Method and system for tracking and managing maintenance progress of industrial Internet of Things equipment

Abstract

The invention discloses a maintenance progress tracking management method and system for industrial Internet of Things equipment, and the method comprises the steps: building a maintenance task list of the industrial Internet of Things equipment, and distributing progress tracking identifiers for all maintenance tasks in the maintenance task list; acquiring equipment operation data of each maintenance task in the maintenance task list in real time, and associating the equipment operation data with the corresponding maintenance task; calculating the actual execution progress and the predicted execution progress of each maintenance task in real time according to the associated data; analyzing the actual execution progress, the predicted execution progress and the equipment operation data of each maintenance task, and generating a progress deviation report; and updating a progress tracking identifier and task progress information of each maintenance task based on the progress deviation report so as to realize maintenance progress tracking management. Potential problems can be found and solved in time through the progress deviation report, and then the maintenance task efficiency is improved by adjusting the progress tracking identifier and the progress information of each maintenance task.

Description

Technical Field

[0001] The present invention relates to the technical field of maintenance progress tracking, and in particular to a maintenance progress tracking management method and system for industrial Internet of Things equipment. Background Art

[0002] With the rapid development of the Industrial Internet of Things (IIoT), more and more industrial equipment is becoming intelligent and automated through sensors and network connectivity. Traditional maintenance progress tracking methods rely primarily on manual experience to record maintenance progress, which is subject to delays and cannot reflect maintenance progress in a timely manner. This can lead to potential problems not being discovered and resolved in a timely manner, and thus production interruptions caused by equipment failures cannot be avoided. Therefore, how to provide timely and effective maintenance progress information to improve maintenance task efficiency has become a pressing issue.

[0003] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of the present invention is to provide a maintenance progress tracking and management method and system for industrial Internet of Things equipment, aiming to solve the technical problem of how to provide effective maintenance progress information in a timely manner and thus improve the efficiency of maintenance tasks.

[0005] To achieve the above objectives, the present invention provides a maintenance progress tracking and management method for industrial Internet of Things equipment, the method comprising:

[0006] Establish a maintenance task list for industrial IoT equipment and assign a progress tracking indicator to each maintenance task in the maintenance task list;

[0007] Acquire the equipment operation data of each maintenance task in the maintenance task list in real time, and associate the equipment operation data with the corresponding maintenance task;

[0008] Calculate the actual and expected progress of each maintenance task in real time based on the associated data;

[0009] Analyze the actual execution progress, expected execution progress and equipment operation data of each maintenance task and generate progress deviation reports;

[0010] The progress tracking identifier and task progress information of each maintenance task are updated based on the progress deviation report to realize maintenance progress tracking management.

[0011] Optionally, the real-time acquisition of equipment operation data for each maintenance task in the maintenance task list includes:

[0012] Acquire the device operating parameters collected by the built-in sensors of the industrial Internet of Things device in real time through a preset communication protocol;

[0013] Determining a data parsing rule corresponding to the preset communication protocol;

[0014] Parsing the device operating parameters according to the data parsing rules to obtain device operating parsing data;

[0015] The equipment operation data corresponding to each maintenance task in the maintenance task list is extracted from the equipment operation analysis data.

[0016] Optionally, the actual execution progress of each maintenance task is calculated in real time based on the associated data, including:

[0017] Extract the actual start time and expected end time of each maintenance task from the associated data;

[0018] The actual execution progress of each maintenance task is obtained according to the current time, the actual start time and the expected end time through the actual progress formula.

[0019] Optionally, the actual progress formula is:

[0020]

[0021] Where, T i is the actual execution progress of the i-th maintenance task, T0 is the current time, T s is the actual start time, T e Estimated end time.

[0022] Optionally, the actual execution progress, expected execution progress and equipment operation data of each maintenance task are analyzed to generate a progress deviation report, including:

[0023] Calculate the progress deviation value based on the actual execution progress and the expected execution progress of the corresponding maintenance task;

[0024] Determine whether the absolute value of the progress deviation value is greater than a preset deviation threshold;

[0025] If yes, the maintenance task corresponding to the progress deviation value is taken as the deviation maintenance task, and the progress deviation value and equipment operation data of the deviation maintenance task are analyzed for the deviation cause to obtain the deviation cause result;

[0026] Determine the remaining working hours of the deviation maintenance task based on the deviation cause result;

[0027] Generate a progress deviation report based on the actual execution progress and expected execution progress of each maintenance task, the remaining working hours of the deviation maintenance task and the deviation reasons.

