Intelligent work order distribution method and system for electromechanical maintenance, medium and equipment

Abstract

The invention discloses an intelligent work order distribution method, system, medium and equipment for electromechanical maintenance, the system comprises an intelligent work order integration system and an intelligent work order robot, the intelligent work order integration system is used for gathering, processing and distributing work orders, and the intelligent work order robot is used for semantic analysis, task mapping and data adaptation. The method has the advantages that through intelligent semantic analysis and multi-platform work order automatic deduplication and combination, maintenance personnel are liberated from repeated input work. Actual measurement data shows that the system can reduce work order processing time by more than 50%, and the overall efficiency of maintenance work is greatly improved. A worker only needs to complete operation on one platform, the system can automatically synchronize to other related platforms, and the industrial pain point caused by repeated input of multiple platforms is thoroughly solved.

Description

Technical Field

[0001] The present invention relates to the field of industrial Internet, and specifically to an intelligent work order distribution method, system, medium and equipment for electromechanical maintenance. Background Art

[0002] In the field of electromechanical equipment maintenance, the existing work order management system has prominent problems such as repeated entry on multiple platforms, semantic conflicts, poor data flow security, and low quality inspection efficiency. Maintenance personnel often need to repeatedly fill out the same work order on multiple independent platforms (such as the electromechanical business management platform, the electromechanical maintenance platform, etc.), which accounts for a high proportion of manual time. In addition, due to differences in terminology between platforms (such as "brake inspection" and "brake detection"), the system cannot automatically merge tasks, resulting in high coordination costs. In addition, the cross-platform work order feedback relies on manual operation, which has a high failure rate, and unencrypted transmission is prone to data leakage risks; the quality inspection link relies on manual review, with a missed detection rate of over 30%, making it difficult to verify the authenticity of the operation in real time. Existing solutions (such as simple API docking) cannot solve the problems of semantic fusion and end-to-end security.

[0003] In view of this, it is necessary to provide an intelligent work order allocation method, system, medium and equipment for electromechanical maintenance. Summary of the Invention

[0004] The present invention provides an intelligent work order allocation method, system, medium and equipment for electromechanical maintenance, which effectively solves the problems of low efficiency in allocating work orders and repeated dispatching of work orders in existing work order management systems.

[0005] The technical solution adopted in the present invention is:

[0006] An intelligent work order distribution system for electromechanical maintenance includes an intelligent work order integration system and an intelligent work order robot. The intelligent work order integration system is used to aggregate, process and dispatch work orders, and the intelligent work order robot is used for semantic analysis, task mapping and data adaptation.

[0007] The intelligent work order integration system specifically includes:

[0008] The intelligent work order system aggregation module is used to aggregate work requirements from different platforms;

[0009] An intelligent work order engine module, which is used to dynamically reorganize work processes based on an inference framework and supports the regeneration and dispatch of work orders;

[0010] The task platform module is used to dispatch workers based on site conditions and personnel schedules;

[0011] On the mobile side, staff can record their work content by selecting, taking photos, videos, and text;

[0012] The quality inspection module is used to monitor the safety and quality of the operation process in real time and compare the operation records with the standard operating requirements through the residual network;

[0013] Big data module, used to store equipment, personnel, and work order data, and supports encrypted data flow;

[0014] The intelligent work order robot specifically includes:

[0015] The business rule knowledge base has a semantic parsing unit and uses the BERT model to identify the semantic equivalence of work order texts on different platforms, supporting manual calibration and machine learning updates.

[0016] The task mapping and data adaptation module is used to establish a correlation matrix between platform requirements and national and industry standards, support the merging, deduplication, and recombination of work orders, and generate standardized XML / JSON format output;

[0017] The encryption channel establishment and key verification module is used to establish the mapping relationship between the original platform work order and the summary order and the key pair;

[0018] The RPA executor module is used to configure multi-threaded task scheduling strategies to achieve cross-platform data synchronization.

