Preparation method of an antibacterial metal medical material for additive manufacturing

Abstract

The present invention provides a preparation method for an additive manufacturing antibacterial metal medical material, which relates to the technical field of the preparation of antibacterial metal medical materials. The method includes collecting object information of the object to be replaced, performing information extraction based on additive manufacturing to form additive data of the object to be replaced; according to the additive data of the object to be replaced, collecting additive material information, and performing material usage analysis based on material matching to form additive material characteristic data; collecting additive manufacturing process information, and combining with the additive material characteristic data, performing process control analysis to form additive process control data; according to the additive process control data, collecting real-time process control information, and performing process monitoring analysis to form additive manufacturing real-time monitoring data. By adopting the additive manufacturing method to control the component ratio and mechanical properties of the antibacterial metal medical material, the method ensures that the antibacterial metal medical material has more excellent use characteristics.

Description

Technical Field

[0001] The present invention relates to the technical field of the preparation of antibacterial metal medical materials, and more particularly, to a preparation method of an antibacterial metal medical material by additive manufacturing. Background Art

[0002] Biomedical metal materials are metals or alloys used for biomedical materials, also known as surgical metal materials, which are a type of inert materials. Such 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 applications of such materials are very extensive, covering various aspects such as hard tissues, soft tissues, artificial organs, and surgical aids. With the progress of technology, adding a certain amount of other metals to biomedical metal materials can achieve a better antibacterial effect.

[0003] Although biomedical metals have antibacterial properties after adding appropriate other metals, since the metal materials themselves have a higher density than the tissues such as bones in the body they replace, they are prone to cause stress shielding, resulting in unreasonable use and damage to other associated biological structures. Therefore, it is necessary to reasonably design and control the weight of biomedical metals. With the development of additive manufacturing technology, it has become possible to more reasonably control the density and manufacturing accuracy of the preparation 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, designing a preparation method of an antibacterial metal medical material by additive manufacturing, through the use of additive manufacturing to control the composition ratio and mechanical properties of the antibacterial metal medical material, ensuring that the antibacterial metal medical material has more excellent use characteristics, is an urgent problem to be solved at present. Summary of the Invention

[0005] The purpose of the present invention is to provide a preparation method of an antibacterial metal medical material by additive manufacturing. By extracting the printing characteristics of the human tissue to be replaced by the antibacterial metal medical material based on additive manufacturing, relevant human tissue characteristic information about additive manufacturing is obtained, and then the composition content of the antibacterial metal medical material that can be replaced is reasonably proportioned. At the same time, considering the influence of the process on the printing result, reasonable material proportion control data is determined to achieve accurate and reasonable control of the entire additive manufacturing process, ensuring that the antibacterial metal medical material formed by additive manufacturing can better match the replaced human tissue in terms of use performance and enhancing the superiority of the use characteristics of the antibacterial metal medical material.

[0006] In a first aspect, the present invention provides a method for preparing an antibacterial metal medical material by additive manufacturing, which includes collecting object information of the object to be replaced, performing information extraction based on additive manufacturing to form additive data of the object to be replaced; collecting additive material information according to the additive data of the object to be replaced, and performing material usage analysis based on material matching to form additive material characteristic data; collecting additive manufacturing process information, and combining with the additive material characteristic data to perform process control analysis to form additive process control data; collecting real-time process control information according to the additive process control data, and performing process monitoring analysis to form real-time monitoring data of additive manufacturing.

[0007] In the present invention, the method extracts the printing characteristics based on additive manufacturing for the human tissue to be replaced by the antibacterial metal medical material, obtains the relevant human tissue characteristic information about additive manufacturing, and then rationally proportions the component content of the antibacterial metal medical material that can be replaced. At the same time, considering the influence of the process on the printing result, it determines the reasonable material proportion control data, realizes the accurate and reasonable control of the entire additive manufacturing process, and ensures that the antibacterial metal medical material formed by additive manufacturing can better match the replaced human tissue in terms of performance, enhancing the superiority of the usage characteristics of the antibacterial metal medical material.

[0008] As a possible implementation, collecting object information of the object to be replaced, performing information extraction based on additive manufacturing to form additive data of the object to be replaced includes: performing additive analysis based on appearance characteristics according to the object information of the object to be replaced to establish an object printing model; endowing mechanical characteristics according to the object printing model and combining with the object information to determine the mechanical additive information of the object printing model; combining the object printing model and the corresponding mechanical additive information to form additive data of the object to be replaced.

[0009] In the present invention, when extracting the features of the object to be replaced regarding additive manufacturing information, two aspects are mainly considered. One is that the finished material formed by additive manufacturing can be highly interchangeable with the object to be replaced in terms of position and shape. Therefore, the extracted feature information must include the shape and size features of the object to be replaced. Considering the process of additive manufacturing, the extraction target of the features is the printing model of the object to be replaced, that is, to form model data that can be recognized by the printing device. The other is that since the metal material is used in additive manufacturing, there are significant differences in density and elastic modulus compared with the object to be replaced, and this difference is macroscopically reflected in weight and mechanical properties, which directly affects the interchangeability between the additive manufacturing material and the object to be replaced. Therefore, the density and elastic modulus data of the object to be replaced are extracted to provide a reference for subsequent control of the additive manufacturing process and ensure that the material formed by additive manufacturing is more matched with the object to be replaced in these properties. Of course, for the feature information of density and elastic modulus, since the process of additive manufacturing needs to be fully considered, after extraction, it is assigned to the printing model to ensure that the analysis and processing of these data information can be synchronously completed when the additive manufacturing obtains and analyzes the model data, and complete and accurate process control data can be formed.

