Equipment full-life-cycle management method and system based on cloud service platform

Abstract

The invention relates to the technical field of equipment full-life-cycle management, and discloses an equipment full-life-cycle management method and system based on a cloud service platform, and the method comprises the steps: building a full-life-cycle management database of equipment on the cloud service platform, and carrying out the centralized storage and management of the data of each stage of the equipment; monitoring the health state of the equipment in real time, and regularly uploading monitoring data to the cloud platform; a data analysis tool in the cloud platform is utilized to intelligently analyze the equipment data, identify potential faults and provide predictive maintenance suggestions; collecting user feedback and operation data, evaluating equipment performance, and dynamically adjusting a management strategy according to feedback; and generating an equipment life cycle report, evaluating the environmental influence of the equipment, and formulating a corresponding optimization scheme. According to the method, a centralized management life cycle database is established, efficient integration and management of data of equipment in different stages are achieved, the problem of data islands can be effectively solved, and transparency and real-time performance of information circulation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment life cycle management, and in particular to a method and system for equipment life cycle management based on a cloud service platform. Background Art

[0002] In the context of the rapid development of today's industrial Internet and intelligent manufacturing, equipment lifecycle management (LCM) technology has gradually become an important tool for improving enterprise operational efficiency and optimizing resource allocation. With the continuous maturity of cloud computing, big data analysis and Internet of Things (IoT) technology, enterprises can use these advanced technologies to drive the integrated management of equipment data and realize digital management of all stages from equipment design, manufacturing, use to maintenance and scrapping. In particular, in terms of equipment health monitoring, predictive maintenance and user feedback collection, existing technologies can provide certain support in a data-driven way, giving enterprises higher operational efficiency and more accurate decision-making basis.

[0003] However, although the existing technology has achieved certain results in the management of the entire life cycle of equipment, there are still significant shortcomings. First, the existing system often lacks effective data integration capabilities and cannot centrally manage and analyze information from different stages, resulting in serious data islands and the inability to evaluate equipment performance and potential failures from a global perspective. This not only affects decision-making efficiency, but also makes it impossible to accurately maintain and manage equipment. Secondly, the application of real-time health monitoring technology is still restricted by factors such as sensor selection, data collection frequency, and outlier detection, which easily leads to insufficient data accuracy and reliability. In addition, the current user feedback collection methods are mostly offline or non-real-time means, resulting in feedback lags, unable to quickly respond to user needs and equipment operating conditions, and thus reducing the overall performance and user satisfaction of the equipment. In summary, these problems make equipment management face challenges in an increasingly complex industrial environment, seriously restricting the sustainable development of enterprises. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a device full life cycle management method based on a cloud service platform, which can solve the problem of data islands from the source by adopting a microservice architecture to design a database and implement modular management.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a method for equipment life cycle management based on a cloud service platform, comprising: establishing a equipment life cycle management database on the cloud service platform to centrally store and manage data at each stage of the equipment; real-time monitoring of the health status of the equipment, and regular uploading of the monitoring data to the cloud platform; using the data analysis tools in the cloud platform to intelligently analyze the equipment data, identify potential faults, and provide predictive maintenance recommendations; collecting user feedback and operation data, evaluating equipment performance, and dynamically adjusting management strategies based on feedback; generating equipment life cycle reports, evaluating the environmental impact of the equipment, and formulating corresponding optimization plans to support subsequent management of the equipment.

[0007] As a preferred solution of the device life cycle management method based on a cloud service platform described in the present invention, wherein: the establishment of a device life cycle management database includes: using a microservice architecture to design the database, dividing it into independent small modules, each module has an independent API interface for data sharing and interaction, collecting device status data in real time through IoT devices and sensors, and pushing the data to the cloud platform through a customized MQTT protocol;

[0008] For information in the design and manufacturing phase, a user-friendly interface is provided to allow designers and engineers to manually upload documents and data in a standardized JSON or XML format;

[0009] Equipment specific data includes: design phase data, manufacturing phase data, usage phase data, maintenance phase data, and scrapping phase data.

