Method and system for adaptive grinding of silicon carbide semiconductor focus ring

Abstract

The application provides a silicon carbide semiconductor focusing ring adaptive grinding control method and system based on lattice vector mapping, and belongs to the technical field of semiconductor manufacturing equipment control. The application aims to solve the edge collapse and uneven surface quality problems of silicon carbide materials caused by lattice anisotropy and intermittent cutting. The method fuses visual geometric data and X-ray lattice angle data, establishes a composite coordinate system and calculates the phase deviation; based on the crystal symmetry, a full-circumferential grinding resistance model is constructed to generate a variable-speed interpolation instruction that dynamically changes with the angle; and a soft landing strategy of feed ratio rewriting and vector micro-deflection is executed for the Notch notch. The application realizes the deterministic feedforward control based on the physical mechanism, effectively eliminates the surface processing texture difference, and significantly reduces the notch edge collapse rate.

Description

Technical Field

[0001] This invention relates to the field of semiconductor manufacturing equipment and precision machining control technology, specifically to a numerical control strategy for machining hard and brittle materials, and more particularly to an adaptive grinding control method and system for silicon carbide semiconductor focusing rings based on lattice vector mapping. Background Technology

[0002] As semiconductor integrated circuit manufacturing processes advance to the nanometer node, the demand for edge rings—a key consumable material within plasma etching chambers—is increasing daily. Due to its excellent resistance to plasma erosion and high purity, silicon carbide (SiC) has gradually replaced traditional silicon or quartz as the mainstream material for edge rings. However, silicon carbide is a typical high-hardness, high-brittleness, and significantly anisotropic crystalline material, with a Mohs hardness as high as 9.2-9.5, making it extremely difficult to process.

[0003] In existing precision grinding of focusing rings, especially for irregularly shaped grinding with Notch notches (locating grooves), traditional CNC grinding machines typically use constant machining parameters (such as constant speed and constant feed rate) for full-circumference machining. Some advanced existing technologies (such as the patent with publication number CN115091287A, "A method for adjusting ultra-precision grinding parameters and a grinding system") propose a method that uses sensors to collect temperature or grinding force data during the grinding process and performs posterior analysis and parameter compensation using a BP neural network model.

[0004] However, the aforementioned existing technologies still have limitations in practical applications:

[0005] First, there is the issue of hysteresis. Feedback based on grinding force or temperature is a form of "post-hoc control," meaning that by the time the sensor detects a sudden change in force or a rise in temperature, microscopic damage or subsurface cracks have often already occurred on the workpiece surface, making it too late to adjust the parameters.

[0006] Second, the material's physical properties were ignored. Silicon carbide has a single-crystal or polycrystalline structure with significant lattice anisotropy, meaning that its material removal energy (hardness) and cleavage brittleness are completely different at different angles. Existing technologies typically treat the focusing ring as a homogeneous "isotropic" object, failing to optimize the processing path according to the lattice growth direction. This leads to surface ripples easily appearing at the "anti-crystalline direction" position and deep fractures easily occurring at the "cleavage plane" position.

[0007] Third, the machining of notch areas is high-risk. Notch areas involve intermittent cutting and drastic stress changes. Relying solely on fuzzy predictions from neural networks makes it difficult to achieve precise impact suppression at the millisecond-level entry / exit moments, resulting in a persistent bottleneck in yield at this location.

[0008] Therefore, there is an urgent need for a grinding method that can combine the microscopic lattice properties and macroscopic geometric features of materials to achieve a priori and deterministic control. Summary of the Invention

[0009] This invention provides an adaptive grinding control method and system for silicon carbide semiconductor focusing rings based on lattice vector mapping. Existing technologies mainly rely on sensor data feedback (posterior compensation) or general neural network prediction after grinding occurs, ignoring the processing resistance fluctuations caused by the inherent lattice anisotropy of silicon carbide materials. This cannot fundamentally eliminate problems such as edge chipping and uneven surface quality caused by lattice orientation changes and intermittent cutting (at the Notch).

