Additive part durability evaluation method, device, equipment, medium and program

Abstract

The invention discloses an additive part durability evaluation method, device and equipment, a medium and a program. The method comprises the steps that a target part is printed into a durability limit evaluation sample, and a basic sample is obtained through heat treatment and linear cutting; dividing the basic sample into a reference group and at least two experimental groups to obtain a reference sample and a contrast sample group; performing a rotary bending fatigue test on each reference sample and each contrast sample to obtain fatigue limit data under different processes; calculating a surface durability limit reduction coefficient of the experimental group by taking the fatigue limit of the reference group as a reference; and substituting the surface durability limit reduction coefficient as a fatigue limit correction factor into a safety margin calculation formula, and evaluating whether the fatigue durability meets the design requirements or not according to the safety margin. According to the embodiment of the invention, the influence of different surface processes on the fatigue performance is quantified through contrast tests, and the actual working condition is associated with the safety margin, so that a reliable basis is provided for additive part surface process screening, and the part failure risk is reduced.

Description

Technical Field

[0001] This invention relates to the field of additive manufacturing technology, and in particular to methods, apparatus, equipment, media and procedures for evaluating the durability of additively manufactured parts. Background Technology

[0002] Laser additive manufacturing (LAM) is an advanced manufacturing technology based on the discrete-stacking principle. It uses high-energy heat sources such as lasers or electron beams to melt and solidify metal powder layer by layer, directly forming complex metal parts. This technology has shown significant advantages in manufacturing complex structural parts in fields such as aerospace due to its mold-free nature and high design freedom. However, due to the layer-by-layer forming characteristic of this technology, the surface quality of the manufactured parts is often difficult to match the level of traditional forgings or machined parts. Furthermore, for features with overhanging structures, the difference in heat dissipation conditions between the upper and lower surfaces makes them more prone to macroscopic defects such as powder adhesion and spheroidization, as well as metallurgical defects such as porosity and lack of fusion.

[0003] Although surface finishing is widely used to improve the surface quality of additive manufacturing parts and thus enhance their fatigue performance, the axial fatigue testing methods commonly used in engineering have significant limitations. The fatigue performance obtained by this method is the result of the combined effects of internal and surface defects, failing to effectively isolate and quantify the individual impact of surface defects on fatigue performance, particularly durability limits. Therefore, it is difficult to accurately assess the actual effectiveness of different surface finishing processes in improving the fatigue performance of additive manufacturing parts, and it also cannot provide quantitative data support and design basis for selecting manufacturing processes focused on fatigue life. Summary of the Invention

[0004] Based on this, the present invention provides a method, apparatus, equipment, medium and procedure for evaluating the durability of additive manufacturing parts, in order to solve the problem that traditional axial fatigue testing cannot separate the influence of surface defects.

[0005] In a first aspect, embodiments of the present invention provide a method for evaluating the durability of additively manufactured parts, including:

[0006] According to the design requirements of the additive manufacturing part drawings, the target part is printed with a durability limit evaluation sample using laser additive manufacturing technology, and the durability limit evaluation sample is subjected to heat treatment and wire cutting to obtain a base sample separated from the forming substrate.

[0007] The basic sample is divided into a reference group and at least two experimental groups. A uniform full-machine process is performed on the reference group to obtain reference samples with consistent surface conditions. A specific non-machine process is performed on each experimental group to form a control sample group with different surface conditions.

[0008] Rotational bending fatigue tests were conducted on each reference specimen in the reference group and each control specimen in the experimental group to obtain fatigue limit data of each specimen under different processes.

[0009] Based on the fatigue limit data, and taking the fatigue limit of the benchmark group as the benchmark, the surface durability limit reduction factor of the experimental group is calculated.

[0010] The surface durability limit reduction factor is used as the fatigue limit correction factor and substituted into the safety margin calculation formula to calculate the safety margin of the additively manufactured part under the target load condition after non-machining process, and the fatigue durability performance is evaluated based on the safety margin to determine whether it meets the design requirements.

[0011] Secondly, embodiments of the present invention also provide an additive manufacturing part surface durability performance evaluation device, comprising:

[0012] The basic sample acquisition module is used to print a durability limit evaluation sample for the target part using laser additive manufacturing technology according to the design requirements of the additive manufacturing part drawing, and to perform heat treatment and wire cutting on the durability limit evaluation sample to obtain a basic sample separated from the forming substrate.

[0013] The sample processing module is used to divide the basic sample into a reference group and at least two experimental groups, perform a uniform full-machine processing process on the reference group to obtain reference samples with consistent surface conditions, and perform specific non-machine processing processes on each experimental group to form control sample groups with different surface conditions.

[0014] The fatigue testing module is used to perform rotational bending fatigue tests on each reference specimen in the reference group and each control specimen in the experimental group to obtain fatigue limit data of each specimen under different processes.

[0015] The reduction factor calculation module is used to calculate the surface durability limit reduction factor of the experimental group based on the fatigue limit data and with the fatigue limit of the benchmark group as the benchmark.

[0016] The durability performance evaluation module is used to substitute the surface durability limit reduction factor as the fatigue limit correction factor into the safety margin calculation formula, calculate the safety margin of the additively manufactured part after non-machining process under the target load condition, and evaluate whether its fatigue durability performance meets the design requirements based on the safety margin.

[0017] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising:

[0018] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform an additive manufacturing surface durability performance evaluation method according to any embodiment of the present invention.

