A method and system for evaluating 3D printed composites

Abstract

The application discloses a kind of 3D printing composite material evaluation method and system, belong to material design technical field.It includes the performance data of each to be evaluated composite material;According to performance data, determine evaluation index;According to evaluation index, construct index system;Based on index system, evaluation index is handled by triangular fuzzy theory, obtains standardized decision matrix and carries out weighting processing, generates boundary approximate region matrix;The distance of each to be evaluated composite material and boundary approximate region matrix is calculated respectively, according to distance each to be evaluated composite material is sorted, obtains the evaluation result of to be evaluated composite material.Can realize the accurate evaluation of 3D printing composite material, solves the problem that existing evaluation method is too strong and does not consider multi-attribute decision making by subjective influence.

Description

Technical Field

[0001] This invention relates to the field of materials design technology, and in particular to a method and system for evaluating 3D printed composite materials. Background Technology

[0002] The statements in this section merely refer to the background art related to this invention and do not necessarily constitute prior art.

[0003] 3D printing has become a key technology in modern manufacturing, offering greater design freedom for product development, reducing waste, shortening development cycles, and driving innovation and sustainability across multiple industries. One of the key advancements in this technology is the ability to print objects using continuous carbon fiber reinforced composites. However, to meet practical engineering requirements, the selection of composite materials requires compromises between conflicting criteria, such as thermal stability, cost, and processing parameters. Choosing the right composite material for 3D printing is a complex, multi-attribute decision-making problem.

[0004] Because composite material design parameters are characterized by fuzzy uncertainty and correlation during the evaluation process, and most existing 3D printing composite material evaluation methods use a single decision-making approach, they have the following shortcomings:

[0005] 1. Because the material selection decision-making process requires decision-makers to have multidisciplinary knowledge, the experts involved in the decision-making process are often influenced by their own knowledge structure and cognitive level, which can easily lead to subjective hesitation and indecisiveness. Experts sometimes find it difficult to provide evaluation information expressed in precise numbers.

[0006] 2. Traditionally, the information used for material evaluation is mostly real information. However, due to differences in actual situations and evaluation needs, the traditional expression of information is often ineffective in material evaluation.

[0007] 3. In the existing technology, methods such as TOPSIS and TODIM are used for material evaluation and selection decisions, but they lack a systematic evaluation index system that considers the different properties of composite materials, and most of their decision matrices are obtained through expert scoring, which is highly subjective. Summary of the Invention

[0008] To address the shortcomings of existing technologies, this invention provides a method, system, electronic device, and computer-readable storage medium for evaluating 3D printed composite materials. It employs an ITARA (Integrated Weighted Approximation Area) solution method that considers the dispersion of index data to rationally allocate weights and introduces the Multi-Attribute Boundary Approximate Region Comparison (MABAC) decision-making method into the decision-making process for selecting 3D printed composite material schemes.

[0009] In a first aspect, the present invention provides a method for evaluating 3D printed composite materials;

[0010] A method for evaluating 3D printed composite materials, comprising:

[0011] Obtain the performance data of each composite material to be evaluated;

[0012] Based on performance data, determine evaluation indicators; based on evaluation indicators, construct an indicator system.

[0013] Based on the indicator system, the evaluation indicators are processed using triangular fuzzy theory to obtain a standardized decision matrix and perform weighted processing to generate a boundary approximate region matrix.

[0014] Calculate the distance between each composite material to be evaluated and the boundary approximate region matrix, sort the composite materials to be evaluated according to the distance, and obtain the evaluation results of the composite materials to be evaluated.

[0015] Furthermore, the evaluation indicators are processed using triangular fuzzy theory to obtain a standardized decision matrix, including:

[0016] Determine the correspondence between evaluation linguistic variables and fuzzy scales, and score subjective evaluation indicators based on the correspondence between evaluation linguistic variables and fuzzy scales;

[0017] The performance data corresponding to the objective evaluation indicators are converted into triangular fuzzy numbers to obtain the fuzzy decision matrix;

[0018] The fuzzy decision matrix is ​​standardized to obtain a standardized decision matrix.

[0019] Preferably, the standardization process of the fuzzy decision matrix to obtain the standardized decision matrix specifically involves:

[0020] The fuzzy decision matrix is ​​standardized to obtain the score decision matrix;

[0021] Based on the scoring decision matrix, a standardized decision matrix is ​​obtained according to the type of evaluation indicator.

