Product reliability evaluation method and device, computer device and storage medium

Abstract

The application relates to a product reliability evaluation method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: comparing a product to be evaluated with an in-service similar product, obtaining reliability evaluation similar data and reliability evaluation difference data of the product to be evaluated and the in-service similar product; reading a first correction factor corresponding to the product to be evaluated, the first correction factor being a ratio of an in-service failure rate prediction value corresponding to the in-service similar product to an in-service failure rate field estimation value; obtaining a similar initial reliability evaluation result based on the reliability evaluation similar data, and obtaining a difference reliability evaluation result based on the reliability evaluation difference data; correcting the similar initial reliability evaluation result according to the first correction factor to obtain a similar target reliability evaluation result; and fusing the difference reliability evaluation result and the similar target reliability evaluation result to obtain a reliability evaluation result of the product to be evaluated. The method can improve the accuracy of the reliability evaluation result.

Description

TECHNICAL FIELD

[0001] The present application relates to the reliability field, in particular to a product reliability evaluation method and device, computer equipment, storage medium and computer program product. BACKGROUND

[0002] With the development of reliability technology, the increasingly fierce market competition and the increasingly high requirements of users on product quality and reliability, it is generally necessary to evaluate the product reliability in the product design stage, find the weak links of the product, and then improve the design.

[0003] At present, there are various reliability prediction methods, including manual-based prediction method, similar product method, expert scoring method, performance parameter method, failure physics method, etc. Different prediction methods have their own advantages and disadvantages. The manual-based prediction method, the similar product method and the expert scoring method are strong in engineering practicability, but the prediction results are questionable. The failure physics method has a complex modeling process and requires many parameters, and is poor in engineering operation. In summary, the current reliability prediction methods are not perfect, and the accuracy of the obtained reliability evaluation results is low. SUMMARY

[0004] Therefore, it is necessary to provide a product reliability evaluation method and device, computer equipment, computer readable storage medium and computer program product capable of improving the accuracy of reliability evaluation results.

[0005] In a first aspect, the present application provides a product reliability evaluation method, which comprises:

[0006] Comparing a product to be evaluated with an in-service similar product, obtaining reliability evaluation similar data and reliability evaluation difference data of the product to be evaluated and the in-service similar product;

[0007] Reading a first correction factor corresponding to the product to be evaluated, the first correction factor being a ratio of an in-service failure rate prediction value corresponding to the in-service similar product to an in-service failure rate field estimation value;

[0008] Obtaining a similar initial reliability evaluation result based on the reliability evaluation similar data, and obtaining a difference reliability evaluation result based on the reliability evaluation difference data;

[0009] Correcting the similar initial reliability evaluation result according to the first correction factor to obtain a similar target reliability evaluation result;

[0010] Fusing the difference reliability evaluation result and the similar target reliability evaluation result to obtain a reliability evaluation result of the product to be evaluated.

[0011] In one of the embodiments, the obtaining of the reliability evaluation similar data and the reliability evaluation difference data of the product to be evaluated and the similar product in service comprises:

[0012] obtaining product to be evaluated attribute information of the product to be evaluated and similar product attribute information of the similar product in service;

[0013] comparing the product to be evaluated attribute information and the similar product attribute information based on a similarity judgment principle to obtain a similarity judgment result;

[0014] obtaining the reliability evaluation similar data and the reliability evaluation difference data of the product to be evaluated and the similar product in service based on the similarity judgment result.

[0015] In one of the embodiments, the similar initial reliability evaluation result comprises similar initial failure rates corresponding to each failure factor in the reliability evaluation similar data.

[0016] The modifying the similar initial reliability evaluation result according to the first correction factor to obtain a similar target reliability evaluation result comprises:

[0017] calculating a product of the similar initial failure rate corresponding to each failure factor and the first correction factor to obtain a sub-whole correction result corresponding to each failure factor;

[0018] calculating a sum of the sub-whole correction results to obtain a whole correction result;

[0019] judging whether the whole correction result meets a preset reliability evaluation result range to obtain a preset reliability evaluation result;

[0020] obtaining a similar target reliability evaluation result according to the preset reliability evaluation result.

[0021] In one of the embodiments, the obtaining of the similar target reliability evaluation result according to the preset reliability evaluation result comprises:

[0022] if the preset reliability evaluation result is that the whole correction result meets the preset reliability evaluation result range, taking the whole correction result as the similar target reliability evaluation result;

[0023] if the preset reliability evaluation result is that the whole correction result does not meet the preset reliability evaluation result range, determining a product to be evaluated life based on the reliability evaluation similar data and determining a similar product in service life based on similar product in service data of the similar product in service;

[0024] determining a second correction factor based on a ratio of the in-service failure life and the to-be-evaluated failure life;

[0025] locally correcting each of the sub-entire correction results corresponding to the failure factors according to the second correction factor to obtain a locally corrected result;

[0026] obtaining a similar target reliability evaluation result based on the locally corrected result and the entire correction result.

