A management system and method for intelligent scheduling of maintenance tools based on hardware and software collaboration.

Abstract

This invention discloses a management system and method for intelligent scheduling of maintenance tools based on hardware and software collaboration. The method includes: acquiring maintenance tasks and generating associated tool and mold lists; responding to a user's first retrieval request, controlling a first storage unit to release molds and recording the mold retrieval status; only after confirming that the mold has been retrieved, responding to a user's second retrieval request, controlling a second storage unit to release tools; automatically detecting the actual retrieved tool information after retrieval and comparing it with the tool list for verification; if the verification fails, blocking the retrieval process; and responding to a return request, first verifying the tool return information, allowing mold return only after the tool return verification passes. This invention achieves closed-loop management of the maintenance tool storage and retrieval process, deep awareness of usage status, and dynamic self-optimization of the task list, significantly improving the intelligence level and scheduling efficiency of maintenance tool management.

Description

Technical Field

[0001] This invention relates to the fields of industrial Internet of Things and intelligent warehouse management technology, and more specifically, to a management system and method for intelligent scheduling of maintenance tools based on hardware and software collaboration. Background Technology

[0002] Rail transit vehicles, including high-speed trains, locomotives, and subways, require extensive use of various types of non-standard tooling, specialized tools, and measuring instruments during the maintenance of hydraulic vibration dampers. Currently, the management of these maintenance tools relies primarily on manual methods, which presents the following technical challenges: First, the storage and retrieval efficiency is low and the process is uncontrollable. Tools are stored in ordinary tool cabinets or racks, lacking unified storage standards and location guidance. Requisitioning requires manual searching and registration, and returning them can be done haphazardly. Furthermore, there is a lack of a mandatory control mechanism for the retrieval process, which easily leads to problems such as missed molds and incorrect tools being taken.

[0003] Second, the usage status of tools is unknown, leading to blind resource scheduling. Existing management systems can only detect whether a tool has been borrowed, but cannot know whether the tool has been actually used during the borrowing period or what the usage progress is. When an emergency maintenance task requires calling a borrowed tool, the system cannot determine the tool's availability probability and estimated availability time, resulting in a lack of data support for scheduling decisions.

[0004] Third, the lack of data support for tool configuration leads to resource waste. Due to a lack of awareness of actual tool usage behavior, managers cannot accurately determine the necessity of tools. Many tools are included in the task list but are actually used very infrequently, resulting in idleness and increased management costs.

[0005] Fourth, fixed-location management is difficult to implement, leaving tools on-site poses safety hazards, and the periodic calibration of measuring instruments relies on manual records, which is prone to omissions and overdue calibrations. Therefore, there is an urgent need for an intelligent scheduling and management method that can achieve mandatory control over tool access processes, intelligent perception of usage status, and dynamic optimization of task lists. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides an intelligent scheduling and management method for maintenance tools based on hardware and software collaboration. This method effectively solves the technical problems of uncontrollable processes, unknown status, non-optimized configuration, and non-closed-loop data in the prior art, achieving significant intelligent management results.

[0007] To achieve the above-mentioned objectives, a management method for intelligent scheduling of maintenance tools based on hardware and software collaboration includes the following steps: Obtain maintenance tasks and generate associated tool and mold lists based on the maintenance tasks; In response to the user's first retrieval request, the first storage unit is controlled to release the molds in the mold list and record the retrieval status of the molds; Only when it is confirmed that the mold has been removed, in response to the user's second retrieval request, control the second storage unit to release the tools in the tool list; After the tool is taken out, the system automatically detects the actual tool information taken out by the user and compares it with the tool list. If the verification fails, the current retrieval process is blocked. In response to a user's return request, the tool return information is first received and verified. Only after the tool return verification is passed will the return of the mold be allowed. Collect operational data during the retrieval and return process, and use it to optimize the tool list and mold list for subsequent maintenance tasks.

