Thermal process control method and system for quartz diffusion tube
By optimizing the thermal process of quartz diffusers using digital twin models and thermal simulation technology, the quality and consistency issues caused by reliance on manual operation in the thermal process were resolved, resulting in a higher yield.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHEJIANG FULEDE QUARTZ TECH CO LTD
- Filing Date
- 2026-01-28
- Publication Date
- 2026-05-01
AI Technical Summary
The thermal processes in the current production of quartz diffusers rely on manual operation, resulting in low quality and batch consistency, and a low yield.
By establishing a digital twin model of the quartz diffuser, the process parameter range of the associated process group is obtained, thermal simulation is performed, the target process parameters are determined, and the parameters are sent to the equipment for execution to optimize the heat transfer digital model of the thermal process.
This improved the quality and batch consistency of quartz diffuser tubes, and increased the yield.
Smart Images
Figure CN121959949A_ABST
Abstract
Description
A method and system for thermal process control of quartz diffuser tubes Technical Field
[0001] This application relates to the field of electrical digital data processing technology, and in particular to a thermal process control method and system for a quartz diffuser tube. Background Technology
[0002] Quartz diffusion tubes (also known as oxide diffusion tubes) use high-purity quartz as the substrate. Due to their excellent high-temperature resistance and chemical stability, they have become a key carrier for diffusion processes in semiconductors, photovoltaics, and other fields. The production of quartz diffusion tubes is crucial to the precision of chip oxidation and has a vital impact on chip quality. In particular, the production technology of quartz diffusion tubes with particularly large usage (φ350mm large cavity, φ400mm extra-large cavity), and even double-layer large cavity quartz diffusion tubes, has become a bottleneck problem for the development of integrated circuit chip technology in my country.
[0003] Thermal processing is the core technology in the production of quartz diffusers, including thermal welding and thermal polishing. Currently, most thermal processes are manual, requiring highly skilled and experienced workers. This leads to inconsistent quality and batch-to-batch performance of the quartz diffusers, resulting in a low yield. Therefore, a better thermal process control scheme for quartz diffusers is needed to overcome these difficulties. Summary of the Invention
[0004] This application provides a thermal process control method and system for quartz diffusers to improve the quality and batch consistency of quartz diffusers, thereby increasing the yield of quartz diffusers.
[0005] In a first aspect, this application provides a thermal process control method for a quartz diffuser tube. The thermal process control system includes a simulation unit, which is configured to: perform modeling processing based on the physical structure of the quartz diffuser tube to obtain a digital twin characterizing the quartz diffuser tube; acquire associated process groups related to the thermal process, and determine the process parameter range of the thermal process based on the process parameters of the thermal process in the associated process group, wherein the associated process group is a combination of processes that jointly affect the quality of the quartz diffuser tube; perform transient temperature distribution thermal simulation processing on the digital twin within the process parameter range to obtain simulation results; and, based on the simulation results, determine target process parameters from the process parameter range and send the process parameters to the equipment related to the thermal process so that the equipment executes the target process parameters.
[0006] Furthermore, the thermal process control system includes multiple GPU engines; the process of performing transient temperature distribution thermal simulation on the digital twin within the process parameter range to obtain simulation results includes: sending a temperature iteration command to the GPU engines at time t, where each GPU engine corresponds to an iteration point, and the iteration point is a node in the digital twin whose temperature needs to be calculated; receiving the temperature of the iteration point at time t+1 sent by the GPU engines, where t and t+1 are any times when the thermal simulation is performed; displaying the temperature of the iteration point at time t+1 to obtain the simulation results; the GPU engines are used to: calculate the temperature of the iteration point at time t+1 based on the kernel function and the temperature of the kernel node surrounding the iteration point at time t, and send the temperature of the iteration point at time t+1 to the simulation unit.
[0007] Furthermore, the step of calculating the temperature of the iteration point at time t+1 based on the kernel function and the temperature of the kernel node surrounding the iteration point at time t, and sending the temperature of the iteration point at time t+1 to the simulation unit, includes: reading the temperature of the iteration point and the temperature of the kernel node surrounding the iteration point at time t from the address pointed to by the first pointer; iterating the temperature of the iteration point based on the kernel function and the temperature of the kernel node surrounding the iteration point at time t to obtain the temperature of the iteration point at time t+1; obtaining the temperature of the kernel node surrounding the iteration point at time t+1, and storing the temperature of the iteration point and the temperature of the kernel node at time t+1 at the address pointed to by the second pointer; swapping the addresses pointed to by the first pointer and the second pointer, and sending the temperature corresponding to the first pointer to the simulation unit.
