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GB/T 45507-2025: Intelligent service - Performance evaluation method of predictive maintenance
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Intelligent service - Performance evaluation method of predictive maintenance
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GB/T 45507-2025
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Basic data | Standard ID | GB/T 45507-2025 (GB/T45507-2025) | | Description (Translated English) | Intelligent service - Performance evaluation method of predictive maintenance | | Sector / Industry | National Standard (Recommended) | | Classification of Chinese Standard | N19 | | Classification of International Standard | 25.040.40 | | Word Count Estimation | 18,138 | | Date of Issue | 2025-03-28 | | Date of Implementation | 2025-10-01 | | Issuing agency(ies) | State Administration for Market Regulation, China National Standardization Administration | GB/T 45507-2025: Intelligent service - Performance evaluation method of predictive maintenance---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.
GB/T 45507-2025 English version. Intelligent service - Performance evaluation method of predictive maintenance
ICS 25.040.40
CCSN19
National Standard of the People's Republic of China
Performance evaluation method for predictive maintenance of intelligent services
Released on 2025-03-28
2025-10-01 Implementation
State Administration for Market Regulation
The National Standardization Administration issued
Table of Contents
Preface III
1 Scope 1
2 Normative references 1
3 Terms and Definitions 1
4 General Principles 1
5 Performance evaluation indicator system 3
5.1 Basic indicators 3
5.1.1 Downtime losses 3
5.1.2 Maintenance labor cost 3
5.1.3 Maintenance material costs 4
5.1.4 Management costs 4
5.1.5 System construction cost 4
5.1.6 Operating energy cost 4
5.1.7 Inventory costs 4
5.1.8 Production quality cost 5
5.1.9 Equipment failure rate 5
5.1.10 Mean time between failures 5
5.1.11 Equipment reliability 5
5.1.12 Equipment availability 5
5.1.13 Equipment service life 5
5.1.14 Inspection Time 6
5.1.15 Maintenance plan time 6
5.1.16 Maintenance preparation time 6
5.1.17 Maintenance implementation time 6
5.1.18 Total maintenance time 6
5.1.19 Total maintenance times 6
5.1.20 Average single maintenance time 6
5.2 Cost indicators 7
5.2.1 Total operation and maintenance cost 7
5.2.2 Risk Cost 7
5.2.3 System usage cost 7
5.2.4 System construction cost 8
5.3 Performance indicators 8
5.3.1 Overview 8
5.3.2 Performance evaluation indicators 8
5.3.3 Calculation method 9
5.3.3.1 Difference calculation method 9
5.3.3.2 Ratio calculation method 9
6 Performance Evaluation Process 9
Reference 11
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.
Please note that some of the contents of this document may involve patents. The issuing organization of this document does not assume the responsibility for identifying patents.
This document was proposed by the 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 was drafted by. Mechanical Industry Instrumentation Comprehensive Technical and Economic Research Institute, Frequency Exploration Intelligent Technology Jiangsu Co., Ltd., Weichai
Power Co., Ltd., Beijing Institute of Technology, Tsinghua University, Beijing Jiaotong University, CGN Research Institute Co., Ltd., China University of Petroleum (Beijing
Beijing), Wuhan Dongyan Smart Design Institute Co., Ltd., CNOOC Safety Technology Service Co., Ltd., Siemens (China) Co., Ltd., Sky
Fu (China) Co., Ltd., Shanghai Electric Group Co., Ltd., Chongqing University of Posts and Telecommunications, Luculent Smart Technology Co., Ltd., Shanghai Huaxing
Digital Technology Co., Ltd., University of Electronic Science and Technology of China, Beijing Benz Automotive Co., Ltd., Beijing Tianze Zhiyun Technology Co., Ltd., Southwest Jiaotong University
Institute of Physical Science, Chinese Academy of Sciences, Beijing Institute of Satellite Environment Engineering, Beijing University of Posts and Telecommunications, Qingdao Mingsiwei Technology Co., Ltd.