[0010] The core technology of this invention is to construct a "physical-lattice" composite coordinate system, pre-calculate the anisotropic grinding resistance model of the entire circumference, and generate the spindle speed and feed interpolation command that dynamically change with the angle, so as to realize the deterministic adaptive machining of silicon carbide focusing ring.

[0011] In a first aspect, the present invention provides an adaptive grinding control method for silicon carbide semiconductor focusing rings, the method comprising the following steps:

[0012] Step S1: Construct a geometry-lattice composite coordinate system; acquire geometric notch position data of the silicon carbide focusing ring through a visual monitoring system and establish a physical coordinate system; acquire lattice growth principal axis direction data of the silicon carbide focusing ring through an X-ray orientation device and establish a lattice coordinate system; calculate the phase deviation angle between the geometric notch position and the lattice growth principal axis direction.

[0013] Step S2: Generate an anisotropic material removal model; based on the phase deviation angle and the lattice symmetry characteristics of silicon carbide material, construct an equivalent grinding resistance model that varies with the circumferential angle;

[0014] Step S3: Generate variable parameter interpolation instructions; based on the equivalent grinding resistance model, calculate the target grinding parameters corresponding to each angular position on the full circumferential grinding path, and generate machining code containing dynamic spindle speed and dynamic feed rate;

[0015] Step S4: Perform adaptive grinding; control the actuator of the CNC grinding machine to run the machining code, improve grinding efficiency when the grinding point is in the para-crystalline region, and reduce grinding impact when the grinding point is in the anti-crystalline or cleavage region.

[0016] Furthermore, in step S2, the equivalent grinding resistance model R θ The calculation formula is as follows:

[0017]

[0018] Where θ is the current circular rotation angle. Remove resistance from the reference material. Where n is the anisotropy coefficient of the material and n is the lattice symmetry coefficient. This is the phase deviation angle;

[0019] Accordingly, in step S3, the dynamic feed rate and the equivalent grinding resistance model R θ There is a negative correlation.

[0020] Furthermore, in step S3, the generation of variable parameter interpolation instructions for the geometrically notched region of the focusing ring also includes a "virtual soft landing" strategy:

[0021] Define the preset angle range on both sides of the physical edge of the geometric gap as a high-risk zone;

[0022] In the generated machining code, when the grinding path enters the high-risk zone, the feed rate multiplier is forcibly rewritten to 30% to 50% of the preset standard speed;

[0023] Simultaneously, a C-axis micro-deflection command is generated to control the force direction vector at the grinding contact point to always deflect towards the solid side of the focusing ring, so as to form a compressive stress cutting state.

[0024] Furthermore, the specific process of obtaining the lattice growth principal axis direction data in step S1 is as follows:

[0025] The C-axis turntable is controlled to drive the focusing ring to rotate, and the edge of the focusing ring is diffracted and scanned using an X-ray orientation device.

[0026] Record the C-axis angular position when the X-ray diffraction intensity reaches its peak.

[0027] This angular position is determined as the normal vector direction of the principal cleavage plane of the crystal lattice, and serves as the zero-point reference of the crystal coordinate system.

[0028] Furthermore, the method does not rely on real-time force or temperature feedback sensors during the grinding process for parameter correction; the machining code is calculated and generated once before grinding begins based on the phase deviation angle.

[0029] In a second aspect, the present invention provides an adaptive grinding control device for silicon carbide semiconductor focusing rings based on lattice vector mapping, comprising:

[0030] The multi-source data acquisition module is equipped with a visual monitoring interface and an X-ray orientation interface, which are used to acquire the geometric contour data and internal lattice angle data of the focusing ring, respectively.

[0031] The vector mapping calculation module is used to receive geometric contour data and lattice angle data, calculate the phase deviation angle between the geometric notch and the lattice principal axis, and construct a full-circumference grinding resistance distribution model based on the characteristics of silicon carbide crystal.

