Machine room operation and maintenance work order construction method and system

Abstract

The embodiment of the invention provides a machine room operation and maintenance work order construction method and system, and relates to the technical field of operation and maintenance automation. The method comprises the following steps: acquiring operation monitoring data of machine room operation and maintenance equipment, and generating equipment alarm event data according to a preset alarm rule based on the operation monitoring data; based on the equipment alarm event data, according to an intelligent order establishment rule maintained by operation and maintenance management personnel, statistics is carried out on occurrence conditions of alarm events in a preset time range; when the statistical result meets an order establishment condition corresponding to the intelligent order establishment rule and there is no problem order which is generated based on the same intelligent order establishment rule and is in a processing state, generating a corresponding problem order; and after the problem list is processed and archived, intelligent list establishment rule statistics and judgment are carried out on the subsequent alarm event again based on an archiving result. Automatic triggering, restraining and restarting of the problem order are achieved, and therefore the work order generation process has continuity, controllability and closed-loop execution capacity.

Description

Technical Field

[0001] This application relates to the field of operation and maintenance automation technology, specifically to a method for constructing data center operation and maintenance work orders and a data center operation and maintenance work order construction system. Background Technology

[0002] As information systems continue to expand in scale, the types and operating states of equipment involved in data center operations and maintenance are becoming increasingly complex. Operations and maintenance management is gradually shifting from manual inspections to centralized management based on monitoring data. Currently, data center operations and maintenance typically rely on monitoring equipment operating parameters and collecting alarm information, and handling anomalies through work orders. However, existing work order generation and processing methods still have many shortcomings.

[0003] Traditional work order systems generally rely on manual input, filtering, and classification of alarm information. The generation of work orders is highly dependent on the experience and judgment of maintenance personnel. The response process has a significant time delay, and the processing effect is greatly affected by the quality and experience level of personnel, making it difficult to maintain stability and consistency in large-scale maintenance scenarios.

[0004] Although some existing systems have introduced rule-driven automatic order creation mechanisms, most of the relevant rules are statically set, such as based on fixed priorities or single alarm conditions. They lack comprehensive consideration of factors such as alarm frequency, time span, and spatial distribution, making it difficult to adapt to the complex scenarios in which different devices, different areas, and different alarm types intertwine during the operation of the data center, which can easily lead to false triggering or missed triggering.

[0005] In the existing work order processing workflow, there is a lack of effective linkage control between work order allocation and processing status. This leads to frequent instances of duplicate work orders and unprocessed orders exceeding time limits, resulting in low efficiency in the utilization of maintenance resources. For completed work orders, the processing results are often simply stored as records without being effectively linked to subsequent alarm handling processes. This causes the same or similar problems to recur in subsequent operations, increasing the workload of maintenance personnel.

[0006] Therefore, how to effectively collect and judge alarm events based on existing data center operation and maintenance monitoring, and how to build a work order generation and management mechanism with closed-loop control capabilities, remains a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0007] The purpose of this application is to provide a method and system for constructing data center operation and maintenance work orders, which solves the problem of imperfect alarm event statistics and work order control in the existing work order generation process.

[0008] To achieve the above objectives, the first aspect of this application provides a method for constructing data center operation and maintenance work orders. The method includes: acquiring operation monitoring data of data center operation and maintenance equipment, and generating equipment alarm event data based on the operation monitoring data according to preset alarm rules; statistically analyzing the occurrence of alarm events within a preset time range based on the equipment alarm event data and according to intelligent work order creation rules maintained by operation and maintenance personnel; generating a corresponding problem work order when the statistical result meets the work order creation conditions corresponding to the intelligent work order creation rule, and there are no problem work orders generated based on the same intelligent work order creation rule and in a processing state; and re-executing the intelligent work order creation rule statistics and judgment for subsequent alarm events based on the archiving result after the problem work order is processed and archived.

[0009] In this embodiment, acquiring operational monitoring data of data center maintenance equipment and generating equipment alarm event data based on the operational monitoring data according to preset alarm rules includes: collecting and associating the operational monitoring data based on the equipment type and corresponding monitoring points of the data center maintenance equipment; performing threshold judgment on the operational monitoring data according to the triggering conditions set in the alarm rules for the equipment type and monitoring points to determine whether the alarm triggering conditions are met; generating corresponding equipment alarm event data when the alarm triggering conditions are met; wherein, the equipment alarm event data includes any one or more of alarm equipment, alarm time, alarm level, and alarm content; terminating the alarm status of the corresponding equipment alarm event when the operational monitoring data meets the recovery conditions set in the alarm rules.

[0010] In this embodiment of the application, the triggering conditions set in the alarm rule include: for the corresponding monitoring point under the current device type, a preset threshold relationship condition is used to characterize the abnormal operating status, which is used to determine whether the magnitude relationship between the operating monitoring data and the corresponding threshold meets the preset magnitude relationship condition; and / or, based on the change of the operating monitoring data within a preset time range, a preset proportional relationship condition is used to characterize the trend of the change in the operating status, which is used to determine whether the change amplitude of the operating monitoring data meets the preset proportional relationship condition; when the operating monitoring data meets any of the preset magnitude relationship conditions or the preset proportional relationship conditions, it is determined that the alarm triggering condition corresponding to the alarm rule is met.

[0011] In this embodiment, based on the device alarm event data, and according to the intelligent order creation rules maintained by the operation and maintenance personnel, the occurrence of alarm events within a preset time range is statistically analyzed. This includes: classifying and grouping alarm events based on the device alarm event data; determining the correspondence between the classified and grouped alarm events based on the combination of alarm devices, alarm rooms, and alarm types set in the intelligent order creation rules to form corresponding statistical objects; performing time window filtering processing on the statistical objects according to the time range set in the intelligent order creation rules to determine the set of alarm events falling within the set time range; and counting the number of alarm events that meet the corresponding conditions of the intelligent order creation rules based on the set of alarm events.