[0019] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions, which are used to cause a processor to execute and implement the additive manufacturing part surface durability evaluation method described in any embodiment of the present invention.

[0020] This invention, through a benchmark-experimental group comparative design, combined with rotational bending fatigue testing and surface durability limit reduction factor calculation, transforms the influence of different surface processes on fatigue performance into quantifiable parameters, avoiding biases in subjective evaluation. Based on the safety margin calculation using the reduction factor, it directly correlates with actual load conditions, clarifying whether the fatigue durability performance of parts treated by various non-machining finishing processes meets the standards, providing an intuitive and reliable basis for screening additive manufacturing surface processes. From sample preparation to safety margin evaluation, the entire process is anchored to the design requirements and service conditions of the target part, avoiding the disconnect between laboratory data and actual applications, and effectively reducing the risk of part failure due to insufficient process adaptability.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a method for evaluating the surface durability of additive manufacturing parts according to Embodiment 1 of the present invention;

[0024] Figure 2 This is a flowchart of another method for evaluating the surface durability of additive manufacturing parts according to Embodiment 2 of the present invention;

[0025] Figure 3 This is a schematic diagram of the structure of an additive manufacturing part surface durability performance evaluation device provided in Embodiment 3 of the present invention;

[0026] Figure 4 This is a schematic diagram of the structure of an electronic device that implements a method for evaluating the surface durability of additive parts according to an embodiment of the present invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] Example 1

[0030] Figure 1 This is a flowchart of a method for evaluating the surface durability of additive manufacturing parts according to Embodiment 1 of the present invention. This embodiment is applicable to situations where fatigue limit data of samples under different processes are obtained through rotary bending fatigue testing to quantitatively compare and evaluate the impact of each process on the fatigue performance of the samples. This method can be executed by an additive manufacturing part surface durability evaluation device, which can be implemented in hardware and / or software and can be configured in a rotary bending fatigue testing machine. Figure 1 As shown, the method includes:

[0031] S110. According to the design requirements of the additive manufacturing part drawing, a durability limit evaluation sample is printed on the target part using laser additive manufacturing technology, and the durability limit evaluation sample is heat-treated and wire-cut to obtain a base sample separated from the forming substrate.

[0032] This invention aims to establish a standardized method for quantitatively evaluating the surface treatment process effects of metal additive manufacturing parts. Its core is to quantify the impact of surface condition on fatigue performance into a set of engineering-usable parameters through scientific comparative experimental design. Specifically: First, the sample preparation stage strictly simulates the actual part manufacturing process. Based on the target part's drawing requirements, laser additive manufacturing technology is used to form the sample, ensuring it has the same metallurgical structure and initial defect characteristics as the real part. After forming, the sample undergoes specialized heat treatment to eliminate residual stress, preventing deformation or data distortion due to stress release during subsequent processing or testing. Finally, wire cutting, a cold process, is used to precisely separate the sample from the substrate, thereby obtaining a batch of representative basic samples with consistent initial states.

[0033] S120. Divide the basic sample into a reference group and at least two experimental groups. Perform a uniform full-machine processing process on the reference group to obtain reference samples with consistent surface conditions. Perform specific non-machine processing processes on each experimental group to form control sample groups with different surface conditions.

[0034] The samples were randomly divided into multiple groups. A benchmark group underwent full machining (such as precision grinding and polishing) to achieve a near-ideal smooth surface. The test results of this group represent the upper limit of fatigue performance achievable by the material under the current internal mass. The experimental groups underwent different non-machining surface treatments (such as sandblasting and electropolishing). Each process altered the surface morphology, introduced residual stress, or reduced defects in different ways, resulting in one benchmark group and multiple experimental groups with varying surface conditions, each corresponding to a specific treatment process.

[0035] S130. Perform rotational bending fatigue tests on each reference specimen in the reference group and each control specimen in the experimental group to obtain fatigue limit data of each specimen under different processes.

[0036] The reason this invention chose the rotational bending fatigue test is that during rotation, the stress on the sample surface is the greatest, decreasing towards the core. This stress distribution characteristic ensures that fatigue cracks inevitably initiate at surface defects. Therefore, the test results can extremely sensitively reflect the quality of different surface conditions, effectively shielding the interference of internal defects and accurately characterizing the true effects of different surface treatment processes. The lifting method is used to efficiently and accurately measure the fatigue limit of the material with fewer samples, obtaining precise fatigue limit data for each group of samples. These data directly reflect the influence of different surface treatment processes on fatigue performance.

[0037] S140. Based on the fatigue limit data, and taking the fatigue limit of the benchmark group as the benchmark, calculate the surface durability limit reduction factor of the experimental group.

[0038] The significance of calculating the surface durability limit reduction factor lies in the fact that it no longer focuses on the absolute value of the fatigue limit, but rather on the performance retention rate relative to the ideal state. For example, a Factor value of 0.9 for a certain process group means that after this process, the fatigue performance of the material reaches 90% of its ideal surface state. This factor purely and quantitatively expresses the efficiency of a certain surface treatment process.

[0039] S150. Substitute the surface durability limit reduction factor as the fatigue limit correction factor into the safety margin calculation formula to calculate the safety margin of the additively manufactured part under the target load condition after non-machining process, and evaluate whether its fatigue durability performance meets the design requirements based on the safety margin.

