A large-scale preparation and management method for liquid metal materials for 3D printing

Abstract

The present invention provides a large-scale preparation management method for liquid metal materials for 3D printing, which belongs to the field of data management technology, and specifically comprises: determining the control difficulty coefficients of different preparation links and the optimized preparation links according to the parameter deviation conditions in different preparation links in the number of deviation parameter preparations, determining the optimal scale interval in the available scale interval based on the distribution data and control difficulty coefficient of the optimized preparation links in different available scale intervals, determining the optimized processing scheme of the preparation equipment in the optimized preparation link based on the parameter deviation conditions of the optimized preparation link in the optimal scale interval in different preparation scale intervals and in combination with the economic cost of the preparation equipment in the optimized preparation link, thereby improving the reliability of large-scale processing.

Description

Technical Field

[0001] The present invention belongs to the technical field of data management, and in particular relates to a large-scale preparation management method of liquid metal materials for 3D printing. Background Art

[0002] In the field of 3D printing technology, large devices can be manufactured quickly by using liquid metal for printing. Therefore, liquid metal materials have been widely used in the field of 3D printing. This makes how to achieve large-scale preparation of liquid metal materials for 3D printing a technical problem that needs to be solved urgently.

[0003] In view of the above technical problems, the core is to analyze and manage the data in the material preparation process, and optimize the process in the material preparation process according to the analysis and management results. Specifically, in the invention patent application CN202311070373.1 "High-consistency purified micronized flavonoids preparation management system and method", the process mapping table is used to output the corresponding raw material outbound batching scheme for the preparation task, so as to achieve the preparation of highly consistent purified micronized flavonoids. However, the above technical solution has the following technical problems:

[0004] For liquid metal materials for 3D printing, at different preparation scales, the parameter deviations of different preparation links vary. Therefore, if the preparation scale of the metal material cannot be determined based on the parameter deviations at different preparation scales, it is impossible to improve the preparation quality while ensuring the preparation scale.

[0005] In response to the above technical problems, the present invention proposes a large-scale preparation and management method for liquid metal materials for 3D printing. Summary of the invention

[0006] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0007] According to one aspect of the present invention, a method for managing the large-scale preparation of liquid metal materials for 3D printing is provided.

[0008] A method for large-scale preparation and management of liquid metal materials for 3D printing, specifically comprising:

[0009] S1 divides the historical preparation times into different preparation scale intervals based on the analysis results of the historical preparation data of the liquid metal material, obtains the parameter deviation of the liquid metal material between different historical preparation times in different preparation scale intervals, and uses the parameter deviation to determine the available scale interval in the preparation scale interval;

[0010] S2, based on the parameter deviation, determining the number of preparations of the deviation parameter in the historical preparation times, and determining the control difficulty coefficients of different preparation links and optimizing the preparation links according to the parameter deviations in different preparation links in the number of preparations of the deviation parameter;

[0011] S3: determining the optimal scale interval in the available scale interval based on the distribution data of the optimized preparation links in different available scale intervals and the control difficulty coefficient;

[0012] S4 determines the optimization treatment plan of the preparation equipment in the optimized preparation link based on the parameter deviation of the optimized preparation link in the optimal scale interval in different preparation scale intervals and in combination with the economic cost of the preparation equipment in the optimized preparation link.

[0013] The beneficial effects of the present invention are:

[0014] 1. The available scale intervals in the preparation scale intervals are determined based on the parameter deviations of the liquid metal materials between different historical preparation times in different preparation scale intervals, thereby realizing the determination of the available scale intervals in the preparation scale intervals based on the deviations of the preparation parameters of the liquid metal materials, avoiding the technical problem that the reliability of the preparation results cannot meet the requirements due to the serious parameter deviations in some preparation scale intervals, and also laying the foundation for determining the optimal scale interval.

[0015] 2. The optimization treatment plan for the preparation equipment in the preparation link is determined by optimizing the parameter deviation in different preparation scale ranges and optimizing the economic cost of the preparation equipment in the preparation link. This not only takes into account the economic cost of optimizing the preparation link under the simultaneous production of multiple preparation equipment through parallel processing, but also takes into account the parameter deviation of multiple preparation equipment caused by the difference in preparation scale. This achieves the optimization of the preparation link from the two perspectives of economy and parameter reliability, and improves the economy and reliability of the optimization treatment.