[0012] In this embodiment, the intelligent order creation rule includes: a spatial rule for limiting the scope of application of alarm events, wherein the spatial rule distinguishes alarm events based on alarm devices and alarm rooms to determine the statistical range corresponding to the alarm events; a timeliness rule for limiting the statistical time range of alarm events, wherein the timeliness rule is used to set the statistical time window of alarm events; an alarm type rule for limiting the alarm event statistical objects, wherein the alarm type rule is used to distinguish between alarm events of the same alarm type and alarm events of different alarm types; and a frequency rule for limiting the number of times an alarm event triggers the order creation condition, wherein the frequency rule is used to set the occurrence frequency condition of the alarm event within the time range limited by the timeliness rule.

[0013] In this embodiment of the application, based on the alarm event set, the number of alarm events that satisfy the conditions corresponding to the smart order creation rule is counted, including: for the alarm event set, counting each alarm event one by one according to the statistical criteria set in the smart order creation rule to obtain the cumulative number of alarm events under the corresponding statistical object; comparing the cumulative number of alarm events with the number rule set in the smart order creation rule to determine whether the alarm event set satisfies the number rule corresponding to the smart order creation rule.

[0014] In this embodiment, when the statistical results meet the order creation conditions corresponding to the intelligent order creation rule, and there are no problem orders generated based on the same intelligent order creation rule and currently in a processing state, a corresponding problem order is generated. This includes: constructing problem order generation conditions to characterize the current alarm triggering situation based on the alarm event set and the alarm event occurrence count; when the problem order generation conditions meet the order creation conditions corresponding to the intelligent order creation rule, creating a corresponding problem order and marking the problem order as pending; when creating the problem order, extracting the corresponding alarm device, alarm time, and alarm content based on the device alarm event data contained in the alarm event set, and generating the problem title of the problem order in conjunction with the intelligent order creation rule that triggered the generation of the problem order; and arranging the alarm event records according to the alarm time order based on the device alarm event data contained in the alarm event set, and summarizing the arranged alarm event records to generate the problem content of the problem order.

[0015] In this embodiment of the application, when creating the problem ticket, after the problem ticket is processed and archived, the intelligent ticket creation rule statistics and judgment are re-executed for subsequent alarm events based on the archiving result. This includes: based on the archived status of the problem ticket, removing the alarm event statistics restriction under the intelligent ticket creation rule corresponding to the problem ticket; after removing the alarm event statistics restriction, re-executing the alarm event statistical processing according to the intelligent ticket creation rule for newly generated device alarm event data; and based on the re-executed alarm event statistical processing result, re-executing the ticket creation condition judgment corresponding to the intelligent ticket creation rule for subsequent alarm events. A second aspect of this application provides a data center operation and maintenance work order construction system. The system includes: a data acquisition unit, used to acquire operation monitoring data of data center operation and maintenance equipment, and generate equipment alarm event data based on the operation monitoring data according to preset alarm rules; a statistics unit, used to statistically analyze the occurrence of alarm events within a preset time range based on the equipment alarm event data and according to intelligent work order creation rules maintained by operation and maintenance personnel; a generation unit, used to generate a corresponding problem order when the statistical result meets the work order creation conditions corresponding to the intelligent work order creation rule, and there are no problem orders generated based on the same intelligent work order creation rule and in a processing state; and an archiving unit, used to re-execute intelligent work order creation rule statistics and judgment on subsequent alarm events based on the archiving result after the problem order is processed and archived.

[0016] A third aspect of this application provides a processor configured to execute the above-described data center operation and maintenance work order construction method.

[0017] A fourth aspect of this application provides a machine-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the aforementioned data center maintenance work order construction method.

[0018] The fifth aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for constructing data center operation and maintenance work orders.

[0019] Through the above technical solution, this invention achieves automatic creation and triggering control of work orders by performing rule-based statistics and judgment on alarm events generated from the monitoring data of data center operation and maintenance equipment. By introducing an alarm event statistics mechanism based on a time range, work order generation no longer relies on single alarms or manual experience, but is based on the occurrence characteristics of alarm events within a certain time scale, reducing the risk of false triggering and missed triggering. Simultaneously, by judging work orders already in the processing state before generating a work order, duplicate work order creation is effectively avoided, ensuring the controllability of the work order triggering process. After the work order is processed and archived, the corresponding rules are reactivated to perform statistics and judgment on subsequent alarm events, giving the work order generation mechanism continuous effectiveness and status recovery capabilities. This forms a closed-loop control process between alarm processing and work order management, improving the continuity and consistency of alarm handling in data center operation and maintenance scenarios. Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0020] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings: Figure 1 This illustration schematically shows a flowchart of the steps involved in constructing a data center operation and maintenance work order according to an embodiment of this application. Figure 2 This illustration schematically shows a system architecture diagram of a data center operation and maintenance work order construction system according to an embodiment of this application; Figure 3 The diagram illustrates the internal structure of a computer device according to an embodiment of this application. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0022] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0023] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0024] The acquisition, transmission, storage, use, and processing of data in this application comply with relevant laws and regulations. Furthermore, it should be noted that certain software, components, models, and other existing industry solutions may be mentioned in the embodiments of this application. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0025] Figure 1 The illustration schematically shows a flowchart of a data center operation and maintenance work order construction method according to an embodiment of this application. For example... Figure 1 As shown in one embodiment of this application, a method for constructing a data center operation and maintenance work order is provided, including the following steps: Step S10: Obtain the operation monitoring data of the data center maintenance equipment, and generate equipment alarm event data based on the operation monitoring data according to the preset alarm rules.