[0040] The reduction factor is substituted into the safety margin formula as a correction factor to correct the reference fatigue limit (to obtain the actual usable fatigue limit under the corresponding process). Then, combined with the actual stress under the target load, the safety margin is calculated. By comparing the safety margin with the threshold, it is finally determined whether the non-machining process can make the part meet the fatigue durability requirements under actual working conditions. This embodiment completes the implementation from sample testing to actual application of the part, and achieves the ultimate goal of the evaluation method.

[0041] This invention, through a benchmark-experimental group comparative design, combined with rotational bending fatigue testing and surface durability limit reduction factor calculation, transforms the influence of different surface processes on fatigue performance into quantifiable parameters, avoiding biases in subjective evaluation. Based on the safety margin calculation using the reduction factor, it directly correlates with actual load conditions, clarifying whether the fatigue durability performance of parts treated by various non-machining finishing processes meets the standards, providing an intuitive and reliable basis for screening additive manufacturing surface processes. From sample preparation to safety margin evaluation, the entire process is anchored to the design requirements and service conditions of the target part, avoiding the disconnect between laboratory data and actual applications, and effectively reducing the risk of part failure due to insufficient process adaptability.

[0042] Optionally, the basic sample is divided into a reference group and at least two experimental groups. A uniform full-machining process is performed on the reference group to obtain reference samples with consistent surface conditions. Specific non-machining processes are performed on each experimental group to form control sample groups with different surface conditions. This may include:

[0043] A unique reference group is formed by selecting quantitative samples from the basic samples and performing a uniform full-machine process on all basic samples in the reference group to obtain at least one reference sample with a consistent surface finish.

[0044] Quantitative samples were selected from the remaining basic samples to form at least two experimental groups. A specific non-machining process was performed on each experimental group to form multiple control samples with different surface states. The non-machining processes used in different experimental groups were selected from at least one of the following: process type, process parameters, or process combination sequence.

[0045] From the initial prepared basic samples, a unique benchmark group was selected, with quantitative samples chosen to ensure the statistical reliability of subsequent experimental data, and uniqueness to establish a unified performance reference standard. Subsequently, all basic samples within the benchmark group underwent a completely uniform machining process: the sequence of operations from rough turning and finish turning to grinding was consistent, and the tools and cutting parameters used were also identical. The core purpose of this was to eliminate machining differences and ultimately obtain at least one benchmark sample with consistent surface roughness, surface residual stress, and microstructure. The consistency of its surface state directly determines the scientific validity of subsequent comparisons.

[0046] First, select quantitative samples from the remaining basic samples and form at least two experimental groups according to the experimental requirements, ensuring that the number of samples in each experimental group also meets the data statistical requirements. Then, perform a specific non-machining process on each experimental group: for example, experimental group A uses shot peening, experimental group B uses electrochemical polishing, or experimental groups A and B both use shot peening, but with different parameters such as shot intensity and shot material. The key is that the non-machining processes used in different experimental groups must have clear differences. These differences can come from at least one of the following: process type, process parameters, or process combination sequence. Through this differentiated treatment, multiple control samples with different surface states are ultimately formed.

[0047] Furthermore, substituting the surface durability limit reduction factor as a fatigue limit correction factor into the safety margin calculation formula, the safety margin of the additively manufactured part processed by non-machining technology under the target load condition is calculated, and the fatigue durability performance is evaluated based on the safety margin to determine whether it meets the design requirements. This may include:

[0048] Extract structural dimensional parameters for stress calculation from the design drawings of additively manufactured parts, extract cyclic load parameters from the technical documents that match the target parts, and extract the allowable stress of the target parts under the target load conditions;

[0049] A stress calculation model is constructed based on the structural dimension parameters, and the cyclic load parameters are applied to the stress calculation model as loading conditions. Through stress analysis and calculation, the actual working stress amplitude of the target part under the target load condition is obtained.

[0050] The first type of fatigue limit value of the benchmark group is extracted as the basic fatigue limit value;

[0051] Based on the set of surface durability limit reduction coefficients, the surface durability limit reduction coefficient of each experimental group is multiplied by the basic fatigue limit value to obtain the processed corrected fatigue limit value.

[0052] Substitute the actual working stress amplitude and the corrected fatigue limit value into the preset safety margin calculation formula to obtain the safety margin of the part under the process treatment corresponding to the current experimental group.

[0053] The safety margin corresponding to each non-machining finishing process is compared with the preset qualified threshold. If the safety margin is not less than the qualified threshold, the fatigue durability performance of the part processed by the process is determined to meet the design requirements; otherwise, it is determined not to meet the requirements.

[0054] First, it is necessary to accurately obtain the structural dimensional parameters used for stress calculation from the design drawings of the additively manufactured part, such as the cross-sectional dimensions and geometric contours of the key stress-bearing parts of the part. These parameters form the basis for subsequent stress model construction. Simultaneously, cyclic load parameters, such as the magnitude, direction, and frequency of the cyclic load, must be extracted from the technical documents accompanying the target part (e.g., load specifications, operating condition descriptions). These parameters directly relate to the actual stress state of the part. Furthermore, the allowable stress of the target part under the target load condition must also be obtained simultaneously. This value represents the minimum standard for the part's safe load-bearing capacity and is predetermined by the design specifications or technical documents. These three factors together constitute the basic data pool for subsequent calculations, ensuring that the entire evaluation process begins with the actual design and operating condition requirements of the part.