Hangzhou Sanhai Electronic Technology Co., Ltd., Beijing Jiaodongli Technology Co., Ltd., Shuocheng (Xiamen) Technology Co., Ltd., China Engineering Materials
Power Department of the Institute of Science and Technology, Schaeffler (China) Co., Ltd., Phoenix (China) Investment Co., Ltd., Schneider Electric (China) Co., Ltd.,
Chongqing Mengxun Electronic Technology Co., Ltd., the Fifth Electronic Research Institute of the Ministry of Industry and Information Technology, Nanjing Phoenix Contact Co., Ltd., Wuhan Zhongyun
Kangchong Technology Co., Ltd., China Railway Engineering Equipment Group Co., Ltd., Nanjing High-precision Gear Group Co., Ltd., Aerospace Intelligent Control (Beijing) Monitoring Technology
Technology Co., Ltd., Xi'an Yinlian Information Technology Co., Ltd., China National Electric Equipment Group Science and Technology Research Institute Co., Ltd., Wuhan University, Shanghai
Dazhi Technology Co., Ltd., Shanghai Hangshu Intelligent Technology Co., Ltd., FAW Jiefang Automobile Co., Ltd., Tsinghua University Shanxi Clean Energy Research Institute
Institute of Science and Technology, Hangzhou Anmaisheng Intelligent Technology Co., Ltd., Shanghai University of Technology, Sinochem Huayi Engineering Technology Group Co., Ltd., Chinese Academy of Sciences
Shenyang Automation Research Institute, Beijing Xinliantie Group Co., Ltd., Dandong Huatong Measurement and Control Co., Ltd., Liaoning University, China Special Equipment Inspection
Institute of Measurement and Testing, Central South University, Anhui Rongzhi Rixin Technology Co., Ltd., Fuzhou Xinan Intelligent Technology Co., Ltd., Shenzhen Shuanghe Smart Technology
Technology Co., Ltd., Beijing Huakong Zhijia Technology Co., Ltd., Dalian University of Technology, Shandong Energy Digital Cloud Technology Co., Ltd., Wuxi Hou
German Instrument Technology Research Institute Co., Ltd., Beijing Aerospace Measurement and Control Technology Co., Ltd., Xi'an Huayun Zhilian Information Technology Co., Ltd., Shanghai Steam Turbine
Machinery Factory Co., Ltd., Shijiazhuang Railway University.
The main drafters of this document are. Wang Chengcheng, Wang Kai, Yi Xiaojian, Zhang Feibin, Zhou Linfei, Zhang Kaihuan, Qin Yong, Zhu Chao, Huang Qingqing, Wang Jinjiang,
Huang Chenguang, Jin Chao, Huang Ziping, You Heping, Wang Min, Li Zhe, Qin Taichun, Tan Hongzhi, Guo Liang, Hu Jieying, Wang Biao, Guo Dongdong, Tang Huan, Zhang Zuchao,
Zuo Mingjian, Shen Deji, Wu Zhenyu, Qiao Jingyu, Qu Qianshang, Meng Li, An Huiping, Song Peng, Chang Guangzhong, Jiang Ningtao, Chen Jing, Tang Bo, Ding Xiaojian, Yang Ming,
Wang Peng, Cui Baozhou, He Qi, Jia Lianhui, Tang Li, Yang Sheng, Gong Songjian, Wang Peng, Hu Yong, Tian Qin, Guo Jiang, Xu Wei, Hu Peng, Yang Bingchun, Li Yiwen,
Zhao Xu, Zhang Xiao, Zhang Zhiyong, Xu Bin, Jiang Lijie, Zhang Jiwang, Wang Kai, Li Yun, Zhang Yang, Song Yan, Li Hongkun, Wang Kai, Liu Jia, Weng Liang, Wang Zhongfeng,
Ma Bing, Wang Peng, Yuan Fang, Wang Xiangxiang, Wu Jun, Zhang Haiyun, Ren Zhigang, Fei Qiang, Fang Hongzheng, Wen Yongliang, Du Wenbo, Wang Yongnian, Huang Jinfeng, Yu Yaoxiang,
Fanlei Meng, Yan Zhang, Jie Yu, Zechao Liu, Fengdan Li.
Performance evaluation method for predictive maintenance of intelligent services
1 Scope
This document specifies the performance evaluation index system and performance evaluation process for predictive maintenance of industrial equipment.
This document is applicable to manufacturers, users, solution providers and third parties to implement predictive maintenance of industrial equipment to determine its effectiveness and value.
Calculation and improvement.
2 Normative references
The contents of the following documents constitute essential clauses of this document through normative references in this document.
For referenced documents without a date, only the version corresponding to that date applies to this document; for referenced documents without a date, the latest version (including all amendments) applies to
This document.
GB/T 40571-2021 General requirements for predictive maintenance of intelligent services
GB/T 43555-2023 Evaluation method for predictive maintenance algorithms for intelligent services
3 Terms and definitions
The terms and definitions defined in GB/T 40571-2021, GB/T 43555-2023 and the following apply to this document.
3.1
Predictive maintenance
Maintenance that is performed continuously or intermittently based on observed conditions to monitor, diagnose, or predict the condition of a structure, system, or component.
Piece indicator.
[Source. GB/T 40571-2021, 3.5]
3.2
Preventive maintenance
Activities to detect, eliminate or mitigate degradation of structures, systems or components in use so that degradation and failures are kept to acceptable levels.
level to maintain or extend its service life.
[Source. GB/T 40571-2021, 3.6, modified]
3.3
Corrective repair
After a device fails, the fault is repaired to restore the normal operation of the device.
3.4
Maintenance
The combination of all technical and administrative activities performed to maintain or restore a product to a condition where it can perform its required functions.
NOTE. Includes supervisory activities.
[Source. GB/T 2900.99-2016, 192-06-01, modified]
4 General
This document is based on the evaluation of the complete equipment maintenance process and constructs a performance evaluation index system and evaluation method.
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