Equipment decommissioning process management method and device, equipment and readable storage medium

Abstract

The invention relates to an equipment decommissioning process management method and device, equipment and a readable storage medium. The method comprises the following steps: acquiring identification information, state information and full life cycle information of each device; for the identification information, based on the full life cycle information, performing multi-modal data fusion and weighting processing on the state information in sequence, and generating health score data of the equipment; and determining health state information of the equipment based on the health score data. By adopting the method, the equipment management can be optimized.

Description

Technical Field

[0001] This application relates to the technical field of equipment management, and particularly to a method, device, equipment, and readable storage medium for managing the equipment retirement process. Background Art

[0002] With the rapid development of information technology, the number of information technology (IT) devices in enterprises has increased sharply, and equipment retirement management has become an important part of IT asset management.

[0003] Traditional IT equipment retirement processes often rely on manual records and tracking, making it difficult to effectively manage IT equipment. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method, device, equipment, and readable storage medium for managing the equipment retirement process that can optimize equipment management.

[0005] In a first aspect, this application provides a method for managing the equipment retirement process, including:

[0006] Obtain the identification information, status information, and full life cycle information of each device;

[0007] For the identification information, based on the full life cycle information, perform multi-modal data fusion and weighted processing on the status information in sequence to generate the health score data of the device;

[0008] Based on the health score data, determine the health status information of the device.

[0009] In one embodiment, the above status information includes the running time, historical maintenance records, and the number of failures; the full life cycle information includes the initial stage, the mature stage, and the decline stage. Based on the full life cycle information, performing multi-modal data fusion and weighted processing on the status information in sequence includes:

[0010] In the initial stage, the mature stage, and the decline stage, perform data fusion processing on the running time, historical maintenance records, and the number of failures respectively to obtain the fused status information;

[0011] Determine the weight information corresponding to the multiple fused status information respectively;

[0012] Perform weighted processing on the multiple weight information to determine the health status information of the device.

[0013] In one embodiment, the above method further includes:

[0014] Based on the adaptive weighted algorithm, perform weight adjustment processing on the multiple weight information to obtain the adjusted weight information;

[0015] Correspondingly, multiple weight information is weighted to determine the health status information of the device, including:

[0016] The multiple adjusted weight information is weighted to determine the health status information of the device.

[0017] In one embodiment, the above method further includes:

[0018] The health status information is divided into a healthy state, a sub-healthy state, a critical retirement state, and an immediate retirement state according to a preset status level;

[0019] When the status information corresponding to the device indicates that the device is in the immediate retirement state, a retirement process is triggered;

[0020] Based on the identification information and the retirement process, the retirement process information corresponding to the device is recorded.

[0021] In one embodiment, the above method further includes:

[0022] After the device is retired, data erasure processing or destruction processing is performed on the data on the device.

[0023] In one embodiment, the above method further includes:

[0024] Based on the retirement process information of multiple devices, the usage pattern information of the devices is determined;

[0025] Based on the usage pattern information, retirement trend prediction processing is performed on a type of device corresponding to the device.

[0026] In a second aspect, the present application further provides a device retirement process management device, including:

[0027] An acquisition module, configured to acquire the identification information, status information, and full life cycle information of each device;

[0028] A processing module, configured to perform multi-modal data fusion and weighting processing on the status information in sequence based on the full life cycle information for the identification information, to generate health score data of the device;

[0029] A determination module, configured to determine the health status information of the device based on the health score data.

[0030] In a third aspect, the present application further provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0031] Acquire the identification information, status information, and full life cycle information of each device;

[0032] For the identification information, based on the full - life - cycle information, perform multi - modal data fusion and weighted processing on the status information in sequence to generate the health score data of the device;

[0033] Based on the health score data, determine the health status information of the device.

[0034] In a fourth aspect, the present application also provides a computer - readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0035] Obtain the identification information, status information, and full - life - cycle information of each device;

[0036] For the identification information, based on the full - life - cycle information, perform multi - modal data fusion and weighted processing on the status information in sequence to generate the health score data of the device;

[0037] Based on the health score data, determine the health status information of the device.

[0038] In a fifth aspect, the present application also provides a computer program product, including a computer program. When the computer program is executed by a processor, the following steps are implemented:

[0039] Obtain the identification information, status information, and full - life - cycle information of each device;

[0040] For the identification information, based on the full - life - cycle information, perform multi - modal data fusion and weighted processing on the status information in sequence to generate the health score data of the device;

[0041] Based on the health score data, determine the health status information of the device.