[0008] Preferably, the mold carries work sequence information corresponding to the tool list; the work sequence information is written into the electronic tag of the mold or attached to the mold in a readable manner.

[0009] As a preferred option, an emergency dispatch step is also included: When a new maintenance task requiring the use of a target tool is received, and it is detected that the target tool has been borrowed by a currently incomplete maintenance task, the operation sequence information corresponding to the currently incomplete maintenance task is obtained, and the expected usage position of the target tool in the operation sequence information is determined. Based on the execution time and historical usage model of the currently incomplete maintenance tasks, calculate the availability probability of the target tool at the current moment; Scheduling recommendations are generated based on the availability probability.

[0010] Preferably, at least a portion of the tool is provided with a usage status detector for collecting actual usage data of the tool during the period when the tool is removed; the usage status detector includes at least one of the following: a vibration sensor, an acceleration sensor, a gyroscope, a torque sensor, and a timer.

[0011] Preferably, the operational data collected during the acquisition, retrieval, and return process, and used to optimize the tool list and mold list for subsequent maintenance tasks, specifically includes: Statistics were compiled on the actual frequency and intensity of use of various tools during multiple historical executions of the same maintenance task type. Tools that have been removed but are determined to be unused or have a usage intensity below a preset threshold based on data collected by the usage status detector are identified. The identified tools are marked as items to be removed, and the tool list for subsequent maintenance tasks is optimized accordingly.

[0012] Preferably, the automatic detection of the tool information actually taken out by the user is achieved through one of the following methods: radio frequency identification, optical character recognition, QR code scanning, weight sensing, or contact electrical signal detection.

[0013] Preferably, the radio frequency identification method includes: binding a unique RFID electronic tag to each tool, integrating an RFID reader array within the second storage unit, and automatically inventorying the remaining tools in the cabinet after a tool is taken out or returned using the RFID reader array, thereby determining the information of the tools actually taken out; and / or, The second storage unit is equipped with a location guidance device, which includes LED indicator lights corresponding to the locations of each tool in the tool list, used to illuminate the location of the corresponding tool when the user picks up or returns the tool.

[0014] Preferably, it also includes at least one of the following steps: fault reporting, overdue return, overdue verification, and access control: The fault reporting steps include: in response to the tool fault information submitted by the user, marking the status of the corresponding tool as faulty; prohibiting the tool with the faulty status from being used again, and sending a fault notification to the administrator; The overdue return process includes: recording the time each tool is taken out, and automatically triggering a return reminder when the removal time exceeds a preset threshold; The overdue verification step includes: recording the verification cycle of tools that need to be verified regularly, and automatically triggering a verification reminder when the preset verification reminder date is reached; The permission management steps include: presetting user job information and / or qualification information, establishing the association between user permissions and the maintenance task type; and allowing the generation of corresponding tool lists and mold lists only when the current user has the permissions required to perform the maintenance task.

[0015] Preferably, the step of generating the associated tool list and mold list based on the maintenance task specifically includes: Multiple kit plans are pre-established, each kit plan is associated with a maintenance task type, and includes a list of tools and molds required to complete that maintenance task type; Match the corresponding kit plan according to the maintenance task to generate the tool list and mold list.

[0016] The present invention also provides an intelligent scheduling and management system for maintenance tools based on hardware and software collaboration, comprising: a management server for executing the method described in any of the above-mentioned embodiments; a first storage unit for storing molds; a second storage unit for storing tools; and a user interaction terminal for receiving user operations and communicating with the management server.

