A 3D printing material forming device graphical user interaction method and system

Abstract

The present application relates to the technical field of material forming device graphical user interaction, and particularly relates to a 3D printing material forming device graphical user interaction method and system, the method comprising the following steps: obtaining a three-dimensional model file to be printed and selected printing material information; analyzing the three-dimensional model file to obtain geometric feature information, and extracting rheological property data of the selected printing material from a material database based on the selected printing material information; based on the geometric feature information and the rheological property data, predicting actual deposition deviation caused by flow property change of the material in the printing process; generating a compensatory printing parameter adjustment strategy according to the actual deposition deviation, and visually displaying the compensatory printing parameter adjustment strategy and the adjusted expected deposition effect; and applying the compensatory printing parameter adjustment strategy to printing instruction generation. The above can improve the geometric precision and structural integrity of the printed part.

Description

Technical Field

[0001] This invention relates to the technical field of graphical user interaction for material forming devices, and specifically to a graphical user interaction method and system for a 3D printing material forming device. Background Technology

[0002] In industrial production, 3D printing material forming equipment has become an important tool for manufacturing complex, high-precision parts. Operators typically manage printing tasks through a graphical user interface on the equipment, including importing 3D models, setting printing parameters, and displaying printing progress and equipment status in real time. However, with the widespread application of 3D printing technology in precision manufacturing, higher demands are placed on the geometric accuracy, detail precision, and consistency of printed parts. For example, when manufacturing microfluidic chips, precision mechanical parts, or medical devices with complex internal structures, the ability to accurately reproduce feature dimensions, wall thickness, surface smoothness, and internal structures faces significant challenges. Summary of the Invention

[0003] The purpose of this invention is to address the aforementioned shortcomings by proposing a graphical user interaction method and system for a 3D printing material forming device.

[0004] The present invention adopts the following technical solution:

[0005] A graphical user interaction method for a 3D printing material forming device, the method comprising the following steps:

[0006] Obtain the 3D model file to be printed and the information of the selected printing material;

[0007] The 3D model file is analyzed to obtain geometric feature information, and the rheological property data of the selected printing material is extracted from the material database based on the selected printing material information;

[0008] Based on geometric feature information and rheological data, the actual deposition deviation caused by changes in the flow characteristics of the material during the printing process is predicted.

[0009] Based on the actual deposition deviation, a compensatory printing parameter adjustment strategy is generated, and the compensatory printing parameter adjustment strategy and the expected deposition effect after adjustment are visualized.

[0010] A compensatory print parameter adjustment strategy is applied to print command generation.

[0011] Through this technical solution, this application can predict the actual deposition deviation caused by changes in the flow characteristics of the material during the printing process, and generate a compensatory printing parameter adjustment strategy. At the same time, the expected deposition effect after adjustment is visualized, thereby effectively solving the problem that the existing technology cannot predict and compensate for changes in the material flow characteristics, significantly improving the geometric accuracy and structural integrity of the printed parts, and reducing trial and error costs.

[0012] Furthermore, the method also includes the following steps:

[0013] Estimate the maximum drift range of the rheological properties of the selected printing material under prolonged heating;

[0014] Obtain real-time environmental parameters inside the printing cavity;

[0015] Based on the maximum drift range and real-time environmental parameters, dynamic adjustment rules are generated;

[0016] The compensatory printing parameter adjustment strategy is adjusted according to the dynamic adjustment rules.

[0017] Furthermore, the method also includes the following steps:

[0018] During the printing process, material extrusion tests are periodically performed in non-critical areas, and the geometry of the test extrusion line is captured in real time by a high-resolution imaging unit.

[0019] The geometry of the test extrusion line is compared with the design target to obtain the deviation between the current rheological properties of the material and the initial data;

[0020] Based on the deviation, the rheological property data are dynamically adjusted;

[0021] Based on the adjusted rheological data, the actual deposition deviation of subsequent printed layers is re-predicted.

[0022] Furthermore, the steps for generating a compensatory printing parameter adjustment strategy based on actual deposition deviations include:

[0023] Identify regions with complex geometric features in 3D model files;

[0024] Assess the surface roughness, risk of localized stress concentration, and material overlap quality with adjacent areas in regions with complex geometries.

[0025] Identify the potential negative impacts of compensatory printing parameter adjustment strategies on surface roughness, risk of localized stress concentration, and the quality of material overlap with adjacent areas;

[0026] The potential negative impacts are sorted according to the preset print task priority, and the sorting results are obtained.

[0027] Based on actual deposition deviation, sorting results, surface roughness, risk of local stress concentration, and material overlap quality with adjacent areas, a multi-objective collaborative compensation strategy is generated.

[0028] By adjusting multiple compensatory printing parameters, the adverse effects of the multi-objective collaborative compensation strategy on other objectives are minimized while satisfying high-priority objectives.

[0029] Multi-dimensional visualization demonstrates the expected impact of multi-objective collaborative compensation strategies on surface roughness, local stress concentration risk, and the quality of material overlap with adjacent areas.

[0030] Furthermore, the steps for multi-dimensional visualization of the expected impact of the multi-objective collaborative compensation strategy on surface roughness, local stress concentration risk, and material overlap quality with adjacent areas include:

[0031] By dynamically adjusting the transparency or saturation of color coding, the priority of information in different dimensions can be distinguished on the 3D model preview interface.

[0032] Provides an information filtering panel that allows operators to selectively display or hide information in specific dimensions;

[0033] When an operator selects to view information in a specific dimension, the corresponding area on the 3D model preview interface is displayed by zooming in or highlighting the relevant area, and detailed performance indicators for that specific dimension are simultaneously displayed in a dedicated data panel.

[0034] It provides an impact chain analysis function to demonstrate the expected impact of compensatory printing parameter adjustments on geometric accuracy, surface roughness, risk of local stress concentration, and the quality of material overlap with adjacent areas;

[0035] The summary displays the overall impact of compensatory print parameter adjustments on the priority of the overall print job.

[0036] Furthermore, it provides an impact chain analysis function, demonstrating the expected impact of compensatory printing parameter adjustments on geometric accuracy, surface roughness, risk of localized stress concentration, and material overlap quality with adjacent areas. The steps include:

[0037] Identify the material types and the locations of overlap interfaces between materials in collaborative printing;

[0038] Based on the material type used in collaborative printing, establish the influence relationships of parameters, properties, and quality within each material.

[0039] For the interface locations between materials, data on the interfacial bonding force and the difference in the interfacial thermal expansion coefficient between different materials are extracted from the material database.

[0040] Based on interfacial bonding force data and interfacial thermal expansion coefficient difference data, the cross-material interface influence relationship is established. The cross-material interface influence relationship includes the expected impact of a material's compensatory printing parameter adjustment on the extrusion behavior of adjacent materials, as well as the expected impact on the interfacial bonding quality.

[0041] The influence relationships of parameters, properties, and quality within each material are integrated with the influence relationships across material interfaces to form an overall influence chain;

[0042] When an operator adjusts the compensating printing parameters for any material, the overall impact chain demonstrates the expected effects of the adjustment on geometric accuracy, surface roughness, risk of localized stress concentration, and the quality of material overlap with adjacent areas. It also indicates the expected effects on the extrusion behavior of adjacent materials and the expected effects on the quality of interfacial bonding.

[0043] Furthermore, when the operator adjusts the compensating printing parameters for any material, the expected impact of the adjustment on geometric accuracy, surface roughness, risk of localized stress concentration, and the quality of material overlap with adjacent areas is demonstrated through the overall influence chain. The steps involved in the expected impact on the extrusion behavior of adjacent materials and the expected impact on interfacial bonding quality are also outlined:

[0044] Before printing, rheological property calibration tests are performed on each batch of materials to obtain calibrated rheological property data;

[0045] During the printing process, multi-material extrusion tests are periodically performed in non-critical areas, and the geometry of the extrusion lines of each material and the geometry of the material overlap interface are captured in real time by a high-resolution imaging unit.

[0046] The geometry of the extrusion line for each material test is compared with the design expectation to obtain the deviation between the current rheological properties of each material and the calibrated rheological property data.

[0047] The geometry of the material interface is compared with the design benchmark to obtain the deviation between the interface bonding quality and the preset target.