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

[0011] In the present invention, establishing a printing model based on appearance features for the object to be replaced is to extract the size and shape feature information of the object to be replaced 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 size deviation that considers the obvious influence of model data recognition on the manufacturing result, etc., to ensure that the recognition of the model data by additive manufacturing can accurately and reasonably form complete reference data for controlling manufacturing process parameters.

[0012] As a possible implementation method, based on the object printing model and combined with the object information, mechanical features are assigned to determine the mechanical additive information of the object printing model, including: determining the object volume of the object to be replaced according to the object printing model; extracting the object weight of the object to be replaced according to the object information, and combining the object volume to determine the object density of the object to be replaced ; according to the object density , collect the elastic modulus of different objects to be replaced with the same average density and object density , the average elastic model is determined , and the average elastic model is assigned to the object printing model to form the object elastic modulus of the object printing model , where , n represents the number of the replaced objects with the same or different average density and object density .

[0013] In the present invention, it can be understood that most of the replaced objects are human tissues. For the interchange of antibacterial metal medical materials in human tissues, the mechanical properties of the materials must be considered. At the same time, for human tissues, with the differences in age, race, etc., the same tissues will also show different mechanical characteristics. Therefore, to determine reasonable mechanical characteristic information, sufficient data analysis is required. Among them, for density data, it can be determined according to the weight and volume data formed by the printing model information. For the elastic modulus, big data collection with the same density can be carried out based on the density data to obtain reasonable elastic modulus parameters. For obtaining big data based on density data, it is considered that the replaced objects with the same nature have a large degree of similarity in density parameters. Therefore, the obtained data with the same nature has reasonable referenceability.

[0014] As a possible implementation manner, according to the additive manufacturing data of the replaced object, the additive manufacturing material information is collected, and the material consumption analysis based on material matching is carried out to form the additive manufacturing material characteristic data, including: according to the object density , different additive manufacturing ingredients and the corresponding material consumption ratio ranges are determined; for different additive manufacturing ingredients, according to the corresponding material consumption ratio ranges and combined with the additive manufacturing data of the replaced object, the material matching degree analysis is carried out to form the additive manufacturing ingredient matching degree data.

[0015] In the present invention, of course, for the object density, it is considered that the material of the replaced object itself is determined. However, for the antibacterial metal medical materials that are interchangeable with the replaced object, due to the differences in the antibacterial metals, substrates, etc. used, when the density of the material formed by additive manufacturing is close to the density of the replaced object, the ratio combinations between different metal materials are different. Therefore, 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 adjustability of the density by the process and also considering that various combinations can be achieved in terms of density for different ratio combinations, the composition ratio based on density can achieve various different combinations of composition ratios while the combination of metal categories remains unchanged. In this way, the material ratio is a range value when the density is the target, which also provides a wider range of choices for subsequent ratio selection and process parameter control. Additionally, when analyzing the material ratio in combination with the density, the influence of the elastic modulus on the material ratio needs to be considered. After all, the materials formed by different content combinations have obvious or even large differences in mechanical properties, and the elastic modulus is exactly the reference for measuring such characteristic differences. The analysis of the 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 and in combination with the additive data of the replaced object, perform material matching degree analysis to form additive ingredient matching degree data, including: determining the standard process of additive manufacturing, 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 ratio density function corresponding to the additive ingredient under the standard process of additive manufacturing , where , k represents the number of different additive ingredients, represents the material ratio range corresponding to the additive ingredient numbered k; according to the ratio density function corresponding to different additive ingredients, endow the 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 ingredient under the standard process of additive manufacturing , where ; according to the ratio density function and the material ratio modulus function , and in combination with the object density and the object elastic modulus , perform material matching degree analysis of different material ratios to form additive ingredient matching degree data.

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

[0018] As a possible implementation, according to the ratio density function and the material ratio modulus function , and in combination with the object density and the object elastic modulus , perform the material matching degree analysis of different material ratios to form additive ingredient matching degree data, including: according to the ratio density function and the object density , determine the density matching difference function , where , 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 , where , β represents the elastic modulus matching equivalent factor; according to the density matching difference function corresponding to the unified material ratio and the modulus matching difference function , determine the corresponding material matching difference function , where ; for different additive ingredients, according to the corresponding material matching difference function , determine the corresponding minimum material matching difference , and the additive ingredient ratio density and additive ingredient ratio elastic modulus corresponding to obtaining the minimum material matching difference , and calibrate the additive ingredient ratio density as the ingredient optimal density corresponding to the additive ingredient , and calibrate the additive ingredient ratio elastic modulus as the ingredient optimal elastic modulus corresponding to the additive ingredient ; collect the ingredient optimal ratio, ingredient optimal density and ingredient optimal elastic modulus corresponding to different additive ingredients to form additive ingredient matching degree 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 composition combination, this relationship can be combined to match the composition combination with the best material ratio for additive manufacturing when obtaining the density and elastic modulus information of the object to be replaced. It should be noted here that for different composition combinations, within the applicable material ratio range, the closest material ratio is determined by simultaneously considering the closeness of the density and elastic modulus of the material formed by the ratio to the object to be replaced. This closeness is reflected by determining the total deviation value of the density and elastic modulus relative to the object to be replaced. The matching equivalent factor can be set according to the actual situation or determined based on big data analysis. After determining the closest material ratio under different composition combinations, the material matching difference between the best values of these different composition combinations is compared to determine the composition combination closest to the object to be replaced, thereby realizing the determination of the material composition and material ratio used in additive manufacturing.