[0042] For the above - mentioned device retirement process management method, device, equipment, and readable storage medium, first obtain the identification information, status information, and full - life - cycle information of each device; for the identification information, based on the full - life - cycle information, perform multi - modal data fusion and weighted processing on the status information in sequence to generate the health score data of the device; finally, based on the health score data, determine the health status information of the device. In this method, by obtaining the identification information, status information, and full - life - cycle information of each device, all - round data of the device can be obtained. Through these information, the current health status of the device can be deeply understood, so as to be able to timely judge whether maintenance, component replacement, or retirement is required, and then optimize device management. In addition, by generating the health status information of the device based on the health score data, priority sorting can be carried out among multiple devices, and more resources can be allocated to those devices with poor health conditions and about to fail. Through this optimized management, it can ensure the maximum utilization efficiency of resources during the operation of the device, reduce the device downtime, and at the same time improve the utilization rate of device assets, and avoid production or operation interruption caused by sudden device failures. Brief Description of the Drawings

[0043] To more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for the description of the embodiments of the present application or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0044] Figure 1 Internal structure diagram of a computer device in one embodiment;

[0045] Figure 2 Flow schematic diagram of the equipment retirement process management method in one embodiment;

[0046] Figure 3 Flow schematic diagram of the equipment retirement process management method in another embodiment;

[0047] Figure 4 Flow schematic diagram of the equipment retirement process management method in another embodiment;

[0048] Figure 5 Flow schematic diagram of the equipment retirement process management method in another embodiment;

[0049] Figure 6 Structural block diagram of the equipment retirement process management device in one embodiment. Detailed Description of the Preferred Embodiments

[0050] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the following further details the present application in conjunction with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0051] In an exemplary embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as shown in Figure 1As shown in the figure. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store relevant data during the management process of the device retirement process. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it realizes a method for managing the device retirement process.

[0052] Those skilled in the art can understand that Figure 1 the structure shown in the figure is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0053] In an exemplary embodiment, as Figure 2 shown, a method for managing the device retirement process is provided. Taking the computer device in Figure 1 as an example for illustration, it includes the following steps 201 to step 203. Among them:

[0054] Step 201, obtain the identification information, status information, and full life cycle information of each device.

[0055] Among them, the identification information refers to the basic data that uniquely identifies the device. The identification information is used to distinguish each device and ensure that each device can be accurately tracked and managed. The identification information may include:

[0056] (1) Device number: The unique identification code of each device;

[0057] (2) Device model: The production model or type of the device;

[0058] (3) Production date: The manufacturing time of the device;

[0059] (4) Device manufacturer: The manufacturer or supplier of the device.

[0060] Status information refers to the data that reflects the current health and operating conditions of a device. It can include the usage history, performance metrics, and current fault status of the device, etc. Status information can include:

[0061] (1) Environmental parameters such as device temperature and vibration: reflecting the impact of the device's working environment on its health;

[0062] (2) Device performance metrics: such as output power, load, efficiency, etc.

[0063] Full life cycle information refers to all relevant information during the entire process of a device from design, manufacturing, use, maintenance, to retirement. Full life cycle information can help comprehensively understand the device's history, current status, and possible future changes. Common full life cycle information includes:

[0064] (1) Design and production stage: the design specifications, production process, and quality control records of the device;

[0065] (2) Usage stage: the usage records, operating environment, maintenance records, and fault history of the device;

[0066] (3) Retirement and scrapping stage: the time of device retirement, reasons for retirement, handling methods, etc.

[0067] In the embodiments of this application, first, the identification information, status information, and full life cycle information of each device need to be obtained. The identification information of the device includes the device ID, model, production date, etc., which is used to uniquely identify the device. The status information includes the performance parameters of the device (such as CPU usage rate, memory usage), as well as environmental parameters such as temperature and vibration, reflecting the current operating conditions of the device. In addition, the full life cycle information of the device records all key data during the process from production to retirement, including the device's manufacturer, historical maintenance records, and retirement information, etc.

[0068] Step 202, for the identification information, based on the full life cycle information, perform multi-modal data fusion and weighted processing on the status information in sequence to generate the health score data of the device.

[0069] Among them, the health score data is a numerical value obtained by analyzing and processing various status information and full life cycle data of the device, and is used to represent the overall health status of the device.

[0070] The health score data can be a continuous value (such as a score from 0 to 100), or it can be a category (such as "good", "needs maintenance", "about to fail", etc.).

[0071] In the embodiments of this application, the computer device performs multi-modal data fusion and weighted processing on the status information of the device based on the identification information and full life cycle information of the device.

[0072] Among them, multi-modal data fusion integrates data from different sources. For example, different types of feature data such as the usage history of the device, performance metrics, and current fault status are fused into a unified feature representation. After fusion, weighted processing is used to assign different importance to various types of data to ensure that the most critical factors in device health assessment are properly emphasized. For example, the current fault status has a greater impact on the device health condition, so a higher weight can be assigned.

[0073] After the fusion and weighted processing are completed, the computer device can generate the health score data of the device through a prediction model. Among them, the health score data is a numerical value, usually in the range of 0 to 100, which is used to represent the overall health condition of the device. According to the health score data, the computer device can further judge the health status of the device. For example, a score above 80 indicates that the device is healthy, a score between 50 and 80 may require maintenance, and a score below 50 may face the risk of an impending failure.

[0074] Step 203: Determine the health status information of the device based on the health score data.

[0075] Among them, the health status information refers to the information obtained by evaluating the current health condition of the device based on the health score data. Based on the health status information, it can be judged whether the device is in a normal working state, needs maintenance, has a high fault risk, etc. The health status information helps technicians in this field take corresponding measures for the device, such as maintenance, repair, replacement, etc. Among them, the categories of the health status information can be: "Healthy (Good)", "Needs Maintenance", "High Fault Risk", "Needs Retirement", etc.

