Health evaluation method, system, equipment and medium for assembly line equipment

Abstract

The present invention belongs to the field of equipment management technology, and discloses a health evaluation method, system, equipment and medium for assembly line special machine equipment to solve the limitations of the existing technology in the health status evaluation of assembly line special machine equipment. The method of the present invention includes obtaining the evaluation index of the equipment and the comprehensive weight value corresponding to each index, and performing calculations based on this to obtain a first health score; obtaining the historical fault data and historical operating time data of the equipment, and based on this, calculating the time interval between the fault occurrence time and the maintenance occurrence time of each fault and constructing a time decay model to calculate the weighted risk score of each fault, thereby calculating a second health score; obtaining the production scheduling data of the equipment and combining it with the health data to calculate to obtain the current production scheduling risk score, thereby completing the health evaluation of the assembly line special machine equipment. The present invention significantly improves the comprehensiveness, accuracy, dynamics and real-time performance of the health evaluation of assembly line special machine equipment.

Description

Technical Field

[0001] The present invention belongs to the technical field of equipment management, and in particular relates to a health evaluation method, system, equipment and medium for assembly line equipment. Background Art

[0002] In modern industrial production, the health of specialized assembly line equipment (such as those used for electricity meter calibration) is directly related to production efficiency and product quality. Because these devices operate under constant high load, real-time monitoring and assessment of their health status is crucial. Accurately assessing the health of these devices not only provides early warning of potential failures and avoids unplanned downtime, but also optimizes maintenance strategies, extends equipment life, and reduces production costs. Therefore, scientifically and comprehensively assessing the health of specialized assembly line equipment has become a key scientific challenge in this field. To address this issue, several equipment health management systems have been proposed. For example, Chinese patent CN201910079283.6 proposes an equipment health management system that assesses equipment health status through a data acquisition module, a database module, an environmental parameter module, a data processing module, a comparison module, a health factor module, an algorithm module, and a health analysis module. Specifically, this system collects equipment operating parameters (such as operating time, load, energy consumption, temperature, and vibration) and, combining these with health factors and algorithms, calculates the equipment's health. The health analysis module then outputs the device's health status. However, existing technologies primarily rely on health factors and algorithms to calculate the health status of equipment. While these can partially reflect the operating status of the equipment, they fail to fully consider the multi-dimensional factors of the equipment. Furthermore, existing health assessment models are mostly static models that cannot reflect the health status and failure risks of the equipment under real-time tasks. In summary, existing technologies still have many limitations in assessing the health status of assembly line equipment, especially in terms of the comprehensiveness of the assessment, dynamic assessment capabilities, prediction accuracy, and intelligence level, which need to be improved. Summary of the Invention

[0003] Based on the above-mentioned shortcomings and deficiencies in the prior art, one of the purposes of the present invention is to at least solve one or more of the above-mentioned problems in the prior art. In other words, one of the purposes of the present invention is to provide a health evaluation method, system, equipment and medium for assembly line special equipment that meets one or more of the above-mentioned needs, so as to achieve the purpose of improving the comprehensiveness of the health evaluation and further improving the accuracy of the assessment.

[0004] In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical solutions:

[0005] In the first aspect, the present invention provides a method for evaluating the health of a dedicated assembly line equipment, comprising the steps of: S1, obtaining the evaluation index of the equipment and the comprehensive weight value corresponding to each index, and calculating based on the obtained index to obtain a first health score. S2. Obtain the historical fault data and historical operating time data of the equipment, and calculate the time interval between the fault occurrence time and the maintenance occurrence time of each fault based on this data. And build a time decay model to calculate the weighted risk score of each failure, thereby calculating the second health score ; S3, based on the first health score and the second health score Calculate the comprehensive health score =a -b , a and b are empirical coefficients, and the equipment historical failure interval is calculated based on the historical failure data , thereby obtaining the health data of the equipment; S4, obtaining the production scheduling data of the equipment and combining the health data to calculate to obtain the current production scheduling risk score , thereby completing the health evaluation of the assembly line equipment.

