AI decision application method based on industrial internet identification operation and maintenance
By adopting AI decision -making methods in the Industrial Internet identification operation and maintenance, automated data analysis and decision -making processing, the problem of low efficiency of artificial decision -making has been solved, and efficient and accurate operation and maintenance management has been realized. User experience.
Patent Information
- Application Number
- CN202411342374.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-25
- Publication Date
- 2025-01-24
AI Technical Summary
The operation and maintenance decisions of existing industrial Internet logos mainly rely on manual labor, which leads to inefficiency and error-prone. The experience and thinking methods of different people lead to differences in processing results and impacts, making it difficult to efficiently manage massive data.
Adopt the use of AI decision -making and use methods based on the Industrial Internet, collect data through the AI platform, use AI algorithms to conduct in -depth analysis and intelligent decision -making, automatically identify and classify problems, trigger decision -making response mechanisms, and continue to learn the decision -making ability through continuous learning.
Greatly reduce artificial intervention, improve the efficiency and accuracy of operation and maintenance, reduce the risk of faults, optimize resource allocation, reduce operation and maintenance costs, and improve user experience and satisfaction.
Smart Images
Figure CN119359238A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of AI decision-making technology, and specifically to an AI decision-making application method based on industrial Internet identification operation and maintenance. Background Art
[0002] The industrial Internet field still faces many challenges in the management and operation and maintenance decision-making of industrial identification. Traditional verification methods are not only inefficient, but also rely heavily on manual decision-making, resulting in untimely problem discovery, long judgment time, and redundant reporting processes, which affects the stability and efficiency of the industrial Internet identification system. At the same time, with the continuous deepening of informatization, the cost of manual learning is also increasing. Because everyone's experience, skills, and thinking methods are different, the decision-making ideas issued are different, which will cause different results and impacts. With the rapid development of the industrial Internet, the number of industrial identification has increased dramatically. Faced with massive amounts of data, how to efficiently manage a series of problems brought about by identification has become a new pain point that needs to be solved urgently. Summary of the invention
[0003] 1. Technical issues to be solved
[0004] In view of the shortcomings of the prior art, the present invention provides an AI decision-making application method based on industrial Internet identification operation and maintenance, which is mainly used to solve the operation and maintenance problems of existing industrial Internet identification. The decision-making method is mainly manual decision-making. However, manual decision-making is inefficient and error-prone when encountering certain problems. Everyone's ideas and experiences will result in different ways of dealing with problems, resulting in different results and impacts.
[0005] (II) Technical solution
[0006] To achieve the above object, the present invention provides the following technical solutions:
[0007] An AI decision-making application method based on industrial Internet identification operation and maintenance includes the following steps:
[0008] S1: Data collection: First, data of various industrial identifiers are collected through the Industrial Internet AI platform;
[0009] S2: Intelligent analysis and decision-making, using AI algorithms to conduct in-depth analysis of the collected identification data, automatically identify and classify according to the frequency of errors based on preset verification rules and conditions;
[0010] S3: Automatic processing and feedback, preventive maintenance, early intervention and warning for common problems based on historical trends. For identified abnormal problems, the AI system will automatically trigger the corresponding decision-making response mechanism;
[0011] S4: Continuous optimization and learning. The AI system continuously learns and optimizes based on processing results and feedback information, and continuously improves its decision-making ability and accuracy.
[0012] Furthermore, the data of various industrial identifications collected in S1 include key information such as the unique prefix of the identification, registration time, and frequency of use.
[0013] On the basis of the above scheme, the AI model in S2 comprehensively considers multi-dimensional information such as the operating status of the entire system, manual decision-making information, historical data results, etc. during classification to make intelligent decision-making.
[0014] As a further solution of the present invention, the decision response mechanism in S3 includes but is not limited to sending alarm notifications, isolating abnormal identification, starting a repair process and taking offline certain abnormally identified devices.
[0015] Furthermore, the AI system in S3 will automatically trigger the corresponding decision-making response mechanism. At the same time, the AI system will also provide real-time feedback of the processing results to the operation and maintenance and management personnel, and provide detailed decision-making basis and suggestions.