[0076] In the embodiment of the present application, according to the health score data, the computer device can generate the health status information of the device and provide support for device management decisions. The health status information can be the health level of the device (such as "Healthy", "Needs Maintenance", or "Impending Failure"), and based on the health status information, suggestions for the subsequent management of the device are provided.

[0077] For example, if the health score is low, the computer device will generate a maintenance suggestion to remind that the device needs to be inspected or components replaced to avoid unexpected failures of the device. In addition, the computer device can also predict faults in advance and send early warnings to help managers perform repairs or replace the device in a timely manner, thereby improving the reliability of the device and reducing the downtime cost.

[0078] In the above device retirement process management method, first obtain the identification information, status information, and full life cycle information of each device; for the identification information, based on the full life cycle information, perform multi-modal data fusion and weighting processing on the status information in sequence to generate the health score data of the device; finally, based on the health score data, determine the health status information of the device; in this method, by obtaining the identification information, status information, and full life cycle information of each device, all-round data of the device can be obtained. Through these information, the current health status of the device can be deeply understood, so as to be able to timely judge whether maintenance, component replacement, or retirement is required, and then optimize device management. In addition, by generating the health status information of the device based on the health score data, priority sorting can be performed among multiple devices, and more resources can be allocated to those devices with poor health conditions and about to fail. Through this optimized management, it is possible to ensure the maximum utilization efficiency of resources during the operation of the device, reduce the device downtime, improve the utilization rate of device assets at the same time, and avoid production or operation interruption caused by sudden device failures.

[0079] In an exemplary embodiment, the above status information includes operation time, historical maintenance records, and the number of failures; the full life cycle information includes the initial stage, the mature stage, and the decline stage. On this basis, as Figure 3 shown, the above-mentioned "performing multi-modal data fusion and weighting processing on the status information in sequence based on the full life cycle information" in the above embodiment includes steps 301 to 303. Among them:

[0080] Step 301, in the initial stage, the mature stage, and the decline stage, perform data fusion processing on the operation time, historical maintenance records, and the number of failures respectively to obtain the fused status information.

[0081] Among them, the operation time refers to the cumulative working time of the device from the start of use to the current moment, usually in hours or days. The operation time reflects the usage intensity of the device, and long-term operation may cause device aging or performance degradation.

[0082] The historical maintenance record refers to the detailed record of all maintenance operations of the device during its life cycle. It includes information such as the time, content, and maintenance personnel of the maintenance. The historical maintenance record can help analyze the long-term health status of the device and identify potential failure modes.

[0083] The number of failures refers to the number of times the device fails during use. The number of failures is an important indicator for evaluating the reliability and health status of the device. Frequent failures usually mean a decline in the performance of the device or serious problems.

[0084] The initial stage refers to the initial stage of the device life cycle, usually a period of time when the device is first put into use. In this stage, the performance of the device is usually relatively stable, and the probability of failure is relatively low.

[0085] The maturity stage refers to the stable stage in the equipment life cycle. The performance of the equipment is relatively stable, the operating efficiency is high, and the frequency and degree of failures are relatively low. The equipment has been used for a period of time, and its performance tends to be stable.

[0086] The decline stage refers to the final stage of the equipment life cycle. The equipment performance deteriorates, the failure frequency may increase, and the equipment may be approaching its intended service life. This stage usually requires more frequent maintenance and inspections.

[0087] In the embodiment of the present application, in the initial stage of the equipment, the equipment is usually in a relatively stable state, with fewer failures and a shorter operating time. At this time, the health assessment of the equipment mainly relies on the operating time and historical maintenance records. The fusion step can be: combining the operating time of the equipment with the first maintenance record. For example, if the equipment has a short operating time and no failures or maintenance occur, it indicates that the health state of the equipment is good, thus obtaining the fused state information in the initial stage. If the equipment has had some minor failures or maintenance problems at this stage, these information should be combined to make appropriate adjustments to the fused state information.

[0088] After entering the maturity stage, the number of equipment failures and maintenance records begins to increase. Therefore, the number of failures and maintenance records gradually become the key indicators for equipment health assessment. In this stage, the fusion steps are as follows:

[0089] The increase in the equipment failure frequency usually means that the equipment is gradually aging or the performance of some components is deteriorating. Therefore, the number of failures needs to be fused with the historical maintenance records (such as the number of repairs, repair types, repair times, etc.) to obtain the fused state information in the maturity stage.

[0090] In the decline stage, the impact of the number of equipment failures and maintenance records is the most significant because the equipment fails frequently and the maintenance work is also more frequent at this time. The data fusion method in the decline stage is as follows:

[0091] By analyzing the equipment failure history (such as the frequency of failure occurrence, failure types, complexity of repair, etc.) and maintenance records (such as overhaul records, replacement of key components, etc.), the decline degree of the equipment can be effectively judged, thus obtaining the fused state information in the decline stage.