[0017] Compared with the prior art, the present invention has the following beneficial effects: This invention employs a collaborative retrieval mechanism that allows tools to be released only after the mold has been confirmed to have been removed, and a reverse process that allows molds to be returned only after the tools have been returned and verified. This process design forces a closed loop, and combined with automatic comparison and verification after retrieval, it eliminates problems such as missing molds, incorrect tools, and incomplete returns, effectively reducing the risk of tool loss and on-site safety hazards. By carrying the work sequence information on the mold, when an urgent task requires the use of the target tool that has been borrowed, the system can calculate the availability probability and generate scheduling suggestions based on the work sequence information, the execution time and the historical usage model, providing scientific decision support for production scheduling. By setting up usage status detectors on at least some tools, collecting actual usage data, and statistically analyzing the usage frequency and intensity of each tool under the same maintenance task type, tools that are not actually used or whose usage intensity is below the threshold are identified and marked as recommended removal items. Based on this, the subsequent task list is optimized to make the tool configuration more streamlined and reasonable. Through various automatic detection methods such as radio frequency identification and optical identification, especially by using RFID electronic tag binding tools and automatic inventory with reader arrays, as well as LED indicator position guidance, the tool retrieval and return can be quickly located and automatically verified. Through steps such as fault reporting, overdue return reminders, overdue verification reminders, and access control, as well as pre-built kit plans to quickly match maintenance tasks, the entire lifecycle of tools can be automatically monitored and managed in a refined manner. Attached Figure Description

[0018] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is the main flowchart of the scheduling and management method of the present invention; Figure 2 This is an emergency dispatch flowchart of the present invention; Figure 3 This is a flowchart of the task list self-optimization process of the present invention.

[0019] Figure 4 This is a system architecture diagram of the present invention. Detailed Implementation

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in conjunction with the accompanying drawings and descriptions of the embodiments or the prior art. Obviously, the following description of the structure of the accompanying drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0021] It should be understood that the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0022] refer to Figures 1-4 The intelligent scheduling and management method for maintenance tools based on hardware and software collaboration provided in this invention can be applied to the maintenance of hydraulic vibration dampers in rail transit equipment, and can also be extended to other industrial maintenance fields that require refined tool management. The system implementing this method includes a back-end management server, multiple intelligent mold cabinets, multiple intelligent tool cabinets, a central control self-service terminal, and user mobile terminals. The back-end management server is the management system, the multiple intelligent mold cabinets are the first storage unit, and the multiple intelligent tool cabinets are the second storage unit. The intelligent mold cabinets are used to store the matching molds required for various maintenance tools, and each mold is embedded with an RFID electronic tag. The intelligent tool cabinets are used to store various maintenance tools, each maintenance tool is bound to a unique RFID electronic tag, each shelf of the tool cabinet has an LED indicator, and the cabinet integrates an RFID reader / writer array, automatically triggering inventory when the cabinet door is closed. The back-end management server stores a set plan library, a user permission library, a usage history database, and is equipped with a task scheduling engine, a data analysis and optimization module, and an emergency scheduling module.

[0023] First, when the production management system (such as a Manufacturing Execution System, MES) issues a maintenance plan to the backend management server, or when an administrator manually creates a maintenance task at the central control self-service terminal, the management server obtains the maintenance task information. This information includes at least the vehicle model, shock absorber model, and work type. The vehicle model is a specific model of a rail transit vehicle, specifically CR400AF or CRH1A. The shock absorber model can be KYB or 9121-40. The work type can be overall assembly or component assembly. The management server matches a preset assembly plan based on the maintenance task information, generating a related tool list and mold list. For example, for the task "CR400AF vehicle model, KYB shock absorber, overall assembly," the system matches the "CR400AF (KYB) overall assembly" assembly plan. The tool list associated with this plan includes 17 tools such as torque wrenches, special sockets, and piston calipers, and the mold list includes one "CR400AF overall assembly mold A." The tool list and mold list are then sent to the task queue for processing.