[0027] In one of the embodiments, the locally correcting each of the sub-entire correction results corresponding to the failure factors according to the second correction factor to obtain a locally corrected result comprises:

[0028] obtaining a sub-entire correction result corresponding to a weak failure factor in each of the failure factors, the weak failure factor being a factor causing failure of the to-be-evaluated product under a set experimental condition;

[0029] calculating a product of the sub-entire correction result corresponding to the weak failure factor and the second correction factor to obtain the locally corrected result.

[0030] In one of the embodiments, the obtaining the to-be-evaluated life based on the reliability evaluation similar data and the in-service similar life based on the in-service similar data of the similar product comprises:

[0031] obtaining a to-be-evaluated three-dimensional model corresponding to the reliability evaluation similar data and an in-service similar three-dimensional model corresponding to the in-service similar data;

[0032] performing thermal simulation based on the to-be-evaluated three-dimensional model to obtain a to-be-evaluated simulation result and performing vibration simulation based on the in-service similar three-dimensional model to obtain an in-service similar simulation result;

[0033] inputting the to-be-evaluated simulation result and the in-service similar simulation result into a life simulation model respectively and combining a competitive failure mechanism to obtain a to-be-evaluated failure life and an in-service failure life respectively.

[0034] In one of the embodiments, the obtaining a similar target reliability evaluation result based on the locally corrected result and the entire correction result comprises:

[0035] calculating a sum of the locally corrected result and a sub-entire correction result corresponding to a failure factor other than the weak factor in the entire correction result to obtain the similar target reliability prediction result.

[0036] In a second aspect, the application further provides a product reliability evaluation device, the device comprising:

[0037] The comparison module is configured to compare the product to be evaluated with the similar product in service, and obtain reliability evaluation similarity data and reliability evaluation difference data of the product to be evaluated and the similar product in service.

[0038] The data reading module is configured to read a first correction factor corresponding to the product to be evaluated, the first correction factor being a ratio of an in-service failure rate prediction value corresponding to the similar product in service to an in-service failure rate field estimation value.

[0039] The first data processing module is configured to obtain a similar initial reliability evaluation result based on the reliability evaluation similarity data, and obtain a difference reliability evaluation result based on the reliability evaluation difference data.

[0040] The second data processing module is configured to correct the similar initial reliability evaluation result according to the first correction factor to obtain a similar target reliability evaluation result.

[0041] The reliability evaluation module is configured to fuse the difference reliability evaluation result and the similar target reliability evaluation result to obtain a reliability evaluation result of the product to be evaluated.

[0042] In a third aspect, the present application also provides a computer device, including a memory and a processor, the memory stores a computer program, and the processor implements the steps of the product reliability evaluation method when executing the computer program.

[0043] In a fourth aspect, the present application also provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the product reliability evaluation method when executed by a processor.

[0044] In a fifth aspect, the present application also provides a computer program product, including a computer program, and the computer program implements the steps of the product reliability evaluation method when executed by a processor.

[0045] The product reliability evaluation method, device, computer device, storage medium and computer program product can read a first correction factor corresponding to the product to be evaluated after obtaining reliability evaluation similarity data and reliability evaluation difference data, so that the similar initial reliability evaluation result corresponding to the reliability evaluation similarity data can be corrected according to the first correction factor to obtain a similar target reliability evaluation result, thereby improving the accuracy of the similar initial reliability evaluation result, and finally fusing the difference reliability evaluation result corresponding to the reliability evaluation difference data and the similar target reliability evaluation result to obtain a reliability evaluation result of the product to be evaluated. The above method can effectively improve the precision of the reliability evaluation result of the product to be evaluated. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 a flowchart of a product reliability evaluation method in an embodiment;

[0047] Figure 2 a flowchart of a product reliability evaluation method in another embodiment;

[0048] Figure 3 a flowchart of a product reliability evaluation method in yet another embodiment;

[0049] Figure 4 a structural block diagram of a product reliability evaluation device in an embodiment;

[0050] Figure 5 an internal structural diagram of a computer device in an embodiment. DETAILED DESCRIPTION

[0051] In order to make the purposes, technical solutions and advantages of the present application clearer, further detailed description will be made to the present application in combination with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not used to limit the present application.

[0052] The product reliability evaluation method provided by the embodiments of the present application and the product reliability acceleration coefficient evaluation method provided by the embodiments of the present application can be applied in a terminal. Specifically, the terminal compares a product to be evaluated with a similar product in service, obtains reliability evaluation similar data and reliability evaluation difference data of the product to be evaluated and the similar product in service, reads a first correction factor corresponding to the product to be evaluated, the first correction factor being a ratio of an in-service failure rate prediction value corresponding to the similar product in service to an in-service failure rate field estimation value, obtains a similar initial reliability evaluation result based on the reliability evaluation similar data, and obtains a difference reliability evaluation result based on the reliability evaluation difference data, corrects the similar initial reliability evaluation result according to the first correction factor to obtain a similar target reliability evaluation result, and fuses the difference reliability evaluation result and the similar target reliability evaluation result to obtain a reliability evaluation result of the product to be evaluated. Optionally, the product reliability acceleration coefficient evaluation method described above can also be applied in a server. The terminal can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, Internet of Things devices and portable wearable devices, the Internet of Things device can be a smart speaker, a smart television, a smart air conditioner, a smart vehicle-mounted device, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The server can be implemented by an independent server or a server cluster composed of multiple servers.