[0032] The interpolation control module is used to decompose the standard circular motion trajectory into variable speed motion commands that vary with angle, based on the grinding resistance distribution model.

[0033] The drive module is used to connect and drive the spindle motor and feed axis motor of the grinding machine to execute speed change commands.

[0034] Furthermore, the mechanical body that executes the control of the drive module includes:

[0035] The dual-spindle assembly includes a horizontal spindle for grinding the outer diameter and a vertical spindle for grinding the end face and notch.

[0036] The C-axis direct-drive rotary table is used to support the focusing ring for precise indexing rotation.

[0037] The interpolation control module is configured to coordinate the feed of the dual spindle assembly and the rotation speed of the C-axis direct drive rotary table based on the phase deviation angle.

[0038] Furthermore, the interpolation control module has a pre-set notch protection logic unit; the notch protection logic unit is configured to: when it is determined that the current machining position is within a preset distance of the geometric notch edge, automatically trigger the feed rate limit function and set the spindle load threshold; once the load exceeds the threshold, a slight retraction is triggered.

[0039] Furthermore, it also includes a materials and processes database;

[0040] The database stores the anisotropy coefficient λ and the baseline removal resistance K for different types of silicon carbide materials. base The vector mapping calculation module retrieves the corresponding coefficients from the database to build the model based on the workpiece material type input by the user.

[0041] Thirdly, the present invention provides a readable storage medium storing a computer program, the computer program including program code for controlling a process to execute the process, the process including the above-described adaptive grinding control method for silicon carbide semiconductor focusing rings based on lattice vector mapping.

[0042] The main contributions and innovations of this invention are as follows:

[0043] 1. Significantly improved surface integrity consistency: By establishing an anisotropic velocity control model, this invention can adjust grinding parameters in real time according to the "hardness" direction of the lattice (acceleration in the para-crystalline direction and deceleration in the anti-crystalline direction), effectively offsetting the cutting force fluctuations caused by material anisotropy, so that the surface roughness (Ra) of the entire circumference of the focusing ring can be stably controlled below 0.2μm, eliminating local processing texture differences.

[0044] 2. Significantly reduce Notch chipping rate: For the most vulnerable Notch area, this invention does not rely on hysteretic sensor feedback, but executes a "virtual soft landing" strategy (forced rewriting of feed rate and micro-deflection of vector) based on precise position calculation. This eliminates the rigid impact during cutting in / out from a physical principle, which can significantly reduce the edge chipping rate.

[0045] 3. High computational efficiency and strong real-time performance: Unlike the BP neural network in the existing technology that relies on a large number of samples for training and has complex calculations, the control algorithm of this invention is based on a deterministic trigonometric function mapping model, which consumes very few computational resources and can be directly embedded into the CNC underlying controller to achieve microsecond-level response, making it more suitable for mass production in industrial settings.

[0046] 4. Achieving a leap from "blind cutting" to "seeing through": The introduction of X-ray orientation technology enables the control system to no longer "blindly" cut the workpiece, but to "see through" the crystal lattice texture inside the material, thereby selecting the optimal machining posture, extending the service life of the grinding wheel tool and reducing the dressing frequency.

[0047] Details of one or more embodiments of the present invention are set forth in the following drawings and description, so that other features, objects and advantages of the invention will be more readily understood. Attached Figure Description

[0048] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0049] Figure 1 This is a block diagram of the principle of the adaptive grinding control system for silicon carbide semiconductor focusing ring based on lattice vector mapping according to an embodiment of the present invention;

[0050] Figure 2 This is a flowchart of an adaptive grinding control method for silicon carbide semiconductor focusing rings based on lattice vector mapping according to an embodiment of the present invention;

[0051] Figure 3 This is a flowchart illustrating the mapping between the geometric coordinate system and the lattice coordinate system according to an embodiment of the present invention;

[0052] Figure 4 This is a schematic diagram of the mapping between the geometric coordinate system and the lattice coordinate system according to an embodiment of the present invention;

[0053] Figure 5 This is an anisotropic velocity control curve diagram according to an embodiment of the present invention;

[0054] Figure 6 This is a control logic diagram for "soft landing" at the Notch gap according to an embodiment of the present invention. Detailed Implementation

[0055] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with one or more embodiments of this specification. Rather, they are merely examples of apparatuses and methods consistent with some aspects of one or more embodiments of this specification as detailed in the appended claims.