[0006] As a preferred solution, the evaluation indicators include operation indicators, economic indicators and maintenance indicators;

[0007] The comprehensive weight value includes a subjective weight value and objective weights ; The calculation formula of the comprehensive weight value is , Indicates the evaluation index number, Indicates the total number of evaluation indicators; the first health score The calculation formula is , Indicates the The comprehensive weight of the evaluation indicators, Indicates the The first device The standardized value of the evaluation indicator.

[0008] As a preferred solution, the time interval The calculation formula is , Indicates the time when the equipment failure occurs. Indicates the time when equipment maintenance occurs; calculates the time interval Then also includes the time interval Normalize to the working time of the entire device to make the data of different devices or different time periods comparable. The normalization formula is: , Indicates the current moment of evaluation, Indicates the starting time when the device starts working.

[0009] As a preferred solution, the expression of the time decay model is: , Indicates the time at which the device The risk score, Indicates the risk score of the device at the initial moment, represents the time decay factor, Indicates time starting from a reference point.

[0010] As a preferred solution, the weighted risk score of each failure includes the steps of: The numerical value of each fault is assigned a weight , and the larger Corresponding to lower weights, smaller corresponds to a higher weight; the expression of the weight is , is a positive number;

[0011] The weight of each fault is adjusted based on the time decay coefficient to obtain a time-adjusted risk score The second health score The calculation formula is , Indicates the total number of faults.

[0012] As a preferred solution, the production scheduling data includes the total number of orders that need to be processed within a future preset window. , the total number of equipment involved in production k, the order quantity assigned to each equipment m, and the equipment's production capacity and standard production time The production scheduling data of the equipment is obtained and combined with the health data to calculate the current production scheduling risk score The steps include: calculating the equipment efficiency coefficient of each equipment in the production scheduling data To evaluate the efficiency of equipment in production scheduling; allocate orders proportionally based on the equipment efficiency coefficient corresponding to each equipment to obtain the order quantity allocated to each equipment , is the total number of orders, k is the total number of equipment involved in production; calculate the expected failure time during equipment production after allocating orders proportionally The risk index is calculated , For production time, is the standard production time; based on the comprehensive health score and the risk indicators Calculate the current scheduling risk score .

[0013] As a preferred solution, the equipment efficiency coefficient corresponding to each device is The calculation formula is , Indicates the overall health score of the device. represents the single-task production time, Indicates the maintenance time; the expected failure time corresponding to each device The calculation formula is , Indicates the order quantity assigned to the device, is the production capacity of the equipment, The mean time between failures of the equipment; the current production scheduling risk score The calculation formula is , is the comprehensive health score, R is the risk index, is the maximum risk threshold.

[0014] In a second aspect, the present invention provides a health evaluation system for assembly line equipment, which is used to implement the health evaluation method described in the first aspect.

[0015] In a third aspect, the present invention provides an electronic device, wherein the computer device includes a memory, a processor, and a computer program, and when the computer program is executed by the processor, the health assessment method as described in the first aspect is implemented.

[0016] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the health assessment method as described in the first aspect.

[0017] Compared with the prior art, the present invention has the following beneficial effects:

[0018] 1. This invention constructs a time decay model by acquiring device evaluation indicators and the corresponding comprehensive weights for each indicator, combining historical failure data and historical operating time data. This model comprehensively considers multiple factors, including device operational stability, failure frequency, and historical failure data. Compared to existing assessment methods that rely solely on health factors and algorithms, this invention provides a more comprehensive reflection of device health.

[0019] 2. This invention builds a time-decay model to calculate a weighted risk score for each failure. Combined with the equipment's production schedule data, it dynamically assesses the equipment's health and failure risk under the current production schedule. Compared to existing static assessment models, this invention can reflect changes in equipment health in real time, significantly improving its dynamic assessment capabilities for equipment aging trends and failure risks.