[0048] Based on the deviation between the current rheological properties of each material and the calibrated rheological property data, and the deviation between the interface bonding quality and the preset target, the influence relationships of parameters, properties, and quality within each material in the overall influence chain, as well as the influence relationships across material interfaces, are dynamically adjusted.

[0049] Based on the adjusted overall impact chain, the expected impact of compensatory printing parameter adjustments on geometric accuracy, surface roughness, risk of local stress concentration, and material overlap quality with adjacent areas is updated and displayed in real time, as well as the expected impact on the extrusion behavior of adjacent materials and the expected impact on interface bonding quality.

[0050] Furthermore, during the printing process, the steps of periodically performing multi-material extrusion tests in non-critical areas include:

[0051] Identify key printing areas in 3D model files that have high geometric accuracy requirements or complex structures;

[0052] Analyze the material extrusion path, printing speed variation, and thermal environment characteristics of the interface between adjacent materials in the key printing area.

[0053] In non-critical areas, test areas that are similar to the material extrusion path, printing speed variation, and thermal environment characteristics of the interface between adjacent materials in critical printing areas are selected.

[0054] Multi-material extrusion tests were conducted within similar test areas to simulate the material extrusion path, printing speed variations, and thermal environment characteristics of the interface between adjacent materials in key printing areas.

[0055] Furthermore, within similar test areas, the steps for conducting multi-material extrusion tests, simulating material extrusion paths, printing speed variations, and thermal environment characteristics at the interfaces between adjacent materials in key printing areas, include:

[0056] Within a test area with similarity, microstructures with geometry and size similar to the key printed area are set up;

[0057] Multi-material extrusion tests were conducted in test areas with similar microstructures to simulate the material extrusion path, printing speed variation, and thermal environment characteristics of the interface between adjacent materials in key printing areas.

[0058] In-situ monitoring technology is used to obtain physical parameters in real time during the solidification process of materials within the microstructure.

[0059] Based on the physical parameters during the curing process of materials within the microstructure, in-situ monitoring technology is used to obtain the physical parameters during the interface formation process within the microstructure in real time.

[0060] This application also discloses a graphical user interaction system for a 3D printing material forming device, applied to a graphical user interaction method for a 3D printing material forming device. The system includes:

[0061] The information acquisition module is used to acquire the 3D model file to be printed and the information of the selected printing material;

[0062] The data processing module analyzes the 3D model file to obtain geometric feature information and extracts the rheological property data of the selected printing material from the material database based on the selected printing material information.

[0063] The prediction module, based on geometric feature information and rheological data, predicts the actual deposition deviation caused by changes in the flow characteristics of the material during the printing process.

[0064] The strategy processing module generates a compensatory printing parameter adjustment strategy based on the actual deposition deviation, and visualizes the compensatory printing parameter adjustment strategy and the expected deposition effect after adjustment.

[0065] The instruction application module applies a compensatory printing parameter adjustment strategy to the generation of printing instructions.

[0066] Through this technical solution, the system, with its modular design, can efficiently complete functions such as information acquisition, data processing, deviation prediction, strategy generation, and command application. It provides powerful graphical user interaction capabilities for 3D printing material forming devices, thereby effectively solving the problem of not being able to predict and compensate for changes in material flow characteristics in existing technologies. It significantly improves the geometric accuracy and structural integrity of printed parts and reduces trial and error costs.

[0067] This application, by introducing the analysis of material rheological property data and the prediction of actual deposition deviations, can identify potential printing defects in advance and generate targeted compensation strategies. More importantly, this application visualizes the compensatory printing parameter adjustment strategy and the expected deposition effect after adjustment, allowing operators to intuitively see the effect of the compensation measures. This enables them to have a more accurate expectation of the printing result before printing, avoiding a "black box" optimization process. Therefore, this application can significantly improve the geometric accuracy, detail refinement, and consistency of 3D printed parts, reduce trial and error costs and time, and improve the efficiency and reliability of 3D printing technology in the field of precision manufacturing.

[0068] To further understand the features and technical content of the present invention, please refer to the following detailed description and drawings of the present invention. However, the drawings provided are for reference and illustration only and are not intended to limit the present invention. Attached Figure Description

[0069] Figure 1 This is a flowchart of a graphical user interaction method for a 3D printing material forming device according to the present invention.

[0070] Figure 2 This is a schematic diagram of the graphical user interaction system of a 3D printing material forming device according to the present invention. Detailed Implementation

[0071] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can understand the advantages and effects of the present invention from the content disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and various details in this specification can also be modified and changed based on different viewpoints and applications without departing from the spirit of the present invention. Furthermore, the accompanying drawings of the present invention are for simple illustrative purposes only and are not depictions of actual dimensions; this is stated in advance. The following embodiments will further describe the relevant technical content of the present invention in detail, but the disclosed content is not intended to limit the scope of protection of the present invention.

[0072] This embodiment provides a graphical user interaction method and system for a 3D printing material forming device, combined with... Figure 1 and Figure 2 As shown.

[0073] refer to Figure 1 A graphical user interaction method for a 3D printing material forming device, the method comprising the following steps:

[0074] Obtain the 3D model file to be printed and the information of the selected printing material;

[0075] The 3D model file is analyzed to obtain geometric feature information, and the rheological property data of the selected printing material is extracted from the material database based on the selected printing material information;

[0076] Based on geometric feature information and rheological data, the actual deposition deviation caused by changes in the flow characteristics of the material during the printing process is predicted.

[0077] Based on the actual deposition deviation, a compensatory printing parameter adjustment strategy is generated, and the compensatory printing parameter adjustment strategy and the expected deposition effect after adjustment are visualized.

[0078] A compensatory print parameter adjustment strategy is applied to print command generation.

[0079] This application effectively solves the printing accuracy problem caused by changes in material rheological properties in traditional 3D printing by predicting the actual deposition deviation of the material during the printing process and generating a compensatory printing parameter adjustment strategy. It significantly improves the geometric accuracy, detail fineness and consistency of printed parts, reduces trial and error costs and improves production efficiency.

[0080] The method proposed in this application is mainly applied to the graphical user interface of a 3D printing material forming device, aiming to optimize the material deposition accuracy during the printing process. Here, "3D model file" refers to a data file describing the geometry and structure of the object to be printed, such as an STL, OBJ, or AMF format file. "Printing material information" includes material type, brand, batch, etc., which is used to retrieve corresponding "rheological property data" from the "material database." "Rheological property data" refers to data describing the material's viscosity, yield stress, and other rheological parameters at different temperatures and shear rates. "Geometric feature information" refers to geometric details extracted from the 3D model, such as wall thickness, curvature, pore size, and corners. "Actual deposition deviation" refers to the difference between the actual amount or shape of deposited material and the design expectation due to changes in rheological properties during the printing process. "Compensatory printing parameter adjustment strategy" refers to the adjustment scheme for printing parameters (such as extrusion ratio, printing speed, nozzle temperature, etc.) to correct the actual deposition deviation. "Expected deposition effect" refers to the anticipated material deposition state after applying the compensation strategy.

[0081] In practice, the first step is to obtain the 3D model file to be printed and the information of the selected printing material. For example, the operator can upload an STL format 3D model file through the graphical user interface and select "PLA material, brand A, batch number 20230101" from the drop-down menu. This information is then received by the system and used for subsequent processing.

[0082] Next, the system analyzes the 3D model file to obtain geometric feature information and extracts the rheological property data of the selected printing material from the material database based on the selected printing material information. For example, the system can parse STL files, identify geometric features such as thin-walled regions, sharp corners, and pinholes in the model, and calculate their dimensions and curvature. Simultaneously, based on the operator's selection of "PLA material, brand A, batch number 20230101," the system will search and extract rheological property data such as viscosity curves and shear thinning index of that batch of PLA material at different temperatures and shear rates from the preset material database.

[0083] Subsequently, based on geometric feature information and rheological data, the system predicts the actual deposition deviation caused by changes in the flow characteristics of the material during printing. For example, for a thin-walled region in the model, the system combines the printing speed of that region (determined by geometric features) and the shear thinning characteristics of the PLA material (determined by rheological data) to predict the actual viscosity change of the material at that printing speed, and then estimates the deviation between the actual extrusion amount and the expected extrusion amount. For example, it predicts that the actual thickness of the thin-walled region may be 0.05 mm thinner than the design value.