[0010] As a preferred solution of the equipment life cycle management method based on the cloud service platform described in the present invention, the centralized storage and management includes using the cloud storage service to slice the data, storing different types of data in different storage buckets, storing design data in the "design-bucket", manufacturing data in the "manufacturing-bucket", and usage and maintenance data in the "usage-maintenance-bucket";

[0011] Set up an automated scheduled backup mechanism to enable quick recovery in the event of a failure or accidental data deletion, and establish an API interface to allow users to retrieve data according to different conditions.

[0012] As a preferred solution of the device life cycle management method based on a cloud service platform described in the present invention, the real-time monitoring of the health status of the device includes: the sensor regularly collects data and stores the data in a local cache until the next upload;

[0013] By establishing a filtering system to exclude outliers, the standard deviation σ is used for filtering:

[0014] D f =D\{x|x>μ+kσ or x<μ-kσ}

[0015] Among them, D f is the filtered data set, D is the original data set, x is the data in the data set, μ is the data mean, and k is the selected threshold;

[0016] Use the improved Z-Score method combined with weighted IQ to evaluate equipment health status in real time:

[0017]

[0018] Among them, H is the health status score, X is the currently monitored device status value, μ x is the expected mean value of the device, σ x is the standard deviation of the device status value, W is the weight factor;

[0019] In each fixed time period or when the monitored status changes exceed the threshold, the upload mechanism is triggered to package each monitored sensor data and health status into JSON format, and the uploaded data is encrypted using HTTPS or MQTT protocol.

[0020] As a preferred solution of the device life cycle management method based on a cloud service platform described in the present invention, the identifying of potential faults includes classifying risks using fuzzy logic and setting fuzzy values ​​according to user feedback and device operation data.

[0021]

[0022] Among them, P risk is the potential failure risk score, N is the number of features, α k is the kth monitoring indicator data, D k is the fuzzy weight of the feature; P risk >0.7, the risk level is high. If a potential fault is identified, the equipment detection and confirmation will be completed within a fixed time. Physical inspection will be carried out within 3 hours after the fault is identified. If confirmed, maintenance will be carried out. If no feedback is given within the specified time, the system will automatically adjust the confidence level.

[0023] As a preferred solution of the device life cycle management method based on a cloud service platform described in the present invention, the dynamic adjustment management strategy includes providing a feedback entry in the device interface, and the user fills in a feedback form after using the device, and the feedback form covers the user's overall satisfaction, the reliability of the device, and the convenience of maintenance;

[0024] The collected rating data will be immediately entered into the backend database and saved as structured data through the API interface. User feedback is stored in the feedback_data table, which records user ID, rating and other related information. The average of user feedback quality ratings is calculated regularly, and regular reports are generated through SQL queries. The specific calculation formula is:

[0025]

[0026] Among them, U q is the user feedback quality score, r i is the score of the i-th user; the score is displayed on the user feedback dashboard. The device status is monitored in real time through IoT sensors, the operating time and production efficiency are automatically recorded, and the data is sent to the back-end database in real time. The monitoring dashboard is configured to display the performance score and user feedback in real time, and an automatic alarm mechanism is set. When the comprehensive score or user feedback drops significantly, the relevant personnel are notified immediately. The user feedback and equipment performance analysis are integrated into the evaluation system to realize the "feedback-evaluation-adjustment" cycle. The management process and strategy are updated in combination with the latest data and user feedback.

[0027] As a preferred solution of the device life cycle management method based on a cloud service platform described in the present invention, wherein: the environmental impact assessment of the device includes automatically collecting relevant data at different life cycle stages of the device;

[0028] In the design stage, the information of CAD files generated by the design software is stored; in the manufacturing stage, the energy consumption and material waste data in the production process are recorded; in the use stage, the operation time, maintenance records, and failure frequency of the equipment are monitored in real time; in the scrapping stage, the waste disposal method and related environmental impact information are recorded;

[0029] Quantitatively and qualitatively summarize the data collected at each stage, use ETL tools to organize the data, establish a dynamic evaluation model, and establish a causal relationship network for each stage;

[0030] Define multiple dimensions of environmental impact assessment, calculate overall carbon emissions based on energy consumption and service life, calculate the amount of water resources used during equipment manufacturing and use, and measure the amount of solid waste and recyclable components generated during the use and scrapping stages.

