Preparation method of additive manufacturing antibacterial metal medical material

Abstract

The invention provides a preparation method of an additive manufacturing antibacterial metal medical material, and relates to the technical field of antibacterial metal medical material preparation. The method comprises the steps that object information of a replaced object is collected, information extraction based on material increase manufacturing is carried out, and material increase data of the replaced object are formed; according to the material increase data of the replaced object, material increase material information is collected, material use analysis based on material matching is carried out, and material increase material feature data is formed; additive manufacturing process information is collected, process control analysis is carried out in combination with the additive material characteristic data, and additive process control data is formed; and according to the additive manufacturing process control data, real-time process control information is collected, process monitoring analysis is carried out, and additive manufacturing real-time monitoring data is formed. According to the method, the composition proportion and the mechanical property of the antibacterial metal medical material are controlled in an additive manufacturing mode, and it is guaranteed that the antibacterial metal medical material has more excellent use characteristics.

Description

Technical Field

[0001] The present invention relates to the technical field of preparation of antibacterial metal medical materials, and in particular to a method for preparing antibacterial metal medical materials by additive manufacturing. Background Art

[0002] Biomedical metal materials are metals or alloys used in biomedical materials, also known as surgical metal materials, which are a type of inert materials. These materials have excellent properties such as high mechanical strength, fatigue resistance and easy processing, and are the most widely used load-bearing implant materials in clinical applications. The application of these materials is very extensive, involving various aspects such as hard tissue, soft tissue, artificial organs and surgical auxiliary equipment. With the advancement of science and technology, adding a certain amount of other metals to biomedical metal materials can achieve better antibacterial effects.

[0003] Although biomedical metals have antibacterial properties after adding other appropriate metals, the metal material itself is denser than the bone and other tissues it replaces in the body, which can easily cause stress shielding, resulting in unreasonable use and damage to other related biological structures. Therefore, it is necessary to reasonably design and control the weight of biomedical metals. With the development of additive manufacturing technology, it is possible to more reasonably control the density and manufacturing accuracy of biomedical metals, and at the same time, it is also possible to more reasonably control the content of the added antibacterial metal to ensure the use characteristics of medical materials.

[0004] Therefore, it is an urgent problem to design a preparation method for additively manufactured antibacterial metal medical materials, and to control the composition ratio and mechanical properties of antibacterial metal medical materials by using additive manufacturing to ensure that the antibacterial metal medical materials have more superior usage characteristics. Summary of the invention

[0005] The purpose of the present invention is to provide a preparation method of antibacterial metal medical materials by additive manufacturing. By performing printing feature extraction based on additive manufacturing on human tissues to be replaced by antibacterial metal medical materials, relevant human tissue feature information about additive manufacturing is obtained, and then the component content of the antibacterial metal medical materials that can be replaced is reasonably proportioned. At the same time, considering the influence of the process on the printing results, reasonable material proportion control data is determined, and accurate and reasonable control of the entire process of additive manufacturing is achieved, ensuring that the antibacterial metal medical materials formed by additive manufacturing can better match the replaced human tissues in terms of performance, thereby improving the superiority of the use characteristics of the antibacterial metal medical materials.

[0006] In the first aspect, the present invention provides a method for preparing antibacterial metal medical materials by additive manufacturing, comprising collecting object information of a replaced object, performing information extraction based on additive manufacturing, and forming additive data of the replaced object; collecting additive material information based on the additive data of the replaced object, and performing material analysis based on material matching to form additive material characteristic data; collecting additive manufacturing process information, and performing process control analysis in combination with the additive material characteristic data to form additive process control data; collecting real-time process control information based on the additive process control data, performing process monitoring analysis, and forming additive manufacturing real-time monitoring data.

[0007] In the present invention, the method extracts printing features based on additive manufacturing of human tissues to be replaced by antibacterial metal medical materials, obtains relevant human tissue feature information about additive manufacturing, and then reasonably proportions the component contents of the antibacterial metal medical materials that can be replaced. At the same time, considering the influence of the process on the printing results, reasonable material proportion control data is determined to achieve accurate and reasonable control of the entire process of additive manufacturing, ensure that the antibacterial metal medical materials formed by additive manufacturing can better match the replaced human tissues in terms of performance, and enhance the superiority of the use characteristics of the antibacterial metal medical materials.

[0008] As a possible implementation method, object information of the replaced object is collected, and information extraction based on additive manufacturing is performed to form additive data of the replaced object, including: based on the object information of the replaced object, additive analysis based on appearance features is performed to establish an object printing model; based on the object printing model and in combination with the object information, mechanical features are assigned to determine the mechanical additive information of the object printing model; and the object printing model and the corresponding mechanical additive information are combined to form the additive data of the replaced object.

[0009] In the present invention, feature extraction of additive manufacturing information on the replaced object mainly considers two aspects. One is that the finished material formed by additive manufacturing can be highly interchangeable with the replaced object in position and shape. Therefore, the extracted feature information must include the shape and size characteristics of the replaced object. Considering the process of additive manufacturing, the feature extraction target is the printing model of the replaced object, that is, to form model data that can be recognized by the printing device. The other is that since additive manufacturing uses metal materials, there are large differences in density and elastic modulus compared with the replaced object, and this difference is reflected in the weight and mechanical properties macroscopically, which directly affects the interchangeability of additive manufacturing materials with the replaced object. Therefore, the density and elastic modulus data of the replaced object are extracted to provide a reference for the subsequent control of the additive manufacturing process, so as to ensure that the material formed by additive manufacturing is more matched with the replaced object in these properties. Of course, the characteristic information of density and elastic modulus must be fully considered in the additive manufacturing process, so it is extracted and assigned to the printing model to ensure that additive manufacturing can simultaneously complete the analysis and processing of these data information when acquiring and analyzing the model data, thereby forming complete and accurate process control data.