[0016] A further technical solution is that the historical preparation data of the liquid metal material includes parameters and preparation scales of the liquid metal material at different historical preparation times.

[0017] A further technical solution is to divide the historical preparation times into different preparation scale intervals, including:

[0018] The historical preparation times are divided into different preparation scale intervals according to the preparation scale intervals of the preparation scales at different historical preparation times.

[0019] A further technical solution is that the parameter deviation of the liquid metal material includes the deviation of the parameters of the liquid metal material at different latitudes.

[0020] A further technical solution is that the method for determining the available scale interval in the preparation scale interval is:

[0021] Based on the parameter deviation of the liquid metal material between the historical preparation times in the preparation scale interval, the deviation of the parameters of the liquid metal material at different latitudes between different historical preparation times is determined, and the similarity dimension parameters between different historical preparation times are determined by using the deviation of the parameters at different dimensions;

[0022] The similar preparation times between different historical preparation times are determined by the number of similar dimension parameters, and whether the preparation scale interval is an available scale interval is determined by the number ratio of the similar preparation times.

[0023] A further technical solution is that when the proportion of the number of similar preparation times in the preparation scale interval is greater than the proportion of the preset preparation number, the preparation scale interval is determined to be an available scale interval.

[0024] A further technical solution is that the method for determining the optimization treatment scheme of the preparation equipment in the optimization preparation link is:

[0025] Based on the parameter deviation of the optimized preparation link in different preparation scale intervals, the parameter deviation of different dimensions of the optimized preparation link in different preparation scale intervals is determined, and the interval deviation coefficient of the optimized preparation link in different preparation scale intervals is determined based on the average value of the parameter deviation;

[0026] Determine a reference scale interval in the preparation scale interval based on the interval deviation coefficient, and determine the number of parallel settings of the optimized preparation links under different reference scale intervals based on the optimal scale interval and the reference scale interval;

[0027] The total economic cost under different numbers of parallel settings is determined through the economic cost of the preparation equipment in the optimized preparation link, and the comprehensive matching coefficient under different numbers of parallel settings is determined using a preset mapping function through the total economic cost and the interval deviation coefficient, and the optimized processing plan for the preparation equipment in the optimized preparation link is determined based on the comprehensive matching coefficient.

[0028] A further technical solution is to determine an optimization processing scheme for the preparation equipment in the optimization preparation link according to the comprehensive matching coefficient, which specifically includes:

[0029] The parallel setting number with the largest comprehensive matching coefficient is used as the recommended parallel setting number, and the optimized preparation link is processed in parallel with the recommended parallel setting number. The preparation equipment based on the parallel setting processing performs synchronous preparation processing in the optimized preparation link.

[0030] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0031] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0033] Figure 1 It is a flow chart of a method for managing the large-scale preparation of liquid metal materials for 3D printing;

[0034] Figure 2 is a flow chart of a method for determining an available scale interval in a preparation scale interval;

[0035] Figure 3 It is a flow chart of a method for determining a control difficulty coefficient of a preparation step;

[0036] Figure 4 It is a flow chart of the method for determining the optimal size interval. DETAILED DESCRIPTION

[0037] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0038] When preparing liquid metal materials for 3D printing, there are differences in parameter deviations in different preparation links at different preparation scales. Therefore, it is necessary to determine the preparation scale of the metal material based on the parameter deviations at different preparation scales.

[0039] Available scale range: Determine the parameter deviation of the liquid metal material between different historical preparation times within the preparation scale range. When the parameter deviation of the liquid metal material between different historical preparation times is within 3%, the corresponding preparation scale range is taken as the available scale range.

[0040] The control difficulty coefficient of the preparation stage is determined by the proportion of the deviation parameter preparation times in the historical preparation times and the parameter deviation rate of different deviation parameter preparation times. When the proportion of the deviation parameter preparation times is 0.3 and the average value of the parameter deviation rate of different deviation parameter preparation times is 0.05, the control difficulty coefficient is 0.35.

[0041] The optimized preparation process is the preparation process with a control difficulty coefficient greater than 0.3.

[0042] Optimal scale range: It is determined based on the product of the proportion of the number of optimized preparation links under the available scale range and the average value of the control difficulty coefficients of different optimized preparation links. When the proportion of the number of optimized preparation links is 0.6 and the average value of the control difficulty coefficients of different optimized preparation links is 0.4, the deviation coefficient of the available scale range is 0.24. The available scale range with a deviation coefficient less than 0.3 is taken as the optimal scale range.