[0020] 3. This invention combines equipment operating data, historical failure data, and a time decay model to more accurately predict the remaining life of equipment. Compared to existing technologies, which lack accurate predictions, this invention provides more precise health assessments, helping managers better formulate maintenance strategies.

[0021] 4. This invention significantly enhances the intelligence of the health assessment model by incorporating a time decay model and weighted risk score calculation, combined with dynamic assessment of equipment scheduling data. Compared to existing rule-based systems, this invention more intelligently reflects the actual operating status of equipment, and is particularly adaptable to complex operating conditions.

[0022] In summary, the present invention significantly improves the comprehensiveness, accuracy, dynamics and real-time performance of the health evaluation of assembly line equipment by introducing innovative technical features such as comprehensive weight values, time decay models, empirical coefficients and production scheduling data, provides scientific decision-making support for equipment maintenance and production management, and reduces production risks and costs.

[0023] Further or more detailed beneficial effects will be described in conjunction with specific examples in the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 paying any creative work.

[0025] Figure 1 4 is a flow chart of the health evaluation method according to an embodiment of the present invention.

[0026] Figure 2 is a structural diagram of the electronic device provided by an embodiment of the present invention.

[0027] Figure Number:

[0028] 200. Electronic equipment;

[0029] 201. Processor; 202. Communication bus; 203. User interface; 204. Network interface; 205. Memory. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0031] In the following description, multiple embodiments of the present invention are provided. Different embodiments may be replaced or combined, and therefore the present invention may be considered to include all possible combinations of the same and / or different embodiments described. Thus, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then the present invention should also be considered to include embodiments that include one or more of all other possible combinations of A, B, C, and D, even if such embodiments may not be explicitly described in the following text.

[0032] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the functions and arrangements of the elements described without departing from the scope of the present invention. Various examples may appropriately omit, replace, or add various processes or components. For example, the described method may be performed in an order different from the order described, and various steps may be added, omitted, or combined. Furthermore, features described in some examples may be combined in other examples.

[0033] In order to facilitate a better understanding of the embodiments of the present invention, before explaining the specific implementation methods of the present invention in detail, its application scenarios are first described.

[0034] The health evaluation method described in the embodiments of this specification is applied to the operation and maintenance process of assembly line special equipment. In these scenarios, the application of the health evaluation method aims to comprehensively improve the operating reliability and production efficiency of the equipment, reduce the risk of failure and maintenance costs through real-time monitoring, dynamic evaluation, optimized maintenance, improved production efficiency, prediction of remaining life and improved intelligent management level, and has important theoretical significance and engineering application value.

[0035] Example 1:

[0036] like Figure 1 As shown, this embodiment provides a method for evaluating the health of a dedicated assembly line device, comprising the steps of: S1, obtaining the evaluation index of the device and the comprehensive weight value corresponding to each index, and performing calculations based on the obtained index to obtain a first health score. S2. Obtain the historical fault data and historical operating time data of the equipment, and calculate the time interval between the fault occurrence time and the maintenance occurrence time of each fault based on this data. And build a time decay model to calculate the weighted risk score of each failure, thereby calculating the second health score ; S3, based on the first health score and the second health score Calculate the comprehensive health score =a -b , a and b are empirical coefficients, and the equipment historical failure interval is calculated based on the historical failure data , thereby obtaining the health data of the equipment; S4, obtaining the production scheduling data of the equipment and combining the health data to calculate to obtain the current production scheduling risk score , thereby completing the health evaluation of the assembly line equipment.