[0010] As a possible implementation method, additive analysis based on appearance features is performed according to the object information of the replaced object to establish an object printing model, including: extracting the size information of the replaced object according to the object information of the replaced object; combining all the size information of the replaced object to construct a model to form an object size model of the replaced object.

[0011] In the present invention, a printing model of the replaced object based on appearance features is established, that is, the size and shape feature information about the replaced object is extracted from the object information to establish model data that can be recognized by additive manufacturing. Of course, this includes the size and shape features of the object, as well as the size position positioning of the established model, the numerical accuracy of the shape size, and the dimensional deviation that has a significant impact on the manufacturing result due to the recognition of the model data, so as to ensure that the recognition of the model data by additive manufacturing can accurately and reasonably form complete reference data for controlling the manufacturing process parameters.

[0012] As a possible implementation method, mechanical characteristics are assigned according to the object printing model and combined with the object information to determine the mechanical additive information of the object printing model, including: determining the object volume of the replaced object according to the object printing model; extracting the object weight of the replaced object according to the object information, and determining the object density of the replaced object in combination with the object volume. ; According to the object density , collect average density and object density The elastic modulus of the same different replaced objects , determine the average elastic model , and the average elastic model Assigning the object printing model to form the object elastic modulus of the object printing model ,in, , n represents the average density and object density obtained The numbers of the same or different replaced objects.

[0013] In the present invention, it can be understood that most of the replaced objects are human tissues, and in order to achieve the interchangeability of antibacterial metal medical materials for human tissues, the mechanical properties of the materials must be considered. At the same time, for human tissues, the same tissue will also show different mechanical properties with different ages, races, etc. Therefore, in order to determine reasonable mechanical characteristic information, sufficient data analysis is required. Among them, the density data can be determined based on the weight and volume data formed by the printed model information. For the elastic modulus, the big data of the same density can be collected based on the density data to obtain a reasonable elastic modulus parameter. For obtaining big data based on density data, it is considered that the replaced objects with the same properties have a large degree of similarity in density parameters, so the obtained same data has reasonable reference value.

[0014] As a possible implementation method, according to the additive material data of the replaced object, the additive material information is collected, and the material analysis based on material matching is performed to form the additive material characteristic data, including: according to the object density , determine different additive ingredients and corresponding material ratio ranges; for different additive ingredients, according to the corresponding material ratio ranges and combined with the additive data of the replaced object, perform material matching analysis to form additive ingredient matching data.

[0015] In the present invention, of course, for the object density, the material of the replaced object itself is considered to be determined, and the antibacterial metal medical material that is interchangeable with the replaced object is different due to the difference in the antibacterial metal, substrate, etc., when the material density formed by additive manufacturing is close to the density of the replaced object, the ratio combination between different metal materials is different, so the object density can be used as the target for determining the different metal ratios. It can be understood that, on the one hand, for materials with the same metal category in the composition, considering the adjustable density of the process, it is also considered that different ratio combinations can be realized in multiple combinations in density. The component ratio based on density can achieve multiple combinations with different component ratios without changing the combination of metal categories. In this way, the material ratio is a range value when the density is the target, which also provides a wider choice for the subsequent ratio selection and process parameter control. In addition, when analyzing the material ratio in combination with density, it is also necessary to consider the influence of the elastic modulus on the material ratio. After all, the materials formed by different content combinations have obvious or even large differences in mechanical properties, and the elastic modulus is a reference for measuring this characteristic difference. The analysis of matching degree mainly considers the change of the elastic modulus.

[0016] As a possible implementation method, for different additive ingredients, according to the corresponding material ratio range, combined with the additive material data of the replaced object, material matching analysis is performed to form additive ingredient matching data, including: determining the additive manufacturing standard process, for different additive ingredients, according to the corresponding material ratio range, determining the additive material ratio density corresponding to different material ratios, and forming the additive ratio density function corresponding to the additive ingredients under the additive manufacturing standard process ,in, , k represents the number of different additive ingredients, Indicates the material ratio range corresponding to the additive ingredient numbered k; according to the ratio density function corresponding to different additive ingredients , assign additive ingredients with different material ratios to the object printing model, determine the additive material ratio elastic modulus of the object printing model corresponding to different material ratios of different additive ingredients, and form the material ratio modulus function corresponding to the additive ingredients under the additive manufacturing standard process ,in, ; According to the ratio density function and material ratio modulus function , and combined with the object density and the object elastic modulus , conduct material matching analysis of different material ratios to form additive material matching data.

[0017] In the present invention, the main purpose of the matching degree analysis is to determine the influence of different material ratios on the elastic modulus, and then establish a direct relationship of the material ratio that considers the influence of the material elastic modulus. Of course, since the material ratio determines both the elastic modulus and the density of the material, when analyzing the matching data, the material ratio is used as the basic data to simultaneously determine the two parameters of density and elastic modulus.

[0018] As a possible implementation method, according to the ratio density function and material ratio modulus function , and combined with the object density and the object elastic modulus , perform material matching analysis for different material ratios to form additive material matching data, including: and object density , determine the density matching difference function ,in, , α represents the density matching equivalent factor; according to the material ratio modulus function and the object elastic modulus , determine the modulus matching difference function ,in, , β represents the elastic modulus matching equivalent factor; according to the density matching difference function corresponding to the uniform material ratio and modulus matching difference function , determine the corresponding material matching difference function ,in, ; For different additive ingredients, match the difference function according to the corresponding material , determine the corresponding minimum material matching difference , and obtain the minimum material matching difference The corresponding additive material ratio density and additive material ratio elastic modulus, and the additive material ratio density is calibrated as the optimal density of the additive material corresponding to the additive material , the elastic modulus of the additive material ratio is calibrated as the optimal elastic modulus of the additive material corresponding to the additive material ratio ; Collect the best proportions and densities of different additive ingredients And the optimal elastic modulus of the ingredients , forming additive ingredient matching data.