[0043] Optimization treatment plan: Based on the parameter deviation of the optimized preparation link in the optimal scale range in different preparation scale ranges, determine the preparation scale corresponding to the optimized preparation link, determine the number of preparation equipment in the optimized preparation link according to the economic cost of the preparation equipment in the optimized preparation link and the preset economic cost threshold, and determine the optimization treatment plan for the preparation equipment in different optimized preparation links based on the number of preparation equipment and the preparation scale corresponding to the optimized preparation link.

[0044] To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, a method for large-scale preparation and management of liquid metal materials for 3D printing is provided, which specifically includes:

[0045] S1 divides the historical preparation times into different preparation scale intervals based on the analysis results of the historical preparation data of the liquid metal material, obtains the parameter deviation of the liquid metal material between different historical preparation times in different preparation scale intervals, and uses the parameter deviation to determine the available scale interval in the preparation scale interval;

[0046] Furthermore, the historical preparation data of the liquid metal material includes parameters and preparation scales of the liquid metal material at different historical preparation times.

[0047] It should be noted that the historical preparation times are divided into different preparation scale intervals, including:

[0048] The historical preparation times are divided into different preparation scale intervals according to the preparation scale intervals of the preparation scales at different historical preparation times.

[0049] It can be understood that the parameter deviation of the liquid metal material includes the deviation of the parameters of the liquid metal material at different latitudes.

[0050] Specifically, Figure 2 As shown, the method for determining the available scale interval in the preparation scale interval is:

[0051] Based on the parameter deviation of the liquid metal material between the historical preparation times in the preparation scale interval, the deviation of the parameters of the liquid metal material at different latitudes between different historical preparation times is determined, and the similarity dimension parameters between different historical preparation times are determined by using the deviation of the parameters at different dimensions;

[0052] The similar preparation times between different historical preparation times are determined by the number of similar dimension parameters, and whether the preparation scale interval is an available scale interval is determined by the number ratio of the similar preparation times.

[0053] Furthermore, when the proportion of similar preparation times in the preparation scale interval is greater than the preset preparation quantity proportion, the preparation scale interval is determined to be an available scale interval.

[0054] It should also be noted that the method for determining the available scale interval in the preparation scale interval is:

[0055] Based on the parameter deviation of the liquid metal material between the historical preparation times in the preparation scale interval, determining the deviation of the parameters of the liquid metal material at different latitudes between different historical preparation times;

[0056] Determine the number of historical preparations of the parameters of different dimensions within a preset range using the deviations of the parameters of different dimensions, and determine the preparation stability coefficient of the parameters of different dimensions using the proportion of the historical preparation times within the preset range;

[0057] The parameter stability coefficient of the preparation scale interval is determined by the average value of the preparation stability coefficients of the parameters in different dimensions, and whether the preparation scale interval is an available scale interval is determined based on the parameter stability coefficient.

[0058] Furthermore, when the parameter stability coefficient of the preparation scale interval is greater than a preset stability coefficient threshold, the preparation scale interval is determined to be an available scale interval.

[0059] Optionally, the method for determining the available scale interval in the preparation scale interval includes steps S11-S13, specifically:

[0060] S11 determines the deviation of the parameters of the liquid metal material at different latitudes between different historical preparation times based on the parameter deviation of the liquid metal material between the historical preparation times in the preparation scale interval;

[0061] S12 determines the number of historical preparations of the parameters of different dimensions within a preset range using the deviations of the parameters of different dimensions, and determines the preparation stability coefficient of the parameters of different dimensions using the proportion of the historical preparation times within the preset range;

[0062] S13 determines the deviation of parameters of liquid metal materials in different latitudes between different historical preparation times, and determines the preparation data deviation coefficient between different historical preparation times through the deviation of parameters in different dimensions, determines the parameter stability coefficient of the preparation scale interval based on different preparation data deviation coefficients and preparation stability coefficients of parameters in different dimensions, and determines whether the preparation scale interval is an available scale interval based on the parameter stability coefficient.

[0063] Optionally, before entering step S12, it is also necessary to determine whether the deviations of the parameters of the liquid metal material at different latitudes between different historical preparation times are all within the preset deviation range. When the deviations of the parameters of the liquid metal material at different latitudes between different historical preparation times are all within the preset deviation range, the preparation scale interval is determined to be an available scale interval. When the deviations of the parameters of the liquid metal material at different latitudes between different historical preparation times are not all within the preset deviation range, proceed to step S12.