[0008] Furthermore, the GPU engine is used to: determine the kernel nodes based on the kernel function, with the iteration point as the center, wherein the kernel nodes are distributed along the coordinate axis corresponding to the kernel function, and the kernel nodes form a square.
[0009] Furthermore, if the smoothness of the isotherm corresponding to the simulation result is lower than a threshold, the simulation unit is used to: adjust the kernel function so that the distance between the kernel nodes corresponding to the adjusted kernel function is smaller than the distance between the corresponding kernel nodes before adjustment; and send the adjusted kernel function to the GPU engine.
[0010] Furthermore, determining the range of process parameters for the thermal process based on the process parameters of the thermal process in the associated process group includes: when the associated process group is a process for good products, determining the range of process parameters based on the process parameters of the thermal process in the associated process group; and when the associated process group is a process for defective products, determining the range of process parameters based on the complement of the process parameters of the thermal process in the associated process group.
[0011] Thirdly, this application provides a computer-readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement the above-described method. The computer-readable storage medium may be volatile or non-volatile.
[0012] Fourthly, this application provides an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the above method when executing instructions stored in the memory.
[0013] Fifthly, this application provides a computer program product including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device performs the above-described method.
[0014] In the embodiments of this specification, after modeling the quartz diffuser to obtain a digital twin, the process parameter range is first obtained from the associated process group. Then, the digital twin is subjected to thermal simulation using this process parameter range to obtain simulation results. Based on the simulation results, the target process parameters are determined and sent. This process, by limiting the process parameters of the thermal process to a range within the associated process group, reduces the data used in thermal simulation to obtain the target process parameters. The application of the target process parameters determined by thermal simulation in the thermal process optimizes the heat conduction digital model of the thermal process, which can improve the quality and batch consistency of the quartz diffuser, thereby increasing the yield of the quartz diffuser.
[0015] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure.
[0016] Other features and aspects of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description
[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0018] Figure 1 illustrates an exemplary architecture of a thermal process control system for a quartz diffuser tube; Figure 2 illustrates an exemplary flow chart of a thermal process control method for a quartz diffuser tube.
[0019] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation
[0020] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.
[0021] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.
[0022] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.
[0023] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.
[0024] Figure 1 illustrates a thermal process control system for a quartz diffuser according to an embodiment of the present disclosure. As shown in Figure 1, the thermal process control system includes a simulation unit 11, which is configured to: perform modeling processing based on the physical structure of the quartz diffuser to obtain a digital twin characterizing the quartz diffuser; acquire associated process groups related to the thermal process, and determine the process parameter range of the thermal process based on the process parameters of the thermal process in the associated process group, wherein the associated process group is a combination of processes that jointly affect the quality of the quartz diffuser; perform transient temperature distribution thermal simulation processing on the digital twin within the process parameter range to obtain simulation results; and, based on the simulation results, determine target process parameters from the process parameter range and send the process parameters to the equipment related to the thermal process so that the equipment executes the target process parameters.
[0025] The simulation unit, used to determine the target process parameters, can be located in the cloud or on the host CPU. This simulation unit can be used to simulate the process chain of quartz diffusers, resulting in a digital twin production line including the equipment and the quartz diffusers. The quartz diffusers in this digital twin production line are referred to as the digital twin. This specification does not provide a specific description of the digital twin production line; it can be determined based on the actual situation.
[0026] The physical structure of a quartz diffuser can include structural data and compositional data. Structural data includes the shape of each component (cube, sphere, cylinder, etc.) and the positional relationships between them (concentric, coplanar, tangent, etc.). Compositional data includes the raw material composition (such as SiO2 purity and impurity concentration) and porosity of the quartz diffuser.
[0027] After obtaining the above physical structure, modeling tools can be used to model one or more of the above structural and compositional data to obtain a digital twin characterizing the quartz diffuser. The modeling tool can be selected according to the actual situation, and this manual does not limit it.