[0028] Optionally, performing deviation cause analysis on the progress deviation value and equipment operation data of the deviation maintenance task to obtain a deviation cause result includes:

[0029] Extracting deviation operation data corresponding to the progress deviation period from the equipment operation data of the maintenance task by a sliding window method;

[0030] performing feature extraction on the deviation operation data to obtain deviation feature information;

[0031] The cause of the deviation is analyzed based on the progress deviation value and the deviation characteristic information to obtain a deviation cause result.

[0032] Optionally, determining the remaining working hours of the deviation maintenance task according to the deviation cause result includes:

[0033] If the cause of the deviation is a device failure, determining a failure category corresponding to the device failure;

[0034] Obtaining historical fault repair times for the fault category, and determining a fault impact coefficient based on the historical fault repair times;

[0035] The remaining working hours of the maintenance task are calculated using a linear regression equation according to the fault impact coefficient and the basic working hours of the maintenance task.

[0036] Optionally, the linear regression equation is:

[0037]

[0038] In the formula, M is the remaining working hours, N is the basic working hours, is the fault impact coefficient.

[0039] Optionally, after updating the progress tracking identifier and task progress information of each maintenance task based on the progress deviation report, the method further includes:

[0040] A maintenance plan is generated according to the updated progress tracking identifier and the adjusted progress information, and the maintenance plan is sent to the mobile terminal of the maintenance personnel to perform corresponding maintenance operations.

[0041] In addition, to achieve the above-mentioned purpose, the present invention also proposes a maintenance progress tracking and management system for industrial Internet of Things devices, the maintenance progress tracking and management system for industrial Internet of Things devices comprising:

[0042] Establish a module for establishing a maintenance task list for industrial Internet of Things equipment and assigning a progress tracking indicator to each maintenance task in the maintenance task list;

[0043] An acquisition module is used to acquire the equipment operation data of each maintenance task in the maintenance task list in real time, and associate the equipment operation data with the corresponding maintenance task;

[0044] The calculation module is used to calculate the actual execution progress and expected execution progress of each maintenance task in real time based on the associated data;

[0045] The generation module is used to analyze the actual execution progress, expected execution progress and equipment operation data of each maintenance task and generate progress deviation reports;

[0046] The adjustment module is used to update the progress tracking identifier and task progress information of each maintenance task based on the progress deviation report to achieve maintenance progress tracking management.

[0047] In addition, to achieve the above-mentioned purpose, the present invention also proposes a maintenance progress tracking and management device for industrial Internet of Things equipment, the device comprising: a memory, a processor, and a maintenance progress tracking and management program for industrial Internet of Things equipment stored on the memory and runnable on the processor, the maintenance progress tracking and management program for industrial Internet of Things equipment being configured to implement the steps of the maintenance progress tracking and management method for industrial Internet of Things equipment as described above.

[0048] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a maintenance progress tracking and management program for industrial Internet of Things devices is stored. When the maintenance progress tracking and management program for industrial Internet of Things devices is executed by a processor, the steps of the maintenance progress tracking and management method for industrial Internet of Things devices as described above are implemented.

[0049] The present invention first establishes a maintenance task list for industrial Internet of Things equipment, and assigns a progress tracking identifier to each maintenance task in the maintenance task list, then obtains the equipment operation data of each maintenance task in the maintenance task list in real time, associates the equipment operation data with the corresponding maintenance task, and then calculates the actual execution progress and expected execution progress of each maintenance task in real time based on the associated data, and analyzes the actual execution progress, expected execution progress and equipment operation data of each maintenance task to generate a progress deviation report, and finally updates the progress tracking identifier and task progress information of each maintenance task based on the progress deviation report to realize maintenance progress tracking management. The present invention can timely discover and solve potential problems through the progress deviation report, and then improve the efficiency of maintenance tasks by adjusting the progress tracking identifier and progress information of each maintenance task. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of the structure of a maintenance progress tracking and management device for an industrial Internet of Things device in a hardware operating environment involved in an embodiment of the present invention;

[0051] Figure 2 This is a schematic diagram of the overall process of the first embodiment of the maintenance progress tracking and management method for industrial Internet of Things equipment of the present invention;

[0052] Figure 3 This is a structural block diagram of the first embodiment of the maintenance progress tracking and management system for industrial Internet of Things equipment of the present invention.