[0084] Based on the actual deposition deviation, the system generates a compensatory printing parameter adjustment strategy and visualizes the strategy and the expected deposition effect after adjustment. For example, for the predicted thickness deviation of 0.05mm in the thin-walled area mentioned above, the system may generate a strategy suggesting increasing the extrusion ratio by 2% or reducing the printing speed by 5% during the printing process in that area. Subsequently, on the graphical user interface, the system compares and displays the original 3D model with the expected deposition effect after applying the compensation strategy. For example, it may use color coding or overlay display to intuitively show that the thin-walled area will reach the design thickness after adjustment, or it may simulate the printing path and material deposition to show the adjusted print linewidth and overlap.

[0085] Finally, the system applies compensatory printing parameter adjustment strategies to print instruction generation. For example, when generating G-code (print instructions), the system integrates the above adjustment strategies into the corresponding print path segments to ensure that when the printer reaches thin-walled areas, it can automatically print according to the adjusted extrusion ratio or print speed, thereby achieving more accurate material deposition.

[0086] This application further proposes a graphical user interaction method for a 3D printing material forming device, which includes the following steps:

[0087] Estimate the maximum drift range of the rheological properties of the selected printing material under prolonged heating;

[0088] Obtain real-time environmental parameters inside the printing cavity;

[0089] Based on the maximum drift range and real-time environmental parameters, dynamic adjustment rules are generated;

[0090] The compensatory printing parameter adjustment strategy is adjusted according to the dynamic adjustment rules.

[0091] Specifically, estimating the maximum drift range of the rheological properties of the selected printing material under prolonged heating refers to determining, before printing begins or upon material warehousing, the maximum possible change in the rheological properties (such as viscosity, shear thinning behavior, etc.) of a particular printing material under prolonged exposure to printing temperatures (e.g., several hours or even longer) through experimental testing, supplier data, or historical data analysis. This maximum drift range can be represented as the upper and lower limits of the rheological property parameters, and its purpose is to provide an expected boundary for subsequent dynamic adjustments.

[0092] Acquiring real-time environmental parameters within the printing cavity can be understood as using various sensors integrated into the 3D printing device to monitor environmental conditions such as temperature, humidity, and air pressure inside the printing cavity in real time. For example, thermocouples or infrared sensors can be used to acquire real-time temperature data, and humidity sensors can be used to acquire real-time humidity data. The purpose is to capture external factors that may affect the rheological properties of the material during the printing process.

[0093] In practical applications, dynamic adjustment rules are generated based on the maximum drift range and real-time environmental parameters. Specifically, this involves using the estimated maximum drift range as a reference, combined with real-time acquired environmental parameters within the printing cavity, and establishing a mapping relationship between changes in environmental parameters and the actual drift of material rheological properties through a pre-defined algorithm model, lookup table, or machine learning model. These rules define how the rheological properties will deviate from their initial values ​​when specific changes occur in environmental parameters, and how this deviation should be compensated for by adjusting printing parameters. The purpose is to provide a basis for the dynamic correction of subsequent compensatory printing parameter adjustment strategies.

[0094] Furthermore, adjusting the compensatory printing parameter adjustment strategy according to dynamic adjustment rules means that once the dynamic adjustment rules are generated, the system continuously monitors real-time environmental parameters. When changes in environmental parameters are detected, or based on the estimated material drift trend, the system calculates the necessary correction amount for the current compensatory printing parameter adjustment strategy in real time according to the dynamic adjustment rules. For example, if an increase in the printing cavity temperature is detected, leading to a decrease in material viscosity, the dynamic adjustment rules may instruct the system to slightly reduce the extrusion temperature or increase the printing speed to maintain stable material deposition. The purpose is to ensure that the actual material deposition effect remains consistent with the expected target throughout the entire printing process.

[0095] In some preferred embodiments, assuming a large and complex polymer part needs to be printed, the viscosity of the polymer material gradually decreases under prolonged high temperatures. Before printing begins, the system estimates the maximum percentage decrease in viscosity that may occur after 8 hours of continuous heating, based on the properties of the polymer material, and determines the maximum drift range of its rheological properties. During printing, a temperature sensor within the printing chamber monitors the chamber temperature in real time. For example, if the system detects that the chamber temperature is slightly higher than the set value after 4 hours of printing, a dynamic adjustment rule is triggered based on the estimated drift range and real-time temperature data. This rule might indicate that, due to the expected further decrease in material viscosity, the extrusion rate needs to be slightly reduced by 0.5%, and the nozzle temperature fine-tuned by 0.2°C, to maintain consistency in extrusion rate and deposition width. The system then adjusts the currently executing compensatory printing parameter adjustment strategy in real time according to these dynamic adjustment rules, ensuring that the deposition accuracy of subsequent printed layers is not affected by the drift of the material's rheological properties.

[0096] This application further proposes a graphical user interaction method for a 3D printing material forming device, which includes the following steps:

[0097] During the printing process, material extrusion tests are periodically performed in non-critical areas, and the geometry of the test extrusion line is captured in real time by a high-resolution imaging unit.

[0098] The geometry of the test extrusion line is compared with the design target to obtain the deviation between the current rheological properties of the material and the initial data;

[0099] Based on the deviation, the rheological property data are dynamically adjusted;

[0100] Based on the adjusted rheological data, the actual deposition deviation of subsequent printed layers is re-predicted.

[0101] Specifically, during the printing process, to monitor changes in the material's rheological properties in real time, extrusion tests can be periodically performed in non-critical areas. Non-critical areas refer to regions where the final product's geometric accuracy or functionality requirements are not high, such as support structures, edge overflow areas, or specially designated test areas. Testing in these areas avoids interfering with the critical structures being formed. Material extrusion testing typically involves extruding a short line or dot at a preset extrusion speed and temperature to reflect the material's flow behavior under current printing conditions.

[0102] The high-resolution imaging unit can be understood as a visual sensor capable of capturing minute geometric features, such as an industrial camera paired with a high-magnification lens. This imaging unit is configured to capture the geometry of the test extrusion line in real time, including but not limited to parameters such as the line's width, height, surface smoothness, and edge sharpness. The purpose of real-time capture is to obtain the latest state of the material's rheological properties as soon as possible.

[0103] In practical applications, comparing the real-time captured geometry of the test extrusion line with the preset design target allows us to obtain the deviation between the material's current rheological properties and the initial data. The design target is typically the extrusion line geometry expected under ideal printing conditions, based on initial rheological property data. By comparing, the difference between the current material rheological properties and the initial settings can be quantified. For example, if the extrusion line width is greater than the design target, it may indicate a decrease in material viscosity or an increase in flowability.

[0104] Based on the acquired deviations, the rheological data is dynamically adjusted. This adjustment can be based on a preset mathematical model or machine learning algorithm, mapping the deviation to correction values ​​for rheological parameters (such as viscosity, yield stress, etc.). The adjusted rheological data will more accurately reflect the actual behavior of the material in the current printing environment.

[0105] Based on the adjusted rheological data, the system will re-predict the actual deposition deviation of subsequent printed layers. This means that as printing progresses, the prediction of deposition deviation no longer depends solely on the initial data, but is updated according to the real-time state of the material, thereby ensuring that the compensatory printing parameter adjustment strategy for subsequent printed layers remains effective.

[0106] In some preferred embodiments, it is assumed that a large and structurally complex aerospace component needs to be printed, with a printing time of tens of hours and extremely high requirements for dimensional accuracy and surface quality. Initially, the system generates an initial compensatory printing parameter adjustment strategy based on initial material data and environmental parameters. However, as printing progresses, temperature fluctuations within the printing chamber and prolonged heating of the material in the extruder may cause the material's viscosity to gradually decrease.

[0107] To address this variation, the proposed solution performs a material extrusion test every 30 minutes in the support structure area (non-critical area) of the printed part. Specifically, the printhead briefly extrudes a test line 5 mm long and 0.5 mm wide. A high-resolution imaging unit mounted next to the printhead immediately captures the actual width and height of this test line. The system compares the captured actual width and height with the expected width and height based on the initial rheological data. For example, if the actual width is found to be 0.02 mm wider than expected, this indicates increased material flowability. Based on this deviation, the system dynamically adjusts the material viscosity parameter by a corresponding percentage using a preset rheological model. Subsequently, based on this updated viscosity parameter, the system recalculates the actual deposition deviation for the next 100 layers and accordingly fine-tunes the compensatory printing parameter adjustment strategy (e.g., slightly reducing the extrusion amount or increasing the printing speed) to ensure that the deposition accuracy of subsequent printed layers is not affected by changes in material rheological properties. Through this periodic monitoring and adjustment, even during long printing processes, the overall quality and accuracy of the printed part are ensured to consistently meet design requirements.