[0064] Optionally, the above step S11 includes steps S111-S112, which are specifically:

[0065] S111 determines the deviation of the parameters of the liquid metal materials at different latitudes between different historical preparation times based on the parameter deviation of the liquid metal materials between the historical preparation times in the preparation scale interval. When the deviation of the parameters of the liquid metal materials at different latitudes between different historical preparation times are all not within the preset range, it is determined that the preparation scale interval does not belong to the available scale interval. When the deviation of the parameters of the liquid metal materials at different latitudes between different historical preparation times are all within the preset deviation range, the process proceeds to step S112.

[0066] S112 regards the deviations of parameters of liquid metal materials at different latitudes between different historical preparation times as similar preparation times when they are all within the preset deviation range. When the proportion of similar preparation times is greater than the preset similar proportion, it is determined that the preparation scale interval belongs to the available scale interval. When the proportion of similar preparation times is not greater than the preset similar proportion, proceed to step S12.

[0067] Optionally, the above step S12 includes steps S121-S123, specifically:

[0068] S121 determines that the preparation scale interval belongs to the available scale interval by using the deviation of the parameters in different dimensions. When the deviation of the parameters in the dimensions between the historical preparation times is not within the preset range, it is determined that the preparation scale interval belongs to the available scale interval. When the deviation of the parameters in the dimensions between the historical preparation times is not within the preset range, the process proceeds to step S322.

[0069] S122 determines the preparation stability coefficients of parameters of different dimensions based on the proportion of the number of historical preparations within a preset range. If there is no parameter whose preparation stability coefficient does not meet the requirements, the process proceeds to step S13. If there is a parameter whose preparation stability coefficient does not meet the requirements, the process proceeds to step S123.

[0070] S123 determines the deviation times of parameters of different dimensions based on the preparation stability coefficients of parameters of different dimensions and the deviation amounts of parameters at the temperature at different historical preparation times. When there are parameters whose deviation coefficients do not meet the requirements, it is determined that the preparation scale interval does not belong to the available scale interval. When there are no parameters whose deviation coefficients do not meet the requirements, proceed to step S13.

[0071] Optionally, the above step S13 includes steps S131-S132, specifically:

[0072] S131 determines the deviation of the parameters of the liquid metal material at different latitudes between different historical preparation times, and determines the preparation data deviation coefficient between different historical preparation times through the deviation of the parameters at different dimensions. When there is a historical preparation number whose preparation data deviation coefficient does not meet the requirements, it is determined that the preparation scale interval does not belong to the available scale interval. When there is no historical preparation number whose preparation data deviation coefficient does not meet the requirements, it proceeds to step S132.

[0073] S132 determines the parameter stability coefficient of the preparation scale interval based on different preparation data deviation coefficients and preparation stability coefficients of parameters in different dimensions, and determines whether the preparation scale interval is an available scale interval based on the parameter stability coefficient.

[0074] S2, based on the parameter deviation, determining the number of preparations of the deviation parameter in the historical preparation times, and determining the control difficulty coefficients of different preparation links and optimizing the preparation links according to the parameter deviations in different preparation links in the number of preparations of the deviation parameter;

[0075] It can be understood that the method for determining the number of times the deviation parameter is prepared is:

[0076] The historical preparation times whose parameter deviations from other historical preparation times are not within the preset parameter deviation range are taken as the deviation parameter preparation times in the historical preparation times.

[0077] Specifically, Figure 3 As shown, the method for determining the control difficulty coefficient of the preparation link is:

[0078] Determine different parameter deviation amounts of the deviation parameter preparation times in the preparation process based on the parameters in the preparation process and the preset parameter threshold value in the deviation parameter preparation times;

[0079] Determine the number of preparations of deviation parameters with parameter deviations in the preparation link based on different parameter deviations in the preparation link, and use it as the number of preparation link deviations;

[0080] The control difficulty coefficient of the preparation link is determined by the proportion of the number of deviations in the preparation link.

[0081] Furthermore, the control difficulty coefficient of the preparation link ranges from 0 to 1, wherein when the control difficulty coefficient of the preparation link is greater than a preset difficulty coefficient, the preparation link is determined to be an optimized preparation link.