[0026] Specifically, based on the equipment type and corresponding monitoring points of the data center maintenance equipment, the operational monitoring data is collected and correlated; for the equipment type and monitoring points, according to the triggering conditions set in the alarm rules, the operational monitoring data is subjected to threshold judgment to determine whether the alarm triggering conditions are met; when the alarm triggering conditions are met, corresponding equipment alarm event data is generated; wherein, the equipment alarm event data includes any one or more of the following: alarm equipment, alarm time, alarm level, and alarm content; when the operational monitoring data meets the recovery conditions set in the alarm rules, the alarm status of the corresponding equipment alarm event is terminated.

[0027] Furthermore, the triggering conditions set in the alarm rule include: for the corresponding monitoring point under the current device type, a preset threshold relationship condition is used to characterize the abnormal operating status, which is used to determine whether the magnitude relationship between the operating monitoring data and the corresponding threshold meets the preset magnitude relationship condition; and / or, based on the changes of the operating monitoring data within a preset time range, a preset proportional relationship condition is used to characterize the trend of operating status changes, which is used to determine whether the change magnitude of the operating monitoring data meets the preset proportional relationship condition; when the operating monitoring data meets any of the preset magnitude relationship conditions or the preset proportional relationship conditions, it is determined that the alarm triggering condition corresponding to the alarm rule is met.

[0028] In this embodiment of the invention, the data center operation and maintenance work order construction method starts from the operating status of the data center operation and maintenance equipment, and forms the basic data source required for subsequent work order construction by acquiring and processing the equipment operation monitoring data.

[0029] Specifically, during the operation of data center maintenance equipment, monitoring units installed on the equipment continuously collect monitoring data related to the equipment's operating status. The operational monitoring data can be collected from different monitoring points depending on the equipment type. For example, electrical equipment can collect parameters such as voltage and current, while environmental equipment can collect parameters such as temperature and humidity. After acquiring the operational monitoring data, the system performs correlation processing based on the equipment type and the corresponding monitoring points, establishing a correspondence between the operational monitoring data and specific equipment and monitoring points to facilitate subsequent rule-based judgments.

[0030] After collecting and correlating operational monitoring data, the system processes the data according to pre-defined alarm rules. These alarm rules are configured by operations and maintenance personnel based on the data center's operational needs and are used to characterize whether any abnormalities have occurred in the equipment's operational status. In this implementation, trigger conditions are set in the alarm rules for different equipment types and their corresponding monitoring points. Based on these trigger conditions, the system performs threshold judgment processing on the operational monitoring data to determine whether the current operational monitoring data meets the alarm trigger conditions.

[0031] When operational monitoring data meets the triggering conditions set in the alarm rules, corresponding equipment alarm event data is generated. Equipment alarm event data is used to record the occurrence of alarms, and its content includes at least one or more of the following: alarm device, alarm time, alarm level, and alarm content. Specifically, the alarm device indicates the specific device that triggered the alarm, the alarm time records the time the alarm occurred, the alarm level characterizes the severity of the alarm, and the alarm content describes the specific circumstances that triggered the alarm. By generating and recording equipment alarm event data, equipment malfunctions can be saved in structured data form, providing a data foundation for subsequent statistics and record creation.

[0032] Meanwhile, when the operating status of the equipment changes, and the operation monitoring data meets the recovery conditions set in the alarm rules, the corresponding equipment alarm event is processed to terminate the alarm status. This means that the operating status of the equipment is considered to have returned to the normal range, thus ending the effective status of the corresponding alarm event. By setting recovery conditions, alarm events have clear start and end states, preventing alarms from remaining in an inactive state for a long time.

[0033] Furthermore, in this embodiment, the triggering conditions set in the alarm rules are not limited to a single judgment method, but include multiple judgment conditions used to characterize abnormal equipment operating status. Specifically, for the corresponding monitoring point under the current equipment type, the alarm rules can preset threshold relationship conditions to characterize abnormal operating status, used to determine whether the magnitude relationship between the operating monitoring data and the corresponding threshold meets the preset magnitude relationship conditions. Through these threshold relationship conditions, it is possible to determine whether the equipment operating parameters exceed the normal range.

[0034] Furthermore, the alarm rules can also be based on the changes in operational monitoring data within a preset time range, pre-setting proportional relationship conditions to characterize the trend of operational status changes. This is used to determine whether the magnitude of the changes in operational monitoring data meets the preset proportional relationship conditions. By introducing trend judgment, alarm triggering not only depends on the operational status at a single moment but also reflects the changes in the equipment's operational status over time. When the operational monitoring data meets any preset magnitude relationship condition or preset proportional relationship condition, the system determines that the alarm triggering condition corresponding to the alarm rule is met and generates the corresponding equipment alarm event data accordingly.

[0035] In another possible implementation, to accommodate fluctuations in the operating status of data center equipment over different time periods, the triggering conditions of alarm rules can be dynamically adjusted based on the equipment's operating history. Specifically, before generating equipment alarm event data, the system obtains the distribution of the equipment's operating status over a preset historical time period based on operational monitoring data, and determines the baseline operating range for the corresponding monitoring points accordingly. When executing alarm rule judgments, the system compares the current operational monitoring data with the baseline operating range. When the current data deviates from the baseline operating range by a preset degree, it determines that the alarm triggering conditions corresponding to the alarm rule are met, thereby generating the corresponding equipment alarm event data. When the operational monitoring data falls back into the baseline operating range, it determines that the recovery conditions set in the alarm rule are met, and the alarm status of the corresponding equipment alarm event is terminated. Through this method, the alarm triggering process can be judged in conjunction with the equipment's own operating characteristics.

