Incremental parallel 3D printing technology method, device, equipment and storage medium

Abstract

This invention relates to the field of transport vehicle control technology, specifically to an incremental parallel 3D printing technology method, apparatus, equipment, and storage medium. The method involves acquiring printing data of the model to be printed, calculating the number of buffer layers based on the printing data, selecting a portion of the pre-generated buffer layers, generating corresponding fill paths for the selected buffer layers, and storing the fill paths in an instruction buffer pool. The method reads the first layer instruction from the buffer pool, executes the printing, uploads the actual data, synchronously processes the data of layers 2N-3N, and generates incremental instructions for the corresponding buffer layers to supplement the buffer pool. After completing the corresponding actions, the next round of printing begins. This solves the problems of existing printing methods, such as the superposition of preprocessing and printing time, resulting in a long overall cycle; and the redundancy of full data, leading to high transmission and storage pressure.

Description

Technical Field

[0001] This invention relates to an incremental parallel 3D printing technology method, apparatus, equipment, and storage medium, belonging to the field of additive manufacturing technology. Background Technology

[0002] Additive manufacturing (3D printing), as a core technology in the field of intelligent manufacturing, has seen mainstream processes such as Fused Deposition Modeling (FDM), Selective Laser Melting (SLM), and Stereolithography (SLA) widely applied in industrial sectors such as aerospace, automotive manufacturing, precision machinery, and high-end equipment. Currently, the core workflows of various mainstream 3D printing processes all follow a rigid technical logic of full-scale preprocessing and sequential execution. This logic, established in the early stages of 3D printing technology development to ensure the integrity of printing instructions, can meet basic usage requirements in low-complexity, small-size model printing scenarios. The 3D printing process is specifically divided into three independent and sequential stages: the full-scale slicing stage, the full-scale path filling stage, and the batch printing stage. The full-scale slicing stage requires loading a complete 3D model (STL / 3MF format), slicing all layers (usually thousands to tens of thousands) from the top to the bottom along the Z-axis, and generating 2D cross-sectional contour data for each layer. For complex models (such as aerospace structural components with hollowed-out cavities), this stage can take 2-8 hours or even several days. The full-scale path filling stage is based on the contours of all sliced ​​layers, calculating the filling path (such as FDM straight line filling, SLM island scanning path), support structure parameters, and process parameters (such as laser power and extrusion speed) for each layer, and finally generating GB-level full-scale printing instructions. This stage takes 50% to 80% of the time of the slicing stage. During the batch printing stage, the equipment must fully read the full-scale printing instructions before it can start. During the printing process, the generated slice or path parameters cannot be modified, and the equipment can only execute the preset instructions layer by layer.

[0003] In traditional workflows, the preprocessing time for the full slicing and full path filling stages is entirely consumed before printing begins. For example, printing a 500mm diameter titanium alloy turbine disk using SLM technology requires 4 hours for full slicing, 2 hours for path filling, and 15 hours for printing, for a total cycle time of 21 hours. Of these, 6 hours are spent idle waiting for data, resulting in an effective equipment utilization rate of only 30%–50%. The printing instructions generated from full preprocessing (such as G-code for a complex model with 10,000 layers) can reach 2–5GB in size, consuming significant storage resources. In summary, current printing workflows suffer from the problems of overlapping preprocessing and printing times, resulting in a lengthy total cycle time; and redundant full data, leading to high transmission and storage pressure. Summary of the Invention

[0004] This invention addresses the shortcomings of existing technologies by providing an incremental parallel 3D printing technology method, apparatus, equipment, and computer-readable storage medium. It aims to solve the problems of existing printing methods, such as the superposition of preprocessing and printing time, resulting in a long total cycle; full data redundancy, and high transmission and storage pressure.

[0005] The technical solution of this invention to solve the above-mentioned technical problems is as follows: An incremental parallel 3D printing technology method, comprising the following steps:

[0006] Obtain the printing data of the model to be printed, and calculate the number of buffer layers based on the printing data;

[0007] Select the first part of the buffer layer, generate the corresponding padding path for the selected part of the buffer layer, and store the padding path into the instruction buffer pool.

[0008] Read the first layer instruction from the buffer pool, execute the printing and upload the actual data, process the data of layers 2N-3N synchronously, and generate the corresponding incremental instruction of the buffer layer to supplement the buffer pool. After completing the corresponding actions, proceed to the next round of printing.

[0009] In some embodiments provided in this application, after the steps of reading the first-level instructions of the buffer pool, executing the printing and uploading of actual data, the method further includes:

[0010] Obtain actual print feedback data and adjust the next layer's print parameters based on the actual print feedback data.

[0011] In some embodiments provided in this application, the printing data includes: model construction data, target number of layers, and the type of printing process used.

