Aoxiang Automatic Control Technology Co., Ltd., Wenzhou University.
The main drafters of this document. Wang Ying, Li Wei, Huang Qingqing, Xiao Honglian, Tian Weirong, Zhang Guiling, He Honghong, Wan Yong, Cheng Jixun, Yu Liming,
Liu Jun, Zhu Guoliang, Li Bo, You Heping, Zhang Jinbin, Zhang Aisen, Sun Yuxin, Wang Gaohong, Dong Ying, Zhang Zhaoyun, Su Xiaoli, Yang Gengxin, Mei Jun, Liu Xiong,
Shen Wenting, Ning Dejun, Xiao Wenkai, Hu Zhengchu, Fan Weijun, Cai Dongwu, Cao Yu, Wang Linying, Zhang Shengli, Li Jia, Han Li, Wang Fei.
Introduction
This document is guided by the intelligent manufacturing system architecture proposed in the "Guidelines for the Construction of National Intelligent Manufacturing Standard System (2021 Edition)".
The intelligent manufacturing system architecture analyzes the activities, equipment, and features involved in intelligent manufacturing from three dimensions. life cycle, system level, and intelligent features.
The symptoms and other contents are described, as shown in Figure 1.
Figure 1 Architecture of intelligent manufacturing system
The life cycle covers all stages from product prototype development to product recycling and remanufacturing, including design, production, logistics, sales, service
services and a series of interrelated value creation activities.
The system level refers to the hierarchical division of the organizational structure related to the production activities of the enterprise, including the equipment level, unit level, workshop level, enterprise level and
Collaboration layer.
Intelligent features refer to the representation of self-perception, self-decision-making, self-execution, self-learning, self-adaptation and other functions of manufacturing activities, including resource
5 layers of intelligent requirements such as elements, interconnection, integration and sharing, system integration and emerging formats.
In order to illustrate the corresponding relationship between industrial data acquisition and intelligent manufacturing system architecture, it is convenient for the implementation of data acquisition in intelligent factories.
In this document, the location of industrial data sources in the "system hierarchy" and the corresponding relationship between data collection methods and each layer of the "system hierarchy" are carried out.
explained. For ease of understanding, the description of each layer of the "system level" is as follows.
---Equipment layer refers to the use of sensors, instruments, machines, devices, etc. to realize the actual physical process and perceive and control the logistics flow
program level;
--- The unit layer refers to the layer used to process information, realize monitoring and control physical processes within the enterprise;
---The workshop level is the level to realize the production management facing the factory or workshop;
---Enterprise layer is the layer that realizes business-oriented management;
---The collaboration layer is the layer where enterprises realize the interconnection and sharing of internal and external information, and realize business collaboration between enterprises.
Industrial Data Acquisition Specifications for Intelligent Manufacturing
1 Scope
This document specifies the general specifications for industrial data collection in intelligent manufacturing.
This document is applicable to the planning and collection of data resources of discrete and process industry enterprises.
2 Normative references
The contents of the following documents constitute the essential provisions of this document through normative references in the text. Among them, dated references
For documents, only the version corresponding to the date is applicable to this document; for undated reference documents, the latest version (including all amendments) is applicable to
this document.
GB/T 42128-2022 Principles of Industrial Data Classification for Intelligent Manufacturing
3 Terms, Definitions and Abbreviations
The following terms and definitions apply to this document.
3.1 Terms and Definitions
3.1.1
data collection data collection
Access to data from sensors, transmitters and other physical signal sources, controllers, monitoring systems, and enterprise information or business management systems
process.
3.1.2
data qualitydataquality
The degree to which a characteristic of data satisfies stated and implied requirements when used under specified conditions.
[GB/T 36344-2018,2.3]
3.2 Abbreviations
The following abbreviations apply to this document.
4 Data sources and collection methods
4.1 Industrial Data Sources
There are two types of data sources for industrial data.
a) Industrial site perception and control equipment, including sensors, controllers, actuators, monitoring systems, etc.
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