[0020] As a possible implementation method, the additive manufacturing process information is collected and combined with the additive material characteristic data for process control analysis to form additive process control data, including: extracting the relevant process parameters that affect the ingredient density and ingredient 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 relative to the standard parameter within the corresponding parameter control range and the ingredient density influence amount of the best ingredient ratio in different additive ingredients, and forming the process density influence relationship information of different relevant process parameters under the best ingredient ratio of the corresponding additive ingredient; for different relevant process parameters, determining the relationship between the deviation value relative to the standard parameter within the corresponding parameter control range and the ingredient elastic modulus influence amount of the best ingredient ratio in different additive ingredients, and forming the process modulus influence relationship information of different relevant process parameters under the best ingredient ratio of the corresponding additive ingredient; 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 best ingredient ratio, determining the adjustment amount of different relevant process parameters so that the adjustment of the best ingredient density and the best ingredient elastic modulus obtains the minimum value of the following formula and is calibrated as the process minimum matching difference : , represents the total density adjustment amount of the best ingredient density formed by adjusting the different relevant process parameters relative to the standard parameter within the corresponding parameter control range for the additive ingredient numbered k under the best ingredient ratio, is the total adjustment amount of the elastic modulus of the additive ingredient numbered k to the optimal elastic modulus of the ingredient after the adjustment of different relevant process parameters within the corresponding parameter control range under the optimal ingredient ratio; for different additive ingredients, determine the minimum value of the minimum matching difference, determine the adjustment amount of different relevant process parameters corresponding to the minimum value as the corresponding process control amount, determine the additive ingredient corresponding to the minimum value as the alternative ingredient, determine the optimal ingredient ratio corresponding to the alternative ingredient as the alternative ingredient ratio, and determine the as the printing density corresponding to the minimum value, and determine the printing elastic modulus corresponding to the minimum value ; collect the process control amounts of different relevant process parameters, alternative ingredient ratios, printing densities and printing elastic moduli corresponding to the minimum value to form additive manufacturing 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 ratios, it is also necessary to consider the influence of the manufacturing process on the performance characteristics of the material forming the matching object to be replaced. Such as the control of the printing thickness and the uniformity of the gaps during the manufacturing process. Since it will affect the performance such as density and elastic modulus, it is necessary to focus on consideration. This application determines the relevant process parameters that affect density and elastic modulus, delimits the range in which these process parameters can be adjusted, and then selects the parameter values for the adjustment amounts of these relevant process parameters. The selection method is also achieved by planning the comprehensive deviation degree of the relevant process parameter values from density and elastic modulus.

[0022] As a possible implementation method, according to the additive manufacturing process control data, collect real-time process control information, conduct process monitoring and analysis, and form additive manufacturing real-time monitoring data, including: collecting the real-time printing volume and real-time printing weight , determining the real-time printing density , where ; according to the real-time printing density and the printing density , conduct printing process monitoring and analysis to form additive manufacturing real-time monitoring data.

[0023] In the present invention, after determining the material composition and corresponding material ratio used in additive manufacturing and related process parameters during 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 adjustment and guidance can be carried out according to the monitoring and analysis results. Here, considering that the purpose of monitoring is to determine that the manufactured material meets the preset requirements in terms of density and elastic modulus, and the elastic modulus is also determined by the density and related process parameters, thus, monitoring can simply achieve the purpose by monitoring the density data in real time.

[0024] As a possible implementation, based on the real-time printing density and the printing density , the printing process is monitored and analyzed to form real-time monitoring data for additive manufacturing, including: setting an allowable process deviation γ, and based on the real-time printing density and the printing density , the following printing process monitoring and analysis is carried out: if , then normal printing monitoring information is formed; if , and , then over-dense printing monitoring information is formed; if , and , then under-dense printing monitoring information is formed.

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

[0026] The beneficial effects of a preparation method for an antibacterial metal medical material by additive manufacturing provided by the present invention are as follows:

[0027] This method extracts the printing characteristics of the human tissue to be replaced by the antibacterial metal medical material based on additive manufacturing, obtains relevant human tissue characteristic information about additive manufacturing, and then reasonably proportions the component content of the antibacterial metal medical material that can be replaced. At the same time, considering the influence of the process on the printing result, reasonable material proportion control data is determined, realizing the accurate and reasonable control of the entire process of additive manufacturing, ensuring that the antibacterial metal medical material formed by additive manufacturing can better match the replaced human tissue in terms of use performance, and enhancing the superiority of the use characteristics of the antibacterial metal medical material. Description of the Drawings

[0028] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments of the present invention. It should be understood that the following drawings only show certain embodiments of the present invention, and thus should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0029] Figure 1 It is a step diagram of a preparation method of an additive manufacturing antibacterial metal medical material provided by an embodiment of the present invention;

[0030] Figure 2 It is a structural schematic diagram of a preparation system of an additive manufacturing antibacterial metal medical material provided by an embodiment of the present invention. Specific Embodiments

[0031] The following will describe the technical solutions in the embodiments of the present invention in combination with the drawings in the embodiments of the present invention.