[0055] Based on the extracted structural dimensional parameters, a stress calculation model is constructed using finite element modeling or analytical calculations to fully reproduce the geometric features and stress paths of the part. Then, the extracted cyclic load parameters are applied to the model according to actual working conditions, such as applying cyclic forces of corresponding magnitude and direction at specific locations on the model. Finally, the actual working stress amplitude of the target part under the target load condition is obtained through stress analysis software or theoretical calculations. Combining the set of surface durability limit reduction factors, the surface durability limit reduction factor for each experimental group is multiplied by the basic fatigue limit value established in the third step: for example, if the reduction factor for a certain process is 0.85 and the basic fatigue limit value is 300 MPa, then the corresponding corrected fatigue limit value for that process is 255 MPa. The essence of this step is to scale the baseline performance using reduction factors, ultimately obtaining the actual fatigue limit achievable by each non-machining process, thus concretizing the impact of the process on performance into specific numerical values.

[0056] The actual working stress amplitude and the corresponding modified fatigue limit value of the process are substituted into a preset safety margin calculation formula. The formula quantifies the safety redundancy between the fatigue performance provided by the process and the actual stress on the part through the ratio of the two values. For example, if the modified fatigue limit value is 255 MPa and the actual working stress amplitude is 200 MPa, the safety margin calculated by the formula directly reflects the performance margin of the part under that process. The safety margins corresponding to each non-machining process are compared one by one with preset acceptance thresholds: if the safety margin of a process is not less than the threshold, it means that under that process, the fatigue durability of the part can withstand the target load condition and meets the design requirements; conversely, if the safety margin is lower than the threshold, it indicates that the process cannot provide sufficient performance assurance for the part and is judged as unacceptable. This step directly outputs the process screening results, providing clear guidance for process selection in actual production.

[0057] Optionally, the preset safety margin calculation formula is as follows:

[0058]

[0059] in, For safety margin, The actual working stress amplitude, This is the surface durability limit reduction factor corresponding to non-machining finishing processes. Allowable stress.

[0060] This refers to the degree of safety redundancy of the fatigue performance of a part under target working conditions after non-machining processes. The higher the value, the safer it is. This refers to the fluctuation range of cyclic stress in key parts of a component under target load conditions, reflecting the severity of the actual stress. This reflects the impact of non-machining processes on the surface durability limit of parts; the smaller the coefficient, the more significant the reduction. The maximum stress that a part can withstand under target operating conditions, as specified in the design phase, is the benchmark threshold for safety performance.

[0061] The essence of this embodiment is to calculate the safety margin by using the ratio of the corrected fatigue limit to the actual stress. First, calculate... After reduction by non-machining finishing processes, the allowable stress that the material can actually rely on is obtained; then divided by the actual working stress amplitude. The ratio of the corrected target reference stress to the actual stress is obtained, reflecting the relative magnitude of the two. Finally, the ratio is converted into a quantitative value of the safety margin MS.

[0062] Example 2

[0063] Figure 2 This is a flowchart of another method for evaluating the surface durability of additively manufactured parts according to Embodiment 2 of the present invention. This embodiment is a refinement based on Embodiment 1. Specifically, as follows... Figure 2 As shown, the method includes:

[0064] S210. According to the design requirements of the additive manufacturing part drawing, a durability limit evaluation sample is printed on the target part using laser additive manufacturing technology, and the durability limit evaluation sample is heat-treated and wire-cut to obtain a base sample separated from the forming substrate.

[0065] S220. Divide the basic sample into a reference group and at least two experimental groups. Perform a uniform full-machine processing process on the reference group to obtain reference samples with consistent surface conditions. Perform specific non-machine processing processes on each experimental group to form control sample groups with different surface conditions.

[0066] S230. According to the preset cycle base, rotational bending fatigue tests are carried out on all reference specimens in the reference group and all control specimens in the experimental group one by one. Cyclic stress is applied according to the unified loading specification during the test.

[0067] Cyclic stress refers to a load form in which the stress amplitude and direction change periodically over time. In rotational bending fatigue testing, the specimen's surface material is subjected to alternating tensile and compressive stresses due to rotational motion. This loading method can simulate the service conditions of typical additive manufacturing parts such as shaft components, ensuring the consistency between the test load and the actual stress state. Loading specifications directly affect the initiation and propagation rate of fatigue cracks in the material. For example, high-frequency loading may lead to accumulated temperature rise on the material surface, altering its microscopic damage mechanism; different stress ratios will affect the contribution of the average stress level to fatigue life. A unified specification can lock the process type as a unique variable, avoiding the dispersion of test data caused by differences in loading conditions, and laying a reliable foundation for subsequent process comparisons. The cycle count is usually set according to industry standards as a "life threshold" for fatigue limit determination. When a specimen is loaded to this number of cycles and still does not fail, it can be considered to have infinite life characteristics at the corresponding stress level. This setting avoids the indefinite extension of the test cycle and provides a unified assessment endpoint for the fatigue performance of different processes.

[0068] S240. If the target reference specimen or target control specimen breaks or cracks of not less than a preset size appear on its surface during loading, the target specimen is determined to be a failure, and the number of failure cycles of the target specimen under the matched loading stress is recorded.