[0016] (III) Beneficial effects
[0017] Compared with the prior art, the present invention provides an AI decision-making application method based on industrial Internet identification operation and maintenance, which has the following beneficial effects:
[0018] 1. The present invention greatly reduces manual intervention through automated detection and decision-making, improves the efficiency and accuracy of industrial identification operation and maintenance, and improves operation and maintenance efficiency.
[0019] 2. The present invention can reduce the risk of failure, timely discover and handle abnormal identification, and avoid the risk of system failure and downtime caused by identification problems.
[0020] 3. The present invention can optimize resource allocation, rationally allocate system resources based on AI intelligent analysis and decision-making, and reduce operation and maintenance costs.
[0021] 4. The present invention can improve user experience, reduce user complaints and dissatisfaction caused by processing problems, and improve user satisfaction and loyalty BRIEF DESCRIPTION OF THE DRAWINGS
[0022] Figure 1 A flowchart of an AI decision-making application method based on industrial Internet identification operation and maintenance proposed by the present invention;
[0023] Figure 2 This is a schematic diagram of an implementation solution for the AI decision-making proposed in the present invention in the industrial Internet identification operation and maintenance system. DETAILED DESCRIPTION
[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0025] Example 1
[0026] Reference Figure 1-Figure 2 , an AI decision-making application method based on industrial Internet identification operation and maintenance, including the following steps:
[0027] S1: Data collection: First, data of various industrial identifiers are collected through the Industrial Internet AI platform;
[0028] S2: Intelligent analysis and decision-making, using AI algorithms to conduct in-depth analysis of the collected identification data, automatically identify and classify according to the frequency of errors based on preset verification rules and conditions, and greatly reduce manual intervention through automated detection and decision-making, thereby improving the efficiency and accuracy of industrial identification operation and maintenance, and improving operation and maintenance efficiency;
[0029] S3: Automatic processing and feedback, preventive maintenance, early intervention and warning for common problems combined with historical trends. For identified abnormal problems, the AI system will automatically trigger the corresponding decision-making response mechanism to promptly discover and handle abnormal identification, avoid system failures and downtime risks caused by identification problems, and reduce failure risks;
[0030] S4: Continuous optimization and learning. The AI system continuously learns and optimizes based on processing results and feedback information, and continuously improves its decision-making ability and accuracy.
[0031] In the present invention, it should be noted that the data of various types of industrial identification collected in S1 include but are not limited to the key information of the unique prefix of the identification, registration time, and frequency of use. In S2, while classifying, the AI model comprehensively considers the operating status of the entire system, manual decision-making information, historical data results and other multi-dimensional information to make intelligent decision-making judgments. The decision-making response mechanism in S3 includes but is not limited to sending alarm notifications, isolating abnormal identifications, starting repair processes, and taking certain abnormal identification devices offline. The present invention can optimize resource allocation, based on AI intelligent analysis and decision-making, reasonably allocate system resources, and reduce operation and maintenance costs. The AI system in S3 will automatically trigger the corresponding decision response mechanism. At the same time, the AI system will also feedback the processing results to the operation and maintenance and management personnel in real time, and provide detailed decision-making basis and suggestions. The present invention can improve user experience, reduce user complaints and dissatisfaction caused by processing problems, and improve user satisfaction and loyalty.
[0032] First, historical operation and maintenance data, industry skill knowledge and official standard data are entered, then collected, processed and converted, and output to the AI interactive system. When problems occur or are about to occur in the field of industrial Internet identification, the AI interactive system automatically makes decisions, records problems, assists in troubleshooting and records trends, and then handles the problem. At the same time, the data of automatic decision-making, problem recording, auxiliary troubleshooting and trend recording are retained in the official standard data.
[0033] Example 2
[0034] Reference Figure 1-Figure 2 , an AI decision-making application method based on industrial Internet identification operation and maintenance, including the following steps:
[0035] S1: Data collection: First, the data of various industrial identifiers are collected through the Industrial Internet AI platform, including but not limited to the unique prefix of the identifier, registration time, and usage frequency.