[0053] In one embodiment, as shown in Figure 1 a product reliability evaluation method is provided, which is taken as an example for description when the method is applied in a terminal, and includes the following steps:

[0054] In step S102, the reliability evaluation similar data and the reliability evaluation difference data of the product to be evaluated and the in-service similar product are obtained by comparing the product to be evaluated and the in-service similar product.

[0055] The product to be evaluated can be any device that needs to be evaluated for reliability, a product formed by devices, or the like, and the device can be an electronic component. The in-service similar product refers to a product that is similar to the product to be evaluated in structure, performance, design, use environment, and the like. The reliability evaluation similar data refers to data of similar parts of the product to be evaluated and the in-service similar product obtained by comparison. The reliability evaluation difference data refers to data of non-similar parts of the product to be evaluated and the in-service similar product obtained by comparison.

[0056] In one embodiment, obtaining the reliability evaluation similar data and the reliability evaluation difference data of the product to be evaluated and the in-service similar product by comparing the product to be evaluated and the in-service similar product includes:

[0057] The product to be evaluated attribute information of the product to be evaluated and the similar product attribute information of the in-service similar product are obtained. The similarity judgment result is obtained by comparing the product to be evaluated attribute information and the similar product attribute information based on a similarity judgment principle. The reliability evaluation similar data and the reliability evaluation difference data of the product to be evaluated and the in-service similar product are obtained based on the similarity judgment result.

[0058] The product to be evaluated attribute information refers to information such as structure, performance, design, material, and manufacturing process of the product to be evaluated. The similar product attribute information refers to information such as structure, performance, design, material, and manufacturing process of the in-service similar product. The similarity judgment principle can refer to a judgment principle set according to each attribute information, so that each attribute information of the product to be evaluated and the in-service similar product can be compared correspondingly. The similarity judgment result refers to a result obtained by judging the product to be evaluated attribute information and the similar product attribute information based on the similarity judgment principle.

[0059] In one embodiment, the product to be evaluated can be C919 (a domestic large passenger plane), and the in-service similar product can be C920, which is a new airplane designed on the basis of C919. The similarity judgment result of C919 and C920 is obtained by the similarity judgment principle. Most of the attributes of C920 are the same as those of C919. Since corresponding components are newly added, the structure and performance and the like have changed. Therefore, the newly added part is a non-similar part, and the data of the non-similar part is the reliability evaluation difference data. The remaining part can be considered as a similar part, and the data of the similar part is the reliability evaluation similar data.

[0060] Step S104, reading a first correction factor corresponding to the product to be evaluated, the first correction factor being a ratio of an in-service failure rate prediction value corresponding to the in-service similar product and an in-service failure rate field estimation value.

[0061] The first correction factor refers to a value that can be used to correct the similar initial reliability evaluation result. The first correction factor can be an overall correction factor, i.e., an overall correction of the similar initial reliability evaluation result. The in-service failure rate prediction value refers to a value obtained by stress analysis of the in-service similar product. The in-service failure rate field estimation value refers to a value obtained by reliability evaluation based on field reliability data obtained by reliability experiment on the in-service similar product.

[0062] In one embodiment, the product to be evaluated is a certain type of circuit board, and the in-service similar product is a similar circuit board of the circuit board. Stress analysis on the similar circuit board can obtain an in-service failure rate prediction value of the similar circuit board of 45.27x10 -6 / h. By collecting field reliability data of the similar circuit board, an in-service failure rate field estimation value of 13.589x10 -6 / h is obtained by analysis. The first correction factor is a ratio of the in-service failure rate prediction value and the in-service failure rate field estimation value, i.e., the first correction factor is 0.3.

[0063] In one embodiment, when obtaining the in-service failure rate field estimation value, a certain number of similar circuit boards (e.g., 120 similar circuit boards) can be obtained by investigation to obtain reliability data. Specifically, after the 120 similar circuit boards are put into the field for a certain cumulative working time (e.g., 660 hours), one of the circuit boards fails, and the remaining circuit boards still work normally after 2400 hours of cumulative working time. The field working test time can be obtained by the following formula:

[0064]

[0065] wherein T0 represents the cumulative field working time, n represents the total number of similar circuit boards, r represents the total number of failed circuit boards, t i represents the time when the similar circuit board fails, and t0 represents the working time.

[0066] After the cumulative field working time is calculated, the in-service failure rate field estimation value can be determined. The specific formula is as follows:

[0067]

[0068] wherein λ u represents the in-service failure rate field estimation value, Chi-square distribution value when confidence level 1-α, confidence level is the probability of event occurrence, confidence level in engineering is generally 0.9, that is, the failure rate occurring under the probability of 90%.

[0069] In step S106, the similar initial reliability evaluation result is obtained based on the reliability evaluation similar data, and the difference reliability evaluation result is obtained based on the reliability evaluation difference data.