[0012] In some embodiments provided in this application, the step of calculating the number of buffer layers based on the printed data includes:

[0013] Obtain basic indicators of process type, complexity indicators of model construction, and equipment processing performance indicators. Based on the basic indicators of process type, use the complexity indicators of model construction and equipment processing performance indicators as correction data to correct the basic indicators of process type and generate the corresponding number of buffer layers.

[0014] In some embodiments provided in this application, the step of correcting the basic process type indicators based on the process type indicators, using the complexity indicators of the model construction and the equipment processing performance indicators as correction data, and generating the corresponding number of buffer layers includes:

[0015] Based on the preset base value of the process type, if the model has more than a predetermined amount of hollow or thin-walled structures, or the number of triangular facets of the model is greater than 100,000, then the preset base value based on the process type is increased. In addition, the preset base value is increased or decreased in combination with the equipment processing performance index, so that the total preprocessing time of the generated buffer layer is less than or equal to the total printing time.

[0016] In some embodiments provided in this application, the method further includes: if a printing abnormality is detected, a pause signal is sent to freeze the buffer pool; after the abnormality is resolved, incremental instructions for the breakpoint layer and subsequent layers are regenerated based on the breakpoint layer data to resume printing.

[0017] This application also provides an incremental parallel 3D printing technology apparatus, comprising:

[0018] The incremental preprocessing module is used to obtain the printing data of the model to be printed, calculate the number of buffer layers based on the printing data, select the partially generated buffer layers, generate the corresponding fill path for the selected partially generated buffer layers, and store the fill path into the instruction buffer pool.

[0019] The dynamic buffer control module is used to synchronously process data from layers 2N to 3N and generate incremental instructions for the corresponding buffer layers to supplement the buffer pool.

[0020] The print execution module is used to read buffer pool instructions, execute printing, and upload the actual data.

[0021] In some other embodiments of the incremental parallel 3D printing technology apparatus provided in this application, it further includes:

[0022] The device interaction feedback module is used to establish bidirectional communication between the printing execution module and the incremental preprocessing module, collect the actual data of the printing execution module in real time, convert it into standardized feedback signals and transmit it to the incremental preprocessing module.

[0023] Furthermore, to achieve the above objectives, the present invention also provides an incremental parallel 3D printing technology device, which includes a processor, a memory, and an incremental parallel 3D printing technology program stored in the memory and executable by the processor. When the incremental parallel 3D printing technology program is executed by the processor, it implements the steps of the incremental parallel 3D printing technology method described above.

[0024] Furthermore, to achieve the above objectives, the present invention also provides a computer-readable storage medium storing an incremental parallel 3D printing technology program, wherein when the incremental parallel 3D printing technology program is executed by a processor, it implements the steps of the incremental parallel 3D printing technology method as described above.

[0025] The beneficial effects of this invention are as follows: By acquiring the printing data of the model to be printed, the number of buffer layers is calculated based on the printing data; a portion of the buffer layers generated first are selected, and corresponding fill paths are generated for the selected portion of the buffer layers, which are then stored in the instruction buffer pool; the instruction for the first layer in the buffer pool is read, printing is executed and the actual data is uploaded, the data for the 2N-3N layers is processed synchronously, and incremental instructions for the corresponding buffer layers are generated to supplement the buffer pool. After completing the corresponding actions, the next round of printing is performed. In the prior art, the preprocessing work of full slicing and full path filling must be completed before printing can start. The preprocessing time and printing time are completely superimposed serially. For large-size, highly complex models, the preprocessing stage alone can take several hours or even days. This application achieves a high degree of overlap between preprocessing time and printing time by executing preprocessing and printing in full parallel, so that only a small amount of preprocessing work for buffer layers needs to be completed before printing starts, and the incremental preprocessing of all subsequent layers is completed synchronously during printing. Compared with the traditional process, the total printing cycle can be shortened by 40% to 60%, completely eliminating the long preprocessing waiting time before printing starts. Existing technologies require generating, transmitting, and storing full print instructions at the GB level, which not only consumes a large amount of storage resources but also easily causes transmission delays due to multiple devices simultaneously retrieving the full data in batch production scenarios, and may even lead to print interruptions due to data packet loss. This application adopts an incremental instruction generation and transmission mode, which only needs to generate, transmit, and store lightweight incremental instructions in the current buffer pool in real time. The size of a single batch instruction is only at the KB level, which does not require a large amount of storage resources. At the same time, it significantly reduces the data transmission bandwidth requirements, completely avoids the delay, packet loss, and print interruption problems caused by full large data transmission, and significantly reduces the memory and computing power performance requirements of the printing device's host computer. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the hardware structure of the incremental parallel 3D printing technology device involved in this invention.

[0027] Figure 2 This is a flowchart illustrating the incremental parallel 3D printing technology method involved in this invention.

[0028] Figure 3 This is a schematic diagram of the incremental parallel 3D printing technology device involved in this invention.