[0036] Step S20: Based on the device alarm event data, and in accordance with the intelligent order creation rules maintained by the operation and maintenance management personnel, the occurrence of alarm events within a preset time range is statistically analyzed.

[0037] Specifically, based on the device alarm event data, and according to the intelligent order creation rules maintained by the operation and maintenance personnel, the occurrence of alarm events within a preset time range is statistically analyzed. This includes: classifying and grouping alarm events based on the device alarm event data; determining the correspondence between the classified and grouped alarm events based on the combination of alarm devices, alarm rooms, and alarm types set in the intelligent order creation rules, to form corresponding statistical objects; performing time window filtering on the statistical objects according to the time range set in the intelligent order creation rules to determine the set of alarm events falling within the set time range; and counting the number of alarm events that meet the corresponding conditions of the intelligent order creation rules based on the set of alarm events.

[0038] Furthermore, the intelligent order creation rules include: spatial rules for limiting the scope of application of alarm events, wherein the spatial rules distinguish alarm events based on alarm devices and alarm rooms to determine the statistical range corresponding to the alarm events; timeliness rules for limiting the statistical time range of alarm events, wherein the timeliness rules are used to set the statistical time window of alarm events; alarm type rules for limiting the alarm event statistical objects, wherein the alarm type rules are used to distinguish between alarm events of the same alarm type and alarm events of different alarm types; and frequency rules for limiting the number of times alarm events trigger order creation conditions, wherein the frequency rules are used to set the occurrence frequency condition of alarm events within the time range limited by the timeliness rules.

[0039] Specifically, based on the alarm event set, the number of alarm events that meet the conditions corresponding to the smart order creation rule is counted, including: for the alarm event set, counting each alarm event according to the statistical criteria set in the smart order creation rule to obtain the cumulative number of alarm events under the corresponding statistical object; comparing the cumulative number of alarm events with the number rule set in the smart order creation rule to determine whether the alarm event set meets the number rule corresponding to the smart order creation rule.

[0040] In this embodiment of the invention, after generating the device alarm event data, the occurrence of alarm events within a preset time range is statistically processed based on the device alarm event data and in accordance with the intelligent order creation rules maintained by the operation and maintenance personnel, so as to provide a basis for judgment on whether to trigger the generation of a problem order in the future.

[0041] Specifically, the system reads device alarm event data generated by the aforementioned alarm rules. This device alarm event data is in structured format and contains at least one or more of the following: alarm device, alarm time, alarm level, and alarm content. Based on this data, the alarm events are categorized and aggregated. This categorization and aggregation process organizes alarm events from different devices and at different times, enabling each alarm event to be processed according to a unified data structure, thereby avoiding the statistical difficulties caused by scattered storage of alarm events.

[0042] After classifying and aggregating alarm events, based on the combination of alarm devices, alarm rooms, and alarm types defined in the smart order creation rules, the classified and aggregated alarm events are processed to determine their correspondence, thus forming corresponding statistical objects. Statistical objects represent the set of alarm events that need to be statistically analyzed under specific rule constraints. For example, under different smart order creation rules, a statistical object may correspond to a set of alarm events from the same alarm device, the same alarm room, or a specific alarm type. This method allows alarm events to be grouped into corresponding statistical objects under different rule dimensions, providing a clear statistical caliber for subsequent statistical processing.

[0043] After the statistical objects are formed, a time window filtering process is performed on each statistical object according to the time range set in the intelligent order creation rules. Specifically, the alarm time information corresponding to each alarm event in the statistical object is read and compared with the time range set in the intelligent order creation rules. Only alarm events whose alarm times fall within the set time range are retained, thus forming an alarm event set. This time window filtering process limits the statistical process to the preset time range, preventing old alarm events from interfering with the current order creation judgment.

[0044] After obtaining the set of alarm events, the system further counts the number of alarm events that meet the conditions for intelligent order creation. This statistical result reflects the actual frequency of alarm events under the current statistical object and time window conditions, providing a quantitative basis for determining whether the order creation conditions are met.

[0045] Furthermore, in this embodiment, the intelligent order creation rule is composed of a combination of multiple rule types. Specifically, it includes spatial rules to limit the applicable scope of alarm events, time-limited rules to limit the statistical time range of alarm events, alarm type rules to limit the statistical objects of alarm events, and frequency rules to limit the conditions for triggering order creation for alarm events. Spatial rules differentiate alarm events based on alarm devices and alarm rooms to determine the corresponding statistical range; time-limited rules are used to set the statistical time window for alarm events; alarm type rules are used to distinguish between alarm events of the same alarm type and alarm events of different alarm types; and frequency rules are used to set the occurrence frequency condition of alarm events within the time range limited by the time-limited rules. Through the combination of these rules, the intelligent order creation rule can constrain alarm events from multiple dimensions such as space, time, and alarm characteristics.

[0046] In the specific count process, for the alarm event set, each alarm event is counted individually according to the statistical criteria set in the intelligent ticket creation rules. Counting each alarm event individually involves iterating through each alarm event in the set and accumulating the count under the corresponding statistical object to obtain the cumulative count of alarm events under that statistical object. Subsequently, the cumulative count of alarm events is compared with the count rules set in the intelligent ticket creation rules to determine whether the alarm event set meets the corresponding count rules. Through this statistical and comparative process, whether a problem ticket generation is triggered can be determined based on clear statistical results, rather than relying on manual experience or a single alarm event.