[0070] The similar initial reliability evaluation result is obtained by performing reliability prediction on the reliability evaluation similar data, for example, by processing the reliability evaluation similar data by using the stress analysis method, and the difference reliability evaluation result is obtained by processing the reliability evaluation difference data.

[0071] In step S108, the similar initial reliability evaluation result is corrected according to the first correction factor to obtain the similar target reliability evaluation result.

[0072] After the similar initial reliability evaluation result is obtained, the similar initial reliability evaluation result can be overall corrected by using the first correction factor, so as to obtain the similar target reliability evaluation result.

[0073] In step S110, the difference reliability evaluation result and the similar target reliability evaluation result are fused to obtain the reliability evaluation result of the product to be evaluated.

[0074] After the difference reliability evaluation result and the similar target reliability evaluation result are obtained, the difference reliability evaluation result and the similar target reliability evaluation result can be fused to obtain the final reliability evaluation result. Specifically, when the fusion is performed, if the difference reliability evaluation result and the similar target reliability evaluation result are both failure rates, they can be directly added, and if the difference reliability evaluation result is a failure rate and the similar target reliability evaluation result is a mean time before failure, the mean time before failure can be converted into a failure rate before being added.

[0075] In the above product reliability evaluation method, after the reliability evaluation similar data and the reliability evaluation difference data are obtained, the first correction factor corresponding to the product to be evaluated is read, so that the similar initial reliability evaluation result corresponding to the reliability evaluation similar data can be corrected according to the first correction factor to obtain the similar target reliability evaluation result, so as to improve the accuracy of the similar initial reliability evaluation result. Finally, the difference reliability evaluation result corresponding to the reliability evaluation difference data and the similar target reliability evaluation result are fused to obtain the reliability evaluation result of the product to be evaluated. Through the above method, the precision of the reliability evaluation result of the product to be evaluated can be effectively improved.

[0076] In one of the embodiments, the similar initial reliability evaluation result comprises similar initial failure rates of failure factors corresponding to similar reliability evaluation data of the product to be evaluated, wherein the failure factors can refer to constituent elements of similar parts of the product to be evaluated and the in-service similar product, for example, the similar parts are a certain type of circuit board, and the failure factors can be resistance, capacitance, and welding points, etc. For each failure factor, there is a similar initial failure rate corresponding thereto. Specifically, the stress analysis method can be used to predict the reliability of each failure factor of the product to be evaluated to obtain the similar initial failure rate corresponding to each failure factor.

[0077] In addition, after obtaining the first correction factor and the similar initial reliability evaluation result, the first correction factor can be used to correct the similar initial reliability evaluation result, as shown in Figure 2 The similar target reliability evaluation result is obtained by correcting the similar initial reliability evaluation result according to the first correction factor, and comprises:

[0078] In step S202, the product of the similar initial failure rate corresponding to each failure factor and the first correction factor is calculated to obtain a sub-entire correction result corresponding to each failure factor.

[0079] The similar initial failure rate corresponding to each failure factor can be multiplied by the first correction factor, so that the similar initial reliability evaluation result is corrected as a whole to obtain a sub-entire correction result corresponding to each failure factor. Specifically, for example, the similar initial failure rate of the resistance is 3.556*10 -6 / h, the similar initial failure rate of the capacitance is 8.558*10 -6 / h, and the first correction factor is 0.3. After multiplication, the sub-entire correction result corresponding to the resistance and the sub-entire correction result corresponding to the capacitance can be obtained.

[0080] In step S204, the sum of the sub-entire correction results is calculated to obtain an entire correction result.

[0081] The entire correction result is obtained by adding the sub-entire correction results.

[0082] In step S206, it is judged whether the entire correction result meets a preset reliability evaluation result range to obtain a preset reliability evaluation result.

[0083] The preset reliability evaluation result range is a range that the entire correction result should meet, and the preset reliability evaluation result is obtained by comparing the entire correction result with the preset reliability evaluation result range.

[0084] In step S208, the similar target reliability evaluation result is obtained according to the preset reliability evaluation result.

[0085] Finally, the similar target reliability evaluation result is obtained according to the preset reliability evaluation result.

[0086] In the embodiment, the similar initial reliability evaluation result is globally modified by the first modification factor, so that the error modification in the whole can be realized, and the precision of the reliability evaluation result is improved.

[0087] On the basis of the above embodiment, after the preset reliability evaluation result is obtained, the similar target reliability evaluation result is obtained through the preset reliability evaluation result, as shown in the following formula: Figure 3 The similar target reliability evaluation result is obtained according to the preset reliability evaluation result, and includes the following steps.

[0088] In step S302, if the preset reliability evaluation result is the global modification result satisfying the preset reliability evaluation result range, the global modification result is taken as the similar target reliability evaluation result.

[0089] If the preset reliability evaluation result is the global modification result satisfying the preset reliability evaluation result range, the global modification result is taken as the similar target reliability evaluation result, that is, the global modification result has reached the evaluation requirement at this time, and secondary modification is not needed.

[0090] In step S304, if the preset reliability evaluation result is the global modification result not satisfying the preset reliability evaluation result range, the to-be-evaluated life is determined based on the reliability evaluation similar data, and the in-service similar life is determined based on the in-service similar data of the in-service similar product.