[0082] It can be understood that the number of deviations in the preparation process is the number of deviation parameter preparations in which the parameter deviation amount in the preparation process is greater than a preset parameter deviation threshold.

[0083] It should also be noted that the method for determining the control difficulty coefficient of the preparation step is:

[0084] Determine different parameter deviation amounts of the deviation parameter preparation times in the preparation process based on the parameters in the preparation process and the preset parameter threshold value in the deviation parameter preparation times;

[0085] Determine the average value of the different parameter deviations of the deviation parameter preparation times in the preparation link based on the different parameter deviations in the preparation link, and use it as the parameter deviation average value;

[0086] The control difficulty coefficient of the preparation link is determined by the average value of parameter deviations of different deviation parameter preparation times.

[0087] Optionally, the determination of the control difficulty coefficient of the preparation step includes steps S21-S23, specifically:

[0088] S21 determines different parameter deviation amounts of the deviation parameter preparation times in the preparation process based on the parameters in the preparation process and the preset parameter threshold value in the deviation parameter preparation times;

[0089] S22 determines different parameter deviations of the deviation parameter preparation times in the preparation link based on different parameter deviations in the preparation link, and performs parameter deviation coefficients of different deviation parameter preparation times according to different parameter deviations of the deviation parameter preparation times in the preparation link;

[0090] S23 determines the control difficulty coefficient of the preparation process through the parameter deviation coefficient of different deviation parameter preparation times.

[0091] Furthermore, the control difficulty coefficient of the preparation step is determined according to the average value of the parameter deviation coefficients of different deviation parameter preparation times.

[0092] Optionally, before entering step S22, it is also necessary to determine whether the different parameter deviation amounts of the deviation parameter preparation times in the preparation link are all less than the preset parameter deviation threshold. When the different parameter deviation amounts of the deviation parameter preparation times in the preparation link are all less than the preset parameter deviation threshold, it is directly determined that the preparation link does not belong to the optimized preparation link. When the different parameter deviation amounts of the deviation parameter preparation times in the preparation link are not all less than the preset parameter deviation threshold, then proceed to step S22.

[0093] Optionally, the above step S22 includes steps S221-S223, specifically:

[0094] S221 determines the number of preparation times of the deviation parameter based on the different parameter deviations in the preparation link, and takes the number of preparation times of the deviation parameter with the parameter deviation greater than the preset parameter deviation threshold as the number of preparation link deviations. When the number of preparation link deviations is less than the preset number of deviations threshold, proceed to step S222; when the number of preparation link deviations is not less than the preset number of deviations threshold, proceed to step S223;

[0095] S222 determines whether the average values ​​of the different parameter deviations of the different preparation link deviation times in the preparation link are all within a preset range based on the different parameter deviations of the different preparation link deviation times in the preparation link. If so, directly determines that the preparation link does not belong to the optimized preparation link. If not, proceed to step S223.

[0096] S223 uses the deviation parameter preparation times in the preparation link to perform parameter deviation coefficients for different deviation parameter preparation times. When the parameter deviation coefficients for different deviation parameter preparation times all meet the requirements, it is directly determined that the preparation link does not belong to the optimized preparation link. When there are deviation parameter preparation times whose parameter deviation coefficients do not meet the requirements, it goes to step S23.

[0097] Furthermore, the optimized preparation step is a preparation step in which the difficulty coefficient is controlled to be greater than a preset difficulty coefficient threshold.

[0098] S3: determining the optimal scale interval in the available scale interval based on the distribution data of the optimized preparation links in different available scale intervals and the control difficulty coefficient;

[0099] It should be noted that if Figure 4 As shown, the method for determining the optimal scale interval is:

[0100] Based on the distribution data of the optimized preparation links in the available scale interval, determine the quantity ratio of the optimized preparation links in the available scale interval, and determine the optimized link ratio coefficient in the available scale interval based on the quantity ratio of the optimized preparation links in the available scale interval;

[0101] Determine the mean value of the difficulty coefficient in the available scale interval based on the average values ​​of the control difficulty coefficients of different optimized preparation links in the available scale interval;

[0102] The adaptation deviation coefficient of the available scale interval is determined by multiplying the mean value of the difficulty coefficient by the optimization link proportional coefficient, and whether the available scale interval is the optimal scale interval is determined based on the adaptation deviation coefficient.

[0103] It can be understood that the optimal scale interval is the available scale interval with the smallest adaptation deviation coefficient.