[0069] Using fracture or surface crack size ≥ a preset threshold as the failure criterion is essentially a design based on the progressive characteristics of fatigue failure. Actual component failure often involves the entire process of "crack initiation-propagation-fracture," and using only fracture as the criterion would miss crucial performance information during the crack propagation stage. Preset crack size can accurately capture the early damage state after crack initiation, more comprehensively reflecting the impact of the process on the material's surface resistance to crack initiation.

[0070] Recording the applied stress value and the number of failure cycles allows for the acquisition of fatigue life data under different stress levels, forming a scatter plot of "stress-failure life". Recording the "applied stress of the unfailed specimen + cycle count" supplements the critical data for "stress-safe life". When failure is determined, the "matching applied stress" and "number of failure cycles" must be recorded. These two sets of data are directly related to the stress level and the bearing capacity of the process specimen, and are the basic raw data for subsequent fatigue limit calculations.

[0071] S250. If the target reference specimen or target control specimen does not break or develop a crack of not less than the preset size when loaded to the preset cycle number, the target specimen is deemed not to have failed, and the loading stress and preset cycle number matching the target specimen are recorded.

[0072] The condition for determining that the sample has not failed is that "no fracture or excessive cracks occur when loaded to the preset cycle base number". This means that the sample can reach the preset life requirement under the loading stress. At this time, the "loading stress" and "preset cycle base number" need to be recorded. This set of data can reflect the safe load-bearing capacity of the process sample under specific stress. Combined with failure data, the performance range of different process samples in the "stress-life" relationship can be completely determined.

[0073] S260. Summarize the loading stress values, failure cycles, and preset cycle base of all reference specimens in the reference group, and determine the first type of fatigue limit value of the reference group through statistical analysis.

[0074] Summarizing data from all reference specimens is a prerequisite, requiring the collection of information such as loading stress, failure cycle count, and cycle count before failure for all specimens in the group. Statistical analysis is the key method. Due to the dispersion in performance of specimens from the same process, methods such as the rise-fall method and the group method are needed to process the data and eliminate the influence of individual differences. The final obtained Type I fatigue limit value is a quantitative representation of the fatigue performance of specimens under fully machined processes and will serve as a reference benchmark for subsequent evaluation of non-machined processes.

[0075] S270. Using the same statistical analysis method, summarize the loading stress value, failure cycle number and preset cycle base of all control samples in each experimental group, determine the second type of fatigue limit value of each experimental group, and obtain the fatigue limit data of each sample under different processes.

[0076] Using the same statistical analysis methods ensured data comparability and avoided result bias due to different methods. Data from each experimental group were summarized separately, and the second type of fatigue limit value was determined, allowing for the quantification of fatigue performance under different non-machining processes. Comparing the second type of fatigue limit value of each experimental group with the first type of fatigue limit value of the benchmark group directly revealed the impact of the process on fatigue performance. Obtaining fatigue limit data for each sample under different processes provided a quantitative basis for subsequent process evaluation.

[0077] S280. Separate the first type of fatigue limit value from the fatigue limit data and use it as the calculation benchmark value.

[0078] The benchmark group employs a fully machined process, ensuring a high degree of consistency in the surface condition of its samples after uniform processing. Statistical analysis is then used to process the data. For example, the incremental method determines the stress value corresponding to a 50% failure probability by gradually adjusting the stress level; the group method fits stress-life curves to life data under multiple stress levels, extrapolates to the stress value corresponding to the cycle base, and finally obtains the first type of fatigue limit value, which serves as the fatigue performance benchmark under the fully machined process, providing a reference standard for the performance evaluation of non-machined processes.

[0079] Each experimental group must use the same statistical methods as the baseline group to ensure data comparability. The calculated Type II fatigue limit value can directly quantify the impact of specific non-machining processes on fatigue performance: if its value is higher than the Type I fatigue limit, it indicates that the process has a surface strengthening effect; if its value is lower than the Type I fatigue limit, it indicates that the process may have surface damage.

[0080] S290. Select the target second type fatigue limit value of the current experimental group, and divide the target second type fatigue limit value by the first type fatigue limit value of the benchmark group. Use the quotient as the surface durability limit reduction factor corresponding to the current experimental group and record it.

[0081] The second type of fatigue limit value of the experimental group directly reflects the fatigue performance of the specimens after a specific non-machining process. The calculation of "second type value ÷ first type value" essentially transforms the difference in fatigue performance between this process and the benchmark process into a dimensionless coefficient: if the coefficient = 1, it indicates that the fatigue performance of this process is equivalent to that of a fully machined process; if the coefficient > 1, it indicates that the process has a strengthening effect on fatigue performance; if the coefficient < 1, it means that the process reduces fatigue performance. This coefficient directly quantifies the degree of influence of the process on the surface durability limit, providing crucial process correction parameters for subsequent safety margin calculations.

[0082] S2100, Repeat the operation of selecting the experimental group and dividing it with the first type of fatigue limit value until the calculation of all experimental groups is completed, summarize the quotient values ​​of all records, and form a set of surface durability limit reduction coefficients corresponding to all non-machining processes.

[0083] Different experimental groups correspond to different non-machining processes. By repeating the above division operation, the reduction coefficient for each process can be obtained, ultimately forming a complete dataset of "all non-machining processes - reduction coefficients". The value of this dataset lies in its ability to directly compare the performance impact of different processes horizontally; it provides systematic data support for subsequent "process-safety margin" correlation analysis. By substituting each coefficient in the dataset into the safety margin formula, it is possible to determine whether the corresponding process meets the design requirements, thus realizing the implementation from performance quantification to process selection.