[0032] Biomedical metal materials are metals or alloys used for biomedical materials, also known as surgical metal materials, and are a type of inert materials. Such 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 applications of such materials are very extensive, covering various aspects such as hard tissues, soft tissues, artificial organs, and surgical auxiliary equipment. With the progress of technology, adding a certain amount of other metals to biomedical metal materials can achieve a better antibacterial effect.

[0033] Although biomedical metals have antibacterial properties after adding appropriate other metals, due to the fact that the metal materials themselves have a greater density than tissues such as bones in the body they replace, they are prone to causing stress shielding, resulting in unreasonable use and damage to other related biological structures. Therefore, reasonable design and weight control of biomedical metals are required. With the development of additive manufacturing technology, it has become possible to more reasonably control the density and manufacturing accuracy of the preparation of biomedical metals, and at the same time, it is also possible to more reasonably control the content of the added antibacterial metals to ensure the use characteristics of medical materials.

[0034] Reference Figures 1 to 2, an embodiment of the present invention provides a method for preparing an additive manufacturing antibacterial metal medical material. This method extracts the printing characteristics of the human tissue to be replaced by the antibacterial metal medical material based on additive manufacturing, obtains relevant human tissue characteristic information about additive manufacturing, and then rationally proportions the component content of the antibacterial metal medical material that can be replaced. Considering the impact of the process on the printing result, reasonable material proportion control data is determined to accurately and reasonably control the entire process of additive manufacturing, ensuring that the antibacterial metal medical material formed by additive manufacturing can better match the replaced human tissue in terms of performance and enhancing the superiority of the use characteristics of the antibacterial metal medical material.

[0035] The method for preparing an additive manufacturing antibacterial metal medical material specifically includes the following steps:

[0036] S1: Collect the object information of the object to be replaced, perform information extraction based on additive manufacturing, and form the additive data of the object to be replaced.

[0037] Collect the object information of the object to be replaced, perform information extraction based on additive manufacturing, and form the additive data of the object to be replaced, including: perform additive analysis based on appearance characteristics according to the object information of the object to be replaced, and establish an object printing model; endow mechanical characteristics according to the object printing model and combined with the object information, and 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 object to be replaced.

[0038] When extracting the characteristics of the object to be replaced regarding additive manufacturing information, two aspects are mainly considered. One is that the finished material formed by additive manufacturing can achieve a high degree of interchangeability with the object to be replaced in terms of position and shape. Therefore, the extracted characteristic information must include the shape and size characteristics of the object to be replaced. Considering the process of additive manufacturing, the extraction target of the characteristics is the printing model of the object to be replaced, that is, to form model data that can be recognized by the printing device. The other is that since the metal material is used in additive manufacturing, there are significant differences in density and elastic modulus compared with the object to be replaced, and this difference is macroscopically reflected in weight and mechanical properties, which directly affects the interchangeability between the additive manufacturing material and the object to be replaced. Therefore, the density and elastic modulus data of the object to be replaced are extracted to provide a reference for subsequent control of the additive manufacturing process, ensuring that the material formed by additive manufacturing is more matched with the object to be replaced in these properties. Of course, for the characteristic information of density and elastic modulus, since the process of additive manufacturing needs to be fully considered, after extraction, it is given to the printing model to ensure that the additive manufacturing can synchronously complete the analysis and processing of these data information when obtaining and analyzing the model data, and form complete and accurate process control data.

[0039] Based on the object information of the object to be replaced, perform additive analysis based on appearance features and establish an object printing model, including: extracting the dimensional information of the object to be replaced according to the object information of the object to be replaced; combining all the dimensional information of the object to be replaced to perform model construction and form the object dimensional model of the object to be replaced.

[0040] Establishing a printing model based on the appearance features of the replaced object is to extract the dimensional and shape feature information of the replaced object from the object information to establish model data that can be recognized by additive manufacturing. Of course, this includes the dimensional and shape features of the object, as well as the dimensional position positioning of the established model, the numerical accuracy of the shape dimensions, and the dimensional deviations that consider the obvious impact of model data recognition on the manufacturing results, etc., to ensure that the recognition of the model data by additive manufacturing can accurately and reasonably form complete reference data for controlling manufacturing process parameters.

[0041] According to the object printing model and combined with the object information, endow mechanical features, and determine the mechanical additive information of the object printing model, including: determining the object volume of the object to be replaced according to the object printing model; extracting the object weight of the object to be replaced according to the object information, and combining with the object volume to determine the object density of the object to be replaced ; According to the object density , collect the elastic moduli of different objects to be replaced with the same average density and object density , determine the average elastic model , and endow the average elastic model to the object printing model to form the object elastic modulus of the object printing model , where , n represents the numbers of different objects to be replaced with the same average density and object density . the same.

[0042] It can be understood that for most of the replaced objects are human tissues, and for the interchange of antibacterial metal medical materials for human tissues, the mechanical properties of the materials must be considered. At the same time, for human tissues, with the differences in age, race, etc., the same tissues will also show different mechanical characteristics. Therefore, to determine reasonable mechanical feature information, sufficient data analysis is required to achieve. Among them, for density data, it can be determined according to the weight and volume data formed by the printing model information. For the elastic modulus, reasonable elastic modulus parameters can be obtained by collecting big data with the same density based on density data. Considering that the replaced objects with the same nature have a large degree of similarity in density parameters, the obtained identical data has reasonable referenceability.