[0019] Furthermore, the semantic parsing unit adopts a dynamic threshold adjustment mechanism, and its similarity determination formula is:

[0020] S=α·cosθ+β·J(W1,W2)

[0021] Where α+β=1, β=X·e^(-t / τ), X is the empirical value, cosθ is the cosine similarity of text vectors, J is the Jaccard word set similarity, and τ is the platform characteristic parameter.

[0022] Furthermore, the dynamic threshold adjustment mechanism is used to redesign the deduplicated and merged operation content based on the requirements and specifications of the special equipment for the operation, the historical operation process of the equipment, the equipment form and spatial logic.

[0023] Furthermore, the business knowledge base is based on the special equipment terminology library, standardizes the terminology of work order texts on different platforms, and extracts the core operation elements in the work order through dependency syntax analysis; matches the parsed elements with the industry standard terms in the knowledge graph to generate an equivalent task set.

[0024] Furthermore, the quality inspection module includes:

[0025] Image recognition unit to detect compliance of maintenance operations;

[0026] A data analysis unit, used to verify the integrity of the operation steps through feature extraction;

[0027] The time and space verification unit is used to combine GPS / Beidou positioning data, network clock and equipment operation log for cross-verification.

[0028] Furthermore, the work order regenerated by the intelligent work order engine module is matched with the original work order through different key pairs to ensure the timeliness, confidentiality and reliability of the source work order.

[0029] The intelligent work order allocation method for electromechanical maintenance includes the following steps:

[0030] S1. The intelligent work order system aggregation module receives the operation requirements of different work order platforms;

[0031] S2. The smart work order robot receives the work order content summarized in the smart work order integration system;

[0032] S3, the intelligent work order robot uses a semantic analysis module to identify common needs, establish a task mapping model, and achieve the merging, deduplication, and combination of work orders;

[0033] S4, the intelligent work order engine module receives the work orders merged, deduplicated, and combined by the intelligent work order robot in S3;

[0034] S5, the task platform module receives the work order dispatched by the intelligent work order engine module in S4;

[0035] S6. Workers complete work records and quality inspections through mobile devices, and the quality inspection results are transmitted back to the original work order platform or through smart work order robots for cross-platform data adaptation and automatic transmission.

[0036] Furthermore, the work order is encrypted using the national encryption SM4 algorithm during the distribution and reception process, and an independent key pair is generated for each work order.

[0037] A computer-readable storage medium stores a computer program, which, when processed and executed, implements the steps of the intelligent work order allocation method for electromechanical maintenance.

[0038] A computer device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus:

[0039] The memory is used to store computer programs;

[0040] The processor is used to execute the steps of the intelligent work order allocation method for electromechanical maintenance by running the program stored in the memory.

[0041] Beneficial effects of the invention:

[0042] 1. Through intelligent semantic analysis and automatic deduplication and merging of work orders across multiple platforms, maintenance personnel are relieved of the need for repetitive data entry. Tested data shows that the system can reduce work order processing time by over 50%, significantly improving overall maintenance efficiency. Workers only need to complete operations on one platform, and the system automatically synchronizes them across other related platforms, completely resolving the industry pain point of repetitive data entry across multiple platforms.

[0043] 2. A semantic analysis module based on the BERT model and the special equipment knowledge graph accurately identifies various representations of the same maintenance task across different platforms. Through a three-level processing process (lexical normalization, syntactic parsing, and semantic mapping), the system reduces the work order conflict rate caused by representational discrepancies from the industry average of 25% to below 3%, significantly improving the accuracy of work order management.

[0044] 3. This invention uses the national SM4 algorithm to encrypt work order content and generates a unique key pair for each work order, ensuring security from work order generation to transmission. This mechanism reduces the risk of data leakage to below 0.1%, fully meeting the high security requirements of special equipment operation and maintenance.

[0045] 4. By integrating image recognition, spatiotemporal verification, and real-time data analysis, the intelligent quality inspection platform of this invention can increase the detection rate of maintenance defects from 70% with traditional manual quality inspection to over 95%. The system automatically compares work records with standard operating requirements, identifying and issuing warnings of non-compliant operations in real time, effectively preventing safety accidents caused by maintenance omissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A flowchart of an intelligent work order allocation method for electromechanical maintenance provided in an embodiment of the present application.