[0084] S2110. Substitute the surface durability limit reduction factor as the fatigue limit correction factor into the safety margin calculation formula to calculate the safety margin of the additively manufactured part under the target load condition after non-machining process, and evaluate whether its fatigue durability performance meets the design requirements based on the safety margin.

[0085] In this invention, firstly, through the logic of "benchmark anchoring - single-group quantification - full-group summarization," the complex influence of non-machining processes on fatigue performance is transformed into an intuitive and comparable set of reduction factors. This serves as a crucial bridge connecting fatigue test data with the evaluation of actual process applications, providing a quantitative basis for the scientific selection of additive manufacturing part surface processes. Secondly, through the logical closed loop of "standardized loading - boundary data capture - quantitative statistical analysis," the influence of processes on surface conditions is transformed into directly applicable fatigue limit data. This provides core technical support for subsequent calculation of surface durability limit reduction factors and evaluation of process suitability, and is a key step in shifting additive manufacturing part process selection from experience-based judgment to data-driven approaches.

[0086] Example 3

[0087] Figure 3 This is a schematic diagram of a device for evaluating the surface durability of additively manufactured parts according to Embodiment 3 of the present invention. Figure 3 As shown, the device includes:

[0088] The basic sample acquisition module 310 is used to print a durability limit evaluation sample for the target part using laser additive manufacturing technology according to the design requirements of the additive manufacturing part drawing, and to perform heat treatment and wire cutting on the durability limit evaluation sample to obtain a basic sample separated from the forming substrate.

[0089] The sample processing module 320 is used to divide the basic sample into a reference group and at least two experimental groups, perform a uniform full-machine processing process on the reference group to obtain reference samples with consistent surface conditions, and perform specific non-machine processing processes on each experimental group to form control sample groups with different surface conditions.

[0090] The fatigue test module 330 is used to perform rotational bending fatigue tests on each reference specimen in the reference group and each control specimen in the experimental group to obtain fatigue limit data of each specimen under different processes.

[0091] The reduction factor calculation module 340 is used to calculate the surface durability limit reduction factor of the experimental group based on the fatigue limit data and with the fatigue limit of the benchmark group as the benchmark.

[0092] The durability performance evaluation module 350 is used to substitute the surface durability limit reduction factor as the fatigue limit correction factor into the safety margin calculation formula, calculate the safety margin of the additively manufactured part after non-machining process under the target load condition, and evaluate whether its fatigue durability performance meets the design requirements based on the safety margin.

[0093] This invention, through a benchmark-experimental group comparative design, combined with rotational bending fatigue testing and surface durability limit reduction factor calculation, transforms the influence of different surface processes on fatigue performance into quantifiable parameters, avoiding biases in subjective evaluation. Based on the safety margin calculation using the reduction factor, it directly correlates with actual load conditions, clarifying whether the fatigue durability performance of parts treated by various non-machining finishing processes meets the standards, providing an intuitive and reliable basis for screening additive manufacturing surface processes. From sample preparation to safety margin evaluation, the entire process is anchored to the design requirements and service conditions of the target part, avoiding the disconnect between laboratory data and actual applications, and effectively reducing the risk of part failure due to insufficient process adaptability.

[0094] Optionally, based on the above embodiments, the sample processing module 320 may include:

[0095] The full machining unit is used to select a quantitative number of samples from the basic samples to form a unique reference group, and to perform a uniform full machining process on all basic samples in the reference group to obtain at least one reference sample with a consistent surface finish.

[0096] The non-machining unit is used to select quantitative samples from the remaining basic samples to form at least two experimental groups, and to perform a specific non-machining process for each experimental group to form multiple control samples with different surface states; wherein the non-machining process used in different experimental groups is selected from at least one of the following: process type, process parameters, or process combination sequence.

[0097] Optionally, based on the above embodiments, the fatigue testing module 330 may include:

[0098] The cyclic stress application unit is used to carry out rotational bending fatigue tests on all reference specimens in the reference group and all control specimens in the experimental group according to the preset cycle base number. Cyclic stress is applied according to the unified loading specification during the test.

[0099] If the target reference specimen or target control specimen breaks or develops cracks of a size not smaller than the preset size on its surface during loading, the target specimen is deemed to have failed, and the number of failure cycles of the target specimen under the matched loading stress is recorded.

[0100] The failure state determination unit is used to determine that the target specimen has not failed if the target reference specimen or the target control specimen has not fractured or developed a crack of not less than a preset size when loaded to a preset cycle base number, and to record the loading stress and preset cycle base number that match the target specimen.

[0101] The first type of fatigue limit value determination unit is used to summarize the loading stress value, failure cycle number and preset cycle base of all reference specimens in the reference group, and determine the first type of fatigue limit value of the reference group through statistical analysis.

[0102] The second type of fatigue limit value determination unit is used to summarize the loading stress value, failure cycle number and preset cycle base of all control specimens in each experimental group according to the same statistical analysis method, and determine the second type of fatigue limit value of each experimental group to obtain the fatigue limit data of each specimen under different processes.

[0103] Optionally, based on the above embodiments, the reduction factor calculation module 340 may include:

[0104] The calculation reference value determination unit is used to separate the first type of fatigue limit value of the reference group from the fatigue limit data and use it as the calculation reference value;

[0105] The reduction coefficient determination unit is used to select the target second type fatigue limit value of the current experimental group, and to divide the target second type fatigue limit value with the first type fatigue limit value of the benchmark group. The quotient value is used as the surface durability limit reduction coefficient of the current experimental group and recorded.