[0047] Step S30: When the statistical results meet the order creation conditions corresponding to the intelligent order creation rule, and there are no problem orders generated based on the same intelligent order creation rule and in the processing state, generate the corresponding problem order.

[0048] Specifically, based on the alarm event set and the number of alarm events, a problem ticket generation condition is constructed to characterize the current alarm triggering status; when the problem ticket generation condition satisfies the creation condition corresponding to the intelligent creation rule, a corresponding problem ticket is created and marked as pending; when creating the problem ticket, based on the device alarm event data contained in the alarm event set, the corresponding alarm device, alarm time, and alarm content are extracted, and combined with the intelligent creation rule that triggers the generation of the problem ticket, the problem title of the problem ticket is generated; based on the device alarm event data contained in the alarm event set, the alarm event records are arranged in chronological order, and the arranged alarm event records are summarized to generate the problem content of the problem ticket.

[0049] In this embodiment of the invention, when the statistical results obtained based on the device alarm event data meet the order creation conditions corresponding to the intelligent order creation rule, and there are no problem orders generated based on the same intelligent order creation rule and in the processing state within the current time range, the problem order generation process is executed to realize the conversion of alarm events into problem orders.

[0050] Specifically, after confirming that the conditions for creating an issue ticket are met, issue ticket generation conditions are constructed based on the set of alarm events and the number of times the alarm events occur, to characterize the current alarm triggering status. The issue ticket generation conditions are used to comprehensively reflect the triggering status of the current alarm event under the constraints of the corresponding statistical object, time range, and number of occurrences, so that the generation of subsequent issue tickets is based on clear statistical judgments, rather than relying on a single alarm event or immediate judgment.

[0051] When the conditions for generating a problem ticket are met according to the intelligent problem ticket creation rules, the problem ticket creation operation is executed, and the created problem ticket is marked as pending. By marking problem tickets as pending, subsequent processing flows can clearly distinguish between problem tickets that have not yet been processed and those that have been processed, thus providing a basis for subsequent management and control of problem ticket status.

[0052] During the creation of a problem ticket, alarm information relevant to the generation of this problem ticket is extracted based on the device alarm event data contained in the alarm event set. Alarm information includes at least the alarm device, alarm time, and alarm content. The alarm device indicates the specific device that triggered the alarm, the alarm time reflects the chronological order of the alarm events, and the alarm content describes the specific circumstances that triggered the alarm. By extracting this information, the problem ticket accurately reflects the underlying facts of how the alarm was triggered.

[0053] When generating the issue title, the extracted alarm device information is combined with the intelligent issue creation rule that triggered the issue. Specifically, based on the rule type and constraints of the intelligent issue creation rule, the alarm device information is associated with rules to generate an issue title that represents the reason for triggering the current issue. In this way, the issue title can simultaneously reflect the alarm source and the characteristics of the triggering rule, facilitating subsequent identification and differentiation of issue issues.

[0054] When generating the issue content of an issue ticket, the alarm event records related to this issue ticket generation are organized and processed based on the device alarm event data contained in the alarm event set. Specifically, the alarm event records are arranged in chronological order of alarm occurrence, allowing the alarm events to be presented in the order of their occurrence. Subsequently, the arranged alarm event records are summarized to form the issue content of the issue ticket. The issue content is used to centrally display multiple alarm events that triggered the generation of this issue ticket within a preset time range, enabling the issue ticket to fully reflect the occurrence process of the alarm events.

[0055] In this way, the problem ticket generation process is driven by alarm event statistics and constructs the title and content of the problem ticket based on existing device alarm event data in the alarm event set, ensuring that the problem ticket accurately corresponds to the specific circumstances of alarm triggering. Simultaneously, by checking whether there are any problem tickets in a processing state before generating a problem ticket, duplicate generation of problem tickets under the same intelligent ticket creation rule is avoided, thus ensuring the orderliness and controllability of the problem ticket generation process.

[0056] In another possible implementation, a problem ticket merging and determination process is introduced before generating a problem ticket to avoid triggering multiple highly similar problem tickets within a short period of time due to similar alarms. Specifically, after establishing the problem ticket generation conditions, the features of alarm devices and alarm content are further extracted based on the alarm event set, and these features are compared with the corresponding features of problem tickets that have been generated but not yet archived within a preset time range.

[0057] When the comparison results meet the preset similarity conditions, no new issue ticket is created. Instead, the alarm event records corresponding to the current set of alarm events are merged into the existing issue ticket, and the issue content of the existing issue ticket is updated. When the comparison results do not meet the preset similarity conditions, a new issue ticket is created according to the original issue ticket generation process. In this way, the issue ticket generation process can adaptively adjust according to the degree of correlation between alarm events, thereby achieving centralized processing of similar alarms at the method level.

[0058] Step S40: After the problem ticket is processed and archived, the intelligent ticket creation rule statistics and judgment are re-executed for subsequent alarm events based on the archived results.

[0059] Specifically, based on the archived status of the issue ticket, the alarm event statistics restriction under the smart order creation rule corresponding to the issue ticket is lifted; after the alarm event statistics restriction is lifted, for subsequent newly generated device alarm event data, the alarm event statistics processing is re-executed according to the smart order creation rule; based on the results of the re-executed alarm event statistics processing, the order creation condition judgment corresponding to the smart order creation rule is re-executed for subsequent alarm events.

[0060] In this embodiment of the invention, after a problem ticket is processed and archived, the corresponding intelligent ticket creation process does not terminate. Instead, the relevant intelligent ticket creation rules are reactivated by processing the archived results, thereby continuing to perform statistical and judgment processing on newly generated alarm events to ensure that the ticket creation process has continuity and repeatable triggering capability.

