Health degree evaluation method, system and equipment of assembly line special equipment and medium

Abstract

The invention belongs to the technical field of equipment management, discloses a health degree evaluation method, system and equipment for assembly line special equipment and a medium, and aims to solve the limitation of health state evaluation of the assembly line special equipment in the prior art. The method comprises the steps of obtaining evaluation indexes of equipment and comprehensive weight values corresponding to the indexes, and performing calculation based on the evaluation indexes to obtain a first health degree score; acquiring historical fault data and historical operation time data of the equipment, calculating a time interval between a fault occurrence moment and a maintenance occurrence moment of each fault based on the historical fault data and the historical operation time data, and constructing a time attenuation model to calculate a weighted risk score of each fault so as to calculate a second health score; and obtaining production scheduling data of the equipment, and performing calculation in combination with the health degree data to obtain a current production scheduling risk score, thereby completing health degree evaluation of the assembly line special machine equipment. According to the method, the comprehensiveness, the accuracy, the dynamism and the real-time performance of health degree evaluation of the assembly line special machine equipment are remarkably improved.

Description

Technical Field

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

[0002] In modern industrial production, the health status of assembly line equipment (such as electric energy meter calibration equipment) is directly related to production efficiency and product quality. Since these equipment are in high-load operation for a long time, real-time monitoring and evaluation of their health status is particularly important. By accurately evaluating the health status of the equipment, not only can potential faults be warned in advance and unplanned downtime be avoided, but also maintenance strategies can be optimized, equipment life can be extended, and production costs can be reduced. Therefore, how to scientifically and comprehensively evaluate the health status of assembly line equipment has become a key scientific issue in this technical field. To solve this problem, some equipment health management systems have been proposed in the prior art. For example, Chinese patent CN201910079283.6 proposes an equipment health management system, which realizes the evaluation of equipment health status through data acquisition module, database module, environmental parameter module, data processing module, control module, health factor module, algorithm module and health analysis module. Specifically, the system collects the operating parameters of the equipment (such as operating time, load conditions, energy consumption, temperature, vibration, etc.), combines health factors and algorithms, calculates the health of the equipment, and outputs the health status of the equipment based on the health analysis module. However, existing technologies mainly rely on health factors and algorithms to calculate the health status of equipment. Although they can reflect some of the operating status of the equipment, they fail to fully consider the multi-dimensional factors of the equipment. In addition, the health assessment models of existing technologies are mostly static models, which cannot reflect the health status and failure risks of equipment under real-time tasks in real time. In summary, existing technologies still have many limitations in the health status assessment 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 urgently. Summary of the invention

[0003] Based on the above-mentioned shortcomings and deficiencies in the prior art, one of the objects 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 objects 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 evaluation.

[0004] In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a method for evaluating the health of a production 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 index to obtain a first health score ; S2, obtain the historical fault data and historical running time data of the equipment, and based on this calculate the time interval between the fault occurrence time and the maintenance occurrence time of each fault 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 overall 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.

[0005] As a preferred solution, the evaluation index includes operation index, economic index and maintenance index; The comprehensive weight value includes a subjective weight value and objective weight ; 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 comprehensive weight of the evaluation indicators, Indicates The first device The standardized value of the evaluation index.

[0006] 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, the time interval Normalize to the working time of the whole device to make the data of different devices or different time periods comparable. The normalization formula is: , Indicates the current time of the evaluation, Indicates the time when the device starts working.

[0007] 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.

[0008] 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; 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.

[0009] As a preferred solution, the production scheduling data includes the total number of orders 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 to obtain 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 the equipment in production scheduling; to allocate orders in proportion to 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 in proportion 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 .

[0010] 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, is the average 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.

[0011] 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 as described in the first aspect.

[0012] 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.

[0013] 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.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention obtains the evaluation index of the equipment and the comprehensive weight value corresponding to each index, and combines historical fault data and historical operating time data to construct a time decay model, which can comprehensively consider multi-dimensional factors such as equipment operation stability, fault frequency, historical fault data, etc. Compared with the existing technology that only relies on health factors and algorithms for evaluation, the present invention can more comprehensively reflect the health status of the equipment.