[0043] S2: Collect additive material usage information based on the additive data of the object to be replaced, and conduct material usage analysis based on material matching to form additive material characteristic data.

[0044] Collect additive material usage information based on the additive data of the object to be replaced, and conduct material usage analysis based on material matching to form additive material characteristic data, including: Based on the object density , determine different additive ingredients and their corresponding material usage ratio ranges; for different additive ingredients, based on the corresponding material usage ratio ranges and combined with the additive data of the object to be replaced, conduct material matching degree analysis to form additive ingredient matching degree data.

[0045] Of course, for the object density, considering that the material of the object to be replaced is determined, and for the antibacterial metal medical materials that are interchanged for the object to be replaced, due to the differences in the antibacterial metals, substrates, etc. used, when the material density formed by additive manufacturing is close to the density of the object to be replaced, the ratio combinations between different metal materials are different. Therefore, 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 adjustability of the density by the process and also considering that multiple combinations can be achieved in terms of density for different ratio combinations, the ingredient ratio based on density can achieve multiple different combinations of ingredient ratios without changing the combination of metal categories. In this way, the material usage ratio is a range value when the density is the target, which also provides a wider range of choices for subsequent ratio selection and process parameter control. In addition, when analyzing the material usage ratio in combination with density, the influence of the elastic modulus on the material usage ratio needs to be considered. After all, materials formed by different content combinations have obvious or even large differences in mechanical properties, and the elastic modulus is exactly a reference for measuring such characteristic differences. The analysis of the matching degree mainly considers the change of the elastic modulus.

[0046] For different additive ingredients, based on the corresponding material usage ratio ranges and combined with the additive data of the object to be replaced, conduct material matching degree analysis to form additive ingredient matching degree data, including: Determine the standard process of additive manufacturing. For different additive ingredients, based on the corresponding material usage ratio ranges, determine the additive material usage ratio density corresponding to different material usage ratios, and form the ratio density function corresponding to the additive ingredient under the standard process of additive manufacturing , where , k represents the number of different additive ingredients, represents the material usage ratio range corresponding to the additive ingredient numbered k; based on the ratio density functions 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 a material ratio modulus function of the additive ingredients corresponding to the standard additive manufacturing process , where ; according to the ratio density function and the material ratio modulus function , and combined with the object density and the object elastic modulus , conduct a material matching degree analysis of different material ratios to form additive ingredient matching degree data.

[0047] For the matching degree analysis, the main purpose is to determine the influence relationship of different material ratios on the elastic modulus, and then establish a direct relationship considering the material ratios that affect the elastic modulus of the material. Of course, since the situation of the material ratio determines both the elastic modulus of the material and the density situation, when analyzing the matching data, the material ratio is used as the basic data to determine the two parameters of density and elastic modulus at the same time.

[0048] According to the ratio density function and the material ratio modulus function , and combined with the object density and the object elastic modulus , conduct a material matching degree analysis of different material ratios to form additive ingredient matching degree data, including: according to the ratio density function and the object density , determine the density matching difference function , where , 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 , where , β represents the elastic modulus matching equivalent factor; according to the density matching difference function and the modulus matching difference function corresponding to the unified material ratio, determine the corresponding material matching difference function , where ; for different additive ingredients, according to the corresponding material matching difference function , determine the corresponding minimum material matching difference , and the additive material ratio density and additive material ratio elastic modulus corresponding to obtaining the minimum material matching difference , and calibrate the additive material ratio density as the corresponding best density of the additive ingredient , calibrate the elastic modulus of the additive material ratio to the optimal elastic modulus of the corresponding additive ingredient ; collect the optimal ratio, optimal density and optimal elastic modulus of the additive ingredient , and form the additive ingredient matching degree data.

[0049] After determining the relationship between different material ratios and the density and elastic modulus of the formed material under the same composition combination, this relationship can be combined to match the optimal composition combination of the additive manufacturing material ratio when obtaining the density and elastic modulus information of the replaced object. It should be noted here that for different composition combinations, within the applicable material ratio range, the closest material ratio is determined by considering the closeness of the density and elastic modulus of the material formed by the ratio to the replaced object. This closeness 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 the actual situation or determined based on big data analysis. After determining the closest material ratio under different composition combinations, compare the optimal values of these different composition combinations for the material matching difference to determine the composition combination closest to the replaced object, thereby realizing the determination of the material composition and material ratio used in additive manufacturing.

[0050] S3: Collect additive manufacturing process information, and combine it with additive material characteristic data to conduct process control analysis and form additive process control data.