[0019] In the present invention, after determining the relationship between different material ratios and the density and elastic modulus of the formed material under the same component combination, this relationship can be combined to match the component combination for additive manufacturing with the best material ratio when obtaining the density and elastic modulus information of the replaced object. It should be noted here that for different component combinations, the closest material ratio is determined within the applicable material ratio range by simultaneously considering the density and elastic modulus of the material formed by the ratio and the degree of proximity to the replaced object. This degree of proximity is reflected by determining the total deviation value of the density and elastic modulus relative to the replaced object. The matching equivalent factor can be set according to actual conditions, or it can be determined based on big data analysis. After determining the closest material ratio under different component combinations, the best values ​​of these different component combinations are compared with each other by the material matching difference to determine the component combination closest to the replaced object, thereby realizing the determination of the material composition and material ratio used for additive manufacturing.

[0020] As a possible implementation method, the additive manufacturing process information is collected, and combined with the additive material characteristic data, process control analysis is performed to form additive process control data, including: extracting relevant process parameters that affect the ingredient density and ingredient elastic modulus based on the additive manufacturing process information, and determining the parameter control range of different relevant process parameters; for different relevant process parameters, determining the relationship between the deviation value of the relative standard parameter within the corresponding parameter control range and the ingredient density influence amount of the optimal ingredient ratio in different additive ingredients, and forming different phases under the optimal ingredient ratio of the corresponding additive ingredients. The process density influence relationship information of the relevant process parameters is obtained; for different relevant process parameters, the relationship between the deviation value of the relative standard parameter within the corresponding parameter control range and the influence amount of the elastic modulus of the ingredients in the optimal ratio of the ingredients in different additive ingredients is determined, and the process modulus influence relationship information of different relevant process parameters under the optimal ratio of the ingredients of the corresponding additive ingredients is formed; for different additive ingredients, according to the process density influence relationship information and process modulus influence relationship information corresponding to different relevant process parameters under the corresponding optimal ratio of ingredients, the adjustment amount of different relevant process parameters is determined, so that the optimal density of the ingredients is adjusted. Optimal elastic modulus of ingredients The adjustment is used to obtain the minimum value of the following formula and calibrate it as the minimum process matching difference : , It represents the total density adjustment of the optimal density of the additive ingredient numbered k after adjusting the different relevant process parameters relative to the standard parameters within the corresponding parameter control range under the optimal ingredient ratio. The total adjustment of the elastic modulus of the optimal elastic modulus of the additive ingredient numbered k after adjusting the different related process parameters relative to the standard parameters within the corresponding parameter control range under the optimal ingredient ratio; for different additive ingredients, determine the minimum process matching difference The minimum value of the minimum value is determined as the corresponding process control value, the additive material corresponding to the minimum value is determined as the substitute material, the optimal material ratio corresponding to the substitute material is determined as the substitute material ratio, and the minimum value is determined as the corresponding additive material ratio. Determine the print density , the minimum value corresponding to Determined as the print elastic modulus ; Collect different related process parameters of process control quantity, alternative ingredient ratio, printing density And print elastic modulus , forming additive process control data.

[0021] In the present invention, for additive manufacturing, after determining the composition of the raw materials used in manufacturing and the corresponding material ratio, it is also necessary to consider the impact of the manufacturing process on the performance characteristics of the material that matches the object being replaced. Such as the control of printing thickness during the manufacturing process, the uniformity of the gap, etc. Since it will affect the properties such as density and elastic modulus, they need to be considered as the focus. The present application determines the relevant process parameters that affect the density and elastic modulus, and defines the range in which these process parameters can be adjusted, and then selects parameter values ​​for the adjustment amounts of these relevant process parameters. The selection method is also achieved by planning the relevant process parameter values ​​in terms of the comprehensive deviation of density and elastic modulus.

[0022] As a possible implementation method, based on the additive process control data, real-time process control information is collected, process monitoring and analysis are performed, and real-time monitoring data for additive manufacturing is formed, including: collecting real-time printing volume and real-time print weight , determine the real-time printing density ,in, ; According to real-time printing density and print density , monitor and analyze the printing process to form real-time monitoring data for additive manufacturing.

[0023] In the present invention, after determining the material composition and corresponding material ratio used in additive manufacturing and the relevant process parameters in the manufacturing process, in order to fully ensure that the manufactured material meets the requirements, the process can be reasonably monitored in real time, and reasonable adjustments and guidance can be made based on the monitoring and analysis results. Here, the purpose of monitoring is to determine whether the manufactured material meets the preset requirements in terms of density and elastic modulus, and the elastic modulus will also be determined by the determination of density and related process parameters, so monitoring can simply be achieved by real-time monitoring of density data.

[0024] As a possible implementation method, according to the real-time printing density and print density , monitor and analyze the printing process to form real-time monitoring data for additive manufacturing, including: setting the allowable process deviation γ, and and print density , perform the following printing process monitoring and analysis: If , then print monitoring normal information is generated; if ,and , then the printing monitoring is too confidential; if ,and , then the printing monitoring information will be generated.

[0025] In the present invention, it can be understood that if the difference between the density value obtained in real time and the density value analyzed in advance is within an acceptable range, it is considered that the manufacturing process is within the control range. If the difference is not within the acceptable range and the real-time density is larger than the pre-analyzed density, it is considered that the manufacturing process is caused by too much material provided, resulting in an increase in density, and a prompt is given to guide the adjustment of the feeding amount. If the difference is not within the acceptable range and the real-time density is smaller than the pre-analyzed density, it is considered that the manufacturing process is caused by too little material provided, resulting in a decrease in density, and a prompt is given to guide the adjustment of the feeding amount.