[0091] The to-be-evaluated life refers to the life of the similar part of the to-be-evaluated product and the in-service similar product, the in-service similar life refers to the life of the in-service similar product, and the in-service similar data refers to the data of the in-service similar product itself. The to-be-evaluated life and the in-service similar life are obtained through the reliability evaluation similar data and the in-service similar data.

[0092] In step S306, the second modification factor is determined based on the ratio of the in-service failure life and the to-be-evaluated failure life.

[0093] After the in-service failure life and the to-be-evaluated failure life are obtained, the ratio of the two can be determined as the second modification factor.

[0094] In step S308, the sub-global modification result corresponding to each failure factor is locally modified according to the second modification factor, and the local modification result is obtained.

[0095] The sub-whole results corresponding to each failure factor can be modified according to the second modification factor, and specifically, all sub-whole modified results can be modified, or part of the sub-whole modified results can be modified, and how to modify can be adjusted according to actual conditions.

[0096] In step S310, the similar target reliability evaluation result is obtained based on the local modified result and the whole modified result.

[0097] In the above embodiment, when the whole modified result obtained after the first modification meets the preset reliability evaluation result range, the calculation of the second modification factor is not necessary, and unnecessary resource waste can be avoided, and when the whole modified result obtained after the first modification does not meet the preset reliability evaluation result range, the sub-whole modified results are modified by obtaining the second modification factor, so that the accuracy of the reliability evaluation result is further improved.

[0098] In one of the embodiments, the sub-whole modified result corresponding to each failure factor is locally modified according to the second modification factor to obtain a local modified result, including:

[0099] The sub-whole modified result corresponding to a weak failure factor in each failure factor is obtained, and the weak failure factor refers to a factor causing the failure of the product to be evaluated under the set experimental conditions;

[0100] The product to be evaluated and the in-service similar product are locally modified by multiplying the sub-whole modified result corresponding to the weak failure factor and the second modification factor.

[0101] In the reliability evaluation experiment of the similar part of the product to be evaluated and the in-service similar product, the causes of the failure of the similar part of the product to be evaluated and the in-service similar product can be analyzed, so that the weak part of the similar part of the product to be evaluated and the in-service similar product is determined, and the weak part is the weak failure factor. After the weak failure factor is determined, the sub-whole modified result corresponding to the weak failure factor is multiplied by the second modification factor to obtain a local modified result. Thus, the local modification of the similar part of the product to be evaluated and the in-service similar product can be realized by the above method.

[0102] In one of the embodiments, the service life of the product to be evaluated is determined based on the reliability evaluation similar data, and the in-service similar life is determined based on the in-service similar data of the in-service similar product, including:

[0103] The three-dimensional model corresponding to the reliability evaluation similar data and the three-dimensional model corresponding to the in-service similar data are obtained;

[0104] performing thermal simulation based on the three-dimensional model to be evaluated to obtain a simulation result to be evaluated, and performing vibration simulation based on the three-dimensional model in service to obtain a simulation result in service;

[0105] The simulation result to be evaluated and the simulation result in service are input into a life simulation model, and a corresponding failure life to be evaluated and a failure life in service are obtained respectively by combining a competitive failure mechanism.

[0106] The three-dimensional model to be evaluated and the three-dimensional model in service can be determined by performing potential failure mechanism analysis on similar parts of the product to be evaluated and the product in service and the failure product in service respectively, and combining industry research results.

[0107] The thermal simulation is performed on the three-dimensional model to be evaluated to obtain the simulation result to be evaluated, and the vibration simulation is performed based on the three-dimensional model in service to obtain the simulation result in service. Specifically, the environmental stress profile of the product to be evaluated and the failure product in service can be established according to the input requirements of the three-dimensional model to be evaluated and the three-dimensional model in service, the environmental stress profile is loaded, and necessary part structure, material, geometry and other model parameters are input to obtain the simulation result to be evaluated and the simulation result in service.

[0108] Finally, the simulation result to be evaluated and the simulation result in service are input into the life simulation model, the shortest failure life is taken as the failure life to be evaluated and the failure life in service corresponding to the product to be evaluated and the product in service by using the competitive failure mechanism. Optionally, to improve the analysis accuracy, the Monte Carlo sampling method can be used for life distribution fitting, and the failure life to be evaluated and the failure life in service under a specified confidence level are calculated.

[0109] In one of the embodiments, the similar target reliability evaluation result is obtained based on the local correction result and the overall correction result, including:

[0110] The sum of the sub-overall correction results corresponding to the failure factors other than the weak factor in the local correction result and the overall correction result is calculated to obtain the similar target reliability prediction result.

[0111] After the local correction result is obtained, the product of the sub-overall correction result corresponding to the weak failure factor and the second correction factor is calculated, and the sum of the sub-overall correction results corresponding to the failure factors other than the weak factor in the overall correction result is calculated to obtain the similar target reliability prediction result.

[0112] In one of the embodiments, the process of correcting the similar initial reliability evaluation result of the product to be evaluated is described by taking the target circuit board and the similar product in service as examples.