[0047] Figure 2 A framework diagram of the intelligent work order distribution system for electromechanical maintenance and the work order demand platform provided in an embodiment of the present application.

[0048] Figure 3 A framework diagram of the intelligent work order integration system for the intelligent work order distribution system for electromechanical maintenance provided in an embodiment of the present application.

[0049] Figure 4 This is a framework diagram of the intelligent work order robot for the intelligent work order distribution system for electromechanical maintenance provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0051] like Figure 2 As shown, the first embodiment provided by this application is an intelligent work order distribution system for electromechanical maintenance, including an intelligent work order integration system and an intelligent work order robot. The intelligent work order integration system is used to aggregate, process and dispatch work orders, and the intelligent work order robot is used for semantic analysis, task mapping and data adaptation.

[0052] The intelligent work order integration system specifically includes:

[0053] Intelligent work order system aggregation module, namely Figure 3 The intelligent work order aggregation layer in is used to aggregate job requirements from different platforms;

[0054] Intelligent work order engine module, namely Figure 3 The intelligent work order system engine in is used to dynamically reorganize the work process based on the reasoning framework and support the regeneration and dispatch of work orders;

[0055] Task platform module, i.e. Figure 3 The task platform in the system is used to dispatch workers based on the site conditions and staff schedules;

[0056] Mobile, that is Figure 3 The business operation end of the app supports staff to record work content by selecting, taking photos, videos, and text;

[0057] Quality inspection module, i.e. Figure 3 The quality inspection platform is used to monitor the safety and quality of the operation process in real time, and compare the operation records with the standard operating requirements through the residual network;

[0058] Big data module, i.e. Figure 3 The elevator big data platform is used to store equipment, personnel, and work order data, and supports encrypted data flow;

[0059] The intelligent work order robot specifically includes:

[0060] Business rule knowledge base, i.e. Figure 4 The entry rule knowledge base in the platform has a semantic parsing unit, uses the BERT model to identify the semantic equivalence of work order texts on different platforms, and supports manual calibration and machine learning updates.

[0061] The task mapping and data adaptation module is used to establish a correlation matrix between platform requirements and national and industry standards, support the merging, deduplication, and recombination of work orders, and generate standardized XML / JSON format output;

[0062] The encryption channel establishment and key verification module is used to establish the mapping relationship between the original platform work order and the summary order and the key pair;

[0063] The RPA executor module is used to configure multi-threaded task scheduling strategies to achieve cross-platform data synchronization. This includes calling RPA tools, automatically identifying the corresponding platform, and writing back the corresponding content.

[0064] In specific implementation, combined with Figure 2 、 Figure 3 and Figure 4 , assuming that the platforms requiring work order requirements include the large-scale property / enterprise special equipment management platform, the medium-sized property / enterprise special equipment management platform, the special equipment supervision platform in place A, the special equipment supervision platform in place B, and the special equipment supervision platform in place X; the intelligent work order integration system receives the work order information of the large-scale property / enterprise special equipment management platform, the medium-sized property / enterprise special equipment management platform, the special equipment supervision platform in place A, the special equipment supervision platform in place B, and the special equipment supervision platform in place X, and establishes key pairs with the large-scale property / enterprise special equipment management platform, the medium-sized property / enterprise special equipment management platform, the special equipment supervision platform in place A, the special equipment supervision platform in place B, and the special equipment supervision platform in place X respectively. The work order requirements of different platforms are then sent to the smart work order robot through a key. After receiving the work order requirements, the smart work order robot performs task mapping, merges, deduplicates and recombines all work orders according to the job type, and pushes them to the smart work order integration system. After the operator completes the task order in the smart work order system, the smart work order system can push the job content to other integrated platforms through the interface. At the same time, the smart work order system will push the job results to the smart work order robot, and the smart work order robot will send the job results to the corresponding platform.