[0024] Before starting work, users first go to the central control self-service terminal or directly to the area where the intelligent mold cabinet is located, and complete identity verification through facial recognition or IC card swiping. After successful verification, the system responds to the user's first retrieval request by issuing an unlock command to the designated intelligent mold cabinet, or by selecting the corresponding set plan at the mold cabinet terminal, controlling the first storage unit to release the molds in the mold list. The first retrieval request can be made by clicking the "Retrieve Mold" button on the central control screen. After the user opens the cabinet door, takes out the matching mold, and closes the cabinet door, the RFID reader built into the mold cabinet automatically identifies the tag of the retrieved mold and returns the mold borrowing success status to the management server, while recording the mold retrieval time, the user, and other information. The management server only allows subsequent tool retrieval after receiving the mold borrowing success status, that is, only after confirming that the mold has been retrieved, responding to the user's second retrieval request, controlling the second storage unit to release the tools in the tool list. Specifically, the system searches for one or more intelligent tool cabinets associated with the set plan corresponding to the borrowed mold, for example, tool cabinet No. 1 stores the CR400AF complete assembly tools, and generates a second retrieval command. Users go to the designated smart tool cabinet, confirm their task at the tool cabinet terminal, and the system unlocks the corresponding tool cabinet door. As the door opens, LED indicators on each shelf corresponding to the tool in the tool list automatically illuminate, guiding the user to quickly find the required tools. After retrieving the tools according to the indicator lights, the user closes the cabinet door. Upon detection of the door closing signal by the tool cabinet controller, the integrated RFID reader array immediately triggers an automatic inventory of remaining tools. This automatically detects the tools actually retrieved by the user and compares them with the tool list. If the inventory shows that the number of tools missing from the cabinet matches the tool list perfectly, the verification passes. If the retrieved tools do not match the list (e.g., too many, too few, or the wrong tools), the system issues a voice alarm and prevents the retrieval process from completing. This means the task status is not closed, the cabinet door is reopened, and the user is prompted to correct the error until the verification passes. After completing the maintenance work, the user initiates a return request through the central control self-service terminal or any tool cabinet terminal. In response to the request, the system first enters the tool return phase: based on the user's list of currently unreturned tools, the corresponding smart tool cabinet is unlocked, and LED indicators guide the user to place the tools back in their original positions one by one. After closing the cabinet door, the RFID reader automatically checks and confirms that the tools have been correctly returned; that is, the system first receives and verifies the tool return information. Only after the tool return verification is successful does the system enter the mold return phase: the corresponding smart mold cabinet is unlocked, allowing the return of molds to be received. After the user returns the mold, they close the door to confirm the completion of the entire return process.Throughout the entire borrowing and returning process, the management server automatically collects operational data, including the borrowing time, return time, borrower, number of borrowings, execution status of the borrowing list, and verification results of tools and molds. This data is stored in the historical database and used to optimize the tool and mold lists corresponding to subsequent maintenance tasks.

[0025] Based on the above basic process, the present invention also has several preferred embodiments. In one preferred embodiment, the mold carries work sequence information corresponding to the tool list. This work sequence information is written into the mold's electronic tag or attached to the mold in a readable manner (such as a QR code or barcode). Specifically, while generating the tool list, the management server automatically calculates the theoretical usage order of all tools in the task according to the preset process standard procedures (e.g., step 1—safety valve wrench, step 2—piston rod caliper, step 3—torque wrench, etc.). This sequence information is encoded into a dynamic sequence tag and written into the electronic tag of the matching mold via an RFID reader. Users can read the sequence tag on the mold at any time during on-site operations and use the tools in sequence, avoiding process errors. Based on this, the present invention also provides an emergency scheduling step: when the management server receives a new maintenance task that requires the use of a target tool, and detects that the target tool has been borrowed by a currently incomplete maintenance task, the system retrieves the job sequence information corresponding to the currently incomplete maintenance task to determine the expected usage position of the target tool in the job sequence information; then, based on the execution time and historical usage model of the currently incomplete maintenance task, i.e., the time distribution of similar processes obtained from a large amount of historical task data statistics, the system calculates the availability probability of the target tool at the current moment; finally, based on the availability probability, a scheduling suggestion is generated. For example, if the probability is higher than a preset threshold, it is suggested to wait or directly contact the work group personnel; if it is lower than the threshold, it is suggested to "activate the backup tool". This emergency scheduling function provides scientific data decision support for production scheduling and significantly improves emergency response capabilities.