[0029] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0030] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0031] The incremental parallel 3D printing technology method involved in the embodiments of the present invention is mainly applied to incremental parallel 3D printing technology equipment, which can be a PC, portable computer, mobile terminal or other device with display and processing functions.

[0032] Reference Figure 1 , Figure 1 This is a schematic diagram of the hardware structure of the incremental parallel 3D printing technology device involved in the embodiment of the present invention. In this embodiment, the incremental parallel 3D printing technology device may include a processor 1001 (e.g., CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize communication between these components; the user interface 1003 may include a display screen or an input unit such as a keyboard; the network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface); the memory 1005 may be a high-speed RAM memory or a stable non-volatile memory, such as a disk storage device, and the memory 1005 may optionally be a storage device independent of the aforementioned processor 1001.

[0033] Those skilled in the art will understand that Figure 1 The hardware structure shown does not constitute a limitation on incremental parallel 3D printing equipment and may include more or fewer parts than shown, or combine certain parts, or have different part arrangements.

[0034] Continue to refer to Figure 1 , Figure 1 The memory 1005, which is a computer-readable storage medium, may include an operating system, a network communication module, and an incremental parallel 3D printing technology program.

[0035] exist Figure 1 In this embodiment, the network communication module is mainly used to connect to the server and communicate with the server for data; while the processor 1001 can call the incremental parallel 3D printing technology program stored in the memory 1005 and execute the incremental parallel 3D printing technology method provided in this embodiment of the invention.

[0036] This invention provides an incremental parallel 3D printing technology method, referencing... Figure 2 The steps include:

[0037] S10, Obtain the printing data of the model to be printed, and calculate the number of buffer layers based on the printing data;

[0038] S20: Select the part of the buffer layer that was generated first, generate the corresponding filling path for the selected part of the buffer layer, and store the filling path into the instruction buffer pool.

[0039] S30: Read the first layer instruction from the buffer pool, execute the printing and upload the actual data, process the data of layers 2N-3N synchronously, generate the corresponding incremental instruction of the buffer layer to supplement the buffer pool, and after completing the corresponding actions, proceed to the next round of printing.

[0040] In this embodiment, the printing data of the model to be printed is obtained, and the number of buffer layers is calculated based on the printing data. A portion of the buffer layers generated first are selected, and corresponding fill paths are generated for the selected buffer layers. The fill paths are stored in the instruction buffer pool. The first layer instruction is read from the buffer pool, printing is executed, and the actual data is uploaded. Data for layers 2N-3N is processed synchronously, and incremental instructions for the corresponding buffer layers are generated and added to the buffer pool. After completing the corresponding actions, the next round of printing is performed. In existing technologies, preprocessing work involving full slicing and full path filling must be completed before printing can begin. Preprocessing time and printing time are completely superimposed serially. For large-size, highly complex models, the preprocessing stage alone can take several hours or even days. This application achieves parallel execution of preprocessing and printing, requiring only a small amount of buffer layer preprocessing work to be completed before printing starts. During printing, incremental preprocessing of all subsequent layers is completed synchronously, achieving a high degree of overlap between preprocessing time and printing time. Compared to traditional processes, this can shorten the total printing cycle by 40% to 60%, completely eliminating the long preprocessing waiting time before printing starts. Existing technologies require generating, transmitting, and storing gigabyte-level full print commands, which not only consumes significant storage resources but also easily leads to transmission delays and even print interruptions due to data packet loss in multi-device batch production scenarios when multiple devices simultaneously retrieve the full data. This application adopts an incremental command generation and transmission mode, which only needs to generate, transmit, and store lightweight incremental commands in the current buffer pool in real time. The size of a single batch of commands is only in the kilobyte range, eliminating the need for large storage resources and significantly reducing data transmission bandwidth requirements. This completely avoids the delay, packet loss, and print interruption problems caused by full-volume data transmission, while also significantly reducing the memory and computing power performance requirements of the printing device's host computer.

[0041] Specifically, this method first calculates the number of buffer layers based on the printing data of the model to be printed. By quantifying and matching the correspondence between printing process, model features, and equipment performance, it determines the optimal number of buffer layers that can support continuous and uninterrupted printing. This fundamentally solves the problem of data interruption caused by the lack of reasonable buffer matching and the tendency for slicing speed to lag behind printing speed in existing printing solutions. This application does not need to process all the data of the complete 3D model; it only needs to generate the filling path of the selected initial buffer layer. This lightweight incremental printing instruction can then be stored in the instruction buffer pool, completing the preloading before printing starts. The precondition for printing starts is compressed from full data readiness to initial data readiness in the buffer pool, reducing the invalid waiting time before printing starts. This method constructs a closed-loop parallel loop mechanism for printing execution, incremental preprocessing, and buffer pool replenishment. While the printing execution module reads the first layer instruction from the buffer pool and executes the printing action, it simultaneously starts the incremental preprocessing of the subsequent 2N-3N layers of data, generates the corresponding incremental printing instructions, and replenishes them to the instruction buffer pool in real time. In this process, the printing action and the subsequent layer slicing and path filling preprocessing actions are carried out in complete parallel. While printing is being performed, incremental data processing and buffer replenishment of subsequent layers are continuously completed until all layers of the model are printed. This fundamentally solves the core problem in existing technologies where preprocessing time and printing time are completely superimposed in sequence, and the equipment is idle for a long time waiting for data.

