GB/T 42127-2022Intelligent manufacturing - Industrial data - Collection specification (English PDF)

Foreword

This document was issued on 30 December 2022 by the State Administration for Market Regulation; Standardization Administration of the PRC and takes effect on 1 July 2023.

It is a GB/T standard: recommended rather than compulsory, but it is the text a Chinese reviewer applies when assessing a submission.

It is classified under ICS 25.040, Chinese classification N10.

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

GB/T 42127-2022 covers the collection of industrial data in intelligent manufacturing, for discrete and process plants planning what data they will hold and how they will take it. It begins with the sources and the collection methods: sensing and control equipment on the shop floor — sensors, controllers, actuators, monitoring systems — alongside the other class of source named in the clause, and the methods that suit each. The requirements clause then sets general rules and works through the data source, the communication protocol, the data format, and the collection and monitoring of the process itself. That last item is the one a plant pays for when it is missing. Data gathered without an agreed format and without a watch on the collection path becomes a historian nobody can read two years later: timestamps that do not line up between lines, tags whose meaning lives only in the head of the engineer who configured them, and silent gaps where a gateway stopped publishing and nothing raised an alarm, found only when someone tries to trace a defective batch. Written for manufacturers building out data collection, for the integrators and platform suppliers doing the work, and for those specifying it in a contract.

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.