A method for evaluating the quality of an additively manufactured metal lattice sandwich structure product

Abstract

The application discloses a kind of quality evaluation methods of additive manufacturing metal lattice sandwich structure product, and the present application provides a kind of quality evaluation method of small-size metal lattice sandwich structure product of small batch additive manufacturing for engineering application, fills the blank of "additive manufacturing+metal lattice structure" technical engineering application in product quality evaluation aspect, and the evaluation method provided can use the score weight and calibration function of product quality evaluation project to calculate calibration value and carry out comprehensive evaluation, evaluation result can be calculated, quantifiable, evaluation result confidence is high, user side risk is small, the evaluation method provided has strong universality, can be applicable to different industry fields, especially suitable for the aviation, aerospace field of product quality and reliability requirement high but product batch, small batch.

Description

Technical Field

[0001] This invention relates to the field of additive manufacturing and lattice sandwich structures, specifically to a method for evaluating the quality of additively manufactured metal lattice sandwich structure products. Background Technology

[0002] Additive manufacturing technology is a manufacturing method that combines digital design with material processing and forming, constructing solids "bottom-up" by stacking specialized materials layer by layer. It is a disruptive manufacturing technology that addresses the forming needs of complex structures and high-performance components, possessing unique advantages in rapid manufacturing of complex structural parts, integrated design and manufacturing, and efficient material utilization. Selective laser melting (SLM) technology is particularly suitable for manufacturing metal components such as aluminum alloys and titanium alloys. Metal lattice sandwich structures are a new type of lightweight structure composed of a skin and an internal periodic lattice core, possessing multifunctional characteristics such as high specific stiffness, high specific strength, and high thermal insulation (heat transfer).

[0003] Products using additive manufacturing technology have been gradually applied in aerospace and aviation fields. Metal lattice sandwich structures are composed of thin-walled skins and slender rod lattices, exhibiting geometric characteristics across scales, from macroscopic components and fine lattices to microscopic materials. Their mechanical properties are closely related to their structural form and dimensions, and their performance characterization differs significantly from that of traditional metal structural components based on raw material properties. Furthermore, the dynamic evolution within the molten pool during metal additive manufacturing involves multi-factor, multi-physical field thermophysical behavior, inevitably resulting in initial manufacturing defects such as micropores, cracks, porosity, and residual stress, which significantly impact the product's mechanical properties and service reliability.

[0004] For mass production, a scientific and accurate evaluation of the performance of lattice sandwich structures formed using metal additive manufacturing technology is crucial for ensuring batch product quality. Currently, no publicly available performance evaluation methods or standards applicable to single-piece or batch production of metal additive manufactured lattice sandwich structures are available for engineering use. Therefore, this application proposes a quality evaluation method for additively manufactured metal lattice sandwich structures. Summary of the Invention

[0005] To address the problems mentioned in the background art, this invention provides a method for evaluating the quality of additively manufactured metal lattice sandwich structure products, so as to scientifically and accurately evaluate the performance of mass-produced lattice sandwich structure products formed by metal additive manufacturing technology.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for evaluating the quality of additively manufactured metal lattice sandwich structures includes:

[0008] S1: Group the batch of products to be evaluated, with each group including at least one product;

[0009] S2: Set at least one quality evaluation item for metal lattice sandwich structure products;

[0010] S3: Set the score weight for each quality evaluation item;

[0011] S4: Set the calibration function for each quality evaluation item. The calibration function represents the difference between the measured value and the optimal value of the product quality evaluation item.

[0012] S5: Conduct general inspections and spot checks on each group of products according to the quality evaluation items, and record the measured values;

[0013] S6: Based on the measured values ​​recorded in S5, calculate the calibration values ​​of the quality evaluation items for each group of products according to the calibration function of the quality evaluation items determined in S4;

[0014] S7: Normalize the scores based on the weighting of the quality evaluation items and the calibration values ​​of each group of products to obtain the product quality evaluation score;

[0015] S8: Determine whether the score meets the quality evaluation requirements. If not, identify the quality evaluation items where the product quality of this group is weak, analyze and improve the weak links or supplement qualified products and return to S5. If yes, output the evaluation result.