[0026] The beneficial effects of the preparation method of the additive manufacturing antibacterial metal medical material provided by the present invention are as follows: This method extracts printing features based on additive manufacturing of human tissues to be replaced by antibacterial metal medical materials, obtains relevant human tissue feature information about additive manufacturing, and then reasonably proportions the component contents of the antibacterial metal medical materials that can be used as substitutes. At the same time, considering the influence of the process on the printing results, reasonable material proportion control data is determined to achieve accurate and reasonable control of the entire process of additive manufacturing, ensure that the antibacterial metal medical materials formed by additive manufacturing can better match the replaced human tissues in terms of performance, and enhance the superiority of the antibacterial metal medical materials' usage characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 A step diagram of a method for preparing an antibacterial metal medical material by additive manufacturing provided in an embodiment of the present invention; Figure 2 A schematic structural diagram of a system for preparing antibacterial metal medical materials by additive manufacturing provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The technical solutions in the embodiments of the present invention will be described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0030] Biomedical metal materials are metals or alloys used in biomedical materials, also known as surgical metal materials, which are a type of inert materials. These materials have excellent properties such as high mechanical strength, fatigue resistance and easy processing, and are the most widely used load-bearing implant materials in clinical applications. The application of these materials is very extensive, involving various aspects such as hard tissue, soft tissue, artificial organs and surgical auxiliary equipment. With the advancement of science and technology, adding a certain amount of other metals to biomedical metal materials can achieve better antibacterial effects.

[0031] Although biomedical metals have antibacterial properties after adding other appropriate metals, the metal material itself is denser than the bone and other tissues it replaces in the body, which can easily cause stress shielding, resulting in unreasonable use and damage to other related biological structures. Therefore, it is necessary to reasonably design and control the weight of biomedical metals. With the development of additive manufacturing technology, it is possible to more reasonably control the density and manufacturing accuracy of biomedical metals, and at the same time, it is also possible to more reasonably control the content of the added antibacterial metal to ensure the use characteristics of medical materials.

[0032] refer to Figure 1~Figure 2The embodiment of the present invention provides a method for preparing an antibacterial metal medical material by additive manufacturing. The method extracts printing features based on additive manufacturing on human tissues to be replaced by antibacterial metal medical materials, obtains relevant human tissue feature information about additive manufacturing, and then reasonably proportions the component contents of the antibacterial metal medical materials that can be replaced. At the same time, considering the influence of the process on the printing results, reasonable material proportion control data is determined, and accurate and reasonable control of the entire process of additive manufacturing is achieved, ensuring that the antibacterial metal medical materials formed by additive manufacturing can better match the replaced human tissues in terms of use performance, thereby improving the superiority of the use characteristics of the antibacterial metal medical materials.

[0033] The method for preparing antibacterial metal medical materials by additive manufacturing specifically comprises the following steps: S1: Collect object information of the replaced object, perform information extraction based on additive manufacturing, and form additive data of the replaced object.

[0034] Collect object information of the replaced object, perform information extraction based on additive manufacturing, and form additive data of the replaced object, including: perform additive analysis based on appearance features according to the object information of the replaced object, and establish an object printing model; assign mechanical features according to the object printing model and in combination with the object information to determine the mechanical additive information of the object printing model; combine the object printing model and the corresponding mechanical additive information to form the additive data of the replaced object.

[0035] There are two main considerations for feature extraction of additive manufacturing information for the replaced object. One is that the finished material formed by additive manufacturing can be highly interchangeable with the replaced object in terms of position and shape. Therefore, the extracted feature information must contain the shape and size characteristics of the replaced object. Considering the process of additive manufacturing, the feature extraction target is the printing model of the replaced object, that is, to form model data that can be recognized by the printing device. The other is that since additive manufacturing uses metal materials, there are large differences in density and elastic modulus compared with the replaced object, and this difference is reflected in the weight and mechanical properties. This directly affects the interchangeability of additive manufacturing materials and replaced objects. Therefore, the density and elastic modulus data of the replaced object are extracted to provide a reference for the subsequent control of the additive manufacturing process, ensuring that the material formed by additive manufacturing is more matched with the replaced object in these properties. Of course, since the feature information of density and elastic modulus must be fully considered in the process of additive manufacturing, it is extracted and assigned to the printing model to ensure that additive manufacturing can simultaneously complete the analysis and processing of these data information when acquiring and analyzing model data, forming complete and accurate process control data.

[0036] According to the object information of the replaced object, additive analysis based on appearance features is performed to establish an object printing model, including: extracting the size information of the replaced object according to the object information of the replaced object; combining all the size information of the replaced object to construct a model to form an object size model of the replaced object.

[0037] To establish a printing model for the replaced object based on its appearance features is to extract the size and shape feature information about the replaced object from the object information to establish model data that can be recognized by additive manufacturing. Of course, this includes the size and shape features of the object, as well as the size and position positioning of the established model, the numerical accuracy of the shape and size, and the dimensional deviation that has a significant impact on the manufacturing results due to the recognition of model data, so as to ensure that additive manufacturing can accurately and reasonably recognize the model data to form complete reference data for controlling the manufacturing process parameters.

[0038] According to the object printing model, the mechanical characteristics are assigned in combination with the object information to determine the mechanical additive information of the object printing model, including: according to the object printing model, the object volume of the replaced object is determined; according to the object information, the object weight of the replaced object is extracted, and the object density of the replaced object is determined in combination with the object volume. ; According to the object density , collect average density and object density The elastic modulus of the same different replaced objects , determine the average elastic model , and the average elastic model Assigning the object printing model to form the object elastic modulus of the object printing model ,in, , n represents the average density and object density obtained The numbers of the same or different replaced objects.