[0113] First, the reliability prediction is performed for the target circuit board to obtain the similar initial reliability evaluation result. Specifically, the target circuit board has detailed component information, product use environment, electrical stress and other similar reliability evaluation data. The stress analysis method is used to predict the reliability of the product. The environmental coefficient can be Auf in GJB / Z 299C, and the environmental temperature value can be 55℃. The component working failure rate obtained by the GJB / Z 299C stress analysis method is shown in Table 1:

[0114] Table 1

[0115]

[0116] For the similar circuit board, the similar circuit board has detailed in-service similar data. The stress analysis method can obtain the in-service failure rate prediction value of the similar circuit board as 45.27×10 -6 / h.

[0117] Secondly, the in-service failure rate field estimation value of the similar circuit board needs to be obtained. Specifically, when obtaining the in-service failure rate field estimation value, a certain number of similar circuit boards (such as 120 similar circuit boards) can be obtained by investigation. After the 120 similar circuit boards are put into the field for a certain cumulative working time (such as 660 hours), one of the circuit boards fails, and the remaining circuit boards still work normally after 2400 hours of cumulative working. The field working test time can be obtained by the following formula:

[0118]

[0119] Wherein, T0 represents the cumulative field working time, n represents the total number of similar circuit boards, r represents the total number of failed circuit boards, t i represents the time when the similar circuit board fails, and t0 represents the working time.

[0120] After the cumulative field working time is calculated, the in-service failure rate field estimation value can be determined. The specific formula is as follows:

[0121]

[0122] Wherein, λ u represents the in-service failure rate field estimation value, Chi-square distribution value when the confidence level is 1-alpha, the confidence level is the probability of event occurrence, the value of the confidence level in engineering is generally 0.9, that is, the failure rate occurring under the probability of 90%.

[0123] Therefore, the in-service failure rate prediction value of the similar circuit board is 45.27*10 -6 / h, the in-service failure rate field estimation value is 13.589*10 -6 / h, and the first correction factor is the ratio of the in-service failure rate prediction value to the in-service failure rate field estimation value, that is, the value of the first correction factor is 0.3.

[0124] After obtaining the first correction factor and the similar initial reliability evaluation result, the similar target reliability evaluation result can be obtained by correcting the similar initial reliability evaluation result according to the first correction factor, and the overall correction result of each sub-whole correction result is shown in Table 2:

[0125] Table 2

[0126]

[0127]

[0128] Among them, 10.548*10 -6 / h is the overall correction result, and the overall correction result is compared with the preset reliability evaluation result range to determine whether the preset reliability evaluation result range is met.

[0129] When the preset reliability evaluation range is not met, the target circuit board corresponding to the to-be-evaluated life and the similar circuit board corresponding to the in-service similar life can be obtained, specifically, the three-dimensional models of the similar circuit board and the target circuit board can be established, and thermal simulation and vibration simulation can be respectively implemented, and the simulation results can be input to the life simulation model, and the failure life of the similar circuit board and the target circuit board can be respectively obtained based on the competing failure mechanism, wherein the failure life of the similar circuit board is 44178h, and the failure life of the target circuit board is 58910h.

[0130] Based on the ratio of the in-service failure life to the to-be-evaluated failure life, the second correction factor can be determined, and the value of the second correction factor is 44178 / 58910=0.749.

[0131] By analyzing the failure cause of the target circuit board, it is found that the thinnest part of the target circuit board is the SMT connection between the integrated circuit and the circuit board, therefore, according to the second correction factor, the sub-whole correction result corresponding to the integrated circuit and the SMT connection is locally corrected to obtain the local correction result, and the similar target reliability evaluation result is obtained based on the local correction result and the overall correction result, as shown in Table 3.

[0132] Table 3 Local correction failure rate

[0133]

[0134]

[0135] It should be understood that, although each step in the flowchart involved in each embodiment as described above is shown in sequence according to the direction of the arrow, these steps are not necessarily executed in the order indicated by the arrow. Unless explicitly stated herein, there is no strict order limitation for the execution of these steps, and these steps can be executed in other orders. Moreover, at least part of the steps in the flowchart involved in each embodiment as described above can include multiple steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be alternately or alternately executed with at least part of other steps or steps or stages in other steps.

[0136] Based on the same inventive concept, the embodiments of the present application also provide a product reliability evaluation device for implementing the product reliability evaluation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more product reliability evaluation device embodiments provided below can refer to the limitations of the product reliability evaluation method in the above text, which will not be repeated here.

[0137] In one embodiment, as shown in Figure 4 a product reliability evaluation device is provided, comprising: a comparison module 402, a data reading module 404, a first data processing module 406, a second data processing module 408, and a reliability evaluation module 410, wherein:

[0138] The comparison module 402 is configured to compare the product to be evaluated with the similar product in service, and obtain reliability evaluation similar data and reliability evaluation difference data of the product to be evaluated and the similar product in service.

[0139] The data reading module 404 is configured to read a first correction factor corresponding to the product to be evaluated, the first correction factor being a ratio of an in-service failure rate prediction value corresponding to the similar product in service to an in-service failure rate field estimation value.