[0053] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0054] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0055] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a maintenance progress tracking and management device for industrial Internet of Things devices in the hardware operating environment involved in an embodiment of the present invention.

[0056] like Figure 1 As shown, the maintenance progress tracking and management device for industrial IoT devices may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a maintenance personnel interface 1003, a network interface 1004, and memory 1005. The communication bus 1002 is used to enable communication between these components. The maintenance personnel interface 1003 may include a display and an input unit, such as a keyboard. Optionally, the maintenance personnel interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless Fidelity (Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as a disk drive. Optionally, the memory 1005 may be a storage system independent of the processor 1001.

[0057] Those skilled in the art will understand that Figure 1 The structure shown in does not constitute a limitation on the maintenance progress tracking and management device of industrial Internet of Things equipment, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0058] like Figure 1As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a maintenance personnel interface module, and a maintenance progress tracking management program for industrial Internet of Things devices.

[0059] exist Figure 1 In the maintenance progress tracking and management device of the industrial Internet of Things device shown, the network interface 1004 is mainly used for data communication with the network server; the maintenance personnel interface 1003 is mainly used for data interaction with the maintenance personnel; the processor 1001 and the memory 1005 in the maintenance progress tracking and management device of the industrial Internet of Things device of the present invention can be set in the maintenance progress tracking and management device of the industrial Internet of Things device, and the maintenance progress tracking and management device of the industrial Internet of Things device calls the maintenance progress tracking management program of the industrial Internet of Things device stored in the memory 1005 through the processor 1001, and executes the maintenance progress tracking and management method of the industrial Internet of Things device provided by the embodiment of the present invention.

[0060] The embodiment of the present invention provides a maintenance progress tracking and management method for industrial Internet of Things equipment, referring to Figure 2 , Figure 2 This is a flow chart of the first embodiment of the maintenance progress tracking and management method for industrial Internet of Things equipment of the present invention.

[0061] In this embodiment, the maintenance progress tracking and management method of the industrial Internet of Things equipment includes the following steps:

[0062] Step S1: Create a maintenance task list for industrial IoT equipment, and assign a progress tracking identifier to each maintenance task in the maintenance task list.

[0063] It is easy to understand that the execution subject of this embodiment can be an Internet of Things platform with functions such as data processing, network communication and program running, or other computer devices with similar functions, etc., and this embodiment is not limited.

[0064] In the specific implementation, it is necessary to determine the model, installation location, usage time and maintenance history data of the industrial Internet of Things device in advance, and then associate the maintenance task list of the industrial Internet of Things device with the model, installation location, usage time and maintenance history data of the industrial Internet of Things device.

[0065] It should also be noted that the maintenance task list also includes the name of each maintenance task, unique identification code, actual execution progress, actual start time, expected execution progress, expected start time, expected end time, progress tracking identifier, etc.

[0066] The actual execution progress and the expected execution progress are displayed in percentage.

[0067] The progress tracking indicator is the current status of the corresponding maintenance task, which includes not started, in progress, completed, delayed, paused and cancelled.

[0068] It should also be understood that maintenance personnel can customize color settings for different states of the progress tracking mark, and different colors are used to represent the progress tracking mark in different states.

[0069] It should also be noted that the equipment status sensors collect status operation data, which includes maintenance operation data and normal operation data. The start timestamp corresponding to the maintenance operation data collection is used as the actual start time. The estimated start and end times can be customized by maintenance personnel based on their experience.

[0070] Step S2: Acquire the equipment operation data of each maintenance task in the maintenance task list in real time, and associate the equipment operation data with the corresponding maintenance task.

[0071] Furthermore, the processing method for obtaining the equipment operation data of each maintenance task in the maintenance task list in real time is: obtaining the equipment operation parameters collected by the built-in sensors of the industrial Internet of Things equipment in real time through the preset communication protocol; determining the data parsing rules corresponding to the preset communication protocol; parsing the equipment operation parameters according to the data parsing rules to obtain equipment operation parsing data; extracting the equipment operation data corresponding to each maintenance task from the equipment operation parsing data based on the maintenance task list.