[0042] In this embodiment, to implement the above method steps, this application provides an incremental parallel 3D printing technology apparatus, referencing... Figure 3 The device has the following modules:

[0043] Incremental preprocessing module Z10: Receives 3D model data (STL and other 3D formats), performs incremental slicing (generating 2D contours of each layer in the layer group in CLI and other formats) and incremental filling (calculating the path, support parameters, and process parameters of each layer) according to the number of layers. That is, once each layer slice is prepared, the filling path can be calculated and transmitted to the printer for printing, and lightweight incremental instructions can be output.

[0044] The dynamic buffer control module Z20 receives incremental instructions and stores them in the buffer pool. It monitors the remaining number of layers in the buffer pool in real time. When the remaining number of layers is less than a preset threshold (such as 1 / 3 of the total number of buffer layers), it sends an expedited processing signal to the incremental preprocessing module to trigger the preprocessing of the next set of layers. At the same time, it filters invalid instructions (such as duplicate path instructions) to ensure the validity of the instructions.

[0045] Z30 Equipment Interaction Feedback Module: Establishes bidirectional communication between the printing execution module and the incremental preprocessing module, collects real-time actual data from the printing execution module (such as layer thickness, temperature, and melt pool roundness), converts it into standardized feedback signals, and transmits them to the incremental preprocessing module.

[0046] Printing execution module Z40: Reads incremental instructions from the buffer pool, drives the device to perform printing actions (such as printhead movement, laser scanning, and resin exposure), and simultaneously uploads actual printing data to the device interaction feedback module in real time.

[0047] In this application, 3D printing (additive manufacturing), also known as additive manufacturing, is a digital manufacturing technology that uses a digital model as a basis to build up materials layer by layer to create a physical object, which is different from traditional subtractive and equal-material manufacturing methods.

[0048] In this embodiment, the selectable process types include all mainstream industrial and desktop 3D printing processes such as fused deposition modeling (FDM), selective laser melting (SLM), and stereolithography (SLA). This method can be adapted to the process characteristics and parameter requirements of the above-mentioned processes.

[0049] Printed data includes the following types:

[0050] Model construction data: Complete 3D model data of the object to be printed (such as STL / 3MF format), including the model's geometric contour, number of triangular facets, special structures such as cutouts / thin walls, total number of target printing layers, target layer thickness (usually 0.02-0.1mm), and other core geometric parameters;

[0051] Process type data: The specific 3D printing process type (FDM / SLM / SLA, etc.) used in this printing, and the benchmark indicators such as the basic slicing time, path filling time, and single-layer printing time for different processes;

[0052] Basic process parameters: These are the basic execution parameters corresponding to the printing process, such as the extrusion speed and nozzle temperature of FDM, the laser power, scanning speed, and spot diameter of SLM, and the exposure time and light source power of SLA.

[0053] Equipment performance data: This includes the inherent parameters of the 3D printing equipment used, such as hardware processing performance, standard single-layer printing time, data transmission bandwidth, and sensor acquisition capabilities. It should be noted that the printing data uses existing, commonly used printing data.

[0054] The number of buffer layers (denoted as N) refers to the total number of model layers that need to be pre-processed and stored in the instruction buffer pool before printing starts, as pre-set by this method to ensure continuous and uninterrupted printing. It is a parameter for achieving parallel matching between pre-processing and printing. Its value is automatically calculated by the system based on printing data and can also be manually adjusted. The core calculation logic of the number of buffer layers involves the coordinated correction of three factors: basic process type indicators, model construction complexity indicators, and equipment processing performance indicators. Ultimately, it must satisfy the requirement that the total pre-processing time of N layers ≤ the total printing time of N layers, ensuring that the incremental pre-processing speed ≥ the printing execution speed, thus fundamentally avoiding data interruptions and printing pauses caused by incomplete data during printing. For example, the basic buffer layer number for FDM process is 5 layers, and the basic buffer layer number for SLM process is 15 layers.

[0055] The specific calculation logic for the number of buffer layers is as follows:

[0056] 1. Process type adaptation: The slicing and filling times of different 3D printing processes (FDM / SLM / SLA) vary greatly (e.g., FDM process slicing 1 layer ≈ 2s and filling 1 layer ≈ 1s, SLM process slicing 1 layer ≈ 5s and filling 1 layer ≈ 3s). The system first uses the preset base value of the process (FDM base value is 5 layers, SLM base value is 15 layers). This item can be manually adjusted as a parameter.