[0108] The steps for generating a compensatory printing parameter adjustment strategy based on actual deposition deviations include:

[0109] Identify regions with complex geometric features in 3D model files;

[0110] Assess the surface roughness, risk of localized stress concentration, and material overlap quality with adjacent areas in regions with complex geometries.

[0111] Identify the potential negative impacts of compensatory printing parameter adjustment strategies on surface roughness, risk of localized stress concentration, and the quality of material overlap with adjacent areas;

[0112] The potential negative impacts are sorted according to the preset print task priority, and the sorting results are obtained.

[0113] Based on actual deposition deviation, sorting results, surface roughness, risk of local stress concentration, and material overlap quality with adjacent areas, a multi-objective collaborative compensation strategy is generated.

[0114] By adjusting multiple compensatory printing parameters, the adverse effects of the multi-objective collaborative compensation strategy on other objectives are minimized while satisfying high-priority objectives.

[0115] Multi-dimensional visualization demonstrates the expected impact of multi-objective collaborative compensation strategies on surface roughness, local stress concentration risk, and the quality of material overlap with adjacent areas.

[0116] The first part, "Identifying regions with complex geometric features in 3D model files," refers to automatically detecting regions such as thin-walled structures, sharp corners, overhanging structures, fine features, or surfaces with high curvature variations through geometric analysis of the 3D model. These regions are typically more sensitive to printing accuracy and quality and are more susceptible to changes in material flow characteristics. The second part, "Assessing the surface roughness, local stress concentration risk, and material overlap quality with adjacent regions of regions with complex geometric features," refers to using computational fluid dynamics simulations, finite element analysis, or empirical model-based prediction algorithms to quantitatively evaluate the potential surface roughness, internal stress distribution, and bonding strength between different materials during multi-material printing for these identified complex regions. The third part, "Identifying the potential negative impacts of compensatory printing parameter adjustment strategies on surface roughness, local stress concentration risk, and material overlap quality with adjacent regions," refers to anticipating the potential negative effects of adjustments (e.g., extrusion volume, printing speed, temperature, etc.) on the aforementioned quality indicators when generating compensatory parameter adjustment strategies to correct deposition deviations. For example, increasing the extrusion volume may lead to increased surface roughness, or changing the cooling rate may introduce new stresses. "Ranking potential negative impacts according to preset printing task priorities and obtaining ranking results" refers to ranking the importance of identified potential negative impacts based on different requirements of the user or application scenario for the printed parts (for example, for medical implants, biocompatibility and surface smoothness may have higher priorities; for structural parts, strength and dimensional accuracy may have higher priorities). "Generating a multi-objective collaborative compensation strategy" refers to comprehensively considering the actual deposition deviation, the ranking results of potential negative impacts, and the evaluation results of various quality indicators, and using optimization algorithms (such as genetic algorithms, particle swarm optimization, etc.) to generate a comprehensive parameter adjustment scheme that can simultaneously optimize multiple objectives (e.g., minimizing deposition deviation, minimizing surface roughness, minimizing stress concentration, etc.). "Minimizing the adverse effects of the multi-objective collaborative compensation strategy on other objectives while meeting high-priority objectives by adjusting multiple compensatory printing parameters" refers to ensuring that high-priority quality objectives (such as critical dimensional accuracy) are met, while minimizing the negative impact on other secondary objectives (such as surface roughness), through fine-tuning multiple parameters such as extrusion volume, printing speed, layer height, nozzle temperature, platform temperature, and cooling fan speed within the multi-objective collaborative compensation strategy. "Multi-dimensional visualization of the expected impact of multi-objective collaborative compensation strategies on surface roughness, local stress concentration risk, and material overlap quality with adjacent areas" refers to presenting the expected improvement or trade-off results of the printed parts after adjustment by multi-objective collaborative compensation strategies to the operator in an intuitive and multi-dimensional way through a graphical user interface, such as through color coding, heat maps, numerical charts, etc.

[0117] In some preferred embodiments, it is assumed that a medical device component with complex internal channels and delicate external structure needs to be printed. This component has strict requirements on the dimensional accuracy of the internal channels, the biocompatibility of the external surface (requiring extremely low roughness), and the mechanical properties of the overall structure (requiring no significant stress concentration).

[0118] First, the system identifies the internal flow channels and external fine structures of the component as regions with complex geometries. Next, it assesses the potential surface roughness, risk of localized stress concentration, and material overlap quality (if multi-material is involved) in these regions under standard printing parameters. For example, it predicts potential dimensional inaccuracies within the flow channels due to deposition deviations, excessively high roughness on the external surface due to uneven extrusion, and stress concentrations at certain joints.

[0119] The system then identifies that simply increasing the extrusion amount to correct deposition deviations may further worsen the external surface roughness or even introduce new stresses in some thin-walled areas. Depending on the application scenario of the medical device, the preset printing task priority may set "external surface roughness" and "risk of local stress concentration" as high priorities, while the correction of "deposition deviations" must be carried out under these premises.

[0120] Based on this information, the system generates a multi-objective collaborative compensation strategy. For example, in the external fine structure region, the extrusion rate may be slightly reduced or the printing speed adjusted to sacrifice minimal deposition deviation in exchange for lower surface roughness; while in the internal flow channel region, the focus may be more on ensuring dimensional accuracy by adjusting the extrusion rate and path, while reducing stress concentration by optimizing the cooling strategy.

[0121] Ultimately, the expected impact of this strategy on surface roughness, localized stress concentration risk, and material bonding quality is presented to operators through a multi-dimensional visualization interface. For example, color coding displays the expected roughness levels for different areas of the component, heat maps show areas of stress concentration risk, and numerical indicators compare the improvements before and after compensation. Operators can intuitively see that while meeting high-priority objectives (such as external surface smoothness), other objectives (such as deposition deviation) are also reasonably optimized, thereby ensuring that the overall performance of the printed part meets the requirements of medical applications.

[0122] The steps for multi-dimensional visualization of the expected impact of multi-objective collaborative compensation strategies on surface roughness, local stress concentration risk, and material overlap quality with adjacent areas include:

[0123] By dynamically adjusting the transparency or saturation of color coding, the priority of information in different dimensions can be distinguished on the 3D model preview interface.

[0124] Provides an information filtering panel that allows operators to selectively display or hide information in specific dimensions;

[0125] When an operator selects to view information in a specific dimension, the corresponding area on the 3D model preview interface is displayed by zooming in or highlighting the relevant area, and detailed performance indicators for that specific dimension are simultaneously displayed in a dedicated data panel.

[0126] It provides an impact chain analysis function to demonstrate the expected impact of compensatory printing parameter adjustments on geometric accuracy, surface roughness, risk of local stress concentration, and the quality of material overlap with adjacent areas;

[0127] The summary displays the overall impact of compensatory print parameter adjustments on the priority of the overall print job.

[0128] Specifically, by dynamically adjusting the transparency or saturation of color codes, the priority of information in different dimensions is distinguished on the 3D model preview interface. This involves color-coding corresponding areas on the 3D model preview interface based on different performance indicators, such as surface roughness, local stress concentration risk, or material joint quality. Adjusting the transparency or saturation of these color codes can visually represent the importance or priority of different information. For example, high saturation might be used to highlight high-risk areas, while lower transparency might be used to indicate high-priority information that requires close attention.

[0129] Furthermore, an information filtering panel is provided, allowing operators to selectively display or hide information in specific dimensions. Specifically, this involves setting up an interactive panel in the user interface containing options for selecting or deselecting different dimensions of information, such as checkboxes or drop-down menus. Operators can flexibly choose to display only surface roughness information, or simultaneously display information on localized stress concentration risks and material joint quality, based on their focus, thus customizing their viewing of the required data.