[0028] A related process group is a combination of processes that corresponds one-to-one with a quality control theme. The processes within this group collectively affect the quality of the quartz diffuser. Specifically, the process chain for a quartz diffuser (including cutting, thermal processing, annealing, ultra-precision machining, cleaning, etc.) can have multiple quality control themes, such as improving color consistency and tube diameter consistency. Thus, there can be multiple process groups corresponding to these quality control themes. After obtaining the related process groups for the entire process chain, process groups containing thermal processes can be considered as related process groups associated with thermal processes.
[0029] Furthermore, the range of process parameters for the thermal process can be determined based on the process parameters of the thermal process within the associated process group. For example, when the heating rate is the same as that in the associated process group corresponding to the stress crack in the quartz diffuser, the heating rate within the range of process parameters can be determined based on the heating rate in that associated process group.
[0030] Since quality control can target both good products (e.g., achieving 95% color consistency in quartz diffusers) and defective products (e.g., avoiding diameter consistency below 85%), different methods should be used for thermal processes in different associated process groups. In one possible implementation, determining the range of process parameters for the thermal process based on the process parameters of the thermal process in the associated process group includes: determining the range of process parameters based on the process parameters of the thermal process in the associated process group when the associated process group is for good products; and determining the range of process parameters based on the complement of the process parameters of the thermal process in the associated process group when the associated process group is for defective products.
[0031] Among them, the process parameter range refers to the range of values for the process parameters of each process under the thermal process when performing thermal simulation processing on the digital twin.
[0032] For process groups associated with good products, the range of process parameters for the thermal process in the associated process group can be directly determined as the range of process parameters for the thermal process during thermal simulation. For process groups associated with defective products, the range of process parameters for the thermal process in the associated process group can be supplemented to determine the range of process parameters for the thermal process during thermal simulation.
[0033] In the above-mentioned compensation operation, the process parameters of the thermal process determined by domain experts can be used to compensate for the range of process parameters of the thermal process in the associated process group.
[0034] After determining the range of process parameters, thermal simulation can be performed on the digital twin using the data within that range to obtain simulation results. These simulation results may include deformation diagrams and stress diagrams of the quartz diffuser, etc. This manual does not specify the exact content of the simulation results; it can be determined based on the actual situation.
[0035] Different simulation results can be obtained based on different data within the process parameter range. Thus, multiple simulation results can be obtained based on different data within the process parameter range, and the data corresponding to the best-performing simulation result can be used as the target process parameter. This target process parameter can then be sent to the corresponding equipment so that the equipment executes the target process parameter during the production of quartz diffusion tubes. In one example, a device-side interface can be configured to receive the target process parameter sent from the cloud and manage various devices (e.g., selecting the equipment to perform the production task and sending the corresponding process parameters to that equipment), thereby achieving end-to-cloud collaboration in the process chain management of quartz diffusion tubes.
[0036] In the embodiments of this specification, after modeling the quartz diffuser to obtain a digital twin, the process parameter range is first obtained from the associated process group. Then, the digital twin is subjected to thermal simulation using this process parameter range to obtain simulation results. Based on the simulation results, the target process parameters are determined and sent. This process, by limiting the process parameters of the thermal process to a range within the associated process group, reduces the data used in thermal simulation to obtain the target process parameters. The application of the target process parameters determined by thermal simulation in the thermal process optimizes the heat conduction digital model of the thermal process, which can improve the quality and batch consistency of the quartz diffuser, thereby increasing the yield of the quartz diffuser.
[0037] A GPU engine is a parallel computing unit within the GPU core of a graphics processing unit (GPU). Through the GPU engine, the basic unit that enables various capabilities of the GPU (such as sharpening and rendering) can be provided. In one possible implementation, the thermal process control system includes multiple GPU engines. The process of performing transient temperature distribution thermal simulation on the digital twin within the process parameter range to obtain simulation results includes: sending a temperature iteration command to the GPU engines at time t, where each GPU engine corresponds to an iteration point, and the iteration point is the node in the digital twin whose temperature needs to be calculated; receiving the temperature of the iteration point at time t+1 sent by the GPU engines, where t and t+1 are any times during the thermal simulation; displaying the temperature of the iteration point at time t+1 to obtain the simulation result; the GPU engine is used to: calculate the temperature of the iteration point at time t+1 based on the kernel function and the temperature of the kernel node surrounding the iteration point at time t, and send the temperature of the iteration point at time t+1 to the simulation unit.