[0061] Specifically, after a problem ticket is processed and archived, the first step is to remove the alarm event statistics restriction corresponding to that problem ticket based on its archived status. The alarm event statistics restriction is used to prevent the repeated generation of new problem tickets under the same smart ticket creation rule constraints while the problem ticket is in the processing state. Once a problem ticket enters the archived state, it indicates that the alarm handling process for that problem ticket has ended. At this point, by removing the alarm event statistics restriction, the smart ticket creation rule corresponding to that problem ticket is restored to a state where it can be triggered again.

[0062] After removing the statistical restrictions on alarm events, the method further re-executes the statistical processing of newly generated equipment alarm event data according to the intelligent order creation rules. Newly generated equipment alarm event data refers to data generated after the issue order archiving time, and its source, data structure, and generation method remain consistent with the aforementioned equipment alarm event data. By performing statistical processing only on newly generated alarm event data after archiving, alarm events that participated in the previous round of order creation are avoided from being repeatedly included in the statistical scope, thus ensuring the temporal consistency of the statistical process.

[0063] During the re-execution of alarm event statistical processing, the intelligent order creation rules still process alarm events according to the established rules, including but not limited to forming statistical objects based on alarm devices, alarm rooms, and alarm types, and filtering alarm events within a time window according to the time range set in the intelligent order creation rules, and then counting the occurrence of alarm events. This method ensures that the archived statistical processing is consistent with the initial statistical processing, guaranteeing the consistency of the execution logic of the intelligent order creation rules across different triggering cycles.

[0064] After completing the statistical processing of subsequent alarm events, the method, based on the results of the re-executed alarm event statistical processing, re-executes the order creation condition judgment corresponding to the intelligent order creation rule for subsequent alarm events. The order creation condition judgment is used to determine whether the occurrence of alarm events within the current statistical object and time range meets the order creation conditions set in the intelligent order creation rule. When the number of alarm events obtained from the re-statistics meets the order creation conditions, the problem ticket generation process begins; when the order creation conditions are not met, the statistical processing of newly generated alarm event data continues, and no new problem tickets are generated.

[0065] Through the above processing method, after the issue ticket is archived, the statistical and judgment process of the intelligent ticket creation rules can be restarted, allowing alarm events to participate in the ticket creation judgment again in the new statistical cycle. This implementation method avoids the problem of the intelligent ticket creation process being permanently blocked after the issue ticket is processed. At the same time, by lifting the statistical restrictions and re-statistically executing in stages, the issue ticket generation process has clear trigger boundaries and state recovery mechanisms, thereby ensuring the continuous execution of the entire alarm processing and issue ticket creation process in the time dimension.

[0066] In another possible implementation, a cooling-off window control is introduced during the re-execution of the intelligent order creation rule statistics and judgment process after an issue ticket is archived, to prevent issue tickets from being frequently triggered repeatedly in a short period of time. Specifically, after removing the alarm event statistics restrictions corresponding to the archived issue tickets, a preset cooling-off time range is set for the intelligent order creation rule. Within the cooling-off time range, newly generated equipment alarm event data is still recorded and classified, but alarm events are not included in the order creation condition judgment. Only after the cooling-off time range ends are the alarm events accumulated during the cooling period and the newly generated alarm events after the cooling-off period included in the alarm event statistics processing, and the order creation condition judgment corresponding to the intelligent order creation rule is re-executed. Through the above method, the statistical and judgment process after issue ticket archiving has a buffer mechanism in the time dimension, thereby achieving rhythm control of continuous abnormal scenarios at the method level and avoiding frequent generation of issue tickets due to short-term repeated fluctuations in equipment operating status.

[0067] In one specific implementation, the data center operation and maintenance work order creation method is applied to data center operation and maintenance scenarios with equipment operation monitoring and alarm management capabilities. Roles and permissions are configured for personnel involved in operation and maintenance management to ensure that the maintenance of intelligent work order creation rules and alarm rules has clear management boundaries. Specifically, the roles of maintenance management personnel include system administrators, operation and maintenance managers, operation and maintenance department leaders, and operation and maintenance team leaders. All of these roles have the authority to maintain intelligent work order creation rules and can configure, modify, and update these rules according to data center operation and maintenance management requirements to support work order creation needs under different business scenarios.

[0068] After completing the role and permission configuration, the alarm rules for the data center's maintenance equipment are further maintained and managed. Each type of alarm rule is named and its corresponding parameters are configured by creating new alarm rules. The configuration of alarm rules includes the alarm device, alarm triggering conditions, alarm scope, alarm level, and alarm aggregation rules. Specifically, in the alarm level settings, alarm levels are defined as warning, general alarm, and critical alarm, and adjustments to the alarm level are allowed based on actual maintenance requirements. In the alarm device type settings, the types of devices to be monitored are configured, such as battery banks. In the monitoring point settings, the monitoring points for the device types involved in the alarm are defined; for example, voltage is set as a monitoring point for battery banks.

[0069] In the alarm trigger condition configuration, trigger thresholds and change conditions are set for monitoring points, including threshold-based trigger conditions and change-proportion-based trigger conditions. For example, an alarm can be triggered when the battery pack voltage is less than or equal to a preset value, or when the monitored data increases or decreases by more than a preset proportion. Simultaneously, corresponding recovery conditions are configured. When the monitored data meets the recovery conditions, the alarm status is exited. For example, when the battery pack voltage recovers to a value greater than a preset value, the fault is determined to be recovered and the alarm status is terminated.