[0104] Optionally, the method for determining the optimal scale interval includes steps S31-S33, specifically:

[0105] S31 determines the quantity ratio of the optimized preparation links in the available scale interval based on the distribution data of the optimized preparation links in the available scale interval, and determines the distribution deviation coefficient of the preparation links in the available scale interval based on the quantity ratio of the optimized preparation links in the available scale interval and the number of interval links between different adjacent optimized preparation links;

[0106] S32 determines the comprehensive control difficulty coefficient under the available scale interval based on the control difficulty coefficients of different optimized preparation links under the available scale interval and in combination with the number of optimized preparation links;

[0107] S33 determines the adaptation deviation coefficient of the available scale interval by multiplying the distribution deviation coefficient of the preparation link by the comprehensive control difficulty coefficient, and determines whether the available scale interval is the optimal scale interval based on the adaptation deviation coefficient.

[0108] Optionally, step S31 includes steps S311-S313, specifically:

[0109] S311 determines the proportion of the number of optimized preparation links in the available scale interval based on the distribution data of the optimized preparation links in the available scale interval. When the proportion of the number of optimized preparation links in the available scale interval is greater than the proportion of the number of preset links, it is determined that the available scale interval does not belong to the optimal scale interval. When the proportion of the number of optimized preparation links in the available scale interval is not greater than the proportion of the number of preset links, the process proceeds to step S312.

[0110] S312 determines the aggregate preparation link in the optimization index link based on the number of interval links between different adjacent optimization preparation links. When the number of aggregate preparation links is greater than the preset number of preparation links, it is determined that the available scale interval does not belong to the optimal scale interval. When the number of aggregate preparation links is not greater than the preset number of preparation links, it proceeds to step S313.

[0111] S313 determines the preparation link distribution deviation coefficient within the available scale interval based on the proportion of the number of optimized preparation links within the available scale interval and the number of interval links between different adjacent optimized preparation links. When the preparation link distribution deviation coefficient does not meet the requirements, it is determined that the available scale interval does not belong to the optimal scale interval. When the preparation link distribution deviation coefficient meets the requirements, proceed to step S32.

[0112] Optionally, the above step S32 includes steps S321-S323, specifically:

[0113] S321 is based on the control difficulty coefficients of different optimized preparation links within the available scale range. When there is an optimized preparation link with a control difficulty coefficient greater than the preset control difficulty coefficient, the process proceeds to step S322. When there is no optimized preparation link with a control difficulty coefficient greater than the preset control difficulty coefficient, the process proceeds to step S323.

[0114] S322: When the number of optimized preparation links whose control difficulty coefficient is greater than the preset control difficulty coefficient is greater than the limit value of the number of preparation links, it is determined that the available scale interval does not belong to the optimal scale interval; when the number of optimized preparation links whose control difficulty coefficient is greater than the preset control difficulty coefficient is not greater than the limit value of the number of preparation links, the process proceeds to step S323;

[0115] S323 determines the comprehensive control difficulty coefficient under the available scale interval based on the control difficulty coefficients of different optimized preparation links and the number of optimized preparation links. When the comprehensive control difficulty coefficient under the available scale interval does not meet the requirements, it is determined that the available scale interval does not belong to the optimal scale interval. When the comprehensive control difficulty coefficient under the available scale interval meets the requirements, proceed to step S33.

[0116] S4 determines the optimization treatment plan of the preparation equipment in the optimized preparation link based on the parameter deviation of the optimized preparation link in the optimal scale interval in different preparation scale intervals and in combination with the economic cost of the preparation equipment in the optimized preparation link.

[0117] Specifically, the method for determining the optimization treatment scheme of the preparation equipment in the optimization preparation link is:

[0118] Based on the parameter deviation of the optimized preparation link in different preparation scale intervals, the parameter deviation of different dimensions of the optimized preparation link in different preparation scale intervals is determined, and the interval deviation coefficient of the optimized preparation link in different preparation scale intervals is determined based on the average value of the parameter deviation;

[0119] Determine a reference scale interval in the preparation scale interval based on the interval deviation coefficient, and determine the number of parallel settings of the optimized preparation links under different reference scale intervals based on the optimal scale interval and the reference scale interval;

[0120] The total economic cost under different numbers of parallel settings is determined through the economic cost of the preparation equipment in the optimized preparation link, and the comprehensive matching coefficient under different numbers of parallel settings is determined using a preset mapping function through the total economic cost and the interval deviation coefficient, and the optimized processing plan for the preparation equipment in the optimized preparation link is determined based on the comprehensive matching coefficient.