[0031] As a preferred solution of the equipment life cycle management system based on the cloud service platform described in the present invention, it includes: a data acquisition and processing module, a health monitoring and fault identification module, a feedback management and evaluation module, an environmental impact assessment module, and a report generation and optimization module;

[0032] The data acquisition and processing module is responsible for collecting relevant data at each stage during the entire life cycle of the equipment, including information on the design, manufacturing, use, maintenance, and scrapping stages, and realizing intelligent data preprocessing;

[0033] The health monitoring and fault identification module monitors the health status of the equipment in real time, builds an equipment health scoring model through real-time data collected by sensors, supports dynamic setting of thresholds, and adapts to changes in different equipment models and operating conditions, thereby improving the accuracy and reliability of fault detection;

[0034] The feedback management and evaluation module automatically enters the feedback data into the database in real time, generates dynamic user feedback quality scores, and performs trend analysis;

[0035] The environmental impact assessment module identifies the impact of equipment on the environment throughout its life cycle, provides corresponding environmental optimization suggestions, and promotes the realization of the company's sustainable development goals;

[0036] The report generation and optimization module generates a comprehensive equipment life cycle report, covering information on equipment usage, health status, user feedback, and environmental impact. A computer device includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, it implements the steps of a device full life cycle management method based on a cloud service platform.

[0037] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the computer program implements the steps of a device full life cycle management method based on a cloud service platform.

[0038] The beneficial effects of the present invention are as follows: by establishing a full life cycle management database for equipment, centralized storage and intelligent processing of data at each stage are achieved, and real-time monitoring of health status and predictive maintenance suggestions for fault identification are provided. With the help of dynamically adjusted management strategies, the present invention can quickly adapt to changes in user feedback and equipment operating conditions, and improve the accuracy of fault identification. By comprehensively evaluating environmental impacts, the practice of sustainable development of enterprises is promoted. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0040] Figure 1A schematic flow chart of a method for managing the entire life cycle of equipment based on a cloud service platform is provided as an embodiment of the present invention.

[0041] Figure 2 A schematic diagram of working modules of a device life cycle management system based on a cloud service platform provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0043] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0044] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0045] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0046] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0047] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0048] Example 1, reference Figure 1 , which is the first embodiment of the present invention, and provides a device full life cycle management method based on a cloud service platform, comprising:

[0049] S1: Establish a full life cycle management database for the equipment on the cloud service platform, centrally store and manage the data of each stage of the equipment, monitor the health status of the equipment in real time, and upload the monitoring data to the cloud platform regularly.

[0050] Furthermore, the database is designed using a microservice architecture, which is divided into independent small modules. Each module has an independent API interface for data sharing and interaction. The device status data is collected in real time through IoT devices and sensors, and the data is pushed to the cloud platform through the customized MQTT protocol;

[0051] For information in the design and manufacturing phase, a user-friendly interface is provided to allow designers and engineers to manually upload documents and data in a standardized JSON or XML format;

[0052] Device specific data includes,

[0053] Design phase data: design drawings, specifications, design change records, test data.

[0054] Manufacturing stage data: raw material list, manufacturing process, equipment production records, quality inspection report.

[0055] Usage stage data: usage time, usage frequency, operation records, device status (such as temperature, vibration, etc.).

[0056] Maintenance phase data: maintenance records, fault reports, fault repair time, and maintenance cycles.

[0057] Scrap stage data: scrap reason, scrap time, residual value assessment, environmental impact report.

[0058] Furthermore, the cloud storage service is used to shard the data. Different types of data are stored in different buckets. Design data is stored in the "design-bucket", production data is stored in the "manufacturing-bucket", and usage and maintenance data is stored in the "usage-maintenance-bucket".

[0059] Set up an automated scheduled backup mechanism to enable quick recovery in the event of a failure or accidental data deletion, and establish an API interface to allow users to retrieve data according to different conditions.