[0070] After configuring the alarm rules, further configure the intelligent order creation rules. The professional team leader maintains the applicable device types for the intelligent order creation rules, which apply to all device types by default; when a specific device type is selected, intelligent data retrieval and statistics are performed only for devices within that selected type. Simultaneously, configure the corresponding timeliness rules for each rule type according to actual business needs to limit the statistical time range and trigger frequency conditions for alarm events. The intelligent order creation rules support joint querying of detailed device information, joint querying of alarm records triggered by the rules, and joint querying of generated issue tickets, facilitating traceability of the basis for order creation.

[0071] In this embodiment, the intelligent order creation rules include the following rule types: 1) For a single device, the same alarm must have occurred 3 times within the past year.

[0072] 2) A single device, different alarms, with a time limit of 3 occurrences within the past month.

[0073] 3) The same equipment in the same room, the same alarm, the time limit is 3 times within the past month.

[0074] 4) Different alarms from the same equipment in the same room, with a time limit of 5 occurrences within the past week.

[0075] 5) For the same alarm on different devices, the time limit is 5 times within the past week.

[0076] For each rule category, statistical judgments are made based on alarm devices, alarm rooms, alarm types, and alarm levels that are either critical or general alarms and have not been masked.

[0077] When the alarm occurrence count condition set by the rule is met within the corresponding time frame, an issue ticket will be automatically generated and submitted to the professional team leader of the profession to which the alarm device belongs for processing. If an issue ticket already exists and is being processed based on the same smart ticket creation rule during the continuous occurrence of the alarm, no new issue ticket will be generated. After the issue ticket is processed, if the same rule condition is met again, a new issue ticket will be generated again.

[0078] Once the conditions for intelligent order creation are met, an issue order is generated. Based on the automatic order creation rules and alarm data, real-time calculations are performed to generate an issue order containing information such as the issue description and its source. The person responsible for handling the issue order is determined from a pre-set production safety operation group: when the specialty of the alarm device is clearly defined, the issue order is sent to the corresponding specialty personnel and personnel whose specialty is not specified in the group; when the specialty of the alarm device and the alarm room is not specified or is not unique, the issue order is sent to all personnel in the group.

[0079] Figure 1 This is a flowchart illustrating a method for constructing data center operation and maintenance work orders in one embodiment. It should be understood that, although... Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0080] In one embodiment, such as Figure 2As shown, a data center operation and maintenance work order generation system is provided. The system includes: a data acquisition unit, used to acquire operation monitoring data of data center operation and maintenance equipment, and generate equipment alarm event data based on the operation monitoring data according to preset alarm rules; a statistics unit, used to statistically analyze the occurrence of alarm events within a preset time range based on the equipment alarm event data and according to intelligent work order creation rules maintained by operation and maintenance personnel; a generation unit, used to generate a corresponding problem order when the statistical result meets the work order creation conditions corresponding to the intelligent work order creation rule, and there are no problem orders generated based on the same intelligent work order creation rule and in a processing state; and an archiving unit, used to re-execute intelligent work order creation rule statistics and judgment on subsequent alarm events based on the archiving result after the problem order is processed and archived.

[0081] This application provides a storage medium on which a program is stored. When the program is executed by a processor, it implements the above-described method for constructing data center operation and maintenance work orders.

[0082] This application provides a processor for running a program, wherein the program executes the above-described data center operation and maintenance work order construction method during runtime.

[0083] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 3 As shown in the figure, the computer device includes a processor A01, a network interface A02, a display screen A04, an input device A05, and a memory (not shown) connected via a system bus. The processor A01 provides computing and control capabilities. The memory includes internal memory A03 and a non-volatile storage medium A06. The non-volatile storage medium A06 stores an operating system B01 and a computer program B02. The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 stored in the non-volatile storage medium A06. The network interface A02 is used for communication with external terminals via a network connection. When the computer program is executed by the processor A01, it implements a method for constructing a data center maintenance work order. The display screen A04 can be an LCD screen or an e-ink display screen. The input device A05 can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0084] Those skilled in the art will understand that Figure 3The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0085] This application also provides a computer program product, which, when executed by a processor, implements the above-described method for constructing data center operation and maintenance work orders.

[0086] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0087] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0088] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0089] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0090] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0091] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0092] Computer-readable media include both permanent and non-permanent, removable and non-removable media, which can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0093] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0094] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for constructing data center operation and maintenance work orders, characterized in that, The method includes: Acquire operational monitoring data of the data center maintenance equipment, and generate equipment alarm event data based on the operational monitoring data according to preset alarm rules; Based on the device alarm event data, and in accordance with the intelligent order creation rules maintained by the operation and maintenance personnel, the occurrence of alarm events within a preset time range is statistically analyzed. When the statistical results meet the order creation conditions corresponding to the intelligent order creation rule, and there are no problem orders generated based on the same intelligent order creation rule and in the processing state, the corresponding problem order is generated; After the problem ticket is processed and archived, the intelligent ticket creation rules are re-executed and judged based on the archived results for subsequent alarm events.

2. The method for constructing data center operation and maintenance work orders according to claim 1, characterized in that, Acquire operational monitoring data of the data center maintenance equipment, and generate equipment alarm event data based on the operational monitoring data according to preset alarm rules, including: Based on the equipment type and corresponding monitoring point of the data center operation and maintenance equipment, the operation monitoring data is collected and correlated; For the device type and monitoring point, the operation monitoring data is subjected to threshold judgment according to the triggering conditions set in the alarm rules to determine whether the alarm triggering conditions are met; When the alarm triggering conditions are met, corresponding device alarm event data is generated; wherein, The device alarm event data includes any one or more of the following: alarm device, alarm time, alarm level, and alarm content; When the operational monitoring data meets the recovery conditions set in the alarm rules, the alarm status of the corresponding device alarm event is terminated.