[0022] Furthermore, the weighting process for the standardized decision matrix is ​​as follows:

[0023] The weight of each evaluation index in the standardized decision matrix is ​​determined by the ITARA weighting method under triangular fuzzy sets, and the standardized decision matrix is ​​weighted according to the weight of each evaluation index.

[0024] Furthermore, the specific steps of sorting the composite materials to be evaluated based on distance and obtaining the evaluation results of the composite materials to be evaluated are as follows:

[0025] The sum of distances between the composite material to be evaluated and the boundary approximate region matrix is ​​obtained. The composite materials to be evaluated are sorted according to the sum of distances to obtain the evaluation results of the composite materials to be evaluated.

[0026] Furthermore, the evaluation indicators include economic attributes, environmental attributes, social attributes, and physical performance attributes;

[0027] The economic attributes include initial cost, maintenance cost, processing cost, energy consumption and recycling cost; the environmental attributes include environmental protection, raw material extraction, recycling potential and reuse potential; the social attributes include lightweight level, production efficiency, service life, health and safety; and the material performance attributes include flexural modulus, flexural strength, elongation at break, energy absorption, relative change in width, relative change in thickness, tensile strength and yield stress.

[0028] Secondly, the present invention provides a 3D printing composite material evaluation system;

[0029] A 3D printing composite material evaluation system, comprising:

[0030] The performance data acquisition module is configured to acquire the performance data of each composite material to be evaluated.

[0031] The composite material evaluation module is configured to: determine evaluation indicators based on performance data; construct an indicator system based on the evaluation indicators; process the evaluation indicators using triangular fuzzy theory based on the indicator system to obtain a standardized decision matrix and perform weighted processing to generate a boundary approximation region matrix; calculate the distance between each composite material to be evaluated and the boundary approximation region matrix; sort each composite material to be evaluated according to the distance; and obtain the evaluation results of the composite materials to be evaluated.

[0032] Thirdly, the present invention provides an electronic device;

[0033] An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, complete the steps of the above-described 3D printed composite material evaluation method.

[0034] Fourthly, the present invention provides a computer-readable storage medium;

[0035] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, complete the steps of the above-described 3D-printed composite material evaluation method.

[0036] Compared with the prior art, the beneficial effects of the present invention are:

[0037] 1. The technical solution provided by this invention adopts the weighting method (ITARA) that takes into account the dispersion of indicator data to reasonably allocate weights, reduce the subjectivity of expert scoring, make the weights more objective and neutral, and make the weight allocation of each indicator more scientific.

[0038] 2. The technical solution provided by this invention introduces the Multi-Attribute Boundary Approximate Region Comparison (MABAC) decision method into the decision-making process for selecting 3D printing composite material schemes, which can achieve accurate evaluation of 3D printing composite material design schemes. Attached Figure Description

[0039] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0040] Figure 1 This is a flowchart provided for an embodiment of the present invention;

[0041] Figure 2 This is a schematic diagram illustrating the principle of the MABAC method provided in an embodiment of the present invention;

[0042] Figure 3 A schematic diagram of the comprehensive evaluation index system for 3D printing composite materials provided in an embodiment of the present invention;

[0043] Figure 4 A standardized sample diagram of 3D printed composite materials provided in an embodiment of the present invention. Detailed Implementation

[0044] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0045] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. Furthermore, it should be understood that the terms “comprising” and “having”, and any variations thereof, are intended to cover 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.

[0046] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0047] Example 1

[0048] In existing technologies for evaluating and deciding on 3D printed composite materials, the weight allocation of evaluation indicators is greatly influenced by expert subjectivity and fails to consider the fuzziness and uncertainty in multi-attribute decision-making, resulting in poor evaluation accuracy and robustness, which affects the final decision. Therefore, this invention provides a 3D printed composite material evaluation method that uses the ITARA (Integrated Attribute Assessment) method to reasonably allocate weights and introduces the MABAC (Multi-Attribute Boundary Approximate Region Comparison) decision-making method into the selection of 3D printed composite material schemes, thereby improving the accuracy and robustness of 3D printed composite material evaluation.

[0049] Next, combined Figures 1-4 This embodiment provides a detailed description of a method for evaluating 3D printed composite materials. The method includes the following steps:

[0050] S1. Select the composite material to be evaluated and obtain the performance data of each composite material to be evaluated.

[0051] In this embodiment, the composite material to be evaluated is a composite material composed of polyamide (SCFRPA) filled with short carbon fibers as the effective matrix and continuous carbon fiber (CCF) as the reinforcing material.