[0057] 2. Model Complexity Correction: If the 3D model contains a large number of hollow thin-walled structures (such as turbine disks) and the number of triangular facets is greater than 100,000, the system will adjust the base value (such as increasing the SLM from 15 layers to 20 layers) to ensure sufficient preprocessing time for complex layers;

[0058] 3. Equipment performance matching: If the printer takes less time to print one layer (e.g., industrial-grade SLM prints one layer in only 2 seconds, while desktop SLM takes 5 seconds), the system will dynamically adjust N to ensure that the total preprocessing time for N layers is less than or equal to the total printing time, thus completely avoiding data interruption. This parameter can be manually adjusted.

[0059] A buffer layer is the basic unit constituting the number of buffer layers. It refers to a single layer of the model that has completed preprocessing processes such as slicing and path filling, generated complete print execution instructions, is temporarily stored in the instruction buffer pool, and has not yet been printed. It is the smallest connecting unit between preprocessed data and print execution in this method. This application includes an initial N-layer buffer layer pre-generated before printing starts, as well as subsequent buffer layers that are synchronously preprocessed and continuously replenished to the buffer pool during printing. The buffer layers are ordered according to the Z-axis printing order of the model to ensure the continuity of print execution.

[0060] The general meaning of infill path refers to the trajectory planning of the printing actuator (nozzle, laser galvanometer, etc.) within a single layer cross-section of the model during the 3D printing process. It is a core component of the 3D printing instruction and directly determines the forming accuracy, mechanical properties, and printing efficiency of the printed part. In this application, it refers to the complete execution trajectory and supporting parameters generated by the algorithm for the two-dimensional cross-sectional contour of a single buffer layer. Specifically, it includes: the straight line / honeycomb infill trajectory of FDM process, the island / strip scanning trajectory of SLM process, the generation path of the support structure, and the corresponding process parameters such as laser power, extrusion speed, scanning speed, and start / stop control under the corresponding path.

[0061] The instruction buffer pool is a dedicated storage space for temporarily storing incremental instructions that have completed preprocessing and generated complete print execution instructions but have not yet been executed. It serves as the hub connecting the incremental preprocessing module and the print execution module, and is managed throughout the entire process by the dynamic buffer control module.

[0062] The instruction buffer pool in this application has the following functions:

[0063] Pre-store the print instructions generated before the print start-up of the initial N buffer layers, and trigger the print start-up after the preset number of buffer layers is reached;

[0064] Receive subsequent hierarchical incremental instructions generated synchronously during the printing process in real time, and continuously replenish the instruction inventory;

[0065] The remaining number of executable instructions is monitored in real time. When the remaining number of instructions is lower than a preset threshold (such as 1 / 3 of the total buffered number of instructions), the preprocessing module is triggered to expedite the processing.

[0066] Filtering out invalid and duplicate instructions ensures the validity and continuity of printing instructions, completely avoiding data interruptions.

[0067] The first layer of the instruction buffer refers to the complete print execution instruction stored in the instruction buffer pool, corresponding to the lowest layer (the first layer of printing) in the Z-axis direction of the model to be printed. It is the first instruction executed after the printing equipment starts, and it determines the initial reference and the first layer forming quality of the model printing. At the same time as its execution, the system simultaneously starts the incremental preprocessing of the subsequent 2N-3N layers.

[0068] Actual data refers to the comprehensive measured data related to the actual printing status and forming result collected in real time by various sensors of the equipment during the single-layer printing process. This includes key parameters such as actual printed layer thickness, melt pool temperature and roundness (SLM process), nozzle temperature and extrusion volume (FDM process), actual scanning / moving speed, substrate flatness, forming surface contour deviation, and equipment operating status. It also includes abnormal data such as material blockage and incomplete fusion detected during the printing process.

[0069] N is the number of buffer layers determined by the system calculation. The data of the 2Nth to 3Nth layers refers to the original data of the model layers in the Z-axis direction of the model to be printed, within the range of the second to the third number of buffer layers. It is the target data that the incremental preprocessing module processes synchronously at the same time as the first layer printing instruction.

[0070] Incremental instructions refer to lightweight single-batch printing execution instructions generated through incremental slicing and incremental path filling of a single or multiple consecutive layers of the model to be printed, rather than full instructions covering all layers of the model. A single set of incremental instructions only contains the necessary printing data such as the slice outline data, filling path parameters, process control parameters, and support structure parameters of the corresponding layer. The volume of a single batch is usually in the KB range, much smaller than the traditional GB-level full instructions. It can realize real-time generation, real-time transmission, and real-time replenishment to the instruction buffer pool. It is the core data unit of this method to reduce the computing power and storage consumption of equipment and realize parallel printing.

[0071] The next round of printing refers to the next standardized loop execution process that the system automatically enters after completing the current single-layer printing execution, synchronously completing the subsequent layer incremental preprocessing and buffer pool instruction replenishment. It is the core loop mechanism for realizing continuous parallel printing of the model from the first layer to the last layer.