[0092] Step 302, respectively determine the weight information corresponding to multiple fused state information.

[0093] In the embodiments of the present application, after data fusion processing, weights need to be assigned to the fusion status information of each stage. The influence degrees of the device status information in different life cycle stages on health assessment are different. Therefore, it is necessary to determine their weights according to the actual situation of each stage. Exemplarily, in the initial stage, the running time and historical maintenance records of the device are usually the main bases for evaluating the health status because there are fewer faults and the performance is relatively stable at this time. In the mature stage, the number of faults and historical maintenance records are the main bases for evaluating the health status because the device has been used for a certain period of time and may have small-scale faults or performance degradation. In the decline stage, the number of faults and historical maintenance records have the most significant influence on health assessment because the device may face a higher fault frequency and maintenance requirements at this stage. Therefore, a higher weight needs to be assigned to the fused status information corresponding to the decline stage, the weight assigned to the fused status information corresponding to the mature stage is the second, and the weight assigned to the fused status information corresponding to the initial stage is the lowest.

[0094] Step 303: Perform weighted processing on multiple weight information to determine the health status information of the device.

[0095] In the embodiments of the present application, based on the weight information, weighted processing is performed on the fused status information of each stage to obtain a comprehensive health score. The weighted score can be divided into different health levels according to certain criteria, such as healthy, in need of maintenance, about to fail, etc., providing a clear decision-making basis for device managers.

[0096] Finally, the health status information of the device is obtained by comprehensively considering the health scores of each stage. This health status information reflects the health level of the device throughout its life cycle, helps managers determine whether the device needs maintenance or replacement, and reduces the risk of device failures. Through such a health assessment method, the current state of the device can be accurately reflected, and a scientific basis can be provided for subsequent management and maintenance.

[0097] In an exemplary embodiment, the above method further includes:

[0098] Perform weight adjustment processing on multiple weight information based on an adaptive weighting algorithm to obtain adjusted weight information;

[0099] Correspondingly, performing weighted processing on multiple weight information to determine the health status information of the device includes:

[0100] Perform weighted processing on multiple adjusted weight information to determine the health status information of the device.

[0101] In the embodiments of the present application, the computer device can utilize the adaptive weighting algorithm and dynamically adjust the weight of each status information according to the actual operating conditions of the device, such as the failure frequency, the extension of the operating time, and the change of the maintenance record.

[0102] Exemplarily, when the number of failures of the device increases in a certain stage, the adaptive weighting algorithm can automatically assign a higher weight to the number of failures. If the device has no failures but has a large number of maintenance records, the weight of the maintenance record will be correspondingly reduced. Using this adaptive mechanism, the computer system can continuously optimize each weight according to the health status of the device, making the evaluation result more in line with the actual health status of the device.

[0103] Next, for each status information and its adjusted weight, the comprehensive health score of the device is obtained through weighted processing. The weighted processing can be achieved by weighted average. Each status information is multiplied by its adjusted weight and then summed to finally obtain the health status information.

[0104] In the above embodiments, the weight information is adjusted by the adaptive weighting algorithm, and weighted processing is combined with the device status information to finally determine the health status of the device. This process can not only dynamically adjust the weight to make the device health assessment more accurate, but also continuously optimize the evaluation result according to the real-time operating conditions of the device, thereby effectively improving the management and maintenance efficiency of the device.

[0105] In an exemplary embodiment, as Figure 4 shown, the above method further includes steps 401 to 403. Among them:

[0106] Step 401, divide the health status information into a healthy state, a sub-healthy state, a critical retirement state, and an immediate retirement state according to a preset status level.

[0107] Among them, the healthy state means that the health condition of the device is good, the device can operate stably, and no serious failures or performance degradation occur.

[0108] The sub-healthy state means that there is a certain risk in the health condition of the device. The device may experience a certain degree of performance degradation or occasional minor failures. Although it can still be used temporarily, it needs attention and regular inspections.

[0109] The critical retirement state means that the device is in a state close to retirement, with frequent failures and obvious performance degradation, but it can still be used and does not affect the basic functions.

[0110] The immediate retirement state means that the health condition of the device has deteriorated severely and it can no longer be used effectively, which may affect the safety of the system or other devices.

[0111] In the embodiments of the present application, the computer device divides the device health status into four levels: "healthy status", "sub-healthy status", "critical retirement status", and "immediate retirement required status" according to the health score of the device and the preset status level criteria.

[0112] Step 402, when the status information corresponding to the device indicates that the device is in the immediate retirement required status, trigger the retirement process.

[0113] Among them, the retirement process refers to a series of steps for the procedures of deactivating, disassembling, recycling, or disposing of the device. When the device enters the "immediate retirement required status", the computer device will automatically trigger the retirement process, including links such as device uninstallation, scrapping, and recycling. The purpose of the retirement process is to ensure the safe retirement of the device and conduct appropriate resource recovery and environmental protection treatment for the device.

[0114] In the embodiments of the present application, when the health status of the device is evaluated as the "immediate retirement required status", the computer device will automatically identify and trigger the retirement process. At this time, the device can no longer meet the basic usage requirements and may affect the safety, stability, and performance of the overall system. Therefore, it must be retired immediately.