[0037] Specifically, this embodiment provides a preferred implementation method, wherein the evaluation indicators include operation indicators, economic indicators and maintenance indicators, wherein the operation indicators may include at least the average daily number of failures, the average daily working time and the average daily number of suspensions, the economic indicators may include at least the average daily production capacity and the average daily startup time, and the maintenance indicators may include at least the average daily number of maintenances and the average daily maintenance time. More specifically, the evaluation indicators may be obtained by installing smart sensors, which may include at least temperature and humidity sensors, gas path pressure sensors, vibration sensors, temperature sensors and smart meters to collect various data, which may include at least operation time, load conditions, energy consumption, temperature, humidity, air pressure and vibration; the comprehensive weight value includes a subjective weight value and objective weights The subjective weight value can at least be obtained by cluster analysis, that is, by determining the consistency and difference of different experts' evaluations of each indicator, so as to give the relative weight of each expert in the group decision-making; the calculation formula of the comprehensive weight value is: , Indicates the evaluation index number, Indicates the total number of evaluation indicators; the first health score The calculation formula is , Indicates the The comprehensive weight of the evaluation indicators, Indicates the The first device The comprehensive weight value can also be obtained by the method described in the existing research (Yang Yanfang, Xing Yahui, Shu Liang, et al. Research on Equipment Health Assessment Method Based on Twin Data [J]. Journal of Huazhong University of Science and Technology).

[0038] Specifically, this embodiment provides a preferred implementation method, the time interval The calculation formula is , Indicates the time when the equipment failure occurs. Indicates the time when equipment maintenance occurs; calculates the time interval Then also includes the time interval Normalize to the working time of the entire device to make the data of different devices or different time periods comparable. The normalization formula is: , Indicates the current moment of evaluation, Indicates the starting time of the equipment. It is understandable that as the life of the equipment increases, the failure and maintenance intervals will shorten, which means that the equipment ages faster and its reliability decreases. Therefore, the time interval can be used To reflect this trend of change. Specifically, if over time, the time interval If the time interval is smaller, it means that the equipment health is deteriorating and more frequent maintenance is required. If it is relatively stable or increasing, it may mean that the equipment is in good condition and the maintenance efficiency is high.

[0039] Specifically, this embodiment provides a preferred implementation method. The time decay model can be understood as a model that describes the time decay of the impact of historical fault events and equipment maintenance time on the health score, and determines the time distribution of fault data by statistically analyzing the historical data of equipment operation. The expression of the time decay model is: , Indicates the time at which the device The risk score, Indicates the risk score of the device at the initial moment, represents the time decay factor, Indicates time starting from a reference point.

[0040] Specifically, this embodiment provides a preferred implementation method, wherein the weighted risk score of each failure includes the following steps: The numerical value of each fault is assigned a weight , and the larger Corresponding to lower weights, smaller corresponds to a higher weight; the expression of the weight is , A positive number to prevent the denominator from being zero; the weight of each fault is adjusted based on the time decay coefficient to obtain a time-adjusted risk score The second health score The calculation formula is , Indicates the total number of faults.

[0041] Specifically, this embodiment provides a preferred implementation method, wherein the production scheduling data includes the total number of orders that need to be processed within a future preset window. , the total number of equipment involved in production k, the order quantity assigned to each equipment m, and the equipment's production capacity and standard production time The production scheduling data of the equipment is obtained and combined with the health data to calculate the current production scheduling risk score The steps include: calculating the equipment efficiency coefficient of each equipment in the production scheduling data To evaluate the efficiency of equipment in production scheduling; allocate orders proportionally based on the equipment efficiency coefficient corresponding to each equipment to obtain the order quantity allocated to each equipment , is the total number of orders, k is the total number of equipment involved in production. Allocation based on this formula can ensure that high-health equipment takes on more tasks and at the same time balance the expected total time of each equipment; More specifically, the total production time should also be considered when allocating orders. The total production time is determined by the completion time of the slowest equipment, that is, by calculating the total production time, the risk index of reaching production within the specified time can be obtained. The expected failure time of the equipment during production after allocating orders proportionally is calculated. The risk index is calculated , For production time, For standard production time, according to the work system It can be preferably 24 hours, 16 hours or 8 hours; based on the comprehensive health score and the risk indicators Calculate the current scheduling risk score .