[0065] like Figure 3, Another embodiment, there are platforms and requirements for work order needs: large property / enterprise management agencies (with business platforms and work order management platforms), small and medium-sized property / enterprise management agencies (with management requirements), special inspection institutes (special equipment laws and regulations; local management requirements), electromechanical equipment Internet of Things (equipment life, load, operation monitoring, one elevator one thing). When distributing work orders, small and medium-sized property / enterprise management agencies, special inspection institutes and electromechanical equipment Internet of Things will send the required operation requirements in the form of work orders to the intelligent work order system aggregation layer. Large property / enterprise management agencies will send them to the task platform through the special equipment business management platform of large enterprises and then transmit them. To the intelligent work order aggregation layer, the intelligent work order aggregation layer integrates national standards and regulatory inspection requirements, contract requirements, special equipment information, project basic information, etc., and then the intelligent work order aggregation layer sends all work orders to the intelligent work order system engine. The intelligent work order engine system dynamically reorganizes all work orders and sends them to the task platform. The task platform sends the work orders required by large property / enterprise management agencies to the special equipment business management platform of the large enterprise they own, and sends the remaining work orders to the business operation end and then to the elevator big data platform through the quality inspection platform. Then, through the elevator big data platform, they are sent to small and medium-sized property / enterprise management agencies, special inspection institutes and the Internet of Things for electromechanical equipment.

[0066] like Figure 4 Another embodiment mainly uses a smart work order robot to directly send work orders to various platforms. The platforms that require work orders include large-scale property / enterprise special equipment management platforms, medium-sized property / enterprise special equipment management platforms, special equipment supervision platforms in location A, special equipment supervision platforms in location B, and special equipment supervision platforms in location X. The work orders from each platform are aggregated and summarized by the demand aggregation layer and sent to the business rule knowledge base. The entries are merged, deduplicated, and rearranged, and then reviewed by the expert review and judgment mechanism to generate actual work orders. The actual work orders are then sent to on-site operators. After the work is completed, the on-site operators record the work results through the mobile terminal, then call the RPA tool, automatically identify the corresponding platform, write back the corresponding work order content, and then send the corresponding work order to each platform.

[0067] The above design can avoid maintenance personnel from repeatedly filling in the same work content on different platforms, and can automatically review work order applications on different platforms to avoid duplication of labor due to different ways of expressing work order requests, thereby improving maintenance efficiency.

[0068] Specifically: the semantic parsing unit adopts a dynamic threshold adjustment mechanism, and its similarity determination formula is:

[0069] S=α·cosθ+β·J(W1,W2)

[0070] Where α+β=1, β=X·e^(-t / τ), X is the empirical value, cosθ is the cosine similarity of text vectors, J is the Jaccard word set similarity, and τ is the platform characteristic parameter.

[0071] During the specific implementation, different work order texts are input, such as "elevator maintenance" and "elevator inspection". Assuming that the word set similarity of "elevator maintenance" and "elevator inspection" is 0.75, the text vector similarity is 0.85, and the preset platform characteristic parameter is 10, if the calculation results are S=A, which is greater than the preset S threshold Y, then elevator maintenance and elevator inspection are the same task.

[0072] In the above design, the dynamic threshold adapts to the differences in expressions on different platforms, and can continuously optimize the calculation of similarity and improve the accuracy of work order comparison.

[0073] Specifically: the dynamic threshold adjustment mechanism is used to redesign the deduplicated and merged operation content based on the requirements and specifications of special equipment for the operation, the historical operation process of the equipment, the equipment form and spatial logic.

[0074] Specifically: The business knowledge base is based on the special equipment terminology library, standardizes the terminology of work order texts on different platforms, and extracts the core operation elements in the work order through dependency syntax analysis; matches the parsed elements with the industry standard terms in the knowledge graph to generate an equivalent task set.

[0075] Specifically: the quality inspection module includes:

[0076] Image recognition unit to detect compliance of maintenance operations;

[0077] A data analysis unit, used to verify the integrity of the operation steps through feature extraction;

[0078] The time and space verification unit is used to combine GPS / Beidou positioning data, network clock and equipment operation log for cross-verification.