[0106] The reduction factor summarization unit is used to repeatedly perform the operation of selecting experimental groups and dividing them with the first type of fatigue limit value until the calculation of all experimental groups is completed, summing up the quotient values ​​of all records to form a set of surface durability limit reduction factors corresponding to all non-machining processes.

[0107] Optionally, based on the above embodiments, the durability performance evaluation module 350 may include:

[0108] The necessary parameter extraction unit is used to extract structural dimension parameters for stress calculation from the design drawings of additively manufactured parts, extract cyclic load parameters from the technical documents that are associated with the target part, and extract the allowable stress of the target part under the target load condition.

[0109] The working stress amplitude calculation unit is used to construct a stress calculation model based on the structural dimension parameters, and apply the cyclic load parameters as loading conditions to the stress calculation model. Through stress analysis and calculation, the actual working stress amplitude of the target part under the target load condition is obtained.

[0110] The basic fatigue limit value determination unit is used to extract the first type of fatigue limit value of the benchmark group as the basic fatigue limit value.

[0111] The modified fatigue limit value determination unit is used to multiply the surface durability limit reduction coefficient of each experimental group by the basic fatigue limit value according to the set of surface durability limit reduction coefficients to obtain the processed modified fatigue limit value.

[0112] The safety margin calculation unit is used to substitute the actual working stress amplitude and the corrected fatigue limit value into the preset safety margin calculation formula to obtain the safety margin of the part under the process treatment corresponding to the current experimental group.

[0113] The safety margin comparison unit is used to compare the safety margin corresponding to each non-machining finishing process with the preset qualified threshold. If the safety margin is not less than the qualified threshold, it is determined that the fatigue durability performance of the part processed by the process meets the design requirements; otherwise, it is determined that it does not meet the requirements.

[0114] Optionally, based on the above embodiments, the preset safety margin calculation formula is as follows:

[0115]

[0116] in, For safety margin, The actual working stress amplitude, This is the surface durability limit reduction factor corresponding to non-machining finishing processes. Allowable stress.

[0117] The additive manufacturing parts durability evaluation device provided in this embodiment of the invention can execute the additive manufacturing parts durability evaluation method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0118] Example 4

[0119] Figure 4A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0120] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0121] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0122] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a method for evaluating the durability performance of additive manufacturing parts.

[0123] That is: according to the design requirements of the additive manufacturing part drawing, the target part is printed with a durability limit evaluation sample using laser additive manufacturing technology, and the durability limit evaluation sample is heat-treated and wire-cut to obtain a base sample separated from the forming substrate.

[0124] The basic sample is divided into a reference group and at least two experimental groups. A uniform full-machine process is performed on the reference group to obtain reference samples with consistent surface conditions. A specific non-machine process is performed on each experimental group to form a control sample group with different surface conditions.

[0125] Rotational bending fatigue tests were conducted on each reference specimen in the reference group and each control specimen in the experimental group to obtain fatigue limit data of each specimen under different processes.

[0126] Based on the fatigue limit data, and taking the fatigue limit of the benchmark group as the benchmark, the surface durability limit reduction factor of the experimental group is calculated.

[0127] The surface durability limit reduction factor is used as the fatigue limit correction factor and substituted into the safety margin calculation formula to calculate the safety margin of the additively manufactured part under the target load condition after non-machining process, and the fatigue durability performance is evaluated based on the safety margin to determine whether it meets the design requirements.

[0128] In some embodiments, an additive manufacturing part durability evaluation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the additive manufacturing part durability evaluation method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform an additive manufacturing part durability evaluation method by any other suitable means (e.g., by means of firmware).

[0129] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0130] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0131] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0132] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0133] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0134] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0135] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0136] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for evaluating the durability of additively manufactured parts, characterized in that, include: According to the design requirements of the additive manufacturing part drawings, the target part is printed with a durability limit evaluation sample using laser additive manufacturing technology, and the durability limit evaluation sample is subjected to heat treatment and wire cutting to obtain a base sample separated from the forming substrate. The basic sample is divided into a reference group and at least two experimental groups. A uniform full-machine process is performed on the reference group to obtain reference samples with consistent surface conditions. A specific non-machine process is performed on each experimental group to form a control sample group with different surface conditions. Rotational bending fatigue tests were conducted on each reference specimen in the reference group and each control specimen in the experimental group to obtain fatigue limit data of each specimen under different processes. Based on the fatigue limit data, and taking the fatigue limit of the benchmark group as the benchmark, the surface durability limit reduction factor of the experimental group is calculated. The surface durability limit reduction factor is used as the fatigue limit correction factor and substituted into the safety margin calculation formula to calculate the safety margin of the additively manufactured part under the target load condition after non-machining process, and the fatigue durability performance is evaluated based on the safety margin to determine whether it meets the design requirements.

2. The method according to claim 1, characterized in that, The basic samples are divided into a reference group and at least two experimental groups. A uniform full-machining process is applied to the reference group to obtain reference samples with consistent surface conditions. Specific non-machining processes are applied to each experimental group to form control sample groups with different surface conditions, including: A unique reference group is formed by selecting quantitative samples from the basic samples and performing a uniform full-machine process on all basic samples in the reference group to obtain at least one reference sample with a consistent surface finish. Quantitative samples were selected from the remaining basic samples to form at least two experimental groups. A specific non-machining process was performed on each experimental group to form multiple control samples with different surface states. The non-machining processes used in different experimental groups were selected from at least one of the following: process type, process parameters, or process combination sequence.