[0051] Collect additive manufacturing process information, and combine it with additive material characteristic data to conduct process control analysis and form additive process control data, including: according to the additive manufacturing process information, extract the relevant process parameters that affect the ingredient density and ingredient elastic modulus, and determine the parameter control range of different relevant process parameters; for different relevant 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 ratio of the additive ingredient, and form the process density influence relationship information of different relevant process parameters under the optimal ratio of the corresponding additive ingredient; for different relevant process parameters, determine the relationship between the deviation value relative to the standard parameter within the corresponding parameter control range and the ingredient elastic modulus influence amount of the optimal ratio of the additive ingredient, and form the process modulus influence relationship information of different relevant process parameters under the optimal ratio of the corresponding additive ingredient; 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 the ingredient, determine the adjustment amount of different relevant process parameters so that the adjustment of the optimal ingredient density and optimal ingredient elastic modulus obtains the minimum value of the following formula and is calibrated as the process minimum matching difference : , represents the total density adjustment amount of the additive ingredient numbered k to the optimal density of the ingredient after the adjustment of different relevant process parameters within the corresponding parameter control range relative to the standard parameter under the optimal ingredient ratio. is the total elastic modulus adjustment amount of the additive ingredient numbered k to the optimal elastic modulus of the ingredient after the adjustment of different relevant process parameters within the corresponding parameter control range relative to the standard parameter under the optimal ingredient ratio; for different additive ingredients, the minimum value of the process minimum matching difference is determined, and the adjustment amounts of different relevant process parameters corresponding to the minimum value are determined as the corresponding process control amounts, the additive ingredient corresponding to the minimum value is determined as the alternative ingredient, the optimal ingredient ratio corresponding to the alternative ingredient is determined as the alternative ingredient ratio, and the corresponding to the minimum value is determined as the printing density , and the corresponding to the minimum value is determined as the printing elastic modulus ; the process control amounts of different relevant process parameters, the alternative ingredient ratio, the printing density and the printing elastic modulus are aggregated to form additive manufacturing process control data.

[0052] For additive manufacturing, after determining the composition of the raw materials used in manufacturing and the corresponding material ratios, it is also necessary to consider the influence of the manufacturing process on the performance characteristics of the material that forms the matching object to be replaced. Such as the control of the printing thickness and the uniformity of the gaps during the manufacturing process. Since it will have an impact on properties such as density and elastic modulus, it needs to be considered emphatically. This application determines the relevant process parameters that affect density and elastic modulus, delimits the range within which these process parameters can be adjusted, and then selects the parameter values for the adjustment amounts of these relevant process parameters. The selection method is also achieved by planning the comprehensive deviation degree of the relevant process parameter values on density and elastic modulus.

[0053] S4: According to the additive manufacturing process control data, collect real-time process control information, conduct process monitoring and analysis, and form additive manufacturing real-time monitoring data.

[0054] According to the additive manufacturing process control data, collect real-time process control information, conduct process monitoring and analysis, and form additive manufacturing real-time monitoring data, including: collecting the real-time printing volume and the real-time printing weight , determining the real-time printing density , where ; according to the real-time printing density and the printing density , conduct printing process monitoring and analysis, and form additive manufacturing real-time monitoring data.

[0055] After determining the material composition and corresponding material ratio used in additive manufacturing and the relevant process parameters during 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 adjustment guidance can be carried out based on the monitoring and analysis results. Here, considering that the purpose of monitoring is to determine that 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 relevant process parameters, thus the monitoring can simply take real-time monitoring of the density data to achieve the purpose.

[0056] According to the real-time printing density and the printing density , conduct monitoring and analysis of the printing process to form real-time monitoring data for additive manufacturing, including: setting the allowable process deviation γ, and according to the real-time printing density and the printing density , conduct the following monitoring and analysis of the printing process: If , then form normal printing monitoring information; if , and , then form over-dense printing monitoring information; if , and , then form under-dense printing monitoring information.

[0057] It can be understood that the difference between the density value obtained in real time and the pre-analyzed density value within an acceptable range is regarded as the manufacturing process being within the control range. If the difference is not within the acceptable range, and the real-time density is greater than the pre-analyzed density, it is considered that too much material is provided in the manufacturing, resulting in an increase in density, and a prompt is given to guide the adjustment of the feed rate. If the difference is not within the acceptable range, and the real-time density is less than the pre-analyzed density, it is considered that too little material is provided in the manufacturing, resulting in a decrease in density, and a prompt is given to guide the adjustment of the feed rate.

[0058] The present invention also provides a preparation system for an additive manufacturing antibacterial metal medical material. The system includes an object data acquisition unit for acquiring object information of the object to be replaced and extracting the information to form additive data of the object to be replaced; a matching analysis unit for obtaining the additive data of the object to be replaced formed by the object data acquisition unit and conducting material usage analysis based on material matching to form additive material feature data; a process control analysis unit for acquiring additive manufacturing process information and conducting process control analysis in combination with the additive material feature data formed by the matching analysis unit to form additive process control data; and a real-time monitoring unit for acquiring real-time process control information and forming real-time monitoring data for additive manufacturing in combination with the additive process control data.

[0059] In summary, the beneficial effects of the preparation method for an additive manufacturing antibacterial metal medical material provided by the embodiments of the present invention are as follows:

[0060] This method extracts the printing features of the human tissue to be replaced by the antibacterial metal medical material based on additive manufacturing, obtains the relevant human tissue feature information related to additive manufacturing, and then rationally proportion the component content of the antibacterial metal medical material that can be replaced. Considering the influence of the process on the printing result, it determines the reasonable material proportion control data, realizes the accurate and reasonable control of the entire additive manufacturing process, and ensures that the antibacterial metal medical material formed by additive manufacturing can better match the replaced human tissue in terms of service performance, enhancing the superiority of the service characteristics of the antibacterial metal medical material.

[0061] In the embodiments of the present application, "indicating" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain piece of information is called the information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated. For example, 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. It is also possible to indirectly indicate the information to be indicated by indicating other information, where there is an association relationship between the other information and the information to be indicated. It is also possible to only indicate a part of the information to be indicated, while the other parts of the information to be indicated are known or pre-agreed. For example, it is also possible to use the arrangement order of each piece of information pre-agreed (such as stipulated in the protocol) to indicate specific information, thereby reducing the indication overhead to a certain extent. At the same time, the common parts of each piece of information can be identified and indicated uniformly to reduce the indication overhead caused by separately indicating the same information.