[0079] During specific implementation, if an elevator needs maintenance, the maintenance personnel upload photos of the elevator door lock inspection. The quality inspection module compares the standard operation pictures through the residual network, finds missed screws, marks them as defects, and completes image recognition; the system verifies the GPS coordinates in the operation record (consistent with the elevator location), network timestamp (within the planned time), and equipment log (door lock status has been updated) to confirm the authenticity of the operation and complete time and space verification and data analysis.

[0080] The above design can effectively eliminate false work orders and improve the verification efficiency and accuracy of maintenance projects.

[0081] Specifically: the work order regenerated by the intelligent work order engine module has a different key pair from the original work order.

[0082] For example, if the work order issued by the original demand platform is "fire hydrant maintenance", the key pair at this time is public key B and private key b. After the intelligent work order system receives "fire hydrant maintenance", it will be re-transmitted as "fire hydrant inspection". At this time, the key pair is public key C and private key c.

[0083] The above design can improve the accuracy of work order verification.

[0084] like Figure 1 As shown, the second embodiment provided by the present application is an intelligent work order allocation method for electromechanical maintenance, comprising the following steps:

[0085] S1. The intelligent work order system aggregation module receives the operation requirements of different work order platforms;

[0086] S2. The smart work order robot receives the work order content summarized in the smart work order integration system;

[0087] S3, the intelligent work order robot uses a semantic analysis module to identify common needs, establish a task mapping model, and achieve the merging, deduplication, and combination of work orders;

[0088] S4, the intelligent work order engine module receives the work orders merged, deduplicated, and combined by the intelligent work order robot in S3;

[0089] S5, the task platform module receives the work order dispatched by the intelligent work order engine module in S4;

[0090] S6. Workers complete work records and quality inspections through mobile devices, and the quality inspection results are transmitted back to the original work order platform or through smart work order robots for cross-platform data adaptation and automatic transmission.

[0091] Specifically: the work order is encrypted using the national secret SM4 algorithm during the distribution and reception process, and an independent key pair is generated for each work order.

[0092] For example, the work order content is "Repair of distribution box in community A". After being encrypted through SM4, a key pair (public key A and private key a) is generated. After the recipient receives the distributed work order, it displays "***Distribution box 8*" and uses private key a to decrypt it to obtain the work order content "Repair of distribution box in community A".

[0093] In the above design, by encrypting the work order, the confidentiality of data transmission can be guaranteed and information leakage can be prevented.

[0094] The third embodiment provided by this application is a computer-readable storage medium storing a computer program that, when executed, implements the steps of the intelligent work order assignment method for electromechanical maintenance. Furthermore, the computer-readable storage medium provided in this embodiment may employ any combination of one or more readable storage media, wherein the readable storage medium includes electrical, optical, electromagnetic, infrared, or semiconductor systems, devices, or components, or any combination thereof.

[0095] A fourth embodiment provided by the present application is a computer device, comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus.

[0096] The memory is used to store computer programs;

[0097] The processor is configured to execute the steps of the intelligent work order allocation method for electromechanical maintenance by running the program stored in the memory. As one embodiment of the present invention, the communication bus mentioned in the terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The communication bus can be divided into an address bus, a data bus, a control bus, etc.

[0098] As an embodiment of the present invention, the communication interface is used for communication between the above-mentioned terminal and other devices.

[0099] As an embodiment of the present invention, the memory may include random access memory (RAM) or non-volatile memory, such as at least one disk storage. Optionally, the memory may also be at least one storage device located remote from the processor.