[0060] Furthermore, the sensor collects data at regular intervals and stores the data in a local cache until the next upload;

[0061] By establishing a filtering system to exclude outliers, the standard deviation σ is used for filtering:

[0062] D f =D\{x|x>μ+kσ or x<μ-kσ}

[0063] Among them, D f is the filtered data set, D is the original data set, x is the data in the data set, μ is the data mean, and k is the selected threshold;

[0064] Use the improved Z-Score method combined with weighted IQ to evaluate equipment health status in real time:

[0065]

[0066] Among them, H is the health status score, X is the currently monitored device status value, μ x is the expected mean value of the device, σ x is the standard deviation of the device status value, W is the weight factor;

[0067] In each fixed time period or when the monitored status changes exceed the threshold, the upload mechanism is triggered to package each monitored sensor data and health status into JSON format, and the uploaded data is encrypted using HTTPS or MQTT protocol.

[0068] Real-time analysis of real-time data fluctuation patterns forms a threshold model based on historical data learning. The health status score is combined with the feedback from each sensor to construct a macro-dimensional health index:

[0069]

[0070] Among them, HI is the health index, M is the health score of each sensor, and H i is the number of sensors.

[0071] S2: Use data analysis tools in the cloud platform to intelligently analyze equipment data, identify potential failures, and provide predictive maintenance recommendations.

[0072] Furthermore, based on user feedback and equipment operation data, fuzzy logic is used to classify risks and set fuzzy values.

[0073]

[0074] Among them, P risk is the potential failure risk score, N is the number of features, α k is the kth monitoring indicator data, D k is the fuzzy weight of the feature; P risk >0.7, the risk level is high. If a potential fault is identified, the equipment detection and confirmation will be completed within a fixed time. Physical inspection will be carried out within 3 hours after the fault is identified. If confirmed, maintenance will be carried out. If no feedback is given within the specified time, the system will automatically adjust the confidence level.

[0075] S3: Collect user feedback and operation data, evaluate device performance, and dynamically adjust management strategies based on feedback.

[0076] Furthermore, a feedback portal is provided in the device interface, and users fill out a feedback form after using the device. The feedback form covers the user's overall satisfaction, device reliability, and ease of maintenance;

[0077] The collected rating data will be immediately entered into the backend database and saved as structured data through the API interface. User feedback is stored in the feedback_data table, which records user ID, rating and other related information. The average of user feedback quality ratings is calculated regularly, and regular reports are generated through SQL queries. The specific calculation formula is:

[0078]

[0079] Among them, U q is the user feedback quality score, r i is the rating of the i-th user; if U q <3 / 5 (on a 5-point feedback rating scale), then lower the fault recognition threshold to increase sensitivity; if D q <0.6(D q For operation data scoring), the fault monitoring frequency is increased.

[0080] Combine user feedback quality with device operation data to form a comprehensive performance score:

[0081] PE=w 1 ·U q +w 2 ·D q

[0082] Among them, PE is the comprehensive performance score, w 1 、w 2 are the weights of user feedback and operation data respectively.

[0083] The score is displayed on the user feedback dashboard. The IoT sensor monitors the device status in real time, automatically records the operating time and production efficiency, and sends the data to the back-end database in real time. The monitoring dashboard is configured to display the performance score and user feedback in real time. An automatic alarm mechanism is set up. When the comprehensive score or user feedback drops significantly, the relevant personnel are notified immediately. User feedback and device performance analysis are integrated into the evaluation system to realize the "feedback-evaluation-adjustment" cycle. The management process and strategies are updated in combination with the latest data and user feedback.

[0084] S4: Generate equipment life cycle reports, evaluate the environmental impact of equipment, and develop corresponding optimization plans to support subsequent management of equipment.

[0085] Going a step further, relevant data can be automatically collected at different stages of the equipment’s life cycle;

[0086] In the design stage, the information of CAD files generated by the design software is stored; in the manufacturing stage, the energy consumption and material waste data in the production process are recorded; in the use stage, the operation time, maintenance records, and failure frequency of the equipment are monitored in real time; in the scrapping stage, the waste disposal method and related environmental impact information are recorded;

[0087] Quantitatively and qualitatively summarize the data collected at each stage, use ETL tools to organize the data, establish a dynamic evaluation model, and establish a causal relationship network for each stage;

[0088] Define the multiple dimensions of environmental impact assessment:

[0089] The service life and energy consumption data of the equipment are introduced into the model, and the overall carbon emissions generated by the equipment during the manufacturing and operation process are calculated using the formula:

[0090] Total carbon emissions = (carbon emissions during production + carbon emissions during use) × service life

[0091] For the manufacturing and use stages, the water consumption per unit time is counted to evaluate the overall water use efficiency and environmental impact.