[0130] Furthermore, when an operator selects to view information in a specific dimension, the corresponding area on the 3D model preview interface is magnified or highlighted, and detailed performance indicators for that dimension are simultaneously displayed in a dedicated data panel. Specifically, when an operator clicks or selects a specific area on the 3D model preview interface, that area is automatically magnified or highlighted in a prominent manner (e.g., by a specific color). At the same time, a separate dedicated data panel is activated or updated, displaying detailed performance indicators for the selected dimension in real time, such as specific numerical values, trend charts, or detailed text descriptions, thus providing more in-depth analytical data.

[0131] As a preferred implementation, an impact chain analysis function is provided to demonstrate the expected impact of compensatory printing parameter adjustments on geometric accuracy, surface roughness, risk of localized stress concentration, and material overlap quality with adjacent areas. Specifically, this function clearly depicts, in a graphical or structured manner, such as flowcharts, network diagrams, or interactive charts, how adjustments to compensatory printing parameters (such as extrusion temperature, printing speed, layer thickness, etc.) progressively affect multiple key performance objectives, including geometric accuracy, surface roughness, risk of localized stress concentration, and material overlap quality. This helps operators understand the underlying logic and potential chain reactions of parameter adjustments.

[0132] Therefore, the system summarizes and displays the comprehensive impact of compensatory printing parameter adjustments on the overall printing task priority. Specifically, the system comprehensively evaluates the impact of all dimensions against the preset printing task priority and presents the results in a unified indicator or scoring format. For example, it can display a percentage, a level, or a comprehensive risk index to quantify the contribution or potential risk of the current compensatory printing parameter adjustment strategy to achieving the overall printing task objectives, thereby providing operators with a macro-level decision-making basis.

[0133] This application further proposes steps to provide influence chain analysis capabilities, demonstrating the expected impact of compensatory printing parameter adjustments on geometric accuracy, surface roughness, risk of localized stress concentration, and material overlap quality with adjacent areas, including:

[0134] Identify the material types and the locations of overlap interfaces between materials in collaborative printing;

[0135] Based on the material type used in collaborative printing, establish the influence relationships of parameters, properties, and quality within each material.

[0136] For the interface locations between materials, data on the interfacial bonding force and the difference in the interfacial thermal expansion coefficient between different materials are extracted from the material database.

[0137] Based on interfacial bonding force data and interfacial thermal expansion coefficient difference data, the cross-material interface influence relationship is established. The cross-material interface influence relationship includes the expected impact of a material's compensatory printing parameter adjustment on the extrusion behavior of adjacent materials, as well as the expected impact on the interfacial bonding quality.

[0138] The influence relationships of parameters, properties, and quality within each material are integrated with the influence relationships across material interfaces to form an overall influence chain;

[0139] When an operator adjusts the compensating printing parameters for any material, the overall impact chain demonstrates the expected effects of the adjustment on geometric accuracy, surface roughness, risk of localized stress concentration, and the quality of material overlap with adjacent areas. It also indicates the expected effects on the extrusion behavior of adjacent materials and the expected effects on the quality of interfacial bonding.

[0140] Specifically, identifying the material types and interfacial locations in collaborative printing refers to the system automatically or by the operator specifying all the different material types used in the 3D model file, and precisely determining the areas where these different materials come into contact or connect with each other. These interfacial locations are key to analyzing cross-material effects.

[0141] The process of establishing the influence relationships of parameters, properties, and quality within each material based on the type of material being collaboratively printed can be understood as follows: for each individual printing material, the system analyzes how its own printing parameters (such as extrusion temperature, printing speed, and layer height) affect the material's rheological properties, curing behavior, final geometric accuracy, surface roughness, and mechanical properties. These relationships can be established using experimental data, physical models, or machine learning models.

[0142] In practical applications, for the interface between materials, data on interfacial bonding force and the difference in interfacial thermal expansion coefficients are extracted from material databases. The purpose is to obtain key physical parameters describing the interaction between different materials at the interface. Interfacial bonding force data reflects the adhesion strength or fusion degree of the two materials at the interface, while the difference in interfacial thermal expansion coefficients indicates the risk of interfacial stress or deformation due to temperature changes during printing and cooling. These data are crucial for assessing interface quality.

[0143] Furthermore, based on interfacial bonding force data and interfacial thermal expansion coefficient difference data, a cross-material interface influence relationship is established. The aim is to quantify the expected impact of adjusting the compensatory printing parameters of one material on the extrusion behavior of adjacent materials, as well as the expected impact on the interfacial bonding quality. For example, adjusting the extrusion temperature of the first material may change its viscosity, thereby affecting its spreadability at the overlap interface, and thus indirectly affecting the extrusion path or overlap quality of the adjacent second material.

[0144] Therefore, the influence relationships of parameters, properties, and quality within each material are integrated with the influence relationships across material interfaces to form an overall influence chain. This overall influence chain is a comprehensive model that not only considers the parameter-performance relationships within a single material but also incorporates the complex interactions between multiple materials, thus providing a comprehensive and systematic framework for influence assessment.

[0145] Ultimately, when an operator adjusts the compensating printing parameters for any material, the system can, through the aforementioned overall impact chain, display in real time the expected effects of the adjustment on geometric accuracy, surface roughness, risk of localized stress concentration, and the quality of material overlap with adjacent areas. More importantly, this function also clearly indicates the expected impact on the extrusion behavior of adjacent materials and the expected impact on interfacial bonding quality, enabling operators to clearly understand the comprehensive consequences of their parameter adjustments in a multi-material printing environment.

[0146] In some preferred embodiments, it is assumed that a complex structure needs to be printed, which is composed of two different polymer materials (e.g., a rigid structural material A and a flexible support material B). During the printing process, the operator may need to adjust the extrusion temperature of material A to optimize its geometric accuracy.

[0147] First, the system will identify the types of material A and material B and determine the location of their overlapping interface.

[0148] Next, the system will establish the influence relationship between parameters such as extrusion temperature and printing speed on the rheological properties, curing shrinkage rate, and final geometric accuracy and surface roughness of material A, based on the material type. A similar influence relationship will also be established for material B.

[0149] For the interface between materials A and B, the system extracts data on the interfacial bonding force and the difference in their coefficients of thermal expansion from the material database. For example, if the difference in the coefficients of thermal expansion between materials A and B is large, significant thermal stress may be generated at the interface during cooling.

[0150] Based on this interface data, the system establishes cross-material interface influence relationships. For example, when the extrusion temperature of material A is increased, its viscosity may decrease, causing a slight disturbance to the extrusion path of material B at the overlap interface, or affecting the interfacial bonding strength between material A and material B.

[0151] Subsequently, the system integrates the internal influence relationships of materials A and B with the cross-material interface influence relationships between them to form a complete overall influence chain.

[0152] When an operator attempts to increase the compensatory printing parameters (e.g., extrusion temperature) of material A by 5°C in the graphical user interface, the system immediately calculates and displays the overall impact chain: 1. Impact on material A itself: Geometric accuracy is expected to increase by 0.5%, and surface roughness is expected to decrease by 0.2 micrometers. 2. Expected impact on the extrusion behavior of adjacent material B: Due to the reduced viscosity of material A, the extrusion path of material B in the overlapping area may shift inward by 0.02 millimeters. 3. Expected impact on interfacial bonding quality: Due to the increased temperature potentially leading to a longer curing time for material A at the interface, the interfacial bonding strength is expected to increase by 3%. However, if the thermal expansion coefficients of the two materials differ significantly, the interfacial thermal stress may increase by 5%.

[0153] In this way, operators can gain a comprehensive understanding of the multifaceted impact of adjusting the compensatory printing parameters of material A, thereby making more informed decisions, balancing trade-offs between different performance indicators, and ultimately optimizing the overall quality of multi-material printing.

[0154] When an operator adjusts the compensating printing parameters for any material, the overall impact chain demonstrates the expected effects of these adjustments on geometric accuracy, surface roughness, risk of localized stress concentration, and the quality of material overlap with adjacent areas. The steps outlined include the expected impact on the extrusion behavior of adjacent materials and the expected impact on interfacial bonding quality.

[0155] Before printing, rheological property calibration tests are performed on each batch of materials to obtain calibrated rheological property data;

[0156] During the printing process, multi-material extrusion tests are periodically performed in non-critical areas, and the geometry of the extrusion lines of each material and the geometry of the material overlap interface are captured in real time by a high-resolution imaging unit.