[0026] The historical usage model is constructed by collecting data on the actual usage time and return time of each tool in a large number of historical tasks, grouping and statistically analyzing the data by process position, and fitting the probability distribution function of the completion of use of each tool at different time points.

[0027] In another preferred embodiment of the invention, at least some of the tools are equipped with a usage status detector for collecting actual usage data of the tools while they are being taken out. This usage status detector includes at least one of a vibration sensor, an accelerometer, a gyroscope, a torque sensor, and a timer. For example, an accelerometer and a timer can be integrated into a torque wrench to detect changes in motion posture and record the duration of torque application when the wrench is picked up and torque is applied; a vibration sensor and a torque sensor can be integrated into an electric screwdriver to accurately reflect the working status through vibration frequency and torque value. The detector has a built-in small battery and a short-range wireless communication module, such as Bluetooth or NFC, to continuously collect data while the tools are being borrowed and temporarily store it in local memory. When the tools are returned, the data is automatically read through a communication interface provided in the tool cabinet. Based on the collected actual usage data, this invention further achieves self-optimization of the task list: the system statistically analyzes the actual usage frequency and intensity of each tool in multiple historical executions of the same maintenance task type. Usage intensity is calculated based on cumulative working time, torque output, etc., from detector data. Tools that were removed but, according to data collected by the usage status detector, were determined not to have been actually used or had usage intensity below a preset threshold (e.g., vibration sensors were not triggered throughout, timers were zero, a tool's theoretical usage time should be 5 minutes, but it was actually used on average only 10 seconds). These identified tools are marked as recommended removal items, and the tool list for subsequent maintenance tasks is optimized accordingly, such as removing the tool from the standard task list or adjusting it to an on-demand, individually available option. This self-optimization mechanism makes tool configuration more streamlined and reasonable, reducing resource waste and management costs. Correspondingly, the data detected by the status detector can also be used to optimize the work sequence information corresponding to the tool list. The detected tool usage order, usage time, and whether it was used are used to optimize the work sequence information for the next task assignment.

[0028] Regarding the specific implementation of automatically detecting the actual tools retrieved by the user, this invention can employ at least one of the following: radio frequency identification (RFID), optical character recognition (OCR), QR code scanning, weight sensing, and contact electrical signal detection. In a preferred embodiment, RFID is used: a unique RFID electronic tag is bound to each tool, and an RFID reader array is integrated into the second storage unit (intelligent tool cabinet). This reader array automatically inventories the remaining tools in the cabinet after a tool is retrieved or returned, thereby determining the actual tools retrieved. Simultaneously, the second storage unit is equipped with a location guidance device, which includes LED indicator lights corresponding to the locations of each tool in the tool list. These lights illuminate the corresponding tool's location when the user retrieves or returns a tool, allowing the user to quickly locate the tool they need to operate based on the light color and position. In a specific embodiment, green indicates "to be retrieved," and blue indicates "to be returned."