[0115] After the device enters the "immediate retirement required status", the computer device will start relevant operations according to the predefined steps of the retirement process, including links such as device deactivation, scrapping application, disassembly, and recycling. These steps should include work such as safely deactivating the device, clearing data, evaluating disassembled and reusable parts, etc.

[0116] Step 403, based on the identification information and the retirement process, record the retirement process information corresponding to the device.

[0117] Among them, the retirement process information refers to the relevant data and operation information recorded during the device retirement process. This information includes the time, reason, processing method, responsible person of the device retirement, and the post-retirement processing situation of the device. The retirement process information helps to track the entire process of device retirement, ensure that the retirement process complies with safety and environmental protection standards, and provides data support for future device management and evaluation.

[0118] In the embodiments of the present application, during the device retirement process, the computer device will record detailed retirement process information according to the identification information of the device and the specific steps of the retirement process. The retirement process information includes but is not limited to the time of retirement, reason for retirement, operation steps, responsible person, etc.

[0119] In the above embodiments, it can ensure the safety and compliance of the device during the retirement process and provide data support for the subsequent management and resource recovery of the device.

[0120] In an exemplary embodiment, the above method further includes:

[0121] After the device is retired, data erasure or destruction processing is performed on the data on the device.

[0122] In the embodiments of the present application, first, a comprehensive assessment and classification of the data in the device are required. For example, identify all data types stored in the device, such as user data, system data, temporary data, log files, configuration information, etc. Evaluate the importance, sensitivity, and confidentiality of the data to determine which data needs to be erased or destroyed and which data can be retained or archived.

[0123] Next, select a suitable data erasure method according to the type of data, the storage medium of the device, and the sensitivity of the data. Common data erasure methods include:

[0124] (1) Software erasure: Use specialized software tools to thoroughly empty the storage area on the device to ensure that the data cannot be recovered. This method is applicable to storage media such as hard disks and solid-state drives.

[0125] (2) Physical destruction: For cases where the data on the storage medium is extremely sensitive, physical destruction methods can be adopted, such as crushing hard disks, destroying tapes, thermal destruction, etc., to fundamentally eliminate the existence of the data.

[0126] (3) Encryption erasure: Encrypt the stored data through encryption technology, and then delete the encryption key so that the data cannot be decrypted, thereby achieving the erasure effect.

[0127] After selecting the appropriate erasure method, perform data erasure or destruction according to the predetermined steps. For software erasure, use an authenticated erasure tool to operate according to the standard erasure process to ensure that all storage areas have been thoroughly cleared. For physical destruction, the device should be sent to a compliant destruction company or facility for professional processing to ensure that the hard disk or other storage media cannot be recovered.

[0128] After the data erasure or destruction processing is completed, verification is required to ensure that all data has been thoroughly erased. Verification methods usually include using data recovery tools to scan and check whether there is any residual data. If any data can be recovered through the recovery tool, the erasure process needs to be performed again until the data is completely irrecoverable.

[0129] In the above embodiments, by erasing or destroying the data on the device, enterprises can effectively prevent data leakage and abuse and ensure that the data processing of retired devices complies with industry standards and legal requirements.

[0130] In an exemplary embodiment, as Figure 5 shown, the above method further includes:

[0131] Step 501: Determine the usage pattern information of the device based on the decommissioning process information of multiple devices.

[0132] In the embodiment of the present application, in the process of determining the usage pattern information of the device based on the decommissioning process information of multiple devices and predicting the decommissioning trend, it is first necessary to collect and organize the decommissioning process information of the device. This decommissioning process information includes the decommissioning time of the device, the type of failure, the frequency of failure occurrence, the maintenance record, the reason for decommissioning (such as the number of failures exceeding the threshold, the service life exceeding the life cycle, the performance degradation, etc.), and the post-decommissioning processing method (such as recycling, destruction, reuse, etc.). By integrating the identification information of the device (such as device ID, model, purchase date, etc.) and the status information (such as running duration, number of failures, historical maintenance records, etc.), a comprehensive decommissioning information database is formed.

[0133] After collecting and organizing the decommissioning information of the device, the next step is to analyze the usage pattern of the device. For example, data mining techniques can be used to identify common failure modes of different types of devices during use, or the failure occurrence pattern of devices in different life cycle stages (initial stage, mature stage, decline stage). Through methods such as clustering analysis and pattern recognition, devices can be classified according to similar usage patterns, and those device types or models that show similar characteristics at the time of decommissioning can be found.

[0134] Step 502: Perform decommissioning trend prediction processing on a class of devices corresponding to the device based on the usage pattern information.

[0135] In the embodiment of the present application, based on the extracted usage pattern information, the next step is to establish a decommissioning trend prediction model. Common models include time series models, which can predict the future decommissioning trend of the device based on the time series analysis of historical decommissioning data; regression analysis can predict the remaining service life and decommissioning time of the device through the usage pattern information of the device (such as service life, number of failures, maintenance frequency, etc.); in addition, machine learning models (such as random forest, support vector machine, decision tree, etc.) can also be trained, taking the decommissioning data and usage pattern information of the device as feature inputs to predict the decommissioning trend of different types of devices.