[0157] The geometry of the extrusion line for each material test is compared with the design expectation to obtain the deviation between the current rheological properties of each material and the calibrated rheological property data.

[0158] The geometry of the material interface is compared with the design benchmark to obtain the deviation between the interface bonding quality and the preset target.

[0159] Based on the deviation between the current rheological properties of each material and the calibrated rheological property data, and the deviation between the interface bonding quality and the preset target, the influence relationships of parameters, properties, and quality within each material in the overall influence chain, as well as the influence relationships across material interfaces, are dynamically adjusted.

[0160] Based on the adjusted overall impact chain, the expected impact of compensatory printing parameter adjustments on geometric accuracy, surface roughness, risk of local stress concentration, and material overlap quality with adjacent areas is updated and displayed in real time, as well as the expected impact on the extrusion behavior of adjacent materials and the expected impact on interface bonding quality.

[0161] Specifically, before printing, each batch of material undergoes rheological property calibration testing to establish a precise rheological property benchmark for that batch under standard conditions. For example, parameters such as viscosity and yield stress of the material at different temperatures and shear rates can be measured to form a set of calibrated rheological property data, which serves as an initial reference for real-time monitoring and comparison during subsequent printing. During the printing process, multi-material extrusion tests are periodically performed in non-critical areas. This refers to the system performing small-scale material extrusion operations at a preset frequency in areas that do not affect the function and appearance of the final product. These test areas are usually predefined or automatically identified by the system based on the model structure. High-resolution imaging units, such as vision systems equipped with high-speed cameras or laser scanners, are used to capture the geometry of these test extrusion lines in real time, including their width, height, uniformity, etc., as well as the geometry of the interfaces between different materials, such as the flatness, blending, and presence of gaps or overflows.

[0162] The comparison of the geometry of the test extrusion lines for each material with the design expectation aims to quantify the difference between the actual rheological behavior of the material and the ideal state. For example, if the test extrusion line is wider than the design expectation, it may indicate that the material's viscosity is lower than expected. The comparison of the geometry of the material interface with the design benchmark aims to assess the actual quality of the bond between different materials. The design benchmark may include indicators such as interface smoothness, material penetration depth, and the absence of air bubbles. Through these comparisons, the deviations between the current rheological properties of each material and the calibrated rheological property data, as well as the deviations between the interface bonding quality and the preset targets, can be obtained. These deviation data are key evidence for identifying dynamic changes in material properties and interface quality.

[0163] In practical applications, based on these deviations, the system dynamically adjusts the influence relationships of parameters, properties, and quality within each material in the overall influence chain, as well as the influence relationships across material interfaces. This means that if a change in the rheological properties of material A is detected, the weights or functional relationships of the parameters describing material A's extrusion temperature, extrusion speed, etc., on its own geometric accuracy, surface roughness, etc., will be updated. Similarly, if a deviation occurs in the interface bonding quality, the correlation between the expected impact of compensatory printing parameter adjustments describing a material on the extrusion behavior of adjacent materials and the interface bonding quality will also be corrected. Thus, based on the adjusted overall influence chain, the system can update and display in real time the expected impact of compensatory printing parameter adjustments on geometric accuracy, surface roughness, risk of local stress concentration, and the quality of material overlap with adjacent areas, as well as the expected impact on the extrusion behavior of adjacent materials and the expected impact on interface bonding quality. This ensures that the feedback information obtained by operators when adjusting parameters is always based on the most accurate prediction of the current actual state of the materials and interfaces.

[0164] In some preferred embodiments, it is assumed that two different polymer materials A and B need to be co-printed to manufacture a part with a complex internal structure. Before printing begins, each batch of materials A and B is first subjected to rheological property calibration tests, for example, by measuring their shear viscosity profiles at different temperatures using a capillary rheometer, and these data are stored as calibrated rheological property data.

[0165] During the printing process, the system periodically performs multi-material extrusion tests in non-critical areas of the component (e.g., support structures or internal filling areas). Specifically, the system briefly extrudes a section of material A, followed immediately by a section of material B, forming an overlap interface between the two. The high-resolution imaging unit captures the geometry of these test extrusion lines in real time, such as the width, height, and uniformity of the extrusion lines, as well as the sharpness, smoothness, and blending of the overlap interface between materials A and B.

[0166] Subsequently, the system compares the captured geometry of the extrusion line of material A with the design expectation. For example, if the design expectation for the extrusion line width is 0.5 mm, while the actual measurement is 0.52 mm, the deviation is calculated. Similarly, the comparison is performed on material B. Simultaneously, the geometry of the material interface is compared with a preset design benchmark. For example, if the design benchmark requires a smooth, seamless interface, but a slight gap is observed, the deviation in interface bonding quality is recorded.

[0167] Based on this real-time acquired deviation data, the system dynamically adjusts the previously established overall influence chain. For example, if the actual extrusion linewidth of material A is found to be consistently large, indicating a possible change in its rheology (e.g., decreased viscosity), the system will accordingly adjust the influence of parameters related to material A (such as extrusion temperature and extrusion speed) on its rheological properties and final deposition effect within the overall influence chain. If the interfacial bonding quality remains poor, the system will adjust the cross-material interface influence relationship, for example, by increasing the weight of the interfacial heating temperature or the extrusion pressure of material B, to improve interfacial fusion.

[0168] Through this dynamic adjustment, when an operator adjusts the extrusion temperature of material A on the graphical user interface to optimize the geometric accuracy of a certain area, the system updates and displays in real time, based on the overall impact chain of the latest adjustment, not only the expected impact of the temperature adjustment on the geometric accuracy and surface roughness of material A itself, but also accurately indicating the extrusion behavior of adjacent material B (e.g., whether it will cause material B to overflow or under-extrude) and the expected impact on the interfacial bonding quality between materials A and B. This allows operators to comprehensively assess the potential consequences of their parameter adjustments, thereby making more informed and effective decisions to ensure the printing of high-quality multi-material parts.

[0169] This application further proposes a step in which multi-material extrusion testing is periodically performed in non-critical areas during the printing process, including:

[0170] Identify key printing areas in 3D model files that have high geometric accuracy requirements or complex structures;

[0171] Analyze the material extrusion path, printing speed variation, and thermal environment characteristics of the interface between adjacent materials in the key printing area.

[0172] In non-critical areas, test areas that are similar to the material extrusion path, printing speed variation, and thermal environment characteristics of the interface between adjacent materials in critical printing areas are selected.

[0173] Multi-material extrusion tests were conducted within similar test areas to simulate the material extrusion path, printing speed variations, and thermal environment characteristics of the interface between adjacent materials in key printing areas.

[0174] Specifically, identifying critical printing areas with high geometric accuracy requirements or complex structures in 3D model files refers to automatically or manually identifying areas in the 3D model file that have extremely high requirements for print quality, complex structures, and are susceptible to the influence of material flow characteristics. For example, these areas may include thin-walled structures, sharp corners, overhanging structures, internal channels, microstructure arrays, or multi-material interfaces. The geometric accuracy, surface roughness, or structural integrity of these areas are crucial to the performance of the final product.

[0175] Furthermore, analyzing the material extrusion path, printing speed variations, and thermal environment characteristics of the interface between adjacent materials in key printing areas refers to, for the identified key printing areas, combining the preset printing strategy and material properties, conducting a detailed analysis of the material extrusion trajectory, dynamic changes in printhead movement speed in these areas, and the local temperature field distribution formed by heat sources (such as printhead temperature and print bed temperature) and heat dissipation (such as cooling fans and ambient temperature) during the printing process. For multi-material printing, special attention also needs to be paid to the temperature gradient, thermal expansion differences, and thermal history of different materials at the interface, as well as the interface formation process.

[0176] In non-critical areas, selecting test areas that are similar to the critical printing areas in terms of material extrusion path, printing speed variation, and thermal environment characteristics of adjacent material interfaces refers to identifying non-functional areas (e.g., support structures, skirts, or specially designed test block areas) that can approximate the characteristics of the critical printing areas in terms of geometry, local printing strategies, or thermal conduction conditions, without affecting the quality of the main printed part. This selection can be accomplished through algorithmic analysis or user specification to ensure that the test areas provide material behavior data that is highly correlated with the critical areas.