[0039] It is understandable that most of the replaced objects are human tissues, and in order to achieve the interchangeability of antibacterial metal medical materials for human tissues, the mechanical properties of the materials must be considered. At the same time, for human tissues, the same tissue will exhibit different mechanical properties with different ages, races, etc. Therefore, in order to determine reasonable mechanical characteristic information, sufficient data analysis is required. The density data can be determined based on the weight and volume data formed by the printed model information. For the elastic modulus, the big data of the same density can be collected based on the density data to obtain reasonable elastic modulus parameters. The acquisition of big data based on density data takes into account that the replaced objects with the same characteristics have a large degree of similarity in density parameters, and thus the obtained identical data has reasonable reference value.

[0040] S2: According to the additive material data of the replaced object, the additive material information is collected, and the material analysis based on material matching is performed to form additive material characteristic data.

[0041] According to the additive material data of the replaced object, the additive material information is collected, and the material analysis based on material matching is performed to form the additive material characteristic data, including: according to the object density , determine different additive ingredients and corresponding material ratio ranges; for different additive ingredients, according to the corresponding material ratio ranges and combined with the additive data of the replaced object, perform material matching analysis to form additive ingredient matching data.

[0042] Of course, for the object density, the material of the replaced object itself is determined, and the antibacterial metal medical materials that are interchangeable with the replaced object are different in antibacterial metals, substrates, etc., so when the material density formed by additive manufacturing is close to the density of the replaced object, the ratio combination of different metal materials is different, so the object density can be used as the target for determining different metal ratios. It can be understood that, on the one hand, for materials with the same metal category in the composition, considering the adjustable density of the process, and considering that different ratio combinations can be realized in multiple combinations in density, the composition ratio based on density can achieve multiple combinations of different composition ratios without changing the combination of metal categories. In this way, the material ratio is a range value when the density is the target, which also provides a wider choice for the subsequent ratio selection and process parameter control. In addition, when analyzing the material ratio in combination with density, it is also necessary to consider the influence of elastic modulus on the material ratio. After all, the materials formed by different content combinations have obvious or even large differences in mechanical properties, and the elastic modulus is the reference for measuring this characteristic difference. The analysis of matching degree mainly considers the change of elastic modulus.

[0043] For different additive ingredients, according to the corresponding material ratio range, combined with the additive data of the replaced object, material matching analysis is performed to form additive ingredient matching data, including: determining the additive manufacturing standard process, for different additive ingredients, according to the corresponding material ratio range, determining the additive material ratio density corresponding to different material ratios, and forming the additive ratio density function corresponding to the additive ingredients under the additive manufacturing standard process ,in, , k represents the number of different additive ingredients, Indicates the material ratio range corresponding to the additive ingredient numbered k; according to the ratio density function corresponding to different additive ingredients , assign additive ingredients with different material ratios to the object printing model, determine the additive material ratio elastic modulus of the object printing model corresponding to different material ratios of different additive ingredients, and form the material ratio modulus function corresponding to the additive ingredients under the additive manufacturing standard process ,in, ; According to the ratio density function and material ratio modulus function , and combined with the object density and the object elastic modulus , conduct material matching analysis of different material ratios to form additive material matching data.

[0044] The main purpose of matching analysis is to determine the influence of different material ratios on the elastic modulus, and then establish a direct relationship of the material ratio that affects the elastic modulus of the material. Of course, since the material ratio determines both the elastic modulus and the density of the material, when analyzing the matching data, the material ratio is used as the basic data to simultaneously determine the two parameters of density and elastic modulus.

[0045] According to the ratio density function and material ratio modulus function , and combined with the object density and the object elastic modulus , perform material matching analysis for different material ratios to form additive material matching data, including: and object density , determine the density matching difference function ,in, , α represents the density matching equivalent factor; according to the material ratio modulus function and the object elastic modulus , determine the modulus matching difference function ,in, , β represents the elastic modulus matching equivalent factor; according to the density matching difference function corresponding to the uniform material ratio and modulus matching difference function , determine the corresponding material matching difference function ,in, ; For different additive ingredients, match the difference function according to the corresponding material , determine the corresponding minimum material matching difference , and obtain the minimum material matching difference The corresponding additive material ratio density and additive material ratio elastic modulus, and the additive material ratio density is calibrated as the optimal density of the additive material corresponding to the additive material , the elastic modulus of the additive material ratio is calibrated as the optimal elastic modulus of the additive material corresponding to the additive material ratio ; Collect the best proportions and densities of different additive ingredients And the optimal elastic modulus of the ingredients , forming additive ingredient matching data.

[0046] After determining the relationship between different material ratios and the density and elastic modulus of the formed material under the same component combination, this relationship can be combined to match the component combination for additive manufacturing with the best material ratio when obtaining the density and elastic modulus information of the replaced object. It should be noted here that for different component combinations, the closest material ratio is determined within the applicable material ratio range by simultaneously considering the density and elastic modulus of the material formed by the ratio and the degree of proximity to the replaced object. This degree of proximity is reflected by determining the total deviation value of the density and elastic modulus relative to the replaced object. The matching equivalent factor can be set according to actual conditions, or it can be determined based on big data analysis. After determining the closest material ratio under different component combinations, the best values ​​of these different component combinations are compared with each other by the material matching difference to determine the component combination closest to the replaced object, thereby realizing the determination of the material composition and material ratio used for additive manufacturing.

[0047] S3: Collect additive manufacturing process information, and combine it with additive material characteristic data to conduct process control analysis to form additive process control data.