[0136] After establishing the decommissioning trend prediction model, use these time series models to predict the decommissioning trend of the device. The prediction results include the remaining service life of the device, the possible decommissioning time point of the device, and the high-risk devices that are about to be decommissioned. Through these predictions, enterprises can identify in advance which devices may need maintenance, replacement, or early decommissioning, thereby reducing sudden failures and additional maintenance costs.

[0137] Finally, based on the prediction results, the enterprise can optimize the retirement strategy and allocate resources. By predicting the retirement time and update cycle of the equipment, it is possible to better arrange resources such as equipment updates, spare parts procurement, and personnel scheduling. At the same time, management can use the prediction results of the retirement trend for budget arrangements to avoid the additional economic pressure brought by the sudden retirement of equipment. In addition, according to the prediction results, management can also optimize the equipment maintenance strategy, extend the service life of the equipment or optimize the equipment configuration, and improve the resource utilization efficiency.

[0138] In the above embodiments, by collecting and analyzing the retirement process information of multiple devices, extracting usage rules, and establishing a retirement trend prediction model, it ultimately helps the enterprise formulate a more scientific equipment life cycle management strategy. This can not only improve the operation efficiency and reliability of the equipment, but also reduce the economic losses caused by premature or late retirement of the equipment to a certain extent, and provide data support for the equipment update, maintenance, and resource allocation of the enterprise.

[0139] Some embodiments of the present application provide a method for managing the equipment retirement process, which may include the following steps:

[0140] Step 1, obtain the identification information, status information, and full life cycle information of each device; the status information includes the running time, historical maintenance records, and the number of failures; the full life cycle information includes the initial stage, mature stage, and decline stage.

[0141] Step 2, for the identification information, perform data fusion processing on the running time, historical maintenance records, and the number of failures respectively in the initial stage, mature stage, and decline stage to obtain the fused status information.

[0142] Step 3, determine the weight information corresponding to the multiple fused status information respectively.

[0143] Step 4, perform weight adjustment processing on the multiple weight information based on the adaptive weighting algorithm to obtain the adjusted weight information.

[0144] Step 5, perform weighting processing on the multiple adjusted weight information to determine the health status information of the equipment.

[0145] Step 6, divide the health status information into a healthy state, sub-healthy state, critical retirement state, and immediate retirement state according to the preset status levels.

[0146] Step 7, trigger the retirement process when the status information corresponding to the equipment indicates that the equipment is in the immediate retirement state.

[0147] Step 8, record the retirement process information corresponding to the equipment based on the identification information and the retirement process.

[0148] Step 9, after the device is retired, perform data erasure or destruction on the data on the device.

[0149] Step 10, based on the retirement process information of multiple devices, determine the usage pattern information of the devices.

[0150] Step 11, based on the usage pattern information, perform retirement trend prediction processing on a category of devices corresponding to the devices.

[0151] It should be understood that although the steps in the flowcharts involved in the above embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0152] Based on the same inventive concept, the embodiments of the present application also provide a device retirement process management device for implementing the device retirement process management method involved above. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the device retirement process management device provided below can refer to the limitations on the device retirement process management method in the above text, and will not be repeated here.

[0153] In an exemplary embodiment, as Figure 6 shown, a device retirement process management device is provided, including: an acquisition module 601, a processing module 602, and a determination module 603, where:

[0154] The acquisition module 601 is used to acquire the identification information, status information, and full life cycle information of each device;

[0155] The processing module 602 is used to perform multi-modal data fusion and weighted processing on the status information in sequence based on the full life cycle information for the identification information, and generate the health score data of the device;

[0156] The health status determination module 603 is used to determine the health status information of the device based on the health score data.

[0157] In an exemplary embodiment, the above state information includes the running time, historical maintenance records, and the number of failures; the full life cycle information includes the initial stage, the mature stage, and the decline stage. On this basis, the processing module 602 is specifically configured to perform data fusion processing on the running time, historical maintenance records, and the number of failures respectively in the initial stage, the mature stage, and the decline stage to obtain the fused state information; determine the weight information corresponding to multiple fused state information respectively; perform weighted processing on the multiple weight information to determine the health state information of the device.

[0158] In an exemplary embodiment, the above device further includes:

[0159] An adjustment module 604, configured to perform weight adjustment processing on the multiple weight information based on an adaptive weighting algorithm to obtain the adjusted weight information;

[0160] Correspondingly, performing weighted processing on the multiple weight information to determine the health state information of the device includes:

[0161] Performing weighted processing on the multiple adjusted weight information to determine the health state information of the device.

[0162] In an exemplary embodiment, the above device further includes:

[0163] A division module 605, configured to divide the health state information into a healthy state, a sub-healthy state, a critical retirement state, and an immediate retirement state according to a preset state level;

[0164] A trigger module 606, configured to trigger a retirement process when the state information corresponding to the device indicates that the device is in an immediate retirement state;

[0165] A recording module 607, configured to record the retirement process information corresponding to the device based on the identification information and the retirement process.