[0056] It should be noted that the steps of the corresponding methods are not necessarily performed in the order shown and described in this specification in other embodiments. In some other embodiments, the methods may include more or fewer steps than described in this specification. Furthermore, a single step described in this specification may be broken down into multiple steps in other embodiments; and multiple steps described in this specification may be combined into a single step in other embodiments.

[0057] Example 1: Silicon Carbide Grinding Control System Based on Lattice Vector Mapping

[0058] like Figure 1 As shown, this embodiment provides an adaptive grinding control system for silicon carbide semiconductor focusing rings based on lattice vector mapping. The system mainly consists of three parts: a mechanical execution subsystem, a sensing and detection subsystem, and a central control subsystem. Details are as follows:

[0059] 1. Mechanical Actuation Subsystem: Includes a dual-column gantry machine tool body. A dual-spindle assembly is mounted on the gantry, specifically comprising a horizontal spindle for grinding the outer cylindrical contour of the focusing ring and a vertical spindle for grinding the end face and Notch notch. The worktable is a high-precision C-axis direct-drive rotary table used to support the silicon carbide focusing ring workpiece and capable of precise indexing rotation with extremely high resolution (0.001°). Since this is a prior art machine tool, no accompanying drawings are shown; the improvement of this invention lies in the method.

[0060] 2. Sensing and Detection Subsystem (Multi-Source Data Acquisition Module):

[0061] Visual monitoring unit: It adopts a high-resolution CCD camera and telecentric lens, which is installed above the grinding station to acquire geometric contour images of the focusing ring workpiece in real time and identify the physical location of the Notch notch.

[0062] X-ray orientation unit: This unit integrates a miniature X-ray diffractometer, configured at a pre-alignment station or integrated inside the machine tool. It is used to perform rapid diffraction scanning on the edges of a workpiece, determining the lattice growth principal axis direction (i.e., the cleavage plane normal of the crystal) of single-crystal or polycrystalline silicon carbide by detecting the diffraction intensity peaks of specific crystal planes.

[0063] 3. Central Control Subsystem (Controller): This controller is the core of this invention and is typically composed of an industrial PC or a high-performance CNC controller, integrating a processor and memory. The memory stores a computer program, and when the processor executes this program, it implements the following functional modules:

[0064] Vector mapping calculation module: used to fuse visual data input D geo and X-ray data D cry A geometry-lattice composite coordinate system was constructed, and the phase deviation angle was calculated. .

[0065] Materials and Processes Database: Pre-stores silicon carbide material parameters for different brands and sintering processes (such as reaction sintering RB-SiC or chemical vapor deposition CVD-SiC). Core parameters include anisotropy coefficients (typically ranging from 0.1 to 0.3) and baseline removal resistance. .

[0066] Interpolation control module: Used to generate G-code instructions with variable parameters based on the grinding resistance model.

[0067] Execution drive module: Used to send position, speed and torque commands to the servo driver.

[0068] Example 2: Specific calculation process and logic implementation of the adaptive grinding control method

[0069] like Figure 2 As shown, this embodiment focuses on describing the internal processing of the core algorithm in the control system, including the calculation details of coordinate system mapping, the algorithm for generating velocity curves, and the logic code implementation for Notch gap protection:

[0070] Step S1: Construct a geometry-lattice composite coordinate system

[0071] like Figure 3 As shown, the system first performs an initialization scan before processing begins.