3. The method for constructing data center operation and maintenance work orders according to claim 2, characterized in that, The triggering conditions set in the alarm rules include: For the corresponding monitoring points under the current equipment type, a preset threshold relationship condition is used to characterize abnormal operating status, which is used to determine whether the size relationship between the operating monitoring data and the corresponding threshold satisfies the preset size relationship condition. And / or, based on the changes in the operation monitoring data within a preset time range, a preset proportional relationship condition is used to characterize the trend of changes in the operation status, and to determine whether the change magnitude of the operation monitoring data meets the preset proportional relationship condition; When the monitoring data meets any of the preset size relationship conditions or the preset ratio relationship conditions, it is determined that the alarm triggering condition corresponding to the alarm rule is met.

4. The method for constructing data center operation and maintenance work orders according to claim 1, characterized in that, Based on the device alarm event data, and according to the intelligent order creation rules maintained by the operation and maintenance personnel, the occurrence of alarm events within a preset time range is statistically analyzed, including: Based on the device alarm event data, the alarm events are classified and collected. Based on the combination of alarm devices, alarm rooms, and alarm types set in the intelligent order creation rules, the corresponding relationships of the classified and collected alarm events are determined to form corresponding statistical objects. For the statistical object, a time window filtering process is performed according to the time range set in the intelligent order creation rule to determine the set of alarm events falling within the set time range; Based on the set of alarm events, count the number of alarm events that meet the conditions corresponding to the smart order creation rules.

5. The method for constructing data center operation and maintenance work orders according to claim 4, characterized in that, The intelligent order creation rules include: Spatial rules are used to limit the scope of application of alarm events. These spatial rules distinguish alarm events based on alarm devices and alarm rooms to determine the statistical range corresponding to the alarm events. A timeliness rule used to limit the statistical time range of alarm events, wherein the timeliness rule is used to set the statistical time window for alarm events; Alarm type rules are used to define the objects of alarm event statistics, and the alarm type rules are used to distinguish between alarm events of the same alarm type and alarm events of different alarm types; The frequency rule is used to limit the number of times an alarm event is triggered to create a case. The frequency rule is used to set the number of times an alarm event occurs within the time limit defined by the time limit rule.

6. The method for constructing data center operation and maintenance work orders according to claim 5, characterized in that, Based on the set of alarm events, the number of alarm events that meet the corresponding conditions of the intelligent order creation rule is counted, including: For the set of alarm events, each alarm event is counted according to the statistical criteria set in the smart order creation rules to obtain the cumulative number of alarm events under the corresponding statistical object; The cumulative number of alarm events is compared with the number of events set in the smart order creation rule to determine whether the set of alarm events meets the number of events corresponding to the smart order creation rule.

7. The method for constructing data center operation and maintenance work orders according to claim 1, characterized in that, When the statistical results meet the order creation conditions corresponding to the intelligent order creation rule, and there are no problem orders generated based on the same intelligent order creation rule and currently in a processing state, a corresponding problem order is generated, including: Based on the set of alarm events and the number of times the alarm events occurred, question form generation conditions are constructed to characterize the current alarm triggering situation; When the conditions for generating the problem order meet the conditions for creating the order corresponding to the intelligent order creation rule, a corresponding problem order is created and the problem order is marked as pending. When creating the issue ticket, based on the device alarm event data contained in the alarm event set, the corresponding alarm device, alarm time and alarm content are extracted, and combined with the intelligent ticket creation rule that triggers the generation of the issue ticket, the issue title of the issue ticket is generated; Based on the device alarm event data contained in the alarm event set, the alarm event records are arranged in chronological order of alarm time, and the arranged alarm event records are summarized to generate the problem content of the problem form.

8. The method for constructing data center operation and maintenance work orders according to claim 7, characterized in that, After the issue ticket is processed and archived, the intelligent ticket creation rules are re-executed and judged based on the archived results for subsequent alarm events, including: Based on the archived status of the issue ticket, the alarm event statistics restriction under the smart ticket creation rule corresponding to the issue ticket is lifted; After the alarm event statistics restriction is lifted, the alarm event statistics processing is re-executed according to the smart order creation rules for any newly generated device alarm event data. Based on the statistical processing results of the re-executed alarm events, the order creation condition judgment corresponding to the intelligent order creation rule is executed again for subsequent alarm events.

9. A data center operation and maintenance work order creation system, characterized in that, The system includes: The data acquisition unit is used to acquire the operation monitoring data of the data center maintenance equipment and generate equipment alarm event data based on the operation monitoring data according to the preset alarm rules. The statistics unit is used to perform statistics on the occurrence of alarm events within a preset time range based on the device alarm event data and according to the intelligent order creation rules maintained by the operation and maintenance management personnel. The generation unit is used to generate a corresponding problem order when the statistical results meet the order creation conditions corresponding to the intelligent order creation rule, and there are no problem orders generated based on the same intelligent order creation rule and in the processing state. The archiving unit is used to re-execute intelligent order creation rule statistics and judgment on subsequent alarm events based on the archiving results after the problem order has been processed and archived.

10. A processor, characterized in that, It is configured to execute the data center operation and maintenance work order construction method according to any one of claims 1 to 8.

11. A machine-readable storage medium storing instructions thereon, characterized in that, When executed by the processor, this instruction causes the processor to be configured to perform the data center operation and maintenance work order construction method according to any one of claims 1 to 8.

12. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the data center operation and maintenance work order construction method according to any one of claims 1 to 8.

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