[0092] During the use and disposal phases, record the amount of solid waste generated and the proportion of each type of recyclable components. Use the following formula to evaluate the efficiency of solid waste treatment:

[0093]

[0094] Embodiment 2, the second embodiment of the present invention, is different from the previous embodiment in that:

[0095] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0096] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0097] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0098] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0099] Example 3, reference Figure 2 , is an embodiment of the present invention, and provides a device life cycle management system based on a cloud service platform, characterized in that it includes a data acquisition and processing module 1, a health monitoring and fault identification module 2, a feedback management and evaluation module 3, an environmental impact assessment module 4, and a report generation and optimization module 5;

[0100] The data acquisition and processing module 1 is responsible for collecting relevant data at each stage during the entire life cycle of the equipment, including information on the design, manufacturing, use, maintenance, and scrapping stages, and realizing intelligent data preprocessing;

[0101] The health monitoring and fault identification module 2 monitors the health status of the equipment in real time, builds an equipment health scoring model through real-time data collected by sensors, supports dynamic setting of thresholds, and adapts to changes in different equipment models and operating conditions, thereby improving the accuracy and reliability of fault detection;

[0102] The feedback management and evaluation module 3 automatically enters the feedback data into the database in real time, generates dynamic user feedback quality scores, and performs trend analysis;

[0103] The environmental impact assessment module 4 identifies the impact of equipment on the environment throughout its life cycle, provides corresponding environmental optimization suggestions, and promotes the realization of the company's sustainable development goals;

[0104] The report generation and optimization module 5 generates a comprehensive equipment life cycle report, covering information on equipment usage, health status, user feedback, and environmental impact.

[0105] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A device full life cycle management method based on a cloud service platform, characterized in that: include, Establish a full life cycle management database for equipment on the cloud service platform to centrally store and manage data at each stage of the equipment; Monitor the health status of the equipment in real time and upload the monitoring data to the cloud platform regularly; Use data analysis tools in the cloud platform to intelligently analyze equipment data, identify potential failures, and provide predictive maintenance recommendations; Collect user feedback and operation data, evaluate device performance, and dynamically adjust management strategies based on feedback; Generate equipment life cycle reports, evaluate the environmental impact of equipment, and develop corresponding optimization plans to support subsequent management of equipment.

2. A method for managing the entire life cycle of equipment based on a cloud service platform as claimed in claim 1, characterized in that: The establishment of a full life cycle management database for equipment includes: designing the database using a microservice architecture, dividing it into independent small modules, each module having an independent API interface for data sharing and interaction, collecting equipment status data in real time through IoT devices and sensors, and pushing the data to the cloud platform through a customized MQTT protocol; For information in the design and manufacturing phase, a user-friendly interface is provided to allow designers and engineers to manually upload documents and data in a standardized JSON or XML format; Equipment specific data includes: design phase data, manufacturing phase data, usage phase data, maintenance phase data, and scrapping phase data.

3. A method for managing the entire life cycle of equipment based on a cloud service platform as claimed in claim 2, characterized in that: The centralized storage and management includes using cloud storage services to shard the data, storing different types of data in different storage buckets, with design data stored in "design-bucket", production data stored in "manufacturing-bucket", and usage and maintenance data stored in "usage-maintenance-bucket"; Set up an automated scheduled backup mechanism to enable quick recovery in the event of a failure or accidental data deletion, and establish an API interface to allow users to retrieve data according to different conditions.

4. A method for managing the entire life cycle of equipment based on a cloud service platform as claimed in claim 3, characterized in that: The real-time monitoring of the health status of the device includes the sensor collecting data at regular intervals and storing the data in a local cache until the next upload; By establishing a filtering system to exclude outliers, the standard deviation σ is used for filtering: D f =D\{x|x>μ+kσ or x<μ-kσ} Among them, D f is the filtered data set, D is the original data set, x is the data in the data set, μ is the data mean, and k is the selected threshold; Use the improved Z-Score method combined with weighted IQ to evaluate the health status of equipment in real time: Among them, H is the health status score, X is the currently monitored device status value, μ x is the expected mean value of the device, σ x is the standard deviation of the device status value, W is the weight factor; In each fixed time period or when the monitored status changes exceed the threshold, the upload mechanism is triggered to package each monitored sensor data and health status into JSON format, and the uploaded data is encrypted using HTTPS or MQTT protocol.