3. The method according to claim 1, characterized in that, Rotational bending fatigue tests were conducted on each reference specimen in the reference group and each control specimen in the experimental group to obtain fatigue limit data for each specimen under different processes, including: According to the preset cycle base, rotational bending fatigue tests were carried out on all the reference specimens in the reference group and all the control specimens in the experimental group one by one. Cyclic stress was applied according to the unified loading specification during the test. If the target reference specimen or target control specimen breaks or develops cracks of a size not smaller than the preset size on its surface during loading, the target specimen is deemed to have failed, and the number of failure cycles of the target specimen under the matched loading stress is recorded. If the target reference specimen or target control specimen does not fracture or develop a crack of a size not smaller than the preset number of cycles when loaded to the preset number of cycles, the target specimen is deemed not to have failed, and the loading stress and preset number of cycles matching the target specimen are recorded. The loading stress values, failure cycles, and preset cycle base of all reference specimens in the reference group are summarized, and the first type of fatigue limit value of the reference group is determined through statistical analysis. Using the same statistical analysis method, the loading stress value, failure cycle number and preset cycle base of all control specimens in each experimental group were summarized to determine the second type of fatigue limit value of each experimental group, and the fatigue limit data of each specimen under different processes were obtained.

4. The method according to claim 3, characterized in that, Based on the fatigue limit data, and using the fatigue limit of the benchmark group as a reference, the surface durability limit reduction factor of the experimental group is calculated, including: The first type of fatigue limit value of the benchmark group is separated from the fatigue limit data and used as the calculation benchmark value; Select the target second type fatigue limit value of the current experimental group, and divide the target second type fatigue limit value by the first type fatigue limit value of the benchmark group. Use the quotient value as the surface durability limit reduction factor corresponding to the current experimental group and record it. Repeat the operation of selecting experimental groups and dividing them with the first type of fatigue limit value until the calculation of all experimental groups is completed. Summarize the quotients of all records to form a set of surface durability limit reduction coefficients corresponding to all non-machining processes.

5. The method according to claim 1, characterized in that, The surface durability limit reduction factor is used as the fatigue limit correction factor and substituted into the safety margin calculation formula to calculate the safety margin of the additively manufactured part under the target load condition after non-machining processing. Based on the safety margin, its fatigue durability performance is evaluated to determine whether it meets the design requirements, including: Extract structural dimensional parameters for stress calculation from the design drawings of additively manufactured parts, extract cyclic load parameters from the technical documents that match the target parts, and extract the allowable stress of the target parts under the target load conditions; A stress calculation model is constructed based on the structural dimension parameters, and the cyclic load parameters are applied to the stress calculation model as loading conditions. Through stress analysis and calculation, the actual working stress amplitude of the target part under the target load condition is obtained. The first type of fatigue limit value of the benchmark group is extracted as the basic fatigue limit value; Based on the set of surface durability limit reduction coefficients, the surface durability limit reduction coefficient of each experimental group is multiplied by the basic fatigue limit value to obtain the processed corrected fatigue limit value. Substitute the actual working stress amplitude and the corrected fatigue limit value into the preset safety margin calculation formula to obtain the safety margin of the part under the process treatment corresponding to the current experimental group. The safety margin corresponding to each non-machining finishing process is compared with the preset qualified threshold. If the safety margin is not less than the qualified threshold, the fatigue durability performance of the part processed by the process is determined to meet the design requirements; otherwise, it is determined not to meet the requirements.

6. The method according to claim 5, characterized in that, The preset safety margin calculation formula is as follows: in, For safety margin, The actual working stress amplitude, This is the surface durability limit reduction factor corresponding to non-machining finishing processes. Allowable stress.

7. A device for evaluating the durability of additively manufactured parts, characterized in that, The device includes: The basic sample acquisition module is used to print a durability limit evaluation sample for the target part using laser additive manufacturing technology according to the design requirements of the additive manufacturing part drawing, and to perform heat treatment and wire cutting on the durability limit evaluation sample to obtain a basic sample separated from the forming substrate. The sample processing module is used to divide the basic sample into a reference group and at least two experimental groups, perform a uniform full-machine processing process on the reference group to obtain reference samples with consistent surface conditions, and perform specific non-machine processing processes on each experimental group to form control sample groups with different surface conditions. The fatigue testing module is used to perform rotational bending fatigue tests on each reference specimen in the reference group and each control specimen in the experimental group to obtain fatigue limit data of each specimen under different processes. The reduction factor calculation module is used to calculate the surface durability limit reduction factor of the experimental group based on the fatigue limit data and with the fatigue limit of the benchmark group as the benchmark. The durability performance evaluation module is used to substitute the surface durability limit reduction factor as the fatigue limit correction factor into the safety margin calculation formula, calculate the safety margin of the additively manufactured part after non-machining process under the target load condition, and evaluate whether its fatigue durability performance meets the design requirements based on the safety margin.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform an additive manufacturing durability evaluation method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute and implement the additive manufacturing durability evaluation method according to any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements a method for evaluating the durability of additive manufacturing parts according to any one of claims 1-6.

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