[0042] Specifically, this embodiment provides a preferred implementation method, the device efficiency coefficient corresponding to each device is The calculation formula is , Indicates the overall health score of the device. represents the single-task production time, Represents the maintenance time. This formula takes into account the production speed and failure risk. The lower the health, the higher the maintenance time ratio. It is used as a coefficient for subsequent allocation of orders, so the maintenance time You can choose the average maintenance time of the equipment in the near future; the expected failure time corresponding to each equipment The calculation formula is , Indicates the order quantity assigned to the device, is the production capacity of the equipment, The mean time between failures of the equipment; the current production scheduling risk score The calculation formula is , is the comprehensive health score, R is the risk index, The maximum risk threshold is used to represent the delivery time of the order.

[0043] Example 2:

[0044] This embodiment provides a health evaluation system for dedicated equipment in an assembly line, which is used to implement the health evaluation method described in the first embodiment.

[0045] Example 3:

[0046] like Figure 2 As shown, this embodiment provides an electronic device, which may include: at least one processor, at least one network interface, a user interface, a memory, and at least one communication bus.

[0047] The communication bus can be used to realize the connection and communication among the above components.

[0048] The user interface may include buttons, and the optional user interface may also include a standard wired interface or a wireless interface.

[0049] The network interface may include, but is not limited to, a Bluetooth module, an NFC module, a Wi-Fi module, and the like.

[0050] Among them, the processor may include one or more processing cores. The processor uses various interfaces and lines to connect the various parts of the entire electronic device, and performs various functions of the electronic device and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory, and calling data stored in the memory. Optionally, the processor can be implemented in at least one hardware form of DSP, FPGA, PLA. The processor can integrate one or a combination of CPU, GPU and modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to handle wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor, but may be implemented separately through a chip.

[0051] The memory may include RAM or ROM. Optionally, the memory includes a non-transitory computer-readable medium. The memory can be used to store instructions, programs, codes, code sets, or instruction sets. The memory may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory may optionally be at least one storage device located away from the aforementioned processor. The memory as a computer storage medium may include an operating system, a network communication module, a user interface module, and a health assessment application. The processor may be used to call the health assessment application stored in the memory and execute the health assessment steps mentioned in the above-mentioned embodiments.

[0052] Example 4:

[0053] This embodiment provides a computer-readable storage medium having instructions stored therein, which, when executed on a computer or processor, causes the computer or processor to execute the above-mentioned Figure 1 If the components of the electronic device are implemented in the form of software functional units and sold or used as independent products, they can be stored in the computer-readable storage medium.

[0054] In the above embodiments, all or part of the embodiments can be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this specification are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted via the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital versatile disc (DVD)), or a semiconductor medium (eg, a solid state drive (SSD)).

[0055] Those skilled in the art will appreciate that all or part of the process steps in the method of the first embodiment described above can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When executed, the program can include the processes of the embodiments of the above methods. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks. The technical features of this embodiment and the implementation scheme can be combined in any manner unless they conflict.

[0056] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should be aware that the present invention is not limited by the order of the actions described, because according to the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0057] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0058] The foregoing is merely an exemplary embodiment of the present invention and is not intended to limit the scope of the present invention. That is, any equivalent changes and modifications made in accordance with the teachings of the present invention are still within the scope of the present invention. A person skilled in the art will readily come up with the embodiments of the present invention after considering the specification and practicing the disclosure herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary technical means in the art that are not described in the present invention. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present invention are defined by the claims.