[0072] The standardized process for single-round printing is to read the current layer instruction from the buffer pool, execute the printing and upload the actual data, preprocess the subsequent layers synchronously and supplement the incremental instructions to the buffer pool, and then enter the next round of printing after completing this process, repeating until all layers of the model are printed.

[0073] In some embodiments, after the steps of reading the first-level instructions of the buffer pool, executing the printing and uploading of actual data, the method further includes:

[0074] Obtain actual print feedback data and adjust the next layer's print parameters based on the actual print feedback data.

[0075] This embodiment addresses the inherent limitation of existing technologies where parameters cannot be dynamically adjusted after full preprocessing. In this embodiment, the printing execution module executes only the instructions for the current layer, while the preprocessing and parameter generation for subsequent layers proceed synchronously with the printing process. After completing the printing of the current layer and uploading the actual data, the system obtains the actual printing feedback data for that layer in real time, compares the deviation between the preset parameters and the actual molding result, and makes targeted corrections to the printing parameters of the next layer that have not yet been executed in the buffer pool based on the deviation. The corrected parameters are then used for the next layer's printing execution, ultimately achieving real-time closed-loop control of printing, feedback, and adjustment simultaneously, completely breaking the limitation of traditional technologies where preset parameters cannot be modified. This fundamentally solves the problem of accumulated printing errors, improves molding accuracy, and avoids the problem of accumulated layer thickness deviations and excessive final molding errors caused by uneven substrates. Through real-time parameter correction after single-layer printing, the molding deviation of the current layer can be compensated immediately, preventing the deviation from accumulating layer by layer along the Z-axis. This controls the accumulated error of more than 0.5mm in traditional processes to within 0.05mm, significantly improving the dimensional accuracy of large-size, high-thickness models.

[0076] In some embodiments, the printing data includes: model construction data, target number of layers, and the type of printing process used.

[0077] The step of calculating the number of buffer layers based on the printed data includes:

[0078] Obtain basic indicators of process type, complexity indicators of model construction, and equipment processing performance indicators. Based on the basic indicators of process type, use the complexity indicators of model construction and equipment processing performance indicators as correction data to correct the basic indicators of process type and generate the corresponding number of buffer layers.

[0079] The steps of correcting the basic process type indicators based on process type indicators, using the complexity indicators of the model construction and the equipment processing performance indicators as correction data, and generating the corresponding number of buffer layers include:

[0080] Based on the preset base value of the process type, if the model has more than a predetermined amount of hollow or thin-walled structures, or the number of triangular facets of the model is greater than 100,000, then the preset base value based on the process type is increased. In addition, the preset base value is increased or decreased in combination with the equipment processing performance index, so that the total preprocessing time of the generated buffer layer is less than or equal to the total printing time.

[0081] In this embodiment, the basic index for process type refers to the pre-set baseline value for the number of buffer layers based on the inherent characteristics of different 3D printing processes. It is the core anchor point for calculating the number of buffer layers. This index is set based on industry-standard benchmarks for single-layer slicing time, single-layer path filling time, and single-layer printing time for different processes. For example, in this solution, the basic value for FDM process is 5 layers, and the basic value for SLM process is 15 layers. This basic value also supports manual debugging and optimization.

[0082] The complexity index of model construction refers to the core indicator that quantifies the difficulty of layer slicing and path filling of the model to be printed. It is one of the core bases for adjusting the number of buffer layers. Specifically, it includes the total number of triangular facets of the model, the peak value of single-layer triangular facets, the proportion of hollow / thin-walled / complex curved surface structures, the number of support structures, etc. The higher the index value, the longer the preprocessing time of a single layer of the model is.

[0083] Equipment processing performance indicators are core indicators that quantify the printing execution speed and data processing capabilities of 3D printing equipment. They are another core basis for adjusting the number of buffer layers. Specifically, they include the standard printing time per layer, data transmission bandwidth, processor computing power, and memory capacity, which directly determine the matching relationship between printing execution speed and preprocessing speed.

[0084] Correction data refers to quantitative adjustment parameters that adjust the basic indicators of the process type upwards or downwards based on model complexity indicators and equipment processing performance indicators. Its core function is to make the final number of buffer layers adapt to the actual preprocessing difficulty and equipment execution speed of the current printing task, and ensure that the incremental preprocessing speed is greater than or equal to the printing execution speed.

[0085] The calculation process involves first determining the preset base value for the corresponding process type, then adjusting the base value upwards using quantitative model complexity judgment rules (proportion of hollow or thin-walled structures, number of triangular facets > 100,000) to reserve sufficient preprocessing time for high-complexity layers; subsequently, combining the equipment's processing performance indicators, the base value is adjusted upwards or downwards a second time to adapt to the actual printing speed of the equipment; finally, the final number of buffer layers is checked and locked according to the criterion that the total preprocessing time of N layers ≤ the total printing time of N layers, ensuring that the preprocessing speed always keeps up with the printing execution speed and completely avoiding data interruption.