[0072] 1. Physical Positioning: The C-axis direct-drive rotary table rotates at low speed, and the vision monitoring unit captures images of the focusing ring edge. The image processing algorithm extracts the geometric center line of the Notch notch and records its angle in the machine coordinate system as a geometric angle. (For example, a Notch notch is detected at 0° on the mechanical coordinate).

[0073] For example, the physical notch angle measured by a visual sensor: (Based on the zero point of the machine tool's C-axis).

[0074] 2. Lattice Orientation: The X-ray orientation unit performs a fan-shaped scan of the edge of the focusing ring (e.g., the scan range covers ±30° around the Notch notch or a full circumference coarse scan).

[0075] When the X-ray incident angle satisfies the Bragg diffraction condition with a specific crystal plane of SiC (such as the (11-20) plane), the signal intensity received by the detector reaches its peak. The system records the C-axis angle corresponding to this peak value and determines it as the direction of the lattice growth principal axis. (For example, the principal axis of the crystal lattice is detected to be located at 15° in mechanical coordinates, which is the angle of the principal peak of the crystal lattice as measured by an X-ray diffractometer:) ).

[0076] 3. Phase Deviation Calculation: The vector mapping calculation module calculates the phase deviation angle between the two. (That is, the principal axis angle of the lattice minus the geometric angle), the coordinate mapping relationship between the geometry and the lattice is as follows: Figure 4 As shown. In this example, assume This means that the axis of the hardest or most brittle part of the material is offset by 15 degrees relative to the physical notch.

[0077] That is, if visual detection detects the Notch notch in X-rays detected the most brittle cleavage surfaces at... ,but = .

[0078] Step S2: Generate anisotropic material removal model

[0079] Based on the hexagonal structure of silicon carbide (6H-SiC or 4H-SiC) crystals, its hardness distribution exhibits a six-fold symmetry (n=6). The vector mapping calculation module calls parameters from the database (assuming anisotropy coefficients). (Dimensionless, typical value 0.15~0.25), construct an equivalent grinding resistance model for the entire circumference (0-360°). :

[0080]

[0081] Substituting the parameters, we get:

[0082]

[0083] The model shows that, with angle The grinding resistance fluctuates in a cosine wave pattern due to the changes in the grinding resistance.

[0084] when Time (i.e.) ), Reaching the maximum value , representing the reverse crystal orientation / hard axis (most difficult to grind, easily chipped).

[0085] when Time (i.e.) ), Reaching the minimum value , representing the para-crystalline direction / soft axis (easily removed).

[0086] Step S3: Generate variable parameter interpolation instructions (pre-calculation)

[0087] The interpolation control module does not use traditional constant feed logic, but instead follows the model described above. The optimal machining parameters are derived in reverse to generate machining code.

[0088] 1. Full-circular speed change strategy:

[0089] like Figure 5 The anisotropic speed control curve shown indicates that in the "low resistance zone" (parallel direction) calculated by the model, the system automatically sets a higher table speed (e.g., 30 rpm) and standard feed depth to improve efficiency.

[0090] In the "high resistance zone" (inverse crystal direction or direction perpendicular to cleavage plane) calculated by the model, the system automatically sets a lower table speed (e.g., 15 rpm) to reduce the cutting thickness of a single abrasive grain and prevent the propagation of microcracks due to material brittleness.

[0091] In the final generated command, the C-axis rotational speed is an analog curve that changes continuously with the angle.

[0092] 2. The "virtual soft landing" strategy at the Notch gap:

[0093] like Figure 6 As shown, for Notch notches (physical discontinuous cutting points), the system superimposes special logic into the interpolation algorithm:

[0094] High-risk zone definition: based on geometric gaps Define with angle as the center. The area is a high-risk zone.