[0038] Specifically, the thermal simulation operations can be handled by the GPU engine (GPU engine 12 in Figure 1). In one example, the microcontroller unit (MCU) within the GPU can distribute thermal simulation task data and manage the GPU engine. The simulation process can utilize a technology called Compute Unified Device Architecture (CUDA). TM A general-purpose parallel computing architecture.
[0039] t and t+1 represent adjacent moments in the thermal simulation. In one example, the simulation process can be visualized from the perspective of moments t and t+1. The digital twin is divided into grids, where nodes can be vertices or centers of the grid. Nodes can include iteration points and core nodes. Iteration points are the nodes in the digital twin whose temperatures need to be calculated, while core nodes are a ring of nodes surrounding the iteration points. Clearly, core nodes that extend beyond the boundaries can be excluded from the temperature calculation of the iteration points.
[0040] Specifically, the simulation unit sends a temperature iteration command to the GPU engine at time t. To speed up the calculation, each GPU engine corresponds to an iteration point. After receiving the command, the GPU engine calculates (e.g., sums and averages) the temperature of the iteration point at time t+1 based on the kernel function (the function used by the GPU for calculation) and the temperature of the kernel node at time t. After calculation, it sends the temperature to the simulation unit. After receiving the temperature of the iteration point at time t+1, the simulation unit displays the temperature of the iteration point at time t+1 to obtain the simulation result.
[0041] The GPU engine can use pointers to read temperature during computation. In one possible implementation, the step of calculating the temperature of the iteration point at time t+1 based on the kernel function and the temperature of the kernel node surrounding the iteration point at time t, and sending the temperature of the iteration point at time t+1 to the simulation unit, includes: reading the temperature of the iteration point and the temperature of the kernel node surrounding the iteration point at time t from the address pointed to by the first pointer; iterating the temperature of the iteration point based on the kernel function and the temperature of the kernel node surrounding the iteration point at time t to obtain the temperature of the iteration point at time t+1; obtaining the temperature of the kernel node surrounding the iteration point at time t+1, and storing the temperature of the iteration point and the temperature of the kernel node at time t+1 at the address pointed to by the second pointer; swapping the addresses pointed to by the first pointer and the second pointer, and sending the temperature corresponding to the first pointer to the simulation unit.
[0042] Specifically, firstly, a three-dimensional array is used in the GPU's video memory to store the initial temperature values of the nodes in three-dimensional space, and a pointer pointing to this array is defined as the first pointer; based on the kernel function, a temperature iteration is performed at each iteration point in the space (i.e., address) pointed to by the first pointer; the iteration generates a three-dimensional array space pointed to by another pointer (i.e., the second pointer); the values of the two pointers are swapped, that is, the first pointer points to the data space after the temperature is updated. This will ensure that after each iteration, the first pointer still points to the data that needs to be updated, so that the next temperature iteration is ready.
[0043] In the above process, the simulation unit is combined with the GPU to collaboratively achieve thermal simulation processing. Compared to parallel computing based solely on the CPU, this process can significantly improve the calculation speed through the efficient parallel computing of the GPU. Verification has shown that the speedup (the ratio of instruction throughput to CPU throughput in the same amount of time) of this collaborative thermal simulation processing is greater than 100.
[0044] The kernel function determines the distribution of nodes, which can be a square distribution centered on the iteration point. Clearly, the positional relationship between this square and the coordinate axis corresponding to the kernel function affects the computational speed of the kernel function. In one possible implementation, the GPU engine is used to: determine the kernel nodes based on the kernel function, centered on the iteration point, wherein the kernel nodes are distributed along the coordinate axis corresponding to the kernel function, and the kernel nodes form a square.
[0045] Specifically, the kernel nodes are distributed along the coordinate axes corresponding to the kernel function, meaning that the two adjacent sides of the square are perpendicular to the x-axis and y-axis of the coordinate system, respectively. This positioning of the square, compared to a position where the sides are not perpendicular to the coordinate axes, is more conducive to accelerating the numerical simulation while ensuring the results remain unchanged.