[0121] Further, the optimization processing scheme of the preparation equipment in the optimization preparation link is determined according to the comprehensive matching coefficient, specifically including:

[0122] The parallel setting number with the largest comprehensive matching coefficient is used as the recommended parallel setting number, and the optimized preparation link is processed in parallel with the recommended parallel setting number. The preparation equipment based on the parallel setting processing performs synchronous preparation processing in the optimized preparation link.

[0123] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0124] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0125] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A method for large-scale preparation and management of liquid metal materials for 3D printing, characterized in that: Specifically include: Based on the analysis results of historical preparation data of liquid metal materials, the historical preparation times are divided into different preparation scale intervals, parameter deviations of liquid metal materials between different historical preparation times in different preparation scale intervals are obtained, and the available scale intervals in the preparation scale intervals are determined using the parameter deviations; Based on the parameter deviation, the number of preparations of the deviation parameters in the historical preparation times is determined, and the control difficulty coefficients of different preparation links and the determination of the optimized preparation links are performed according to the parameter deviations in different preparation links in the number of preparations of the deviation parameters; Determining the optimal scale interval in the available scale interval based on the distribution data of the optimized preparation links and the control difficulty coefficient under different available scale intervals; Determining an optimization treatment plan for the preparation equipment in the optimized preparation link based on the parameter deviation of the optimized preparation link in different preparation scale intervals and in combination with the economic cost of the preparation equipment in the optimized preparation link; The method for determining the available scale interval in the preparation scale interval is: Based on the parameter deviation of the liquid metal material between the historical preparation times in the preparation scale interval, the deviation of the parameters of the liquid metal material at different latitudes between different historical preparation times is determined, and the similarity dimension parameters between different historical preparation times are determined by using the deviation of the parameters at different dimensions; Determine the similar preparation times between different historical preparation times by the number of similar dimension parameters, and determine whether the preparation scale interval is an available scale interval by the number ratio of the similar preparation times; When the proportion of similar preparation times in the preparation scale interval is greater than the preset preparation quantity proportion, the preparation scale interval is determined to be an available scale interval.

2. The method for large-scale preparation and management of liquid metal materials for 3D printing according to claim 1, characterized in that: The historical preparation data of the liquid metal material includes parameters and preparation scales of the liquid metal material at different historical preparation times.

3. The method for large-scale preparation and management of liquid metal materials for 3D printing according to claim 1, characterized in that: The historical preparation times are divided into different preparation scale intervals, including: The historical preparation times are divided into different preparation scale intervals according to the preparation scale intervals of the preparation scales at different historical preparation times.

4. The method for large-scale preparation and management of liquid metal materials for 3D printing according to claim 1, characterized in that: The parameter deviation of the liquid metal material includes the deviation of the parameters of the liquid metal material at different latitudes.

5. The method for large-scale preparation and management of liquid metal materials for 3D printing according to claim 1, characterized in that: The method for determining the number of times the deviation parameter is prepared is: The historical preparation times whose parameter deviations from other historical preparation times are not within the preset parameter deviation range are taken as the deviation parameter preparation times in the historical preparation times.

6. The method for large-scale preparation and management of liquid metal materials for 3D printing according to claim 1, characterized in that: The method for determining the control difficulty coefficient of the preparation step is: Determine different parameter deviation amounts of the deviation parameter preparation times in the preparation process based on the parameters in the preparation process and the preset parameter threshold value in the deviation parameter preparation times; Determine the number of preparations of deviation parameters with parameter deviations in the preparation link based on different parameter deviations in the preparation link, and use it as the number of preparation link deviations; The control difficulty coefficient of the preparation link is determined by the proportion of the number of deviations in the preparation link.

7. The method for large-scale preparation and management of liquid metal materials for 3D printing according to claim 6, characterized in that: The control difficulty coefficient of the preparation link ranges from 0 to 1, wherein when the control difficulty coefficient of the preparation link is greater than a preset difficulty coefficient, the preparation link is determined to be an optimized preparation link.

8. The method for large-scale preparation and management of liquid metal materials for 3D printing according to claim 1, characterized in that: The number of preparation link deviations is the number of deviation parameter preparations in which a parameter deviation amount is greater than a preset parameter deviation threshold value in the preparation link.

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