[0062] In addition, the specific indication method can also be various existing indication methods, such as but not limited to, the above indication methods and their various combinations. The specific details of various indication methods can refer to the prior art and will not be elaborated herein. As described above, for example, when it is necessary to indicate multiple pieces of information of the same type, there may be a situation where the indication methods of different pieces of information are different. In the specific implementation process, the required indication method can be selected according to specific needs. The embodiments of the present application do not limit the selected indication method. In this way, the indication methods involved in the embodiments 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.

[0063] 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 periods and / or sending times of these sub-information can be the same or different. The specific sending method is not limited in the embodiments of the present application. Among them, the sending periods and / or sending times of these sub-information can be predefined, such as predefined according to the protocol, or can be configured by the sending device by sending configuration information to the receiving device.

[0064] "Pre - defined" or "pre - configured" can be achieved by pre - saving the corresponding code, table or other means that can be used to indicate relevant information in the device. The embodiments of the present application do not limit the specific implementation method thereof. Among them, "saving" can refer to 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 the memory can be any form of storage medium, and the embodiments of the present application do not limit this.

[0065] The "protocol" involved in the embodiments of the present application can refer to a protocol family in the communication field, a standard protocol similar to the frame structure of a protocol family, or a relevant protocol applied to a future communication system. The embodiments of the present application do not make specific limitations on this.

[0066] 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 a certain objective situation, not limited to time, and it is not required that the device must have a judgment action during implementation, nor does it mean that there are other limitations.

[0067] 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 may represent A or B. The "and / or" in the embodiments of the present application is merely 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 simultaneously, and B exists alone. Here, A and B can be singular or plural. Also, in the description of the embodiments of the present application, unless otherwise specified, "a plurality of" means two or more than two. "At least one (item)" or its similar expression refers to any combination of these items, including any combination of a single item or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple. Additionally, for the convenience of clearly describing the technical solutions of the embodiments of the present application, in the embodiments of the present application, terms such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and roles. Those skilled in the art can understand that terms such as "first" and "second" do not limit the quantity and execution order, and "first", "second", etc. do not necessarily mean different. At the same time, in the embodiments of the present application, words such as "exemplary" or "for example" are used to represent examples, illustrations, or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly, using words such as "exemplary" or "for example" aims to present relevant concepts in a specific manner for easy understanding.

[0068] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), and this processor may also be other general - purpose processors, digital signal processors (DSPs), application - specific integrated circuits (ASICs), field - programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general - purpose processor may be a microprocessor or this processor may also be any conventional processor, etc.

[0069] 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 ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (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 but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0070] 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 processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (such as infrared, wireless, microwave, etc.) means. 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 collections of available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0071] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood by referring to the context.

[0072] In this application, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or its similar expressions refer 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, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0073] It should be understood that in various embodiments of the present application, the magnitude of the sequence numbers of the above processes does not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0074] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Skilled professionals can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0075] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0076] In several embodiments provided in this 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 merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, 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 displayed or discussed coupling, direct coupling, or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of the devices or units can be in an electrical, mechanical, or other form.

[0077] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0078] In addition, the functional units in each embodiment of this application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0079] When the above-mentioned 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 this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0080] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed by this application can easily think of changes or substitutions, which should all be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A preparation method of an antibacterial metal medical material for additive manufacturing, characterized in that, Including: Collect the object information of the object to be replaced, perform information extraction based on additive manufacturing, and form the additive data of the object to be replaced; According to the additive data of the object to be replaced, collect the additive material information, and perform material usage analysis based on material matching to form the additive material characteristic data, including: According to the object density , determine different additive ingredients and the corresponding range of material usage ratios; For different additive ingredients, according to the corresponding material usage ratio range and combined with the additive data of the object to be replaced, perform material matching degree analysis to form the additive ingredient matching degree data: Determine the standard process for additive manufacturing. For different additive ingredients, according to the corresponding material ratio range, determine the additive material ratio density corresponding to different material ratios, and form the ratio density function corresponding to the additive ingredients under the standard process of additive manufacturing , where , k represents the number of different additive ingredients represents the material ratio range corresponding to the additive ingredient numbered k; According to the ratio density function corresponding to different additive ingredients , assign the 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 , where ; according to the ratio density function and the material ratio modulus function , and combined with the object density and the object elastic modulus , conduct a material matching degree analysis of different material ratios to form the additive ingredient matching degree data; Collect the additive manufacturing process information, and combine it with the additive material characteristic data to perform process control analysis to form the additive process control data; According to the additive process control data, collect the real-time process control information, and perform process monitoring analysis to form the additive manufacturing real-time monitoring data.

2. The preparation method of the additive manufacturing antibacterial metal medical material according to claim 1, characterized in that, The collecting the object information of the object to be replaced, performing information extraction based on additive manufacturing, and forming the additive data of the object to be replaced includes: According to the object information of the object to be replaced, perform additive analysis based on appearance characteristics to establish an object printing model; According to the object printing model and combined with the object information, endow mechanical characteristics 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 object to be replaced.