[0140] The first data processing module 406 is configured to obtain a similar initial reliability evaluation result based on the reliability evaluation similar data, and obtain a difference reliability evaluation result based on the reliability evaluation difference data.

[0141] The second data processing module 408 is configured to correct the similar initial reliability evaluation result according to the first correction factor to obtain a target reliability evaluation result.

[0142] The reliability evaluation module 410 is configured to fuse the difference reliability evaluation result and the similar target reliability evaluation result to obtain a reliability evaluation result of the product to be evaluated.

[0143] In one of the embodiments, the comparison module is configured to acquire product attribute information of the product to be evaluated and similar product attribute information of the similar in-service product; compare the product attribute information and the similar product attribute information based on a similarity judgment principle to obtain a similarity judgment result; and acquire reliability evaluation similar data and reliability evaluation difference data of the product to be evaluated and the similar in-service product based on the similarity judgment result.

[0144] In one of the embodiments, the first data processing module is configured to calculate a product of the similar initial failure rate corresponding to each failure factor and the first correction factor to obtain a sub-whole correction result corresponding to each failure factor; calculate a sum of the sub-whole correction results to obtain a whole correction result; judge whether the whole correction result meets a preset reliability evaluation result range to obtain a preset reliability evaluation result; and obtain the similar target reliability evaluation result according to the preset reliability evaluation result, wherein the similar initial reliability evaluation result includes the similar initial failure rate corresponding to each failure factor in the reliability evaluation similar data.

[0145] In one of the embodiments, the first data processing module is configured to, if the preset reliability evaluation result is that the whole correction result meets the preset reliability evaluation result range, take the whole correction result as the similar target reliability evaluation result; if the preset reliability evaluation result is that the whole correction result does not meet the preset reliability evaluation result range, determine a to-be-evaluated life based on the reliability evaluation similar data and determine an in-service similar life based on in-service similar data of the similar in-service product; determine a second correction factor based on a ratio of the in-service failure life to the to-be-evaluated failure life; perform local correction on the sub-whole correction result corresponding to each failure factor according to the second correction factor to obtain a local correction result; and obtain the similar target reliability evaluation result based on the local correction result and the whole correction result.

[0146] In one of the embodiments, the first data processing module is configured to acquire a sub-whole correction result corresponding to a weak failure factor in each failure factor, wherein the weak failure factor refers to a factor causing a fault of the product to be evaluated under a set experimental condition; and calculate a product of the sub-whole correction result corresponding to the weak failure factor and the second correction factor to obtain the local correction result.

[0147] In one of the embodiments, the first data processing module is configured to acquire a to-be-evaluated three-dimensional model corresponding to the reliability evaluation similar data and an in-service similar three-dimensional model corresponding to the in-service similar data, perform thermal simulation based on the to-be-evaluated three-dimensional model to obtain a to-be-evaluated simulation result, and perform vibration simulation based on the in-service similar three-dimensional model to obtain an in-service similar simulation result; input the to-be-evaluated simulation result and the in-service similar simulation result into a life simulation model respectively, and obtain a to-be-evaluated failure life and an in-service failure life respectively by combining a competitive failure mechanism.

[0148] In one of the embodiments, the first data processing module is configured to calculate a sum of sub-entire correction results corresponding to failure factors other than the weak factor in the local correction result and the entire correction result, and obtain a similar target reliability prediction result.

[0149] The above modules in the product reliability evaluation device can be realized by software, hardware, or a combination thereof. The above modules can be embedded in or independent of a processor in a computer device in hardware form, or stored in a memory in the computer device in software form, so as to be called and executed by the processor to perform operations corresponding to the above modules.

[0150] In one embodiment, a computer device is provided, which can be a terminal, and an internal structure diagram thereof can be as shown in FIG. 8. Figure 5 The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is configured to perform wired or wireless communication with an external terminal. The wireless communication can be achieved through WIFI, mobile cellular network, NFC (near field communication), or other technologies. The computer program is executed by the processor to implement a product reliability evaluation method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball, or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0151] Those skilled in the art can understand that Figure 5 The structure shown in FIG. 8 is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0152] In one embodiment, a computer device is provided, comprising a memory and a processor, the memory has stored therein a computer program, the processor implements the steps of the product reliability evaluation method described above when executing the computer program.

[0153] In one embodiment, a computer readable storage medium is provided, having stored thereon a computer program, the computer program is executed by a processor to implement the steps of the product reliability evaluation method described above.

[0154] In one embodiment, a computer program product is provided, comprising a computer program, the computer program is executed by a processor to implement the steps of the product reliability evaluation method described above.

[0155] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties.