[0100] As an embodiment of the present invention, the above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0101] To explain in further detail, it should be understood that the above is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An intelligent work order distribution system for electromechanical maintenance, characterized by: It includes an intelligent work order integration system and an intelligent work order robot. The intelligent work order integration system is used to aggregate, process and dispatch work orders, and the intelligent work order robot is used for semantic analysis, task mapping and data adaptation. The intelligent work order integration system specifically includes: The intelligent work order system aggregation module is used to aggregate work requirements from different platforms; An intelligent work order engine module, which is used to dynamically reorganize work processes based on an inference framework and supports the regeneration and dispatch of work orders; The task platform module is used to dispatch workers based on site conditions and personnel schedules; On the mobile side, staff can record their work content by selecting, taking photos, videos, and text; The quality inspection module is used to monitor the safety and quality of the operation process in real time and compare the operation records with the standard operating requirements through the residual network; Big data module, used to store equipment, personnel, and work order data, and supports encrypted data flow; The intelligent work order robot specifically includes: The business rule knowledge base has a semantic parsing unit and uses the BERT model to identify the semantic equivalence of work order texts on different platforms, supporting manual calibration and machine learning updates. The task mapping and data adaptation module is used to establish a correlation matrix between platform requirements and national and industry standards, support the merging, deduplication, and recombination of work orders, and generate standardized XML / JSON format output; The encryption channel establishment and key verification module is used to establish the mapping relationship between the original platform work order and the summary order and the key pair; The RPA executor module is used to configure multi-threaded task scheduling strategies to achieve cross-platform data synchronization.

2. The intelligent work order distribution system for electromechanical maintenance according to claim 1 is characterized in that: The semantic parsing unit adopts a dynamic threshold adjustment mechanism, and its similarity determination formula is: S=α·cosθ+β·J(W1,W2) Where α+β=1, β=X·e^(-t / τ), X is the empirical value, cosθ is the cosine similarity of text vectors, J is the Jaccard word set similarity, and τ is the platform characteristic parameter.

3. The intelligent work order distribution system for electromechanical maintenance according to claim 2 is characterized in that: The dynamic threshold adjustment mechanism is used to redesign the deduplicated and merged operation content based on the requirements and specifications of the special equipment for the operation, the historical operation process of the equipment, the equipment form and spatial logic.

4. The intelligent work order distribution system for electromechanical maintenance according to claim 1 is characterized in that: The business knowledge base is based on the special equipment terminology library, standardizes the terminology of work order texts on different platforms, and extracts the core operation elements in the work order through dependency syntax analysis; matches the parsed elements with the industry standard terms in the knowledge graph to generate an equivalent task set.

5. The intelligent work order distribution system for electromechanical maintenance according to claim 1 is characterized in that: The quality inspection module includes: Image recognition unit to detect compliance of maintenance operations; A data analysis unit, used to verify the integrity of the operation steps through feature extraction; The time and space verification unit is used to combine GPS / Beidou positioning data, network clock and equipment operation log for cross-verification.

6. The intelligent work order distribution system for electromechanical maintenance according to claim 1 is characterized in that: The work order regenerated by the intelligent work order engine module is matched with the original work order through different key pairs.

7. An intelligent work order allocation method for electromechanical maintenance, characterized by: The following steps are included: S1. The intelligent work order system aggregation module receives the operation requirements of different work order platforms; S2. The smart work order robot receives the work order content summarized in the smart work order integration system; S3, the intelligent work order robot uses a semantic analysis module to identify common needs, establish a task mapping model, and achieve the merging, deduplication, and combination of work orders; S4, the intelligent work order engine module receives the work orders merged, deduplicated, and combined by the intelligent work order robot in S3; S5, the task platform module receives the work order dispatched by the intelligent work order engine module in S4; S6. Workers complete work records and quality inspections through mobile devices, and the quality inspection results are transmitted back to the original work order platform or through smart work order robots for cross-platform data adaptation and automatic transmission.

8. The intelligent work order allocation method for electromechanical maintenance according to claim 7, characterized in that: The work order is encrypted using the national secret SM4 algorithm during the distribution and reception process, and an independent key pair is generated for each work order.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is processed and executed, the steps of the intelligent work order allocation method for electromechanical maintenance according to any one of claims 7 to 8 are implemented.

10. A computer device, characterized in that: The system comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus. The memory is used to store computer programs; The processor is configured to execute the steps of the intelligent work order allocation method for electromechanical maintenance according to any one of claims 7 to 8 by running the program stored in the memory.

Images