[0046] In addition to limiting the angle between the graph formed by the kernel nodes and the coordinate axes, the density of kernel nodes in the kernel function can also be set. In one possible implementation, when the smoothness of the isotherm corresponding to the simulation result is lower than a threshold, the simulation unit is used to: adjust the kernel function so that the distance between the kernel nodes corresponding to the adjusted kernel function is smaller than the distance between the corresponding kernel nodes before adjustment; and send the adjusted kernel function to the GPU engine.
[0047] Specifically, when the density of kernel nodes is low (i.e., the distance between nodes is large), the iteration efficiency is accelerated, but the smoothness of the isotherms in the simulation results is low, appearing granular. In this case, the distance between kernel nodes in the kernel function can be reduced to achieve a balance between temperature iteration efficiency and smoothness, thereby improving the simulation results.
[0048] This adjustment can be performed multiple times until both temperature iteration efficiency and smoothness are achieved. At this point, the adjusted kernel function is sent to the GPU engine.
[0049] The simulation results can be images or matrix data. Specifically, the simulation unit generates two-dimensional matrix data from temperature data through perspective calculation based on the specified three-dimensional spatial cross-section to be displayed, and maps the temperature values to specific color values according to a color chart; in addition, the simulation unit can also push the two-dimensional matrix color value data generated by perspective calculation to the display for display.
[0050] Figure 2 shows a schematic flowchart of a thermal process control method for a quartz diffuser according to an embodiment of the present disclosure. As shown in Figure 2, the thermal process control method for the quartz diffuser is applied to a simulation unit in a thermal process control system. The method includes: step S21, modeling the physical structure of the quartz diffuser to obtain a digital twin representing the quartz diffuser; step S22, acquiring associated process groups related to the thermal process, and determining the process parameter range of the thermal process based on the process parameters of the thermal process in the associated process group, wherein the associated process group is a combination of processes that jointly affect the quality of the quartz diffuser; step S23, performing transient temperature distribution thermal simulation processing on the digital twin within the process parameter range to obtain simulation results; step S24, determining target process parameters from the process parameter range based on the simulation results, and sending the process parameters to the equipment related to the thermal process so that the equipment executes the target process parameters.
[0051] In the embodiments of this specification, after modeling the quartz diffuser to obtain a digital twin, the process parameter range is first obtained from the associated process group. Then, the digital twin is subjected to thermal simulation using this process parameter range to obtain simulation results. Based on the simulation results, the target process parameters are determined and sent. This process, by limiting the process parameters of the thermal process to a range within the associated process group, reduces the data used in thermal simulation to obtain the target process parameters. The application of the target process parameters determined by thermal simulation in the thermal process optimizes the heat conduction digital model of the thermal process, which can improve the quality and batch consistency of the quartz diffuser, thereby increasing the yield of the quartz diffuser.
[0052] This disclosure also proposes a computer-readable storage medium storing computer program instructions that, when executed by a processor, implement the above-described method. The computer-readable storage medium can be volatile or non-volatile.
[0053] This disclosure also proposes an electronic device, including: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.
[0054] This disclosure also provides a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device performs the above-described method.
[0055] This invention is now complete.
[0056] In summary, in the embodiments of this specification, after obtaining a digital twin of the quartz diffuser through modeling, the process parameter range is first obtained from the associated process group. Then, the digital twin is subjected to thermal simulation using this process parameter range to obtain simulation results. Based on the simulation results, the target process parameters are determined and sent. This process, by limiting the process parameters of the thermal process to a range within the associated process group, reduces the data used in thermal simulation to obtain the target process parameters. The application of the target process parameters determined by thermal simulation in the thermal process optimizes the heat conduction digital model of the thermal process, which can improve the quality and batch consistency of the quartz diffuser, thereby increasing the yield of the quartz diffuser.
[0057] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention.
[0058] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not describe the various possible combinations separately.
[0059] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.
[0060] Furthermore, various different implementations of the present invention can be combined arbitrarily, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed in the present invention.