[0177] In practical applications, multi-material extrusion testing, conducted within similar test areas to simulate the material extrusion path, printing speed variations, and thermal environment characteristics of the interface between adjacent materials in critical printing areas, refers to reproducing or approximately reproducing the material extrusion path, printing speed variations, and thermal environment characteristics experienced by critical printing areas within selected non-critical test areas by precisely controlling printing parameters (such as extrusion volume, printing speed, nozzle temperature, print bed temperature, cooling fan intensity, etc.). For example, if the critical area experiences extrusion path changes and speed fluctuations due to rapid turns, similar path and speed changes are implemented within the test area; if the critical area has specific heat accumulation or heat dissipation conditions, these thermal environments are simulated by adjusting local heating or cooling within the test area.

[0178] This application further proposes a multi-material extrusion test procedure within similar test areas, simulating the material extrusion path, printing speed variations, and thermal environment characteristics of adjacent material overlap interfaces in key printing areas. The procedure includes:

[0179] Within a test area with similarity, microstructures with geometry and size similar to the key printed area are set up;

[0180] Multi-material extrusion tests were conducted in test areas with similar microstructures to simulate the material extrusion path, printing speed variation, and thermal environment characteristics of the interface between adjacent materials in key printing areas.

[0181] In-situ monitoring technology is used to obtain physical parameters in real time during the solidification process of materials within the microstructure.

[0182] Based on the physical parameters during the curing process of materials within the microstructure, in-situ monitoring technology is used to obtain the physical parameters during the interface formation process within the microstructure in real time.

[0183] Specifically, "setting up microstructures with geometry and size similar to the critical printing area" refers to pre-designing and manufacturing tiny structures with geometric shapes highly similar to the local features of the critical printing area within a selected test region that is similar to the critical printing area. These microstructures can be localized enlargements or reductions of complex geometric features in the critical area, such as micropillar arrays, microchannels, and micropores. The aim is to more accurately simulate the flow, filling, and solidification behavior of materials in the critical area under a controlled microscopic environment.

[0184] The phrase "real-time acquisition of physical parameters during the curing process of materials within microstructures through in-situ monitoring technology" can be understood as using non-contact or micro-contact sensors to monitor the materials inside the microstructures in real time during multi-material extrusion testing. These physical parameters may include, but are not limited to, temperature distribution, viscosity changes, degree of curing, shrinkage rate, and stress / strain. For example, an infrared thermal imager can be used to monitor the temperature field, a micro-rheometer or acoustic sensor can be used to monitor viscosity changes, and fiber optic sensors or micro-strain gauges can be used to monitor stress / strain during the curing process. The aim is to acquire dynamic physical property data of the material at the microscale during the transition from a liquid to a solid state.

[0185] In practical applications, "based on the physical parameters during the curing process of materials within the microstructure, and through in-situ monitoring technology, to obtain the physical parameters during the interface formation process within the microstructure in real time" specifically refers to, after obtaining the physical parameters during the material curing process, further utilizing in-situ monitoring technologies, such as micro-mechanical sensors, ultrasonic probes, or high-resolution optical microscopes, to conduct real-time observation and measurement of the interface between different materials within the microstructure. The physical parameters during interface formation can include interfacial bonding force, interfacial thickness, the formation and evolution of interfacial defects (such as pores and cracks), and element diffusion at the interface. The aim is to gain a deeper understanding of the formation mechanism and quality evolution of multi-material interfaces during the printing process, providing direct and quantitative data support for evaluating and optimizing interfacial bonding quality.

[0186] In some preferred embodiments, it is assumed that a complex medical device comprising two different polymer materials needs to be printed, containing multiple micrometer-scale overlapping interfaces and fine structures. To precisely control the bonding quality of these interfaces and the geometric accuracy of the structures, a test area with similar extrusion path, printing speed, and thermal environment characteristics to the critical printing area can be selected in a non-critical region. Within this test area, a series of microstructures with similar geometry and size to the critical microstructures of the medical device (e.g., microchannels or micropore arrays) are pre-set using microfabrication techniques.

[0187] In multi-material extrusion testing, two polymer materials are extruded into these microstructures according to preset printing parameters. Simultaneously, in-situ monitoring techniques are used to observe the interior of the microstructures in real time. For example, miniature thermocouple arrays can be embedded to monitor the temperature distribution during material curing, miniature piezoelectric sensors can be used to measure stress changes caused by material curing shrinkage, and high-resolution confocal microscopy can be used to capture the micromorphological evolution at the interface in real time.

[0188] Based on these real-time acquired physical parameters such as temperature, stress, and microstructure, the physical parameters in the interface formation process can be further analyzed. For example, image processing algorithms can be used to quantify interface thickness and porosity, or micromechanical tests can be used to assess interface bonding strength. This refined data is directly fed back to the overall influence chain to dynamically adjust printing parameters, such as extrusion temperature, printing speed, and cooling rate, to ensure that the material curing behavior and interface bonding quality in key printing areas meet design requirements. In this way, even if batch variations in materials or environmental fluctuations occur during the printing process, the system can accurately compensate based on real-time feedback at the microscopic level, thereby ensuring the high quality and reliability of the final printed parts.

[0189] refer to Figure 2 This application proposes a graphical user interaction system for a 3D printing material forming device, applied to a graphical user interaction method for a 3D printing material forming device. The system includes:

[0190] The information acquisition module is used to acquire the 3D model file to be printed and the information of the selected printing material;

[0191] The data processing module analyzes the 3D model file to obtain geometric feature information and extracts the rheological property data of the selected printing material from the material database based on the selected printing material information.

[0192] The prediction module, based on geometric feature information and rheological data, predicts the actual deposition deviation caused by changes in the flow characteristics of the material during the printing process.

[0193] The strategy processing module generates a compensatory printing parameter adjustment strategy based on the actual deposition deviation, and visualizes the compensatory printing parameter adjustment strategy and the expected deposition effect after adjustment.

[0194] The instruction application module applies a compensatory printing parameter adjustment strategy to the generation of printing instructions.

[0195] Specifically, the information acquisition module can be a user interface component that allows operators to upload or select 3D model files and input or select the desired printing material type. For example, it can integrate functions such as a file browser and a material selection drop-down menu to ensure the accuracy of the acquired data.

[0196] The data processing module can include geometric analysis algorithms to identify features of the model such as size, shape, wall thickness, and curvature. Simultaneously, it interacts with a pre-set material database, retrieving and extracting rheological property parameters such as viscosity and yield stress of the material at different temperatures and shear rates, based on the material type selected by the operator.

[0197] The prediction module can use computational fluid dynamics models or machine learning algorithms to simulate the flow behavior of materials during extrusion and deposition, taking into account the influence of factors such as temperature gradient and shear stress on the rheology of materials, thereby predicting the geometric differences between the actual deposited layer and the design layer.

[0198] The strategy processing module receives the output from the prediction module and generates adjustment strategies based on preset optimization goals (such as accuracy and surface quality), such as adjusting parameters like printing speed, extrusion volume, layer height, and temperature. Simultaneously, it provides a graphical user interface that displays the adjusted parameters and the expected printing results simulated using these parameters (such as color-coded deviation graphs and virtual print previews) to the operator.

[0199] The instruction application module is responsible for integrating the adjustment strategies generated by the strategy processing module into the final G-code or other printing instructions, ensuring that the 3D printer can print according to the optimized parameters, thereby achieving effective compensation for actual deposition deviations.

[0200] Through the above technical solution, this application provides a system with a clear structure and well-defined functions for implementing a graphical user interaction method for 3D printing material forming devices. This system significantly improves the efficiency of method implementation and the maintainability of the system by decomposing complex method steps into independent and collaborative modules. Compared with solutions that only describe method steps, this system provides a concrete and deployable software or hardware framework, enabling operators to intuitively understand and operate the adjustment process of printing parameters. This effectively reduces deposition deviations caused by changes in material rheological properties during 3D printing, improving the geometric accuracy and surface quality of printed parts. Furthermore, the modular design facilitates future functional expansion and technological upgrades.

[0201] The content disclosed above is only a preferred and feasible embodiment of the present invention, and is not intended to limit the scope of protection of the present invention. Therefore, all equivalent technical changes made based on the content of the present invention specification and drawings are included within the scope of protection of the present invention. Furthermore, the elements therein can be updated as technology develops.