[0086] The above steps quantify the buffer layer correction rules, enabling reproducible and implementable precise calculations. They clarify the quantitative judgment threshold for high-complexity models, transforming buffer layer correction from vague empirical judgments to standardized numerical calculations. This ensures that the optimal buffer layer number can be calculated for different operators, models, and equipment, improving the feasibility and stability of the technical solution. For complex models, preprocessing redundancy is pre-reserved to prevent printing delays caused by complex layers. For complex industrial models such as turbine disks with numerous blades, thin walls, and hollow structures, the buffer layer number can be increased in advance to prioritize the preprocessing of complex layers. This avoids buffer pool exhaustion and printing pauses due to sudden increases in single-layer preprocessing time, ensuring continuous printing of large-size complex models.

[0087] In summary, based on the above embodiments, this application provides the following implementation examples:

[0088] SLM process for printing titanium alloy turbine disks (Ti-6Al-4V material, diameter 500mm, thickness 100mm).

[0089] 1. Equipment and parameter configuration:

[0090] Equipment: SLM industrial-grade printer (fiber laser, 500W power, 50μm spot diameter, 1000mm / s scanning speed).

[0091] Process parameters: target layer thickness 0.05mm, scanning speed 300-500mm / s, etc.

[0092] System configuration: Buffer layer N=15 (according to model analysis, slicing one layer takes 5 seconds, filling one layer takes 3 seconds, and printing one layer takes 3 seconds. 15 layers of buffer can avoid data interruption and can be combined with AI models).

[0093] 2. Implementation steps:

[0094] Step 1: Model Input and Initialization: Import the turbine disk STL model (containing 12 blades, with a total of 6.2 million triangular facets), the system identifies the process as SLM, sets N=15, buffer pool threshold=5, and complex layer identification threshold=100000 (number of triangular facets).

[0095] Step 2: Buffer pool preloading and complex layer processing: The incremental preprocessing module slices layers 1-15, identifies layers 8-12 as complex layers (more than 100,000 triangular facets), prioritizes filling these 5 layers (strip scanning path, scanning speed 800mm / s), and generates 15 incremental instructions (approximately 500KB in size) which are stored in the buffer pool.

[0096] Step 3: Parallel printing and feedback correction:

[0097] The printing execution module prints layers 1-15 (3 seconds per layer, 45 seconds in total), and the device interaction feedback module feeds back the printing monitoring data (printed images, melt pool temperature, etc.) to the preprocessing module.

[0098] Based on printing feedback, the incremental preprocessing module reduces the laser power of complex layers in layers 16-30 from 350W to 330W, and simultaneously completes the slicing and filling of layers 16-30, replenishing the buffer pool (8 layers remaining, higher than the threshold of 5).

[0099] Step 4: After printing all layers in batches, release the resources consumed by each layer and repeat the above steps.

[0100] In some embodiments, the method further includes: if a printing anomaly is detected, sending a pause signal to freeze the buffer pool; after the anomaly is resolved, regenerating incremental instructions for the breakpoint layer and subsequent layers based on the breakpoint layer data, and resuming printing.

[0101] Buffer pool freezing refers to the buffer pool locking operation performed by the dynamic buffer control module after receiving a pause signal. Specifically, it includes: stopping the replenishment and updating of incremental instructions, locking existing instructions in the buffer pool to prevent them from being read and executed, and preserving all data and states in the buffer pool to avoid the execution of invalid instructions and the corruption of buffer pool data under abnormal conditions.

[0102] During printing, the system monitors the equipment's operating status and printing quality in real time. If a printing anomaly is detected, a pause signal is immediately sent, stopping the printing process and freezing the buffer pool to prevent further part scrap. After the anomaly is resolved, there's no need to reload the full model and perform full slicing and path filling. Instead, based on the actual printing data of the breakpoint layer, the starting layer for resuming printing is determined. The incremental preprocessing module regenerates the incremental instructions for the breakpoint layer and all subsequent layers, replenishing them to the buffer pool before printing resumes. Leveraging the incremental processing characteristic, rapid resuming printing after anomalies is achieved, eliminating the need to reprint from scratch. This reduces material and time waste caused by anomalies and lowers the print scrap rate. Addressing the issue of traditional processes requiring printing to be stopped and full preprocessing and printing to be re-executed after an anomaly, the breakpoint resume mechanism can directly resume printing from the point of the anomaly, avoiding the scrapping of entire sheets of parts due to anomalies in the later stages of large-size model printing. This saves anomaly recovery time and significantly reduces printing material waste.