[0016] Preferably, the product quality evaluation items in S2 are evaluation items determined based on the characteristics of the product and the universality inspection items of the metal lattice sandwich structure product. The evaluation items include at least one Class I item, and each Class I item includes at least one Class II item, wherein the Class II item is a sub-item of the Class I item.

[0017] Preferably, in S3, the entropy method is used to calculate the score weight coefficient of Category I items, and the sum of the weight coefficients of all Category I items is 1. The calculation process is as follows:

[0018]

[0019]

[0020]

[0021]

[0022] Among them, A ik This represents the weight coefficient assigned by the k-th expert to the i-th category I item of the product, k∈[1,l], i∈[1,n], A i This represents the weight coefficient of the i-th item in category I of the product;

[0023] The statistical processing method is used to calculate the score weight coefficient of Category II items. The sum of the weight coefficients of all Category II items under each Category I item is 1. The calculation process is as follows:

[0024]

[0025]

[0026] Among them, A ihk This represents the weight coefficient assigned by the k-th expert to the h-th category II item under the i-th category I item of the product, where h∈[1,t]. ih This represents the weight coefficient of the h-th category II item for the i-th category I item of a product;

[0027] The calibration functions in S4 are divided into three categories: qualitative requirement category, expectation of larger or smaller requirement category, and expectation of target requirement category.

[0028] For qualitative requirements, the most satisfactory calibration value is 1, i.e., W. ih =1, W ih This represents the calibration value of the h-th type II item for the i-th type I item, and the remaining dissatisfaction levels are taken as values ​​less than 1;

[0029] For requirements such as whether the target size is large or small, W ih The calculation method is as follows:

[0030]

[0031]

[0032] Among them, X ih X represents the measured value of the parameter of the h-th type II item for the i-th type I item. ih0 V represents the specified value of the parameter for the h-th type II item of the i-th type I item. ih0 The optimal value for the parameter of the h-th type II item for the i-th type I item;

[0033] For the type of requirement, W ih The calculation method is as follows:

[0034]

[0035] In the formula, X ih1 X ih2 L is the two-sided specified value of the parameter for the h-th type II item of the i-th type I item. ih U ih These are the optimal lower limit and optimal upper limit values ​​for the parameters of the h-th type II project for the i-th type I project, respectively.

[0036] Preferably, in S5, for the items in the general inspection, each quality evaluation item of each product is tested, inspected, or simulated according to the prescribed inspection or testing requirements and methods, and the measured value X is recorded. ih Calculate the calibration value W ih ;

[0037] For the items to be sampled, the quality evaluation items of the sampled products shall be tested or inspected in accordance with the prescribed inspection or testing requirements, and the measured values ​​X shall be recorded. ih Calculate the calibration value W ih When the sampled product has both destructive evaluation items and non-destructive evaluation items, the non-destructive evaluation items should be tested first.

[0038] Preferably, the calculation method for obtaining the product quality evaluation score Q for each group in S7 is as follows:

[0039]

[0040]

[0041] Q i =1-D i ;

[0042]

[0043] Where, ω ih This represents the average value of the calibration of the h-th category II item for the i-th category I item in this product group, where m is the number of products in this group or the sampled items, and D is the average value of the calibration of the h-th category II item for this product group. i Q represents the Euclidean average distance between the calibration value of the i-th item of category I in this product group and the calibration value 1. i Let Q represent the quality evaluation score of the i-th category I item of the product group, and let Q represent the quality evaluation score of the product group.

[0044] Preferably, in S8, the quality evaluation criterion Q0 is determined based on the importance of the product, the user's risk, and the inspection level;

[0045] When Q≥Q0, it indicates that the quality of the group of products meets the requirements and has good consistency, and is acceptable.

[0046] When Q < Q0, it indicates that the quality of this group of products does not meet the requirements, according to the calibration value W. ih Identify the quality evaluation items where the product group has weak quality, analyze and improve the weak points, or remove unqualified and defective products, and re-evaluate the quality after producing the required number of products.

[0047] Compared with the prior art, the beneficial effects of the present invention are:

[0048] 1. A quality evaluation method for small-sized metal lattice sandwich structure products manufactured by small-batch additive manufacturing is proposed, which can be applied in engineering and fills the gap in the engineering application of "additive manufacturing + metal lattice structure" technology in product quality evaluation.