[0048] Collecting additive manufacturing process information, and combining it with additive material characteristic data, conducting process control analysis to form additive process control data, including: extracting relevant process parameters that affect the batch density and the batch elastic modulus according to the additive manufacturing process information, and determining the parameter control range of different relevant process parameters; for different relevant process parameters, determining the relationship between the deviation value of the relative standard parameter within the corresponding parameter control range and the batch density influence amount of the optimal batch ratio of different additive ingredients, and forming the process density influence relationship information of different relevant process parameters under the optimal batch ratio of the corresponding additive ingredients; for different relevant process parameters, determining the relationship between the deviation value of the relative standard parameter within the corresponding parameter control range and the batch elastic modulus influence amount of the optimal batch ratio of different additive ingredients, and forming the process modulus influence relationship information of different relevant process parameters under the optimal batch ratio of the corresponding additive ingredients; for different additive ingredients, determining the adjustment amount of different relevant process parameters according to the process density influence relationship information and process modulus influence relationship information corresponding to different relevant process parameters under the corresponding optimal batch ratio, so that the optimal density of the ingredients is adjusted. Optimal elastic modulus of ingredients The adjustment is used to obtain the minimum value of the following formula and calibrate it as the minimum process matching difference : , It represents the total density adjustment of the optimal density of the additive ingredient numbered k after adjusting the different relevant process parameters relative to the standard parameters within the corresponding parameter control range under the optimal ingredient ratio. The total adjustment of the elastic modulus of the optimal elastic modulus of the additive ingredient numbered k after adjusting the different related process parameters relative to the standard parameters within the corresponding parameter control range under the optimal ingredient ratio; for different additive ingredients, determine the minimum process matching difference The minimum value of the minimum value is determined as the corresponding process control value, the additive material corresponding to the minimum value is determined as the substitute material, the optimal material ratio corresponding to the substitute material is determined as the substitute material ratio, and the minimum value is determined as the corresponding additive material ratio. Determine the print density , the minimum value corresponding to Determined as the print elastic modulus ; Collect different related process parameters of process control quantity, alternative ingredient ratio, printing density And print elastic modulus , forming additive process control data.

[0049] For additive manufacturing, after determining the composition of the raw materials used in manufacturing and the corresponding material ratio, it is also necessary to consider the impact of the manufacturing process on the performance characteristics of the material that matches the object being replaced. Such as the control of printing thickness during the manufacturing process, the uniformity of the gap, etc. Since it will affect properties such as density and elastic modulus, they need to be considered as key considerations. This application determines the relevant process parameters that affect density and elastic modulus, and defines the range in which these process parameters can be adjusted, and then selects parameter values ​​for the adjustment amounts of these relevant process parameters. The selection method is also achieved by planning the relevant process parameter values ​​in terms of the comprehensive deviation of density and elastic modulus.

[0050] S4: Based on the additive process control data, collect real-time process control information, conduct process monitoring and analysis, and form real-time monitoring data for additive manufacturing.

[0051] According to the additive process control data, collect real-time process control information, conduct process monitoring and analysis, and form real-time monitoring data for additive manufacturing, including: collecting real-time printing volume and real-time print weight , determine the real-time printing density ,in, ; According to real-time printing density and print density , monitor and analyze the printing process to form real-time monitoring data for additive manufacturing.

[0052] After determining the material composition and corresponding material ratio used in additive manufacturing and the relevant process parameters in the manufacturing process, in order to fully ensure that the manufactured materials meet the requirements, the process can be reasonably monitored in real time, and reasonable adjustments and guidance can be made based on the monitoring and analysis results. Here, the purpose of monitoring is to determine whether the manufactured material meets the preset requirements in terms of density and elastic modulus, and the elastic modulus will also be determined by the density and related process parameters. Therefore, monitoring can simply be achieved by real-time monitoring of density data.

[0053] According to real-time printing density and print density , monitor and analyze the printing process to form real-time monitoring data for additive manufacturing, including: setting the allowable process deviation γ, and and print density , perform the following printing process monitoring and analysis: If , then print monitoring normal information is generated; if ,and , then the printing monitoring is too confidential; if ,and , then the printing monitoring information will be generated.

[0054] It can be understood that if the difference between the density value obtained in real time and the density value analyzed in advance is within an acceptable range, it is considered that the manufacturing process is within the control range. If the difference is not within the acceptable range and the real-time density is larger than the pre-analyzed density, it is considered that the manufacturing process is caused by too much material provided, resulting in an increase in density, and a prompt is given to guide the adjustment of the feed amount. If the difference is not within the acceptable range and the real-time density is smaller than the pre-analyzed density, it is considered that the manufacturing process is caused by too little material provided, resulting in a decrease in density, and a prompt is given to guide the adjustment of the feed amount.

[0055] The present invention also provides a preparation system for additively manufactured antibacterial metal medical materials, which includes an object data acquisition unit, which is used to acquire object information of the replaced object, and extract information to form additive data of the replaced object; a matching analysis unit, which is used to obtain the additive data of the replaced object formed by the object data acquisition unit, perform material analysis based on material matching, and form additive material characteristic data; a process control analysis unit, which is used to acquire additive manufacturing process information, and perform process control analysis in combination with the additive material characteristic data formed by the matching analysis unit to form additive process control data; a real-time monitoring unit, which is used to acquire real-time process control information, and combine it with the additive process control data to form additive manufacturing real-time monitoring data.