[0166] In an exemplary embodiment, the above device further includes:

[0167] An erasure module 608, configured to perform data erasure processing or destruction processing on the data on the device after the device is retired.

[0168] In an exemplary embodiment, the above device further includes:

[0169] A usage pattern determination module 609, configured to determine the usage pattern information of the device based on the retirement process information of multiple devices;

[0170] A prediction module 610, configured to perform retirement trend prediction processing on a type of device corresponding to the device based on the usage pattern information.

[0171] Each module in the above-mentioned device retirement process management device can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0172] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0173] Obtain the identification information, status information, and full life cycle information of each device;

[0174] For the identification information, based on the full life cycle information, perform multi-modal data fusion and weighted processing on the status information in sequence to generate the health score data of the device;

[0175] Based on the health score data, determine the health status information of the device.

[0176] In one embodiment, the status information includes running time, historical maintenance records, and the number of failures; the full life cycle information includes the initial stage, the mature stage, and the decline stage. When the processor executes the computer program, the following steps are also implemented:

[0177] In the initial stage, the mature stage, and the decline stage, perform data fusion processing on the running time, historical maintenance records, and the number of failures respectively to obtain the fused status information;

[0178] Determine the weight information corresponding to multiple fused status information respectively;

[0179] Perform weighted processing on multiple weight information to determine the health status information of the device.

[0180] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0181] Based on the adaptive weighted algorithm, perform weight adjustment processing on multiple weight information to obtain the adjusted weight information;

[0182] Correspondingly, perform weighted processing on multiple weight information to determine the health status information of the device, including:

[0183] Perform weighted processing on multiple adjusted weight information to determine the health status information of the device.

[0184] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0185] Divide the health status information into a healthy state, a sub-healthy state, a critical retirement state, and an immediate retirement state according to the preset status levels;

[0186] When the status information corresponding to the device indicates that the device is in the immediate retirement state, trigger the retirement process;

[0187] Based on the identification information and the retirement process, record the retirement process information corresponding to the device.

[0188] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0189] After the device is retired, perform data erasure processing or destruction processing on the data on the device.

[0190] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0191] Based on the retirement process information of multiple devices, determine the usage pattern information of the devices;

[0192] Based on the usage pattern information, perform retirement trend prediction processing on a category of devices corresponding to the devices.

[0193] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0194] Obtain the identification information, status information, and full life cycle information of each device;

[0195] For the identification information, based on the full life cycle information, perform multi-modal data fusion and weighting processing on the status information in sequence to generate the health score data of the device;

[0196] Based on the health score data, determine the health status information of the device.

[0197] In one embodiment, the status information includes the running time, historical maintenance records, and the number of failures; the full life cycle information includes the initial stage, the mature stage, and the decline stage. When the computer program is executed by a processor, the following steps are further implemented:

[0198] In the initial stage, the mature stage, and the decline stage, perform data fusion processing on the running time, historical maintenance records, and the number of failures respectively to obtain the fused status information;

[0199] Determine the weight information corresponding to the multiple fused status information respectively;

[0200] Perform weighting processing on the multiple weight information to determine the health status information of the device.

[0201] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0202] Based on an adaptive weighting algorithm, perform weight adjustment processing on multiple weight information to obtain the adjusted weight information;

[0203] Correspondingly, perform weighting processing on multiple weight information to determine the health status information of the device, including:

[0204] Perform weighting processing on multiple adjusted weight information to determine the health status information of the device.

[0205] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0206] According to the preset status levels, divide the health status information into healthy status, sub-healthy status, critical retirement status, and immediate retirement required status;

[0207] In the case where the status information corresponding to the device indicates that the device is in the immediate retirement required status, trigger the retirement process;

[0208] Based on the identification information and the retirement process, record the retirement process information corresponding to the device.

[0209] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0210] After the device is retired, perform data erasure processing or destruction processing on the data on the device.

[0211] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0212] Based on the retirement process information of multiple devices, determine the usage pattern information of the devices;

[0213] Based on the usage pattern information, perform retirement trend prediction processing on a type of device corresponding to the device.

[0214] In one embodiment, a computer program product is provided, including a computer program, which when executed by a processor, implements the following steps:

[0215] Obtain the identification information, status information, and full life cycle information of each device;

[0216] For the identification information, based on the full life cycle information, perform multi-modal data fusion and weighting processing on the status information in sequence to generate the health score data of the device;

[0217] Based on the health score data, determine the health status information of the device.

[0218] In one embodiment, the status information includes the running time, historical maintenance records, and the number of failures; the full - life - cycle information includes the initial stage, the mature stage, and the decline stage. When the processor executes the computer program, the following steps are also implemented:

[0219] In the initial stage, the mature stage, and the decline stage, data fusion processing is respectively performed on the running time, historical maintenance records, and the number of failures to obtain the fused status information;

[0220] The weight information corresponding to multiple fused status information is respectively determined;

[0221] Weighted processing is performed on multiple weight information to determine the health status information of the device.