3. The preparation method of the additive manufacturing antibacterial metal medical material according to claim 2, characterized in that, The performing additive analysis based on appearance characteristics according to the object information of the object to be replaced and establishing an object printing model includes: According to the object information of the object to be replaced, extract the dimensional information of the object to be replaced; Combine all the dimensional information of the object to be replaced to perform model construction to form the object dimensional model of the object to be replaced.

4. The preparation method of the additive manufacturing antibacterial metal medical material according to claim 3, characterized in that The performing mechanical characteristic endowment according to the object printing model and combined with the object information to determine the mechanical additive information of the object printing model includes: According to the object printing model, determine the object volume of the object to be replaced; Extract the object weight of the object to be replaced according to the object information, and combine with the object volume to determine the object density of the object to be replaced ; According to the object density , collect the elastic moduli of different objects to be replaced with the same average density as the object density , and determine the average elastic modulus , and assign the average elastic modulus to the object printing model to form the object elastic modulus of the object printing model , where , , n represents the number of different objects to be replaced with the same average density as the object density .

5. The preparation method of the additive manufacturing antibacterial metal medical material according to claim 1, characterized in that, According to the said ratio density function and the said material ratio modulus function , combined with the said object density and the said object elastic modulus , perform the material matching degree analysis of different material ratios to form the said additive ingredient matching degree data, including: According to the described ratio density function and the object density , a density matching difference function is determined, where , and α represents the density matching equivalent factor; According to the material ratio modulus function and the object elastic modulus , the modulus matching difference function is determined, where , represents the elastic modulus matching equivalent factor; According to the density matching difference function corresponding to the unified material ratio and the modulus matching difference function , determine the corresponding material matching difference function , where ; For different ones of the additive ingredients, a difference function corresponding to the material consumption is matched , to determine a corresponding minimum material consumption matching difference , and to obtain the corresponding additive material ratio density and additive material ratio elastic modulus of the minimum material consumption matching difference, and calibrate the additive material ratio density as the optimal density of the ingredient corresponding to the additive ingredient , and calibrate the additive material ratio elastic modulus as the optimal elastic modulus of the ingredient corresponding to the additive ingredient ; ; Collect the optimal ingredient ratios corresponding to different additive ingredients, the optimal ingredient densities and the optimal elastic moduli of the ingredients , and form the additive ingredient matching degree data.

6. The preparation method of the additive manufacturing antibacterial metal medical material according to claim 5, characterized in that, The collecting the additive manufacturing process information, and combining it with the additive material characteristic data to perform process control analysis to form the additive process control data includes: According to the additive manufacturing process information, extract the relevant process parameters that affect the ingredient density and ingredient elastic modulus, and determine the parameter control range of different relevant process parameters; For different relevant 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 best ingredient ratio in different additive ingredients, and form the process density influence relationship information of different relevant process parameters under the best ingredient ratio of the corresponding additive ingredient; For different relevant process parameters, determine the relationship between the deviation value relative to the standard parameter within the corresponding parameter control range and the ingredient elastic modulus influence amount of the best ingredient ratio in different additive ingredients, and form the process modulus influence relationship information of different relevant process parameters under the best ingredient ratio of the corresponding additive ingredient; For different said additive ingredients, based on the influence relationship information of the process density and the influence relationship information of the process modulus corresponding to different said relevant process parameters under the corresponding best ingredient ratio, determine the adjustment amounts of different said relevant process parameters, so that for the best density of the ingredient and the best elastic modulus of the ingredient the adjustment achieves the minimum value of the following formula, and is calibrated as the process minimum matching difference : , where represents the total density adjustment amount of the best density of the ingredient formed after the relevant process parameters corresponding to the k-th additive ingredient are adjusted relative to the standard parameter within the corresponding parameter control range under the best ingredient ratio of the ingredient, is the total elastic modulus adjustment amount of the best elastic modulus of the ingredient formed after the relevant process parameters corresponding to the k-th additive ingredient are adjusted relative to the standard parameter within the corresponding parameter control range under the best ingredient ratio of the ingredient; for different said additive ingredients, determine the minimum value of the process minimum matching difference , determine the adjustment amounts of different said relevant process parameters corresponding to the minimum value as the corresponding process control amounts, determine the additive ingredient corresponding to the minimum value as the alternative ingredient, determine the best ingredient ratio corresponding to the alternative ingredient as the alternative ingredient ratio, and determine the corresponding to the minimum value as the printing density , and determine the corresponding to the minimum value as the printing elastic modulus ; Aggregate the process control amounts of different said relevant process parameters, the alternative ingredient ratio, the printing density and the printing elastic modulus to form the additive process control data.

7. The preparation method of the additive manufacturing antibacterial metal medical material according to claim 6, characterized in that Collect real-time process control information according to the additive process control data, conduct process monitoring and analysis, and form real-time monitoring data for additive manufacturing, including: collecting real-time printing volume and real-time printing weight , and determining the real-time printing density , where ; According to the real-time printing density and the printing density , monitor and analyze the printing process to form the real-time monitoring data of additive manufacturing.

8. The preparation method of the additive manufacturing antibacterial metal medical material according to claim 7, characterized in that, According to the real-time printing density and the printing density , perform monitoring and analysis of the printing process to form the real-time monitoring data for additive manufacturing, including: setting an allowable process deviation γ, and according to the real-time printing density and the printing density , perform the following printing process monitoring and analysis: If , then the normal printing monitoring information is formed; If and , then over-dense print monitoring information is formed; If and , a printing monitoring sparse information is formed.

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