[0072] In this embodiment, multiple sensors, such as temperature sensors, pressure sensors, vibration sensors, energy consumption sensors, and device status sensors, need to be pre-installed on the device to monitor the device's operating parameters in real time. The device then transmits the collected operating parameters to the IoT platform via a wireless communication module (e.g., Wi-Fi, 4G / 5G, or Long Range Radio LoRa) based on a preset communication protocol (e.g., Message Queuing Telemetry Transport (MQTT) or Constrained Application Protocol (CoAP)). The IoT platform then parses the device operating parameters using the data parsing rules corresponding to the preset communication protocol, converting them into readable data (i.e., device operation parsed data).

[0073] In a specific implementation, the equipment operation data related to each maintenance task can be extracted from the equipment operation analysis data, and the unique identification code (such as ID number) corresponding to each maintenance task can be determined, and the unique identification code of each maintenance task can be associated with the corresponding equipment operation data.

[0074] It should also be noted that the unique identification code can be customized for maintenance personnel, and it is necessary to ensure that the unique identification code corresponding to each maintenance task is different.

[0075] Step S3: Calculate the actual execution progress and expected execution progress of each maintenance task in real time based on the associated data.

[0076] In the specific implementation, after associating the unique identification code of each maintenance task with the corresponding equipment operation data, the actual start time, expected execution progress, expected start time, and expected end time of each maintenance task can be obtained.

[0077] Furthermore, the actual execution progress of each maintenance task is calculated as follows: the actual start time and expected end time of each maintenance task are extracted from the associated data; the actual execution progress of each maintenance task is obtained through the actual progress formula based on the current time, actual start time and expected end time.

[0078] The actual progress formula is:

[0079]

[0080] Where, T i is the actual execution progress of the i-th maintenance task, T0 is the current time, T s is the actual start time, T e Estimated end time.

[0081] It should also be noted that the calculation method for the estimated execution progress is the same as that for the actual execution progress. The estimated execution progress can be obtained by simply replacing the actual start time in the actual progress formula with the estimated start time.

[0082] Step S4: Analyze the actual execution progress, expected execution progress and equipment operation data of each maintenance task and generate a progress deviation report.

[0083] Furthermore, the actual execution progress, expected execution progress and equipment operation data of each maintenance task are analyzed, and the processing method for generating a progress deviation report is as follows: calculate the progress deviation value based on the actual execution progress and the expected execution progress of the corresponding maintenance task; determine whether the absolute value of the progress deviation value is greater than the preset deviation threshold; if so, analyze the deviation cause of the progress deviation value and equipment operation data of the deviation maintenance task to obtain the deviation cause result; if the deviation cause result is equipment failure, determine the fault category corresponding to the equipment failure; obtain the historical fault repair time of the fault category, and determine the fault impact coefficient based on the historical fault repair time; calculate the remaining working hours of the maintenance task through a linear regression equation based on the fault impact coefficient and the basic working hours of the maintenance task; generate a progress deviation report based on the actual execution progress and expected execution progress of each maintenance task, the remaining working hours of the deviation maintenance task and the deviation cause result.

[0084] In a specific implementation, if the absolute value of the progress deviation value is 20% greater than the preset deviation threshold of 10%, the deviation operation data corresponding to the progress deviation period (such as vibration, temperature, current and other parameters corresponding to the deviation period) is extracted from the equipment operation data of the maintenance task through the sliding window method, where the window size = deviation duration. After that, feature extraction is performed on the deviation operation data to obtain deviation feature information (such as extracting the minute-level mean and peak value of the equipment operation data in this period). The progress deviation value, deviation feature information and equipment operation data in this period are sent to the maintenance personnel corresponding to the deviation maintenance task for deviation cause analysis to obtain the deviation cause result.

[0085] If the cause of the deviation is an equipment failure, the fault category corresponding to the equipment failure (such as motor rotor eccentricity, etc.) is determined, and the corresponding linear regression equation is established based on the historical data of the fault category. The historical fault repair time of the fault category is obtained, and the fault impact coefficient is customized according to the historical fault repair time to determine the basic working hours of the maintenance task. The remaining working hours of the maintenance task are calculated through the linear regression equation based on the fault impact coefficient and the basic working hours of the maintenance task. A progress deviation report is generated based on the actual execution progress of each maintenance task, the expected execution progress of each maintenance task, the remaining working hours of the deviation maintenance task, and the deviation cause results.