[0015] 2. The present invention constructs a time decay model, calculates the weighted risk score of each failure, and combines the equipment's production scheduling data to dynamically evaluate the equipment's health status and failure risk under the current production scheduling task. Compared with the static evaluation model of the prior art, the present invention can reflect the changes in the health status of the equipment in real time, especially the dynamic evaluation capability in terms of equipment aging trend and failure risk is significantly improved.

[0016] 3. The present invention can more accurately predict the remaining life of the equipment by combining the equipment's operating data, historical fault data and time decay model. Compared with the shortcomings of the existing technology in terms of prediction accuracy, the present invention can provide more accurate health assessment results to help managers better formulate maintenance strategies.

[0017] 4. The present invention significantly improves the intelligence of the health assessment model by introducing a time decay model and weighted risk score calculation, combined with the equipment's production scheduling data for dynamic assessment. Compared with the rule-based system in the prior art, the present invention can more intelligently reflect the actual operating status of the equipment, especially with stronger adaptability under complex working conditions.

[0018] 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.

[0019] Further or more detailed beneficial effects will be described in detail in conjunction with specific examples in the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 creative work.

[0021] Figure 1 It is a flowchart of the health evaluation method described in an embodiment of the present invention.

[0022] Figure 2 is a structural diagram of the electronic device provided in an embodiment of the present invention.

[0023] Figure Number: 200. Electronic equipment; 201, processor; 202, communication bus; 203, user interface; 204, network interface; 205, memory. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0025] In the following description, multiple embodiments of the present invention are provided, and different embodiments may be replaced or combined, so the present invention may also be considered to include all possible combinations of the same and / or different embodiments described. Therefore, 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 containing one or more of A, B, C, and D, all other possible combinations, even though the embodiment may not be clearly described in the following text.

[0026] 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 processes or components may be appropriately omitted, substituted or added to each example. For example, the described method may be performed in an order different from the described order, and various steps may be added, omitted or combined. In addition, the features described in some examples may be combined in other examples.

[0027] In order to facilitate a better understanding of the embodiments of the present invention, before explaining the specific implementation modes of the present invention in detail, its application scenarios are first described.

[0028] 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.

[0029] Embodiment 1: like Figure 1 As shown, this embodiment provides a method for evaluating the health of a production line equipment, including 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 index to obtain a first health score ; S2, obtain the historical fault data and historical running time data of the equipment, and based on this calculate the time interval between the fault occurrence time and the maintenance occurrence time of each fault 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 overall 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.

[0030] Specifically, this embodiment provides a preferred implementation method, the evaluation indicators include operation indicators, economic indicators and maintenance indicators, the operation indicators may at least include the average daily number of failures, the average daily working time and the average daily number of suspensions, the economic indicators may at least include the average daily production capacity and the average daily startup time, the maintenance indicators may at least include the average daily number of maintenances and the average daily maintenance time, more specifically, the evaluation indicators can be obtained by installing smart sensors, the smart sensors may at least include temperature and humidity sensors, gas path pressure sensors, vibration sensors, temperature sensors, smart meters to collect various data, the data may at least include operating time, load conditions, energy consumption, temperature, humidity, air pressure, vibration; the comprehensive weight value includes a subjective weight value and objective weight , the subjective weight value can at least be obtained by cluster analysis method, that is, by determining the consistency and difference of different experts' evaluation of each indicator, so as to give the relative weight of each expert in 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 comprehensive weight of the evaluation indicators, Indicates 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).

[0031] Specifically, this embodiment provides a preferred implementation, 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, the time interval Normalize to the working time of the whole device to make the data of different devices or different time periods comparable. The normalization formula is: , Indicates the current time of the evaluation, Indicates the time when the equipment starts working. It is understandable that as the life of the equipment increases, the interval between failures and maintenance will shorten, which means that the equipment ages faster and its reliability decreases. Therefore, the time interval can be used To reflect this trend. 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.

[0032] Specifically, this embodiment provides a preferred implementation method. The time decay model can be understood as a model that describes the decay of the impact of historical fault events and equipment maintenance time on the health score over time, 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.

[0033] Specifically, this embodiment provides a preferred implementation method, wherein 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 , 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.