[0029] Furthermore, the method of the present invention includes at least one of the following steps: fault reporting, overdue return, overdue verification, and access control. Fault reporting step: In response to tool fault information submitted by the user, the corresponding tool is marked as faulty, prohibiting the faulty tool from being re-assigned, and a fault notification is sent to the administrator. Overdue return step: The time each tool is retrieved is recorded. When the retrieval time exceeds a preset threshold, a return reminder is automatically triggered, such as via SMS or push notification. Overdue verification step: The verification cycle of tools requiring periodic verification is recorded. When the preset verification reminder date arrives, a verification reminder is automatically triggered, displaying the name and storage location of the tool to be inspected in a pop-up window on the operation interface and notifying the administrator. Access control step: User job information and / or qualification information are preset, establishing a correlation between user permissions and maintenance task types. Only when the current user has the necessary permissions to perform the maintenance task is the corresponding tool and mold list allowed to be generated, thereby eliminating the risk of unqualified personnel using specialized tools from the source. In one specific embodiment of the present invention, the management server pre-establishes multiple package plans, each package plan being associated with a maintenance task type and containing a tool list and mold list required to complete that maintenance task type. The maintenance task type is uniquely determined by the vehicle model, shock absorber model, and work type. When the management server obtains maintenance task information, the system automatically matches the corresponding package plan and directly generates the corresponding tool list and mold list, eliminating the need for manual selection and achieving rapid automatic task configuration. The maintenance task information includes the vehicle model, shock absorber model, and work type specified in the work order transmitted from the MES system.

[0030] As can be seen from the above specific embodiments, the method provided by this invention, in the scenario of hydraulic shock absorber maintenance tool management, effectively solves the technical problems in the prior art, such as uncontrollable access processes, unknown usage status, suboptimal resource allocation, and difficulty in implementing fixed-position management, through the synergistic effect of multiple technical features, including sequential labeling, emergency scheduling, usage status perception, self-optimization, fault reporting, overdue management, and access control. This is achieved through a forced process control of "mold first, then tool; tool first, then mold," automatic detection and comparison verification, operation data collection and feedback optimization, as well as sequential labeling, emergency scheduling, usage status perception, self-optimization, fault reporting, overdue management, and access control. This significantly improves the intelligence level and scheduling efficiency of maintenance tool management. The above descriptions are merely preferred embodiments of this invention and are not intended to limit the invention. For those skilled in the art, several improvements and equivalent substitutions can be made without departing from the spirit and principles of this invention, and these should all be included within the scope of protection of this invention.

[0031] refer to Figure 4As another aspect of the present invention, the present invention also provides an intelligent scheduling and management system for maintenance tools based on hardware and software collaboration. The system includes a management server, a first storage unit, a second storage unit, and a user interaction terminal. The management server is used to execute the methods described in any of the above embodiments, specifically including functions such as task acquisition and list generation, retrieval and return process control, automatic verification, data acquisition and optimization, etc. The first storage unit is an intelligent mold cabinet for storing matching molds; each mold has an embedded RFID electronic tag, and the cabinet door uses an electronic lock. The second storage unit is an intelligent tool cabinet for storing maintenance tools; each tool is bound to a unique RFID electronic tag, and the cabinet integrates an RFID reader / writer array and LED indicator lights. The user interaction terminal includes a central control self-service terminal and a tool cabinet terminal, used to receive user authentication information and retrieval / return requests, and to communicate with the management server.

[0032] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A management method for intelligent scheduling of maintenance tools based on hardware and software collaboration, characterized in that, Includes the following steps: Obtain maintenance tasks and generate associated tool and mold lists based on the maintenance tasks; In response to the user's first retrieval request, the first storage unit is controlled to release the molds in the mold list and record the retrieval status of the molds; Only when it is confirmed that the mold has been removed, in response to the user's second retrieval request, control the second storage unit to release the tools in the tool list; After the tool is taken out, the system automatically detects the actual tool information taken out by the user and compares it with the tool list. If the verification fails, the current retrieval process is blocked. In response to a user's return request, the tool return information is first received and verified. Only after the tool return verification is passed will the return of the mold be allowed. Collect operational data during the retrieval and return process, and use it to optimize the tool list and mold list for subsequent maintenance tasks.

2. The management method for intelligent scheduling of maintenance tools based on hardware and software collaboration as described in claim 1, characterized in that, The mold carries work sequence information corresponding to the tool list; the work sequence information is written into the electronic tag of the mold or attached to the mold in a readable manner.