[0086] It should also be noted that if the cause of the deviation is a human factor (i.e., workers working early or late), the remaining working hours between the current time and the expected end time are calculated, and a progress deviation report is generated based on the actual execution progress of each maintenance task, the expected execution progress of each maintenance task, the remaining working hours of the deviation maintenance task, and the cause of the deviation.

[0087] It should also be noted that the basic working hours are the remaining working hours under normal operation as customized by the maintenance personnel.

[0088] The linear regression equation is:

[0089]

[0090] In the formula, M is the remaining working hours, N is the basic working hours, is the fault impact coefficient.

[0091] In this embodiment, if the absolute value of the progress deviation value is less than or equal to the preset deviation threshold, a progress update report is generated based on the actual execution progress and expected execution progress of each maintenance task, and the progress tracking identifier and task progress information of each maintenance task are updated based on the progress update report.

[0092] Step S5: updating the progress tracking identifier and task progress information of each maintenance task based on the progress deviation report to implement maintenance progress tracking management.

[0093] In the specific implementation, the progress tracking identifier of each maintenance task can be updated based on the progress deviation report (for example, if there is a delay, the identifier of the corresponding maintenance task will be adjusted to a delay identifier; if there is an advance, the identifier of the corresponding maintenance task will be adjusted to a pause, etc.) and the progress information of each maintenance task (that is, the expected end time of each maintenance task, the actual execution progress, etc.), and the priority of each maintenance task can be adjusted according to the updated progress tracking identifier and progress information, and a maintenance plan can be generated and sent to the mobile terminal of the maintenance personnel so that the maintenance personnel can perform the corresponding maintenance operations.

[0094] It should also be noted that the maintenance personnel can also customize the rules corresponding to the progress tracking identifiers of each maintenance task, or they can manually update the progress tracking identifiers, which is not limited in this embodiment.

[0095] In this implementation, a maintenance task list for industrial Internet of Things equipment is first established, and a progress tracking identifier is assigned to each maintenance task in the maintenance task list. Then, the equipment operation data of each maintenance task in the maintenance task list is obtained in real time, and the equipment operation data is associated with the corresponding maintenance task. Then, the actual execution progress and expected execution progress of each maintenance task are calculated in real time based on the associated data, and the actual execution progress, expected execution progress and equipment operation data of each maintenance task are analyzed to generate a progress deviation report. Finally, the progress tracking identifier and task progress information of each maintenance task are updated based on the progress deviation report to realize maintenance progress tracking management. This embodiment can timely discover and solve potential problems through the progress deviation report, and then improve the efficiency of maintenance tasks by adjusting the progress tracking identifier and progress information of each maintenance task.

[0096] Reference Figure 3 , Figure 3This is a structural block diagram of the first embodiment of the maintenance progress tracking and management system for industrial Internet of Things equipment of the present invention.

[0097] Establishing module 3001, for establishing a maintenance task list for industrial Internet of Things equipment, and assigning a progress tracking indicator to each maintenance task in the maintenance task list;

[0098] An acquisition module 3002 is used to acquire, in real time, the equipment operation data of each maintenance task in the maintenance task list and associate the equipment operation data with the corresponding maintenance task;

[0099] The calculation module 3003 is used to calculate the actual execution progress and expected execution progress of each maintenance task in real time based on the associated data;

[0100] The generation module 3004 is used to analyze the actual execution progress, expected execution progress and equipment operation data of each maintenance task and generate a progress deviation report;

[0101] The adjustment module 3005 is used to update the progress tracking identifier and task progress information of each maintenance task based on the progress deviation report to achieve maintenance progress tracking management.

[0102] Other embodiments or specific implementations of the maintenance progress tracking and management system of the industrial Internet of Things equipment of the present invention can refer to the above-mentioned method embodiments and will not be repeated here.

[0103] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0104] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0105] Through the description of the above embodiments, those skilled in the art will clearly understand that the above-mentioned embodiments and methods can be implemented by means of software plus the necessary general-purpose hardware platform. Of course, hardware can also be used, but in many cases the former is a more preferred embodiment. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, or optical disk) and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0106] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A maintenance progress tracking and management method for industrial Internet of Things equipment, characterized in that: The method comprises the following steps: Establish a maintenance task list for industrial IoT equipment and assign a progress tracking indicator to each maintenance task in the maintenance task list; Acquire the equipment operation data of each maintenance task in the maintenance task list in real time, and associate the equipment operation data with the corresponding maintenance task; Calculate the actual and expected progress of each maintenance task in real time based on the associated data; Analyze the actual execution progress, expected execution progress and equipment operation data of each maintenance task and generate progress deviation reports; The progress tracking identifier and task progress information of each maintenance task are updated based on the progress deviation report to realize maintenance progress tracking management.