[0056] In summary, the method for preparing antibacterial metal medical materials by additive manufacturing provided in the embodiments of the present invention has the following beneficial effects: This method extracts printing features based on additive manufacturing of human tissues to be replaced by antibacterial metal medical materials, obtains relevant human tissue feature information about additive manufacturing, and then reasonably proportions the component contents of the antibacterial metal medical materials that can be used as substitutes. At the same time, considering the influence of the process on the printing results, reasonable material proportion control data is determined to achieve accurate and reasonable control of the entire process of additive manufacturing, ensure that the antibacterial metal medical materials formed by additive manufacturing can better match the replaced human tissues in terms of performance, and enhance the superiority of the antibacterial metal medical materials' usage characteristics.

[0057] In the embodiments of the present application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated can also be indirectly indicated by indicating other information, wherein there is an association between the other information and the information to be indicated. It is also possible to indicate only a part of the information to be indicated, while the other parts of the information to be indicated are known or agreed in advance. For example, the indication of specific information can also be achieved by means of the arrangement order of each piece of information agreed in advance (for example, specified by the protocol), thereby reducing the indication overhead to a certain extent. At the same time, the common parts of each piece of information can also be identified and indicated uniformly to reduce the indication overhead caused by indicating the same information separately.

[0058] In addition, the specific indication method may also be various existing indication methods, such as but not limited to the above-mentioned indication methods and various combinations thereof. The specific details of the various indication methods can refer to the prior art and will not be repeated herein. As can be seen from the above, for example, when it is necessary to indicate multiple information of the same type, different indication methods may be used for different information. In the specific implementation process, the desired indication method can be selected according to specific needs. The embodiment of the present application does not limit the selected indication method. In this way, the indication method involved in the embodiment of the present application should be understood to cover various methods that can enable the party to be indicated to obtain the information to be indicated.

[0059] It should be understood that the information to be indicated can be sent as a whole, or divided into multiple sub-information and sent separately, and the sending period and / or sending time of these sub-information can be the same or different. The specific sending method is not limited in the embodiment of the present application. Among them, the sending period and / or sending time of these sub-information can be pre-defined, for example, pre-defined according to a protocol, or can be configured by the sending end device by sending configuration information to the receiving end device.

[0060] "Pre-definition" or "pre-configuration" can be implemented by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in the device, and the embodiments of the present application do not limit the specific implementation method. Among them, "saving" can mean saving in one or more memories. The one or more memories can be set separately or integrated in an encoder or decoder, a processor, or a communication device. The one or more memories can also be partially set separately and partially integrated in a decoder, a processor, or a communication device. The type of memory can be any form of storage medium, which is not limited by the embodiments of the present application.

[0061] The "protocol" involved in the embodiments of the present application may refer to a protocol family in the communication field, a standard protocol with a similar protocol family frame structure, or a related protocol used in future communication systems, and the embodiments of the present application do not make specific limitations on this.

[0062] In the embodiments of the present application, descriptions such as "when...", "in the case of...", "if" and "if" all mean that the device will make corresponding processing under certain objective circumstances. It does not limit the time, nor does it require the device to have a judgment action when implementing it, nor does it mean that there are other limitations.

[0063] In the description of the embodiments of the present application, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship. For example, A / B can represent A or B; "and / or" in the embodiments of the present application is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. These three situations, where A and B can be singular or plural. In addition, in the description of the embodiments of the present application, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple. In addition, in order to facilitate the clear description of the technical solution of the embodiments of the present application, in the embodiments of the present application, the words "first" and "second" are used to distinguish the same or similar items with basically the same functions and effects. Those skilled in the art will appreciate that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit the difference. At the same time, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0064] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0065] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0066] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0067] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0068] In this application, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0069] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0070] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0071] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0072] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0073] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0074] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0075] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0076] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for preparing an antibacterial metal medical material by additive manufacturing, characterized in that: include: Collecting object information of the replaced object, performing information extraction based on additive manufacturing, and forming additive data of the replaced object; According to the additive material data of the replaced object, information on additive material usage is collected, and material usage analysis based on material matching is performed to form additive material usage characteristic data; Collecting additive manufacturing process information, and combining it with the additive material characteristic data, performing process control analysis to form additive process control data; According to the additive process control data, real-time process control information is collected, process monitoring and analysis are performed, and real-time monitoring data for additive manufacturing is formed.

2. The method for preparing antibacterial metal medical materials by additive manufacturing according to claim 1, characterized in that: The collecting of object information of the replaced object, performing information extraction based on additive manufacturing, and forming additive data of the replaced object includes: According to the object information of the replaced object, performing additive analysis based on appearance features and establishing an object printing model; According to the object printing model, mechanical characteristics are assigned in combination with object information to determine mechanical additive information of the object printing model; The object printing model and the corresponding mechanical additive information are combined to form the replaced object additive data.

3. The method for preparing antibacterial metal medical materials by additive manufacturing according to claim 2, characterized in that: The method of performing additive analysis based on appearance features according to the object information of the replaced object and establishing an object printing model includes: Extracting size information of the replaced object according to the object information of the replaced object; Model construction is performed by combining all the size information of the replaced object to form an object size model of the replaced object.

4. The method for preparing antibacterial metal medical materials by additive manufacturing according to claim 3, characterized in that: The step of assigning mechanical characteristics based on the object printing model and combining object information to determine mechanical additive information of the object printing model includes: Determining the object volume of the replaced object according to the object printing model; According to the object information, the object weight of the replaced object is extracted, and combined with the object volume, the object density of the replaced object is determined. ; According to the object density , collect the average density and the object density The elastic modulus of the same different objects , determine the average elastic model , and the average elastic model Assigning the object printing model to form the object elastic modulus of the object printing model ,in, , n represents the average density obtained and the object density The same or different numbers of the replaced objects.

5. The method for preparing antibacterial metal medical materials by additive manufacturing according to claim 4, characterized in that: The method collects the additive material information according to the additive material data of the replaced object, and performs material analysis based on material matching to form additive material feature data, including: according to the density of the object , determine different additive ingredients and corresponding material ratio ranges; For different additive ingredients, material matching analysis is performed according to the corresponding material ratio range and in combination with the additive material data of the replaced object to form additive ingredient matching data.