3. The management method for intelligent scheduling of maintenance tools based on hardware and software collaboration as described in claim 2, characterized in that, It also includes emergency dispatch steps: When a new maintenance task requiring the use of a target tool is received, and it is detected that the target tool has been borrowed by a currently incomplete maintenance task, the operation sequence information corresponding to the currently incomplete maintenance task is obtained, and the expected usage position of the target tool in the operation sequence information is determined. Based on the execution time and historical usage model of the currently incomplete maintenance tasks, calculate the availability probability of the target tool at the current moment; Scheduling recommendations are generated based on the availability probability.

4. The management method for intelligent scheduling of maintenance tools based on hardware and software collaboration as described in claim 1, characterized in that, At least a portion of the tool is equipped with a usage status detector for collecting actual usage data of the tool during the period when the tool is removed; the usage status detector includes at least one of the following: a vibration sensor, an acceleration sensor, a gyroscope, a torque sensor, and a timer.

5. The management method for intelligent scheduling of maintenance tools based on hardware and software collaboration as described in claim 4, characterized in that, The operational data collected during the acquisition, retrieval, and return process, and used to optimize the tool list and mold list for subsequent maintenance tasks, specifically includes: Statistics were compiled on the actual frequency and intensity of use of various tools during multiple historical executions of the same maintenance task type. Tools that have been removed but are determined to be unused or have a usage intensity below a preset threshold based on data collected by the usage status detector are identified. The identified tools are marked as items to be removed, and the tool list for subsequent maintenance tasks is optimized accordingly.

6. The management method for intelligent scheduling of maintenance tools based on hardware and software collaboration as described in claim 1, characterized in that, The automatic detection of the tool information actually taken out by the user is achieved through one of the following methods: radio frequency identification, optical character recognition, QR code scanning, weight sensing, or contact electrical signal detection.

7. The management method for intelligent scheduling of maintenance tools based on hardware and software collaboration as described in claim 6, characterized in that, The radio frequency identification method includes: binding a unique RFID electronic tag to each tool; integrating an RFID reader array within the second storage unit; and automatically inventorying the remaining tools in the cabinet after a tool is taken out or returned using the RFID reader array, thereby determining the information of the tools actually taken out; and / or, The second storage unit is equipped with a location guidance device, which includes LED indicator lights corresponding to the locations of each tool in the tool list, used to illuminate the location of the corresponding tool when the user picks up or returns the tool.

8. The management method for intelligent scheduling of maintenance tools based on hardware and software collaboration as described in claim 1, characterized in that, It also includes at least one of the following steps: fault reporting, overdue return, overdue verification, and access control: The fault reporting steps include: in response to the tool fault information submitted by the user, marking the status of the corresponding tool as faulty; prohibiting the tool with the faulty status from being used again, and sending a fault notification to the administrator; The overdue return process includes: recording the time each tool is taken out, and automatically triggering a return reminder when the removal time exceeds a preset threshold; The overdue verification step includes: recording the verification cycle of tools that need to be verified regularly, and automatically triggering a verification reminder when the preset verification reminder date is reached; The permission management steps include: presetting user job information and / or qualification information, establishing the association between user permissions and the maintenance task type; and allowing the generation of corresponding tool lists and mold lists only when the current user has the permissions required to perform the maintenance task.

9. The management method for intelligent scheduling of maintenance tools based on hardware and software collaboration as described in claim 1, characterized in that, The generation of the associated tool list and mold list based on the maintenance task specifically includes: Multiple kit plans are pre-established, each kit plan is associated with a maintenance task type, and includes a list of tools and molds required to complete that maintenance task type; Match the corresponding kit plan according to the maintenance task to generate the tool list and mold list.

10. A management system for intelligent scheduling of maintenance tools based on hardware and software collaboration, characterized in that, include: A management server for executing the management method according to any one of claims 1 to 9; The first storage unit is used to store the mold; The second storage unit is used to store tools; The user interaction terminal is used to receive user operations and communicate with the management server.

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