[0103] Furthermore, to achieve the above objectives, the present invention also provides an incremental parallel 3D printing technology apparatus, the incremental parallel 3D printing technology apparatus comprising:

[0104] The incremental preprocessing module is used to obtain the printing data of the model to be printed, calculate the number of buffer layers based on the printing data, select the partially generated buffer layers, generate the corresponding fill path for the selected partially generated buffer layers, and store the fill path into the instruction buffer pool.

[0105] The dynamic buffer control module is used to synchronously process data from layers 2N to 3N and generate incremental instructions for the corresponding buffer layers to supplement the buffer pool.

[0106] The print execution module is used to read buffer pool instructions, execute printing, and upload the actual data.

[0107] In some embodiments, a device interaction feedback module is also included, which is used to establish bidirectional communication between the printing execution module and the incremental preprocessing module, collect the actual data of the printing execution module in real time, convert it into a standardized feedback signal and transmit it to the incremental preprocessing module.

[0108] In addition, embodiments of the present invention also provide a computer-readable storage medium.

[0109] The present invention stores an incremental parallel 3D printing technology program on a computer-readable storage medium, wherein when the incremental parallel 3D printing technology program is executed by a processor, it implements the steps of the incremental parallel 3D printing technology method as described above.

[0110] The method implemented when the incremental parallel 3D printing technology program is executed can be referred to in various embodiments of the incremental parallel 3D printing technology method of the present invention, and will not be repeated here.

[0111] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0112] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0113] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0114] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0115] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are exhaustively listed. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0116] For those skilled in the art, various modifications and improvements can be made without departing from the concept of the present invention, and these all fall within the scope of protection of the present invention. The scope of protection of the present invention is defined by the appended claims.

Claims

1. An incremental parallel 3D printing technology method, characterized by the following steps: include: Obtain the printing data of the model to be printed, and calculate the number of buffer layers based on the printing data; Select the first part of the buffer layer, generate the corresponding padding path for the selected part of the buffer layer, and store the padding path into the instruction buffer pool. Read the first layer instruction from the buffer pool, execute the printing and upload the actual data, process the data of layers 2N-3N synchronously, and generate the corresponding incremental instruction of the buffer layer to supplement the buffer pool. After completing the corresponding actions, proceed to the next round of printing.

2. The incremental parallel 3D printing technology method according to claim 1, characterized in that, After reading the first-level instruction of the buffer pool, executing the steps of printing and uploading the actual data, the process further includes: Obtain actual print feedback data and adjust the next layer's print parameters based on the actual print feedback data.

3. The incremental parallel 3D printing technology method according to claim 2, characterized in that, The printing data includes: model construction data, target number of layers, and the type of printing process used.

4. The incremental parallel 3D printing technology method according to claim 3, characterized in that, The step of calculating the number of buffer layers based on the printed data includes: Obtain basic indicators of process type, complexity indicators of model construction, and equipment processing performance indicators. Based on the basic indicators of process type, use the complexity indicators of model construction and equipment processing performance indicators as correction data to correct the basic indicators of process type and generate the corresponding number of buffer layers.

5. The incremental parallel 3D printing technology method according to claim 4, characterized in that, The steps of correcting the basic process type indicators based on process type indicators, using the complexity indicators of the model construction and the equipment processing performance indicators as correction data, and generating the corresponding number of buffer layers include: Based on the preset base value of the process type, if the model has more than a predetermined amount of hollow or thin-walled structures, or the number of triangular facets of the model is greater than 100,000, then the preset base value based on the process type is increased. In addition, the preset base value is increased or decreased in combination with the equipment processing performance index, so that the total preprocessing time of the generated buffer layer is less than or equal to the total printing time.

6. The incremental parallel 3D printing technology method according to claim 1, characterized in that, Also includes: If a printing anomaly is detected, a pause signal is sent, freezing the buffer pool; After the anomaly is resolved, incremental instructions for the breakpoint layer and subsequent layers are regenerated based on the breakpoint layer data, and printing is resumed.

7. An incremental parallel 3D printing technology device, characterized in that, include: The incremental preprocessing module is used to obtain the printing data of the model to be printed, calculate the number of buffer layers based on the printing data, select the partially generated buffer layers, generate the corresponding fill path for the selected partially generated buffer layers, and store the fill path into the instruction buffer pool. The dynamic buffer control module is used to synchronously process data from layers 2N to 3N and generate incremental instructions for the corresponding buffer layers to supplement the buffer pool. The print execution module is used to read buffer pool instructions, execute printing, and upload the actual data.

8. The incremental parallel 3D printing technology apparatus according to claim 7, characterized in that, Also includes: The device interaction feedback module is used to establish bidirectional communication between the printing execution module and the incremental preprocessing module, collect the actual data of the printing execution module in real time, convert it into standardized feedback signals and transmit it to the incremental preprocessing module.

9. An incremental parallel 3D printing technology device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, it implements the steps of the incremental parallel 3D printing method as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, it implements the steps of the incremental parallel 3D printing method as described in any one of claims 1 to 6.

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