[0052] As one implementation method, standardized samples of the composite material to be evaluated are prepared before performance data is obtained: continuous carbon fiber reinforced composite materials are prepared using a 3D printing device (Mark X7, Cambridge, MA, USA) based on fused filament manufacturing technology.

[0053] Specifically, during the 3D printing process, the raw materials (CCF and SCFRPA) are deposited sequentially onto the printing bed through fiber nozzles and matrix nozzles, respectively, arranging the extruded lines row by row on a plane; then, they are arranged layer by layer to form the designed part. The continuous carbon fiber reinforced composite material consists of 46 printed layers, including 30 reinforcing material layers and 16 effective matrix layers, with dimensions of 90×6×6mm. In addition, a matrix sample without reinforcing layers was printed for comparison, such as... Figure 4 As shown.

[0054] As one implementation method, performance tests are performed on each standardized sample to obtain performance data.

[0055] In this embodiment, standardized samples are subjected to heat treatment tests, tensile tests, bending tests, strength tests, and hardness tests to obtain detailed data on the performance of 3D printed composite materials.

[0056] S2. Determine the evaluation indicators based on the performance data; construct an indicator system based on the evaluation indicators.

[0057] Specifically, by comprehensively considering the impact of environmental, social, and economic factors on composite materials, as well as the performance data obtained through mechanical property experiments, evaluation indicators are obtained, and a multi-dimensional indicator system is constructed. The indicator system is a multi-dimensional standard for evaluating a composite material. Only through a multi-angle indicator can the comprehensive performance of a composite material be comprehensively evaluated to determine whether it meets engineering requirements. Only by evaluating indicators from multiple aspects such as material performance, material cost, and material life can the best material be obtained.

[0058] In this embodiment, 20 evaluation indicators S = {S1, S2, ..., S...} are input. 20 The evaluation indicators include economic attributes, environmental attributes, social attributes, and physical performance attributes. Economic attributes include initial cost, maintenance costs, processing costs, energy consumption, and recycling costs. Environmental attributes include environmental protection, raw material extraction, recycling potential, and reuse potential. Social attributes include lightweight level, production efficiency, service life, health, and safety. Material performance attributes include flexural modulus, flexural strength, elongation at break, energy absorption, relative change in width, relative change in thickness, tensile strength, and yield stress.

[0059] S3. Based on the indicator system, the evaluation indicators are processed using triangular fuzzy theory to obtain a standardized decision matrix, which is then weighted to generate a boundary approximation region matrix. Specifically, this includes:

[0060] S301. Determine the correspondence between the evaluation linguistic variables and the fuzzy scale, as follows:

[0061] Table 1 Language Terminology

[0062]

[0063] S302. Based on the correspondence between evaluation language variables and fuzzy scales, score the subjective evaluation indicators; convert the performance data corresponding to the objective evaluation indicators into triangular fuzzy numbers to obtain the fuzzy decision matrix; standardize the fuzzy decision matrix to obtain the standardized decision matrix.

[0064] For example, for each 3D printed composite material A i =(A1,A2,...,A) m ) and evaluation index S of each 3D printed composite material j ={S1,S2,...,S} n The evaluation indicators include subjective indicators (such as the potential for recycling and reuse, environmental protection, etc. in Table 2) and objective indicators (such as yield stress, etc. in Table 2). Subjective indicators are designated indicators, which need to be determined by expert scoring; objective indicators are quantitative indicators, which are obtained through experimentally measured real data.

[0065] Subjective indicators are determined by expert DM k ={DM1,DM2,…,DM l Scoring is based on language level variables, and subjective scores are determined as subjective indicators. The correspondence between language variables and fuzzy scales is used to limit expert scores, thereby reducing the influence of experts' personal experience and preferences on subjective scores.

[0066] Objective indicators are obtained by converting performance test data into triangular fuzzy numbers. The lower bound of the test data's error is used as the minimum possible value in the triangular fuzzy number, the test data itself is used as the most promising value, and the upper bound of the test data's error is used as the maximum possible value. The fuzzy decision matrix is ​​then obtained through the subjective and objective indicators.

[0067]

[0068] Among them, for subjective indicators, The values ​​of the triangular fuzzy numbers in Table 1 correspond to the expert scoring; for objective indicators, These three values ​​represent the lower limit of error, the average test value, and the upper limit of error of the experimental data, respectively, and together they form a triangular fuzzy number.