[0156] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric memory (Ferroelectric Random Access Memory, FRAM), phase change memory (Phase Change Memory, PCM), graphene memory, etc. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0157] Any combination of the technical features of the above embodiments can be made. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0158] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent of the present application. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of protection of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A product reliability assessment method, characterized in that, The method includes: Compare the product to be evaluated with similar products in service to obtain reliability assessment similarity data and reliability assessment difference data between the product to be evaluated and similar products in service. Read the first correction factor corresponding to the product to be evaluated. The first correction factor is the ratio of the expected value of the in-service failure rate to the field estimate of the in-service failure rate corresponding to the similar in-service product. Based on the reliability assessment similarity data, obtain similar initial reliability assessment results, and based on the reliability assessment difference data, obtain differential reliability assessment results; The similar initial reliability assessment result includes the similar initial failure rate corresponding to each failure factor in the similar reliability assessment data; the similar initial reliability assessment result is corrected according to the first correction factor to obtain the similar target reliability assessment result; wherein: The step of correcting the initial reliability assessment result based on the first correction factor to obtain the reliability assessment result of the similar target includes: Calculate the product of the similar initial failure rate corresponding to each failure factor and the first correction factor to obtain the sub-global correction result corresponding to each failure factor; The sum of the sub-global correction results is calculated to obtain the overall correction result; Determine whether the overall correction result meets the preset reliability assessment result range, and obtain the preset reliability assessment result; Based on the preset reliability assessment results, the reliability assessment results of similar targets are obtained; wherein: If the preset reliability assessment result is such that the overall correction result meets the preset reliability assessment result range, the overall correction result will be used as the reliability assessment result of the similar target; If the preset reliability assessment result indicates that the overall correction result does not meet the preset reliability assessment result range, the lifespan to be assessed is determined based on the reliability assessment similarity data, and the similar service lifespan is determined based on the similar service data of similar in-service products; wherein... By analyzing the potential failure mechanisms of the product to be evaluated and similar in-service products, as well as the in-service failed products, and combining industry research results, the three-dimensional model to be evaluated and the in-service similar three-dimensional model corresponding to the reliability assessment similar data are obtained. Based on the input requirements of the three-dimensional model to be evaluated and the in-service similar three-dimensional model, environmental stress profiles of the product to be evaluated and the in-service failed product are established, the environmental stress profiles are loaded, and the model parameters of the part structure, material and geometry are input. Thermal simulation is performed on the three-dimensional model to be evaluated to obtain the simulation results, and vibration simulation is performed based on the in-service similar three-dimensional model to obtain the in-service similar simulation results. The simulation results to be evaluated and the in-service similar simulation results are respectively input into the life simulation model. Combined with the competitive failure mechanism, the shortest failure life is taken as the failure life to be evaluated and the in-service failure life corresponding to the product to be evaluated and the similar in-service product. The life distribution is fitted by Monte Carlo sampling and the failure life to be evaluated and the in-service failure life under the specified confidence level are calculated. A second correction factor is determined based on the ratio of the in-service failure life to the failure life to be evaluated; Based on the second correction factor, the sub-global correction results corresponding to each failure factor are locally corrected to obtain local correction results. Based on the local correction results and the overall correction results, the reliability assessment results of similar targets are obtained; The reliability assessment results of the differential targets and the reliability assessment results of the similar targets are fused together to obtain the reliability assessment results of the product to be evaluated.

2. The method according to claim 1, characterized in that, The comparison of the product to be evaluated with similar in-service products, and the acquisition of reliability assessment similarity data and reliability assessment difference data between the product to be evaluated and similar in-service products, includes: Obtain the product attribute information of the product to be evaluated and the similar product attribute information of the similar products in service; Based on the similarity judgment principle, the similarity judgment result is obtained by comparing the attribute information of the product to be evaluated with the attribute information of similar products. Based on the similarity judgment results, reliability assessment similarity data and reliability assessment difference data between the product to be evaluated and similar products in service are obtained.

3. The method according to claim 1, characterized in that, The step of performing local correction on the sub-global correction results corresponding to each failure factor according to the second correction factor to obtain local correction results includes: Obtain the sub-global correction result corresponding to the weak failure factor among all the failure factors, wherein the weak failure factor refers to the factor among the failure factors that causes the failure of the product to be evaluated under the set experimental conditions; The product of the sub-global correction result corresponding to the weak failure factor and the second correction factor is calculated to obtain the local correction result.

4. The method according to claim 1, characterized in that, The process of obtaining the reliability assessment results for similar targets based on the local correction results and the overall correction results includes: The sum of the sub-global correction results corresponding to failure factors other than weak factors in the local correction results and the overall correction results is calculated to obtain the reliability prediction results of the similar targets.

5. A product reliability assessment device, characterized in that, The apparatus comprising, when using the method according to any one of claims 1-4, includes: The comparison module is used to compare the product to be evaluated with similar products in service, and to obtain reliability assessment similarity data and reliability assessment difference data between the product to be evaluated and similar products in service. The data reading module is used to read the first correction factor corresponding to the product to be evaluated. The first correction factor is the ratio of the expected value of the in-service failure rate to the field estimate of the in-service failure rate corresponding to the similar in-service product. The first data processing module is used to obtain similar initial reliability assessment results based on the reliability assessment similar data, and to obtain differential reliability assessment results based on the reliability assessment difference data. The second data processing module is used to correct the similar initial reliability assessment result according to the first correction factor to obtain the similar target reliability assessment result. The reliability assessment module is used to fuse the differential reliability assessment results and the similar target reliability assessment results to obtain the reliability assessment result of the product to be evaluated.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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