Claims
1. A thermal process control system for a quartz diffuser tube, characterized in that, The thermal process control system includes a simulation unit, which is used to: perform modeling processing based on the physical structure of the quartz diffuser to obtain a digital twin characterizing the quartz diffuser; obtain associated process groups related to the thermal process, and determine the process parameter range of the thermal process based on the process parameters of the thermal process in the associated process group, wherein the associated process group is a combination of processes that jointly affect the quality of the quartz diffuser. Within the range of the process parameters, a thermal simulation of the transient temperature distribution of the digital twin is performed to obtain the simulation results; Based on the simulation results, target process parameters are determined from the range of process parameters, and the process parameters are sent to the equipment related to the thermal process so that the equipment executes the target process parameters.
2. The system according to claim 1, characterized in that, The thermal process control system includes multiple GPU engines; the process of performing transient temperature distribution thermal simulation on the digital twin within the process parameter range to obtain simulation results includes: sending a temperature iteration command to the GPU engines at time t, where each GPU engine corresponds to an iteration point, and the iteration point is a node in the digital twin whose temperature needs to be calculated; receiving the temperature of the iteration point at time t+1 sent by the GPU engines, where t and t+1 are any times when the thermal simulation is performed; displaying the temperature of the iteration point at time t+1 to obtain the simulation results; the GPU engines are used to: calculate the temperature of the iteration point at time t+1 based on the kernel function and the temperature of the kernel node surrounding the iteration point at time t, and send the temperature of the iteration point at time t+1 to the simulation unit.
3. The system according to claim 2, characterized in that, The step of calculating the temperature of the iteration point at time t+1 based on the kernel function and the temperature of the kernel node surrounding the iteration point at time t, and sending the temperature of the iteration point at time t+1 to the simulation unit, includes: reading the temperature of the iteration point and the temperature of the kernel node surrounding the iteration point at time t from the address pointed to by the first pointer; iterating the temperature of the iteration point based on the kernel function and the temperature of the kernel node surrounding the iteration point at time t to obtain the temperature of the iteration point at time t+1; obtaining the temperature of the kernel node surrounding the iteration point at time t+1, and storing the temperature of the iteration point and the temperature of the kernel node at time t+1 at the address pointed to by the second pointer; swapping the addresses pointed to by the first pointer and the second pointer, and sending the temperature corresponding to the first pointer to the simulation unit.
4. The system according to claim 2, characterized in that, The GPU engine is used to: determine the kernel nodes based on the kernel function, with the iteration point as the center, wherein the kernel nodes are distributed along the coordinate axis corresponding to the kernel function, and the kernel nodes form a square.
5. The system according to claim 4, characterized in that, If the smoothness of the isotherm corresponding to the simulation result is lower than a threshold, the simulation unit is used to: adjust the kernel function so that the distance between the kernel nodes corresponding to the adjusted kernel function is smaller than the distance between the corresponding kernel nodes before the adjustment; and send the adjusted kernel function to the GPU engine.
6. The system according to claim 1, characterized in that, The step of determining the range of process parameters for the thermal process based on the process parameters of the thermal process in the associated process group includes: when the associated process group is a process for good products, determining the range of process parameters based on the process parameters of the thermal process in the associated process group; and when the associated process group is a process for defective products, determining the range of process parameters based on the complement of the process parameters of the thermal process in the associated process group.
7. A method for thermal process control of a quartz diffuser tube, characterized in that, A simulation unit for a thermal process control system, the method comprising: modeling the physical structure of the quartz diffuser to obtain a digital twin characterizing the quartz diffuser; acquiring associated process groups related to the thermal process, and determining the process parameter range of the thermal process based on the process parameters of the thermal processes in the associated process groups, wherein the associated process groups are combinations of processes that jointly affect the quality of the quartz diffuser; performing transient temperature distribution thermal simulation on the digital twin within the process parameter range to obtain simulation results; and determining target process parameters from the process parameter range based on the simulation results, and sending the process parameters to the equipment related to the thermal process so that the equipment executes the target process parameters.
8. An electronic device, characterized in that, include: processor; A memory for storing processor-executable instructions; wherein the processor is configured to implement the method of claim 7 when executing the instructions stored in the memory.
9. A non-volatile computer-readable storage medium storing computer program instructions thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method of claim 7.
10. A computer program product comprising computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device performs the method of claim 7.