[0069] Aggregated fuzzy decision matrix:

[0070]

[0071]

[0072]

[0073] The fuzzy decision matrix is ​​standardized to obtain a standardized decision matrix. The specific process is as follows:

[0074] The fuzzy decision matrix is ​​standardized to obtain the score decision matrix, which is represented as follows:

[0075]

[0076] Based on the score decision matrix, and according to the type of evaluation indicator, a standardized decision matrix is ​​obtained. The standardized decision matrix is ​​represented as follows:

[0077] V = [v ij ] m×n

[0078] If the evaluation index S j If it is a benefit-oriented indicator, then:

[0079] If the evaluation index S jIf it is a cost-based indicator, then:

[0080] The weight of each evaluation indicator in the standardized decision matrix is ​​determined using the ITARA weighting method under triangular fuzzy sets. The standardized decision matrix is ​​then weighted according to the weight of each evaluation indicator, and the weighted standardized matrix is ​​expressed as follows:

[0081] Z = (z ij ) m×n , z ij =ω j ·(v ij +1),

[0082] Where, ω j For weights.

[0083] The weight of each indicator is determined using the ITARA weighting method under triangular fuzzy sets:

[0084] in,

[0085] O ij =ρ i+1,j -ρ ij ,ρ (1)j =

[0086] min 1≤i≤m R ij <…<ρ (m)j =max 1≤i≤m R ij .

[0087] The indicator system is divided into an attribute layer and a standard layer, with a total of four attributes and twenty standards. Both attributes and standards have their own weights. The final weight refers to the weight of each standard under the attribute weight, obtained by multiplying the attribute weight by the standard weight. The final weight is used to measure the relative importance of each different indicator; the more important the indicator, the higher its weight percentage, and the greater its impact on the final ranking of the solutions.

[0088] The following table shows the weight correspondence between evaluation indicators:

[0089] Table 2. Weight Correspondence Table of Evaluation Indicators

[0090]

[0091]

[0092] The boundary approximation region matrix is ​​obtained, represented as:

[0093]

[0094] S4. Calculate the distance between each composite material to be evaluated and the boundary approximate region matrix, sort the composite materials to be evaluated according to the distance, and obtain the evaluation results of the composite materials to be evaluated.

[0095] The distance matrix is ​​represented as follows:

[0096]

[0097] Calculate the sum of distances (di) from the candidate solutions to the approximate boundary region, and rank the composite materials to be evaluated according to the value of Qi. i The higher the value, the better the performance of the composite material.

[0098]

[0099] The following composite material ranking table was constructed:

[0100] Table 3. Ranking of Composite Materials

[0101]

[0102]

[0103] The 3D printing composite material evaluation method provided in this embodiment establishes a complex and comprehensive index system that considers four aspects: economy, environment, society, and performance (i.e., properties) to comprehensively select 3D printing composite material solutions. The ITARA method based on triangular fuzzy numbers is used to objectively solve the weights of each index, reducing the influence of expert subjectivity and making the calculation results more scientific and reasonable.

[0104] Example 2

[0105] This embodiment discloses a 3D printing composite material evaluation system, including:

[0106] The performance data acquisition module is configured to acquire the performance data of each composite material to be evaluated.

[0107] The composite material evaluation module is configured to: determine evaluation indicators based on performance data; construct an indicator system based on the evaluation indicators; process the evaluation indicators using triangular fuzzy theory to obtain a standardized decision matrix and perform weighted processing to generate a boundary approximation region matrix; calculate the distance between each composite material to be evaluated and the boundary approximation region matrix; sort each composite material to be evaluated based on the distance; and obtain the evaluation results of the composite materials to be evaluated.

[0108] It should be noted that the performance data acquisition module and composite material evaluation module mentioned above correspond to the steps in Embodiment 1. The examples and application scenarios implemented by these modules and their corresponding steps are the same, but they are not limited to the content disclosed in Embodiment 1. It should also be noted that these modules, as part of the system, can be executed in a computer system, such as a set of computer-executable instructions.

[0109] Example 3

[0110] Embodiment 3 of the present invention provides an electronic device, including a memory and a processor, as well as computer instructions stored in the memory and running on the processor. When the computer instructions are executed by the processor, they complete the steps of the above-mentioned 3D printing composite material evaluation method.

[0111] Example 4

[0112] Embodiment 4 of the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, complete the steps of the above-described 3D printing composite material evaluation method.