[0222] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0223] Based on the adaptive weighting algorithm, weight adjustment processing is performed on multiple weight information to obtain the adjusted weight information;

[0224] Correspondingly, weighted processing is performed on multiple weight information to determine the health status information of the device, including:

[0225] Weighted processing is performed on multiple adjusted weight information to determine the health status information of the device.

[0226] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0227] According to the preset status level, the health status information is divided into healthy status, sub - healthy status, critical retirement status, and immediate retirement status;

[0228] When the status information corresponding to the device indicates that the device is in the immediate retirement status, the retirement process is triggered;

[0229] Based on the identification information and the retirement process, the retirement process information corresponding to the device is recorded.

[0230] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0231] After the device is retired, data erasure processing or destruction processing is performed on the data on the device.

[0232] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0233] Based on the retirement process information of multiple devices, the usage pattern information of the devices is determined;

[0234] Based on the usage pattern information, retirement trend prediction processing is performed on a class of devices corresponding to the device.

[0235] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0236] Obtain the identification information, status information, and full life cycle information of each device;

[0237] For the identification information, based on the full life cycle information, perform multi-modal data fusion and weighted processing on the status information in sequence to generate the health score data of the device;

[0238] Based on the health score data, determine the health status information of the device.

[0239] In one embodiment, the status information includes the running time, historical maintenance records, and the number of failures; the full life cycle information includes the initial stage, the mature stage, and the decline stage. When the computer program is executed by a processor, the following steps are also implemented:

[0240] In the initial stage, the mature stage, and the decline stage, perform data fusion processing on the running time, historical maintenance records, and the number of failures respectively to obtain the fused status information;

[0241] Determine the weight information corresponding to the multiple fused status information respectively;

[0242] Perform weighted processing on the multiple weight information to determine the health status information of the device.

[0243] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0244] Based on the adaptive weighted algorithm, perform weight adjustment processing on the multiple weight information to obtain the adjusted weight information;

[0245] Correspondingly, perform weighted processing on the multiple weight information to determine the health status information of the device, including:

[0246] Perform weighted processing on the multiple adjusted weight information to determine the health status information of the device.

[0247] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0248] According to the preset status levels, divide the health status information into healthy status, sub-healthy status, critical retirement status, and immediate retirement status;

[0249] In the case that the status information corresponding to the device indicates that the device is in the immediate retirement status, trigger the retirement process;

[0250] Based on the identification information and the retirement process, record the retirement process information corresponding to the device.

[0251] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0252] After the device is retired, data erasure processing or destruction processing is performed on the data on the device.

[0253] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0254] Based on the retirement process information of multiple devices, determine the usage pattern information of the devices;

[0255] Based on the usage pattern information, perform retirement trend prediction processing on a type of device corresponding to the device.

[0256] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., and are not limited thereto. The processors involved in the embodiments provided in this application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., and are not limited thereto.

[0257] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope recorded in this application.

[0258] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for managing equipment retirement process, characterized in that: The method comprises: Obtain identification information, status information, and full life cycle information for each device; For the identification information, based on the full life cycle information, the state information is sequentially subjected to multimodal data fusion and weighted processing to generate health score data of the device; Based on the health score data, health status information of the device is determined.

2. The method according to claim 1, characterized in that: The state information includes operating time, historical maintenance records and number of failures; the full life cycle information includes initial stage, mature stage and decay stage. Based on the full life cycle information, multi-modal data fusion and weighted processing are sequentially performed on the state information, including: In the initial stage, the mature stage and the decline stage, data fusion processing is performed on the operating time, the historical maintenance record and the number of failures to obtain fused status information; Respectively determining weight information corresponding to the plurality of fused state information; A plurality of the weight information are weighted to determine the health status information of the device.

3. The method according to claim 2, characterized in that The method further comprises: Performing weight adjustment processing on the plurality of weight information based on an adaptive weighting algorithm to obtain adjusted weight information; Correspondingly, performing weighted processing on the plurality of weight information to determine the health status information of the device includes: The plurality of adjusted weight information are weighted to determine the health status information of the device.

4. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: Classifying the health status information into healthy status, sub-health status, critical retirement status and immediate retirement status according to preset status levels; When the status information corresponding to the device indicates that the device is in a state that needs to be retired immediately, triggering a retirement process; Based on the identification information and the decommissioning process, decommissioning process information corresponding to the device is recorded.

5. The method according to claim 4, characterized in that The method further comprises: After the device is retired, data on the device is erased or destroyed.

6. The method according to claim 4, characterized in that The method further comprises: Determining usage regularity information of the devices based on the retirement process information of the plurality of devices; Based on the usage rule information, retirement trend prediction processing is performed on a class of equipment corresponding to the equipment.

7. An equipment decommissioning process management device, characterized in that: The device comprises: The acquisition module is used to obtain the identification information, status information and full life cycle information of each device; A processing module, configured to perform multimodal data fusion and weighted processing on the status information in sequence based on the identification information and the full life cycle information, so as to generate health score data of the device; A determination module is used to determine the health status information of the device based on the health score data.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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