[0036] S2: Intelligent analysis and decision-making, using AI algorithms to conduct in-depth analysis of the collected identification data, automatically identify and classify according to the frequency of errors based on preset verification rules and conditions. At the same time, the AI model comprehensively considers the operating status of the entire system, manual decision-making information, historical data results and other multi-dimensional information to make intelligent decisions;
[0037] S3: Automatic processing and feedback, preventive maintenance, early intervention and warning for common problems combined with historical trends. For identified abnormal problems, the AI system will automatically trigger the corresponding decision-making response mechanism, which includes but is not limited to sending alarm notifications, isolating abnormal identification, starting the repair process and offline certain abnormal identification equipment. At the same time, the AI system will also feedback the processing results to the operation and maintenance and management personnel in real time, and provide detailed decision-making basis and suggestions. The present invention can improve the efficiency of operation and maintenance, greatly reduce manual intervention through automated detection and decision-making, and improve the efficiency and accuracy of industrial identification operation and maintenance. At the same time, it can reduce the risk of failure, timely discover and process abnormal identification, and avoid the risk of system failure and downtime caused by identification problems;
[0038] S4: Continuous optimization and learning. The AI system continuously learns and optimizes according to the processing results and feedback information, and constantly improves its decision-making ability and accuracy. The present invention is based on AI's intelligent analysis and decision-making, rationally allocates system resources, reduces operation and maintenance costs, and optimizes resource allocation. At the same time, it can improve user experience, reduce user complaints and dissatisfaction caused by processing problems, and improve user satisfaction and loyalty.
[0039] It should be noted that historical operation and maintenance data, industry skill knowledge and official standard data are entered, then collected, processed and converted, and output to the AI interactive system. When problems occur or are about to occur in the field of industrial Internet identification, the AI interactive system will make automatic decisions, record problems, assist in troubleshooting and record trends, and then handle the problem. At the same time, the data of automatic decision-making, problem recording, auxiliary troubleshooting and recording trends are retained in the official standard data.
[0040] In the description of this article, it should be noted that relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.
Claims
1. An AI decision-making application method based on industrial Internet identification operation and maintenance, characterized in that: The following steps are involved: S1: Data collection: First, data of various industrial identifiers are collected through the Industrial Internet AI platform; S2: Intelligent analysis and decision-making, using AI algorithms to conduct in-depth analysis of the collected identification data, automatically identify and classify according to the frequency of errors based on preset verification rules and conditions; S3: Automatic processing and feedback, preventive maintenance, early intervention and warning for common problems based on historical trends. For identified abnormal problems, the AI system will automatically trigger the corresponding decision-making response mechanism; S4: Continuous optimization and learning. The AI system continuously learns and optimizes based on processing results and feedback information, and continuously improves its decision-making ability and accuracy.
2. According to claim 1, an AI decision-making and application method based on industrial Internet identification operation and maintenance is characterized in that: The data of various industrial identifications collected in S1 include, but are not limited to, key information such as the unique prefix of the identification, registration time, and usage frequency.
3. According to claim 2, an AI decision-making and application method based on industrial Internet identification operation and maintenance is characterized in that: In S2, while classifying, the AI model comprehensively considers multi-dimensional information such as the operating status of the entire system, manual decision-making information, historical data results, etc., to make intelligent decision-making judgments.
4. According to the AI decision-making and application method based on industrial Internet identification operation and maintenance according to claim 1, it is characterized in that: The decision response mechanism in S3 includes but is not limited to sending alarm notifications, isolating abnormal identification, starting the repair process and taking offline certain abnormal equipment.
5. According to claim 4, an AI decision-making and application method based on industrial Internet identification operation and maintenance is characterized in that: The AI system in S3 will automatically trigger the corresponding decision-making response mechanism. At the same time, the AI system will also provide real-time feedback of the processing results to the operation and maintenance and management personnel, and provide detailed decision-making basis and suggestions.