[0049] 2. The proposed evaluation method can use the score weights of the product quality evaluation items and the calibration function to calculate the calibration value for comprehensive evaluation. Moreover, the evaluation results are calculable and quantifiable, with high confidence and low risk to users.

[0050] 3. The proposed evaluation method is highly versatile and applicable to different industries, especially suitable for the aviation and aerospace fields where product quality and reliability requirements are high but product batches and quantities are small. Attached Figure Description

[0051] Figure 1 This is a schematic diagram illustrating the specific process of the present invention. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0053] Example 1

[0054] like Figure 1 As shown, a method for evaluating the quality of additively manufactured metal lattice sandwich structures includes:

[0055] S1: Group the batch of products to be evaluated. This method is mainly applicable to small-batch, small-sized products, that is, each batch can be produced in groups, but each group should be continuous. That is, the main factors affecting product quality, such as raw materials, equipment, and processes, have not changed. Generally, there are no more than 5 groups, and each batch does not exceed 10 pieces. Due to the limitations of the capabilities and efficiency of non-destructive testing equipment, the size is generally no larger than 500 mm × 500 mm × 100 mm.

[0056] S2: Set quality evaluation items for metal dot matrix sandwich structure products;

[0057] S3: Set the score weight for each quality evaluation item;

[0058] S4: Set the calibration function for each quality evaluation item. The calibration function represents the difference between the measured value and the optimal value of the product quality evaluation item.

[0059] S5: Conduct general inspections and spot checks on each group of products according to the quality evaluation items, and record the measured values;

[0060] S6: Based on the measured values ​​recorded in S5, calculate the calibration values ​​of the quality evaluation items for each group of products according to the calibration function of the quality evaluation items determined in S4;

[0061] S7: Normalize the scores based on the weighting of the quality evaluation items and the calibration values ​​of each group of products to obtain the product quality evaluation score;

[0062] S8: Determine whether the score meets the quality evaluation requirements. If not, identify the quality evaluation items where the product quality of this group is weak, analyze and improve the weak links, supplement qualified products and return to S5. If yes, output the evaluation result.

[0063] In this embodiment, this application proposes a quality evaluation method for small-sized metal lattice sandwich structure products manufactured in small batches using additive manufacturing, which can be applied in engineering. This fills the gap in the engineering application of "additive manufacturing + metal lattice structure" technology in product quality evaluation. The proposed evaluation method can use the score weights of the product's quality evaluation items and the calibration function to calculate the calibration value for comprehensive evaluation. The evaluation results are calculable and quantifiable, with high confidence and low risk to users. The proposed evaluation method is highly versatile and applicable to different industries, especially suitable for the aerospace industry, which has high requirements for product quality and reliability but small batch sizes.

[0064] Example 2

[0065] The difference between this embodiment and embodiment 1 is that the product quality evaluation items in S2 are determined based on the characteristics of the product and the universal inspection items for metal lattice sandwich structure products. The evaluation items include Class I items, which in turn include Class II items, where Class II items are sub-items of Class I items. The quality evaluation items are shown in Table 1.

[0066] Table 1 General Quality Evaluation Items for Metal Additive Manufacturing Lattice Sandwich Structure Products

[0067]

[0068]

[0069] Example 3

[0070] The difference between this embodiment and embodiment 2 is that in S3, the entropy method is used to calculate the score weight coefficient of category I items, and the sum of the weight coefficients of all category I items is 1. The calculation process is as follows:

[0071]

[0072]

[0073]

[0074]

[0075] Among them, A ik This represents the weight coefficient assigned by the k-th expert to the i-th category I item of the product, k∈[1,l], i∈[1,n], A i This represents the weight coefficient of the i-th item in category I of the product;

[0076] The statistical processing method is used to calculate the score weight coefficient of Category II items. The sum of the weight coefficients of all Category II items under each Category I item is 1. The calculation process is as follows:

[0077]

[0078]

[0079] Among them, A ihk This represents the weight coefficient assigned by the k-th expert to the h-th category II item under the i-th category I item of the product, where h∈[1,t]. ih This represents the weight coefficient of the h-th category II item for the i-th category I item of a product;

[0080] The calibration functions in S4 are divided into three categories: qualitative requirement category, expectation of larger or smaller requirement category, and expectation of target requirement category.