Claims

1. A method for evaluating the health of a production line equipment, characterized in that: Including steps: S1. Obtain the evaluation index of the equipment and the comprehensive weight value corresponding to each index, and calculate based on this to obtain the first health score ; S2. Obtain the historical fault data and historical operating time data of the equipment, and calculate the time interval between the fault occurrence time and the maintenance occurrence time of each fault based on this data. And build a time decay model to calculate the weighted risk score of each failure, thereby calculating the second health score ; S3. Based on the first health score and the second health score Calculate the comprehensive health score =a -b , a and b are empirical coefficients, and the equipment historical failure interval is calculated based on the historical failure data , thereby obtaining the health data of the equipment; S4. Obtain the production scheduling data of the equipment and calculate it in combination with the health data to obtain the current production scheduling risk score , thereby completing the health evaluation of the assembly line equipment; The production scheduling data includes the total number of orders that need to be processed within the future preset window , the total number of equipment involved in production k, the order quantity assigned to each equipment m, and the equipment's production capacity and standard production time ; The production scheduling data of the equipment is obtained and combined with the health data to calculate the current production scheduling risk score Including steps: Calculate the equipment efficiency coefficient of each equipment in the production scheduling data To evaluate the efficiency of equipment in production scheduling; Allocate orders proportionally based on the equipment efficiency coefficient corresponding to each device to obtain the order quantity allocated to each device , is the total number of orders, k is the total number of equipment involved in production; Calculate the expected downtime during equipment production after allocating orders proportionally The risk index is calculated , For production time, is the standard production time; Based on the comprehensive health score and the risk indicators Calculate the current scheduling risk score , the current scheduling risk score The calculation formula is , is the comprehensive health score, R is the risk index, is the maximum risk threshold.

2. The method for evaluating the health of a dedicated assembly line equipment according to claim 1, characterized in that: The evaluation indicators include operation indicators, economic indicators and maintenance indicators; The comprehensive weight value includes a subjective weight value and objective weights ; The calculation formula of the comprehensive weight value is: , Indicates the evaluation index number, Indicates the total number of evaluation indicators; The first health score The calculation formula is , Indicates the The comprehensive weight of the evaluation indicators, Indicates the The first device The standardized value of the evaluation indicator.

3. The method for evaluating the health of a dedicated assembly line equipment according to claim 2, characterized in that: The time interval The calculation formula is , Indicates the time when the equipment failure occurs. Indicates the time when equipment maintenance occurs; Calculate the time interval Then also includes the time interval Normalize to the working time of the entire device to make the data of different devices or different time periods comparable. The normalization formula is: , Indicates the current moment of evaluation, Indicates the starting time when the device starts working.

4. The method for evaluating the health of a dedicated assembly line equipment according to claim 3, characterized in that: The expression of the time decay model is: , Indicates the time at which the device The risk score, Indicates the risk score of the device at the initial moment, represents the time decay factor, Indicates time starting from a reference point.

5. The health evaluation method for assembly line equipment according to claim 4 is characterized in that: The weighted risk score of each failure includes the following steps: according to The numerical value of each fault is assigned a weight , and the larger Corresponding to lower weights, smaller Corresponding to higher weight; The expression of the weight is , is a positive number; The weight of each fault is adjusted based on the time decay coefficient to obtain a time-adjusted risk score ; The second health score The calculation formula is , Indicates the total number of faults.

6. The method for evaluating the health of a dedicated assembly line equipment according to claim 5, characterized in that: The equipment efficiency coefficient corresponding to each device The calculation formula is , Indicates the overall health score of the device. represents the single-task production time, Indicates maintenance time; The expected failure time corresponding to each device The calculation formula is , Indicates the order quantity assigned to the device, is the production capacity of the equipment, The mean time between failures of the equipment.

7. A health evaluation system for assembly line equipment, characterized in that: Used to implement the health assessment method as described in any one of claims 1 to 6.

8. A computer device comprising a memory, a processor, and a computer program, wherein: When the computer program is executed by a processor, the health evaluation method according to any one of claims 1 to 6 is 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 health evaluation method according to any one of claims 1 to 6 is implemented.

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