Claims

1. A graphical user interaction method for a 3D printing material forming device, characterized in that, The method includes the following steps: Obtain the 3D model file to be printed and the information of the selected printing material; The 3D model file is analyzed to obtain geometric feature information, and the rheological property data of the selected printing material is extracted from the material database based on the selected printing material information; Based on geometric feature information and rheological data, the actual deposition deviation caused by changes in the flow characteristics of the material during the printing process is predicted. Based on the actual deposition deviation, a compensatory printing parameter adjustment strategy is generated, and the compensatory printing parameter adjustment strategy and the expected deposition effect after adjustment are visualized. Apply a compensatory print parameter adjustment strategy to print command generation; The steps for generating a compensatory printing parameter adjustment strategy based on actual deposition deviations include: Identify regions with complex geometric features in 3D model files; Assess the surface roughness, risk of localized stress concentration, and material overlap quality with adjacent areas in regions with complex geometries. Identify the potential negative impacts of compensatory printing parameter adjustment strategies on surface roughness, risk of localized stress concentration, and the quality of material overlap with adjacent areas; The potential negative impacts are sorted according to the preset print task priority, and the sorting results are obtained. Based on actual deposition deviation, sorting results, surface roughness, risk of local stress concentration, and material overlap quality with adjacent areas, a multi-objective collaborative compensation strategy is generated. By adjusting multiple compensatory printing parameters, the adverse effects of the multi-objective collaborative compensation strategy on other objectives are minimized while satisfying high-priority objectives. By dynamically adjusting the transparency or saturation of color coding, the priority of information in different dimensions can be distinguished on the 3D model preview interface. Provides an information filtering panel that allows operators to selectively display or hide information in specific dimensions; When an operator selects to view information in a specific dimension, the corresponding area on the 3D model preview interface is displayed by zooming in or highlighting the relevant area, and detailed performance indicators for that specific dimension are simultaneously displayed in a dedicated data panel. It provides an impact chain analysis function to demonstrate the expected impact of compensatory printing parameter adjustments on geometric accuracy, surface roughness, risk of local stress concentration, and the quality of material overlap with adjacent areas; The summary displays the overall impact of compensatory print parameter adjustments on the priority of the overall print job.

2. The graphical user interaction method for a 3D printing material forming device as described in claim 1, characterized in that, The method also includes the following steps: Estimate the maximum drift range of the rheological properties of the selected printing material under prolonged heating; Obtain real-time environmental parameters inside the printing cavity; Based on the maximum drift range and real-time environmental parameters, dynamic adjustment rules are generated; The compensatory printing parameter adjustment strategy is adjusted according to the dynamic adjustment rules.

3. The graphical user interaction method for a 3D printing material forming device as described in claim 1, characterized in that, The method also includes the following steps: During the printing process, material extrusion tests are periodically performed in non-critical areas, and the geometry of the test extrusion line is captured in real time by a high-resolution imaging unit. The geometry of the test extrusion line is compared with the design target to obtain the deviation between the current rheological properties of the material and the initial data; Based on the deviation, the rheological property data are dynamically adjusted; Based on the adjusted rheological data, the actual deposition deviation of subsequent printed layers is re-predicted.

4. The graphical user interaction method for a 3D printing material forming device as described in claim 1, characterized in that, The system provides impact chain analysis capabilities, demonstrating the expected impact of compensatory printing parameter adjustments on geometric accuracy, surface roughness, risk of localized stress concentration, and material overlap quality with adjacent areas. The steps include: Identify the material types and the locations of overlap interfaces between materials in collaborative printing; Based on the material type used in collaborative printing, establish the influence relationships of parameters, properties, and quality within each material. For the interface locations between materials, data on the interfacial bonding force and the difference in the interfacial thermal expansion coefficient between different materials are extracted from the material database. Based on interfacial bonding force data and interfacial thermal expansion coefficient difference data, the cross-material interface influence relationship is established. The cross-material interface influence relationship includes the expected impact of a material's compensatory printing parameter adjustment on the extrusion behavior of adjacent materials, as well as the expected impact on the interfacial bonding quality. The influence relationships of parameters, properties, and quality within each material are integrated with the influence relationships across material interfaces to form an overall influence chain; When an operator adjusts the compensating printing parameters for any material, the overall impact chain demonstrates the expected effects of the adjustment on geometric accuracy, surface roughness, risk of localized stress concentration, and the quality of material overlap with adjacent areas. It also indicates the expected effects on the extrusion behavior of adjacent materials and the expected effects on the quality of interfacial bonding.

5. The graphical user interaction method for a 3D printing material forming device as described in claim 4, characterized in that, When an operator adjusts the compensating printing parameters for any material, the overall impact chain demonstrates the expected effects of these adjustments on geometric accuracy, surface roughness, risk of localized stress concentration, and the quality of material overlap with adjacent areas. The steps outlined include the expected impact on the extrusion behavior of adjacent materials and the expected impact on interfacial bonding quality. Before printing, rheological property calibration tests are performed on each batch of materials to obtain calibrated rheological property data; During the printing process, multi-material extrusion tests are periodically performed in non-critical areas, and the geometry of the extrusion lines of each material and the geometry of the material overlap interface are captured in real time by a high-resolution imaging unit. The geometry of the extrusion line for each material test is compared with the design expectation to obtain the deviation between the current rheological properties of each material and the calibrated rheological property data. The geometry of the material interface is compared with the design benchmark to obtain the deviation between the interface bonding quality and the preset target. Based on the deviation between the current rheological properties of each material and the calibrated rheological property data, and the deviation between the interface bonding quality and the preset target, the influence relationships of parameters, properties, and quality within each material in the overall influence chain, as well as the influence relationships across material interfaces, are dynamically adjusted. Based on the adjusted overall impact chain, the expected impact of compensatory printing parameter adjustments on geometric accuracy, surface roughness, risk of local stress concentration, and material overlap quality with adjacent areas is updated and displayed in real time, as well as the expected impact on the extrusion behavior of adjacent materials and the expected impact on interface bonding quality.

6. The graphical user interaction method for a 3D printing material forming device as described in claim 5, characterized in that, During the printing process, the steps of periodically performing multi-material extrusion tests in non-critical areas include: Identify key printing areas in 3D model files that have high geometric accuracy requirements or complex structures; Analyze the material extrusion path, printing speed variation, and thermal environment characteristics of the interface between adjacent materials in the key printing area. In non-critical areas, test areas that are similar to the material extrusion path, printing speed variation, and thermal environment characteristics of the interface between adjacent materials in critical printing areas are selected. Multi-material extrusion tests were conducted within similar test areas to simulate the material extrusion path, printing speed variations, and thermal environment characteristics of the interface between adjacent materials in key printing areas.

7. The graphical user interaction method for a 3D printing material forming device as described in claim 5, characterized in that, Within similar test areas, the steps for conducting multi-material extrusion tests, simulating material extrusion paths, printing speed variations, and thermal environment characteristics at the interfaces between adjacent materials in key printing areas, include: Within a test area with similarity, microstructures with geometry and size similar to the key printed area are set up; Multi-material extrusion tests were conducted in test areas with similar microstructures to simulate the material extrusion path, printing speed variation, and thermal environment characteristics of the interface between adjacent materials in key printing areas. In-situ monitoring technology is used to obtain physical parameters in real time during the solidification process of materials within the microstructure. Based on the physical parameters during the curing process of materials within the microstructure, in-situ monitoring technology is used to obtain the physical parameters during the interface formation process within the microstructure in real time.

8. A graphical user interaction system for a 3D printing material forming device, applied to the graphical user interaction method for a 3D printing material forming device as described in claim 1, characterized in that, The system includes: The information acquisition module is used to acquire the 3D model file to be printed and the information of the selected printing material; The data processing module analyzes the 3D model file to obtain geometric feature information and extracts the rheological property data of the selected printing material from the material database based on the selected printing material information. The prediction module, based on geometric feature information and rheological data, predicts the actual deposition deviation caused by changes in the flow characteristics of the material during the printing process. The strategy processing module generates a compensatory printing parameter adjustment strategy based on the actual deposition deviation, and visualizes the compensatory printing parameter adjustment strategy and the expected deposition effect after adjustment. The instruction application module applies a compensatory printing parameter adjustment strategy to the generation of printing instructions.

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