[0081] For qualitative requirements, the most satisfactory calibration value is 1, i.e., W. ih =1, W ih This represents the calibration value of the h-th type II item for the i-th type I item, and the remaining dissatisfaction levels are taken as values ​​less than 1;

[0082] For requirements such as whether the target size is large or small, W ih The calculation method is as follows:

[0083]

[0084]

[0085] Among them, X ih X represents the measured value of the parameter of the h-th type II item for the i-th type I item. ih0 V represents the specified value of the parameter for the h-th type II item of the i-th type I item. ih0 The optimal value for the parameter of the h-th type II item for the i-th type I item;

[0086] For the type of requirement, W ih The calculation method is as follows:

[0087]

[0088] In the formula, X ih1 X ih2 L is the two-sided specified value of the parameter for the h-th type II item of the i-th type I item. ih U ih These are the optimal lower limit and optimal upper limit values ​​for the parameters of the h-th type II project for the i-th type I project, respectively.

[0089] In this embodiment, the method proposed in this application can integrate multi-source heterogeneous information to comprehensively evaluate the quality of small-sized metal lattice sandwich structure products manufactured in small batches of additive manufacturing. The evaluation results have high confidence and low risk to users, and can be applied to the quality evaluation of such products in different industries (especially suitable for the aviation and aerospace fields).

[0090] Example 4

[0091] The difference between this embodiment and embodiment 3 is that in S5, for the general inspection items, each quality evaluation item of each product is tested, inspected, or simulated according to the prescribed inspection or testing requirements and methods, and the measured value X is recorded. ih Calculate the calibration value W ih ;

[0092] For the items to be sampled, the quality evaluation items of the sampled products shall be tested or inspected in accordance with the prescribed inspection or testing requirements, and the measured values ​​X shall be recorded. ih And calculate the calibration value W ih When the sampled product has both destructive evaluation items and non-destructive evaluation items, the non-destructive evaluation items should be tested first.

[0093] In this embodiment, general inspection involves a wide range of aspects, many indicators, a large workload, and a strong time requirement, and is suitable for inspection items with low workload. In contrast, random inspection has the characteristics of low difficulty, small error, strong representativeness, high accuracy, and non-destructive experimentation. Sampling surveys have a small workload and the error is often very small. Therefore, random inspection is suitable for inspection items with high workload.

[0094] Example 5

[0095] The difference between this embodiment and embodiment 4 is that the calculation method for obtaining the quality evaluation score Q of each group of products in S7 is as follows:

[0096]

[0097]

[0098] Q i =1-D i ;

[0099]

[0100] Where, ω ih This represents the average value of the calibration of the h-th category II item for the i-th category I item in this product group, where m is the number of products in this group or the sampled items, and D is the average value of the calibration of the h-th category II item for this product group. i Q represents the Euclidean average distance between the calibration value of the i-th item of category I in this product group and the calibration value 1. i Let Q represent the quality evaluation score of the i-th category I item of the product group, and let Q represent the quality evaluation score of the product group.

[0101] Example 6

[0102] The difference between this embodiment and embodiment 5 is that in S8, the quality evaluation criterion Q0 is determined based on the importance of the product, the user's risk, and the inspection level.

[0103] When Q≥Q0, it indicates that the quality of the group of products meets the requirements and has good consistency, and is acceptable.

[0104] When Q < Q0, it indicates that the quality of this group of products does not meet the requirements, according to the calibration value W. ih Identify the quality evaluation items where the product group has weak quality, analyze and improve the weak points, or remove unqualified and defective products, and re-evaluate the quality after producing the required number of products.

[0105] In this embodiment, the evaluation method proposed in this application is highly versatile and can be applied to different industries, especially the aviation and aerospace fields, which have high requirements for product quality and reliability but few product batches and small quantities.