[0113] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0114] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0115] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment, whereby a series of operational steps are performed to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1The steps of the function specified in one or more boxes.

[0116] The descriptions of each embodiment in the above embodiments have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0117] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for evaluating 3D printed composite materials, characterized in that, include: Obtain the performance data of each composite material to be evaluated; Based on performance data, determine the evaluation indicators; Based on the evaluation indicators, construct an indicator system; Based on the indicator system, the evaluation indicators are processed using triangular fuzzy theory to obtain a standardized decision matrix and perform weighted processing to generate a boundary approximate region matrix. The evaluation indicators are processed using triangular fuzzy theory to obtain a standardized decision matrix, including: Determine the correspondence between evaluation linguistic variables and fuzzy scales, and score subjective evaluation indicators based on the correspondence between evaluation linguistic variables and fuzzy scales; The performance data corresponding to the objective evaluation indicators are converted into triangular fuzzy numbers to obtain the fuzzy decision matrix; The fuzzy decision matrix is ​​standardized to obtain a standardized decision matrix. The weighting process for the standardized decision matrix is ​​as follows: The weight of each evaluation index in the standardized decision matrix is ​​determined by the ITARA weighting method under triangular fuzzy set, and the standardized decision matrix is ​​weighted according to the weight of each evaluation index. The distance between each composite material to be evaluated and the boundary approximate region matrix is ​​calculated. The composite materials are then sorted according to their distances to obtain the evaluation results. Specifically: The sum of distances between the composite material to be evaluated and the boundary approximate region matrix is ​​obtained. The composite materials to be evaluated are sorted according to the sum of distances to obtain the evaluation results of the composite materials to be evaluated.

2. The 3D printing composite material evaluation method as described in claim 1, characterized in that, The process of standardizing the fuzzy decision matrix to obtain the standardized decision matrix is ​​as follows: The fuzzy decision matrix is ​​standardized to obtain the score decision matrix; Based on the scoring decision matrix, a standardized decision matrix is ​​obtained according to the type of evaluation indicator.

3. The 3D printing composite material evaluation method as described in claim 1, characterized in that, The performance data was obtained by conducting performance tests on each composite material to be evaluated.

4. The 3D printing composite material evaluation method as described in claim 1, characterized in that, The evaluation indicators include economic attributes, environmental attributes, social attributes, and physical performance attributes; The economic attributes include initial cost, maintenance cost, processing cost, energy consumption and recycling cost; the environmental attributes include environmental protection, raw material extraction, recycling potential and reuse potential; the social attributes include lightweight level, production efficiency, service life, health and safety; and the physical performance attributes include flexural modulus, flexural strength, elongation at break, energy absorption, relative change in width, relative change in thickness, tensile strength and yield stress.

5. A 3D printing composite material evaluation system, characterized in that, include: The performance data acquisition module is configured to acquire the performance data of each composite material to be evaluated. The composite material evaluation module is configured to: determine evaluation indicators based on performance data; and construct an indicator system based on the evaluation indicators. Based on the indicator system, the evaluation indicators are processed using triangular fuzzy theory to obtain a standardized decision matrix, which is then weighted to generate a boundary approximation region matrix. The standardized decision matrix obtained by processing the evaluation indicators using triangular fuzzy theory includes: Determine the correspondence between evaluation linguistic variables and fuzzy scales, and score subjective evaluation indicators based on the correspondence between evaluation linguistic variables and fuzzy scales; The performance data corresponding to the objective evaluation indicators are converted into triangular fuzzy numbers to obtain the fuzzy decision matrix; The fuzzy decision matrix is ​​standardized to obtain a standardized decision matrix. The weighting process for the standardized decision matrix is ​​as follows: The weight of each evaluation index in the standardized decision matrix is ​​determined by the ITARA weighting method under triangular fuzzy set, and the standardized decision matrix is ​​weighted according to the weight of each evaluation index. The distance between each composite material to be evaluated and the boundary approximate region matrix is ​​calculated. The composite materials are then sorted according to their distances to obtain the evaluation results. Specifically: The sum of distances between the composite material to be evaluated and the boundary approximate region matrix is ​​obtained. The composite materials to be evaluated are sorted according to the sum of distances to obtain the evaluation results of the composite materials to be evaluated.

6. An electronic device, characterized in that, It includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, complete the steps of the 3D printed composite material evaluation method according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed by a processor, complete the steps of the 3D printed composite material evaluation method according to any one of claims 1-4.

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