[0034] Specifically, this embodiment provides a preferred implementation method, wherein the production scheduling data includes the total number of orders 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 to obtain 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 the equipment in production scheduling; to allocate orders in proportion to 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 undertakes more tasks and balances the expected total time of each equipment at the same time; 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, and the expected failure time of the equipment during production after allocating orders in proportion can be calculated. The risk index is calculated , For production time, 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 production scheduling risk score .

[0035] Specifically, this embodiment provides a preferred implementation method, the device efficiency coefficient corresponding to each device 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, because is used as a coefficient for subsequent allocation of orders, so the maintenance time You can select 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, is the average 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.

[0036] Embodiment 2: This embodiment provides a health evaluation system for assembly line equipment, which is used to implement the health evaluation method described in the first embodiment.

[0037] Embodiment three: 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.

[0038] The communication bus can be used to realize the connection and communication among the above-mentioned components.

[0039] The user interface may include buttons, and the optional user interface may also include a standard wired interface or a wireless interface.

[0040] The network interface may include but is not limited to a Bluetooth module, an NFC module, a Wi-Fi module, etc.

[0041] 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 executes 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, and PLA. The processor can integrate one or a combination of CPU, GPU, modem, etc. 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; 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.

[0042] Among them, 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, wherein 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 various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory may also 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 can be used to call the health assessment application stored in the memory and perform the steps of the health assessment mentioned in the above-mentioned embodiment.

[0043] Embodiment 4: This embodiment provides a computer-readable storage medium, which stores instructions. When the computer-readable storage medium is executed on a computer or a processor, the computer or the processor executes the above-mentioned Figure 1 One or more steps in the illustrated embodiment. If the components of the electronic device described above 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.

[0044] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part 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, the process or function described in the embodiment of this specification is generated in whole or in part. 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 through the computer-readable storage medium. The computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (Digital Subscriber Line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode. 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 includes one or more available media integrated. 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)).

[0045] A person of ordinary skill in the art can understand that all or part of the processes in the method of the first embodiment can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. The aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes. In the absence of conflict, the technical features in this embodiment and the implementation scheme can be combined arbitrarily.

[0046] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0047] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0048] The above is only an exemplary embodiment of the present invention and cannot be used to limit the scope of the present invention. That is, any equivalent changes and modifications made according to the teachings of the present invention are still within the scope of the present invention. After considering the specification and practicing the disclosure here, it will be easy for those skilled in the art to think of the implementation scheme of the present invention. The present invention is intended to cover any modification, use or adaptation of the present invention, which follows the general principles of the present invention and includes common knowledge or customary technical means in the art that are not recorded in the present invention. The description and examples are only regarded as exemplary, 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: Includes 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 running time data of the equipment, and based on this, calculate the time interval between the fault occurrence time and the maintenance occurrence time of each fault 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.

2. According to claim 1, a method for evaluating the health of a production line equipment is characterized by: The evaluation indicators include operation indicators, economic indicators and maintenance indicators; The comprehensive weight value includes a subjective weight value and objective weight ; 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 comprehensive weight of the evaluation indicators, Indicates The first device The standardized value of the evaluation index.

3. The method for evaluating the health of a production 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, the time interval Normalize to the working time of the whole device to make the data of different devices or different time periods comparable. The normalization formula is: , Indicates the current time of the evaluation, Indicates the starting time when the device starts working.

4. The method for evaluating the health of a production line equipment according to claim 3 is 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 method for evaluating the health of a production line equipment according to claim 4, characterized in that: The weighted risk score of each failure includes the steps of: 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 production line equipment according to claim 5, characterized in that: 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 to obtain the current production scheduling risk score Includes 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 in proportion to the equipment efficiency coefficients corresponding to each equipment to obtain the order quantity allocated to each equipment , is the total order quantity, 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 production scheduling risk score .

7. The method for evaluating the health of a production line equipment according to claim 6, 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, is the mean time between failures of the equipment; The current scheduling risk score The calculation formula is , is the comprehensive health score, R is the risk index, is the maximum risk threshold.

8. 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 7.

9. A computer device, comprising a memory, a processor and a computer program, characterized in that: When the computer program is executed by a processor, the health assessment method according to any one of claims 1 to 7 is 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 health assessment method according to any one of claims 1 to 7 is implemented.

Images