[0106] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A method for evaluating the quality of additively manufactured metal lattice sandwich structures, characterized in that, include: S1: Group the batch of products to be evaluated, with each group including at least one product; S2: Set at least one quality evaluation item for metal lattice sandwich structure products; S3: Set the score weight for each quality evaluation item; S4: Set the calibration function for each quality evaluation item. The calibration function represents the difference between the measured value and the optimal value of the product quality evaluation item. S5: Conduct general inspections and spot checks on each group of products according to the quality evaluation items, and record the measured values; S6: Based on the measured values ​​recorded in S5, calculate the calibration values ​​of the quality evaluation items for each group of products according to the calibration function of the quality evaluation items determined in S4; S7: Normalize the scores based on the weighting of the quality evaluation items and the calibration values ​​of each group of products to obtain the product quality evaluation score; S8: Determine whether the score meets the quality evaluation requirements. If not, identify the quality evaluation items where the product quality of this group is weak, analyze and improve the weak links, supplement qualified products and return to S5. If yes, output the evaluation result. The product quality evaluation items in S2 are evaluation items determined based on the characteristics of the product and the universal inspection items of the metal lattice sandwich structure product. The evaluation items include at least one Class I item, and each Class I item includes at least one Class II item, where the Class II item is a sub-item of the Class I item. In S3, the entropy method is used to calculate the score weight coefficients of Category I items. The sum of the weight coefficients of all Category I items is 1. The calculation process is as follows: ； ； ； ； in, This represents the weight coefficient assigned by the k-th expert to the i-th category I item of the product, where k∈[1, l], i∈[1, n]. This represents the weight coefficient of the i-th item in category I of the product; The statistical processing method is used to calculate the score weight coefficient of Category II items. The sum of the weight coefficients of all Category II items under each Category I item is 1. The calculation process is as follows: ； ； in, Let h represent the weight coefficient assigned by the k-th expert to the h-th category II item under the i-th category I item of the product, where h∈[1,t]. This represents the weight coefficient of the h-th category II item for the i-th category I item of a product; The calibration functions in S4 are divided into three categories: qualitative requirement category, expectation of larger or smaller requirement category, and expectation of target requirement category. For qualitative requirements, the most satisfactory calibration value is 1, i.e. , This represents the calibration value of the h-th type II item for the i-th type I item, and the remaining dissatisfaction levels are taken as values ​​less than 1; For those who want large or small requirements The calculation method is as follows: ； ； Among them, X ih X represents the measured value of the parameter of the h-th type II item for the i-th type I item. ih0 V represents the specified value of the parameter for the h-th type II item of the i-th type I item. ih0 The optimal value for the parameter of the h-th type II item for the i-th type I item; For the type of requirement for viewing the target The calculation method is as follows: ； In the formula, X ih1 X ih2 L is the two-sided specified value of the parameter for the h-th type II item of the i-th type I item. ih U ih These are the optimal lower limit and optimal upper limit values ​​for the parameters of the h-th type II project for the i-th type I project, respectively.

2. The method for evaluating the quality of additively manufactured metal lattice sandwich structure products according to claim 1, characterized in that, In S5, for the general inspection items, each quality evaluation item of each product is tested, inspected, or simulated according to the prescribed inspection or testing requirements and methods, and the measured value X is recorded. ih Calculate the calibration value ; For the items to be sampled, the quality evaluation items of the sampled products shall be tested or inspected in accordance with the prescribed inspection or testing requirements, and the measured values ​​X shall be recorded. ih And calculate the calibration value. When the sampled product has both destructive evaluation items and non-destructive evaluation items, the non-destructive evaluation items should be tested first.

3. The method for evaluating the quality of additively manufactured metal lattice sandwich structure products according to claim 2, characterized in that, The calculation method for obtaining the product quality evaluation score Q for each group in S7 is as follows: ； ； ； ； Where, ω ih This represents the average value of the calibration of the h-th category II item for the i-th category I item in this product group, where m is the number of products in this group or the sampled items, and D is the average value of the calibration of the h-th category II item for this product group. i This represents the Euclidean average distance between the calibration value of the i-th item of category I in this product group and the calibration value 1. Let Q represent the quality evaluation score of the i-th category I item of the product group, and let Q represent the quality evaluation score of the product group.

4. The method for evaluating the quality of additively manufactured metal lattice sandwich structure products according to claim 3, characterized in that, In S8, the quality evaluation criterion Q0 is determined based on the product's importance, the user's risk, and the inspection level. When Q≥Q0, it indicates that the quality of the group of products meets the requirements and has good consistency, and is acceptable. When Q < Q0, it indicates that the quality of this group of products does not meet the requirements, according to the calibration value. Identify the quality evaluation items where the product group has weak quality, analyze and improve the weak points, or remove unqualified and defective products, and re-evaluate the quality after producing the required number of products.

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