2. The method according to claim 1, wherein The real-time acquisition of equipment operation data for each maintenance task in the maintenance task list includes: Acquire the device operating parameters collected by the built-in sensors of the industrial Internet of Things device in real time through a preset communication protocol; Determining a data parsing rule corresponding to the preset communication protocol; Parsing the device operating parameters according to the data parsing rules to obtain device operating parsing data; The equipment operation data corresponding to each maintenance task in the maintenance task list is extracted from the equipment operation analysis data.

3. The method according to claim 1, wherein The actual execution progress of each maintenance task is calculated in real time based on the associated data, including: Extract the actual start time and expected end time of each maintenance task from the associated data; The actual execution progress of each maintenance task is obtained according to the current time, the actual start time and the expected end time through the actual progress formula.

4. The method according to claim 3, wherein The actual progress formula is: ； Where, T i is the actual execution progress of the i-th maintenance task, T0 is the current time, T s is the actual start time, T e Estimated end time.

5. The method according to claim 1, wherein Analyze the actual execution progress, expected execution progress and equipment operation data of each maintenance task and generate a progress deviation report, including: Calculate the progress deviation value based on the actual execution progress and the expected execution progress of the corresponding maintenance task; Determine whether the absolute value of the progress deviation value is greater than a preset deviation threshold; If yes, the maintenance task corresponding to the progress deviation value is taken as the deviation maintenance task, and the progress deviation value and equipment operation data of the deviation maintenance task are analyzed for the deviation cause to obtain the deviation cause result; Determine the remaining working hours of the deviation maintenance task based on the deviation cause result; Generate a progress deviation report based on the actual execution progress and expected execution progress of each maintenance task, the remaining working hours of the deviation maintenance task and the deviation reasons.

6. The method according to claim 5, wherein The deviation cause analysis of the progress deviation value of the deviation maintenance task and the equipment operation data to obtain the deviation cause result includes: Extracting deviation operation data corresponding to the progress deviation period from the equipment operation data of the maintenance task by a sliding window method; performing feature extraction on the deviation operation data to obtain deviation feature information; The cause of the deviation is analyzed based on the progress deviation value and the deviation characteristic information to obtain a deviation cause result.

7. The method according to claim 5, wherein Determining the remaining working hours of the deviation maintenance task according to the deviation cause result includes: If the cause of the deviation is a device failure, determining a failure category corresponding to the device failure; Obtaining historical fault repair times for the fault category, and determining a fault impact coefficient based on the historical fault repair times; The remaining working hours of the maintenance task are calculated using a linear regression equation according to the fault impact coefficient and the basic working hours of the maintenance task.

8. The method according to claim 7, wherein The linear regression equation is: ； In the formula, M is the remaining working hours, N is the basic working hours, is the fault impact coefficient.

9. The method according to claim 1, wherein After the progress tracking identifier and task progress information of each maintenance task are updated based on the progress deviation report, the method includes: A maintenance plan is generated based on the updated progress tracking identifier and task progress information, and the maintenance plan is sent to the mobile terminal of the maintenance personnel to perform corresponding maintenance operations.

10. A maintenance progress tracking and management system for industrial Internet of Things equipment, characterized in that: The maintenance progress tracking and management system of the industrial Internet of Things equipment includes: Establish a module for establishing a maintenance task list for industrial Internet of Things equipment and assigning a progress tracking indicator to each maintenance task in the maintenance task list; An acquisition module is used to acquire the equipment operation data of each maintenance task in the maintenance task list in real time, and associate the equipment operation data with the corresponding maintenance task; The calculation module is used to calculate the actual execution progress and expected execution progress of each maintenance task in real time based on the associated data; The generation module is used to analyze the actual execution progress, expected execution progress and equipment operation data of each maintenance task and generate progress deviation reports; The adjustment module is used to update the progress tracking identifier and task progress information of each maintenance task based on the progress deviation report to achieve maintenance progress tracking management.

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