5. A method for managing the entire life cycle of equipment based on a cloud service platform as claimed in claim 4, characterized in that: The identification of potential failures includes classifying risks using fuzzy logic and setting fuzzy values ​​based on user feedback and equipment operation data. Among them, P risk is the potential failure risk score, N is the number of features, α k is the kth monitoring indicator data, D k is the fuzzy weight of the feature; P risk >0.7, the risk level is high. If a potential fault is identified, the equipment detection and confirmation will be completed within a fixed time. Physical inspection will be carried out within 3 hours after the fault is identified. If confirmed, maintenance will be carried out. If no feedback is given within the specified time, the system will automatically adjust the confidence level.

6. A method for managing the entire life cycle of equipment based on a cloud service platform as claimed in claim 5, characterized in that: The dynamic adjustment management strategy includes providing a feedback portal in the device interface, and the user fills in a feedback form after using the device. The feedback form covers the user's overall satisfaction, device reliability, and maintenance convenience; The collected rating data will be immediately entered into the backend database and saved as structured data through the API interface. User feedback is stored in the feedback_data table, which records user ID, rating and other related information. The average of user feedback quality ratings is calculated regularly, and regular reports are generated through SQL queries. The specific calculation formula is: Among them, U q is the user feedback quality score, r i is the score of the i-th user; the score is displayed on the user feedback dashboard. The device status is monitored in real time through IoT sensors, the operating time and production efficiency are automatically recorded, and the data is sent to the back-end database in real time. The monitoring dashboard is configured to display the performance score and user feedback in real time, and an automatic alarm mechanism is set. When the comprehensive score or user feedback drops significantly, the relevant personnel are notified immediately. The user feedback and equipment performance analysis are integrated into the evaluation system to realize the "feedback-evaluation-adjustment" cycle process. The management process and strategy are updated in combination with the latest data and user feedback.

7. A method for managing the entire life cycle of equipment based on a cloud service platform as claimed in claim 6, characterized in that: The environmental impact assessment of the equipment includes automatically collecting relevant data at different life cycle stages of the equipment; During the design phase, information about CAD files generated by the design software is stored; During the manufacturing stage, record the energy consumption and material waste data during the production process; During the use phase, real-time monitoring of the equipment’s operating hours, maintenance records, and failure frequency is performed; during the scrapping phase, the waste disposal method and related environmental impact information are recorded; Quantitatively and qualitatively summarize the data collected at each stage, use ETL tools to organize the data, establish a dynamic evaluation model, and establish a causal relationship network for each stage; Define multiple dimensions of environmental impact assessment, calculate overall carbon emissions based on energy consumption and service life, calculate the amount of water resources used during equipment manufacturing and use, and measure the amount of solid waste and recyclable components generated during the use and scrapping stages.

8. A system using a device life cycle management method based on a cloud service platform as claimed in any one of claims 1 to 7, characterized in that: It includes data acquisition and processing module, health monitoring and fault identification module, feedback management and evaluation module, environmental impact assessment module, report generation and optimization module; The data acquisition and processing module is responsible for collecting relevant data at each stage during the entire life cycle of the equipment, including information on the design, manufacturing, use, maintenance, and scrapping stages, and realizing intelligent data preprocessing; The health monitoring and fault identification module monitors the health status of the equipment in real time, builds an equipment health scoring model through real-time data collected by sensors, supports dynamic setting of thresholds, and adapts to changes in different equipment models and operating conditions, thereby improving the accuracy and reliability of fault detection; The feedback management and evaluation module automatically enters the feedback data into the database in real time, generates dynamic user feedback quality scores, and performs trend analysis; The environmental impact assessment module identifies the impact of equipment on the environment throughout its life cycle, provides corresponding environmental optimization suggestions, and promotes the realization of the company's sustainable development goals; The report generation and optimization module generates a comprehensive equipment life cycle report, covering information on equipment usage, health status, user feedback, and environmental impact.

9. 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 7 are implemented.

10. 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 7 are implemented.

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