6. The method for preparing antibacterial metal medical materials by additive manufacturing according to claim 5, characterized in that: The method of performing material matching analysis on different additive ingredients according to the corresponding material ratio range and in combination with the additive material data of the replaced object to form additive ingredient matching data includes: Determine the additive manufacturing standard process, determine the additive material ratio density corresponding to different additive ingredients according to the corresponding material ratio range, and form the additive material ratio density function corresponding to the additive ingredient under the additive manufacturing standard process ,in, , k represents the number of the different additive ingredients, Indicates the material ratio range corresponding to the additive ingredient numbered k; According to the ratio density function corresponding to different additive ingredients The additive ingredients with different material ratios are assigned to the object printing model, and the additive material ratio elastic modulus of the object printing model corresponding to different material ratios of the additive ingredients is determined, and a material ratio modulus function corresponding to the additive ingredients under the additive manufacturing standard process is formed. ,in, ; According to the ratio density function and the material ratio modulus function , and combined with the object density and the object elastic modulus , perform material matching analysis of different material ratios to form the additive material matching data.

7. The method for preparing antibacterial metal medical materials by additive manufacturing according to claim 6, characterized in that: The density function according to the ratio and the material ratio modulus function , and combined with the object density and the object elastic modulus , perform material matching analysis of different material ratios to form the additive material matching data, including: According to the ratio density function and the object density , determine the density matching difference function ,in, , α represents the density matching equivalent factor; According to the material ratio modulus function and the object elastic modulus , determine the modulus matching difference function ,in, , β represents the elastic modulus matching equivalent factor; According to the density matching difference function corresponding to the uniform material ratio and the modulus matching difference function , determine the corresponding material matching difference function ,in, ; For different additive ingredients, the difference function is matched according to the corresponding material , determine the corresponding minimum material matching difference , and obtain the minimum material matching difference The corresponding additive material ratio density and additive material ratio elastic modulus, and the additive material ratio density is calibrated as the optimal density of the additive material corresponding to the additive material , the elastic modulus of the additive material ratio is calibrated as the optimal elastic modulus of the additive material corresponding to the additive material ratio ; The optimal proportion of ingredients corresponding to different additive ingredients and the optimal density of the ingredients are collected And the optimal elastic modulus of the ingredients , forming the additive ingredient matching data.

8. The method for preparing antibacterial metal medical materials by additive manufacturing according to claim 7, characterized in that: The collecting of additive manufacturing process information and combining the additive material characteristic data to perform process control analysis to form additive process control data include: Extracting relevant process parameters that affect batch density and batch elastic modulus according to the additive manufacturing process information, and determining parameter control ranges of different relevant process parameters; For different related process parameters, determine the relationship between the deviation value relative to the standard parameter within the corresponding parameter control range and the ingredient density influence amount of the optimal ingredient ratio in different additive ingredients, and form process density influence relationship information of different related process parameters under the optimal ingredient ratio of the additive ingredients; For different related process parameters, determine the relationship between the deviation value relative to the standard parameter within the corresponding parameter control range and the influence amount of the elastic modulus of the ingredients of the optimal proportion of the ingredients in different additive ingredients, and form process modulus influence relationship information of different related process parameters under the optimal proportion of the ingredients of the additive ingredients; For different additive ingredients, according to the process density influence relationship information and the process modulus influence relationship information corresponding to different relevant process parameters under the corresponding optimal ingredient ratio, the adjustment amount of different relevant process parameters is determined so that the optimal density of the ingredients is adjusted. and the optimum elastic modulus of the ingredients The adjustment is used to obtain the minimum value of the following formula and calibrate it as the minimum process matching difference : , represents the total density adjustment amount of the additive ingredient numbered k for the optimal density of the ingredient after the different related process parameters are adjusted relative to the standard parameters within the corresponding parameter control range under the optimal ingredient ratio, is the total adjustment of the elastic modulus of the optimal elastic modulus of the additive ingredient numbered k after adjusting the different related process parameters relative to the standard parameters within the corresponding parameter control range under the optimal ingredient ratio; for different additive ingredients, determine the minimum matching difference of the process The minimum value of the invention is determined, the adjustment amount of the different related process parameters corresponding to the minimum value is determined as the corresponding process control amount, the additive material corresponding to the minimum value is determined as the substitute material, the optimal material ratio corresponding to the substitute material is determined as the substitute material ratio, and the additive material corresponding to the minimum value is determined as the substitute material ratio. Determine the print density , the minimum value corresponding to Determined as the print elastic modulus ; The process control amount of the relevant process parameters, the alternative ingredient ratio, the printing density And the printed elastic modulus , forming the additive process control data.

9. The method for preparing antibacterial metal medical materials by additive manufacturing according to claim 8, characterized in that: The method of collecting real-time process control information based on the additive process control data, performing process monitoring and analysis, and forming additive manufacturing real-time monitoring data includes: Collect real-time printing volume and real-time print weight , determine the real-time printing density ,in, According to the real-time printing density and the print density , perform printing process monitoring and analysis to form the additive manufacturing real-time monitoring data.

10. The method for preparing antibacterial metal medical materials by additive manufacturing according to claim 9, characterized in that: The real-time printing density and the print density , perform printing process monitoring and analysis to form the additive manufacturing real-time monitoring data, including: Setting the allowable process deviation , and according to the real-time printing density and the print density , perform the following printing process monitoring and analysis: like , then the normal information of printing monitoring is formed; like ,and , then the printing monitoring information is too confidential; like ,and , then the printing monitoring information will be generated.

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