[0095] Feed rate rewrite: Insert a command in the G-code to forcibly reduce the feed rate from 100% to 30% a certain distance (e.g., 2mm) before the grinding wheel contact point enters the area. This causes the grinding wheel to "soft-land" into the notch edge at an extremely slow speed and exit at the same slow speed, avoiding edge chipping.

[0096] Vector micro-deflection: When machining the sidewall of the notch, the control system fine-tunes the synthesized motion vector through the linkage of the C-axis and the X / Y-axis, so that the component of the grinding force always points to the solid side of the focusing ring (i.e., generating compressive stress), rather than to the free end (i.e., generating tensile stress), because SiC material is resistant to compression but not to tension.

[0097] For example, to ensure a constant material removal rate (MRR) and suppress damage, the control system generates the target stage speed based on an inverse proportional strategy of "the greater the resistance, the lower the speed". :

[0098]

[0099] in, The reference speed set for the process (e.g., 20 rpm). Below is an example of the core logic code for the interpolation control module to generate G-code:

[0100] / / --- Algorithm Section: Adaptive Velocity Curve Generation ---

[0101] Input: Notch_Angle (0°), Crystal_Angle (15°), Base_Speed ​​(20 rpm), Lambda (0.2)

[0102] Output: Array Speed_Profile

[3600] / / 0.1 degree resolution

[0103] Function Generate_Profile():

[0104] Phase_Shift = Crystal_Angle - Notch_Angle / / Calculate the phase difference of 15°

[0105] For theta = 0 to 360 step 0.1:

[0106] / / 1. Calculate the lattice hardness factor (-1 to 1) for the current angle.

[0107] Hardness_Factor = cos(6 × (theta - Phase_Shift) × PI / 180)

[0108] / / 2. Calculate the target rotational speed according to the formula

[0109] Target_RPM = 20 / (1 + 0.2 × Hardness_Factor)

[0110] / / 3. Notch gap special protection logic (virtual soft landing)

[0111] If abs(theta - Notch_Angle)<5.0 Then

[0112] / / Entering the gap within ±5 degrees, forced coverage is set to ultra-low speed.

[0113] Target_RPM = MIN(Target_RPM, 5.0)

[0114] Set_Feed_Override(30%) / / Reduces the feed rate to 30%

[0115] Else

[0116] Set_Feed_Override(100%)

[0117] End If

[0118] Speed_Profile[theta] = Target_RPM

[0119] End For

[0120] Return Speed_Profile

[0121] Step S4: Perform adaptive grinding

[0122] The execution drive module reads the generated variable parameter machining code and drives the dual-spindle assembly and C-axis direct-drive rotary table to operate in tandem. Since all the speed and parameter changes are calculated before machining, the system does not need to wait for feedback signals from force or temperature sensors during actual grinding; it operates directly according to the predetermined curve. This "prior control" eliminates the lag in sensor feedback found in existing technologies, resulting in a consistent Ra surface roughness better than 0.2 μm across the entire circumference of the machined focusing ring, and a significantly reduced chipping rate at the Notch notch.

[0123] Example 3: Further Explanation of Gap Protection Logic

[0124] As a safety redundancy for the system, the interpolation control module also includes pre-set real-time protection logic. Although this invention primarily relies on a priori models, the system monitors the spindle current load in real time during the actual machining of notch notches. If the spindle load is detected to momentarily exceed a preset threshold at the notch (indicating a possible hard point or wheel passivation), the system immediately triggers a "micro-retraction" action, controlling the feed axis to retract a small distance (e.g., 0.5μm-1μm) while simultaneously issuing an alarm. This dual protection further ensures the safety of high-value SiC workpieces.

[0125] For example, to more clearly illustrate the effects of the present invention, the following provides a comparison of calculations of actual processing parameters:

[0126] set up: .

[0127] 1. At the angle Location (reverse crystal orientation / hardest point):

[0128] Resistance factor .

[0129] System command speed .

[0130] Effect: The rotation speed is automatically reduced, the depth of cut of a single abrasive grain is reduced, and cracking is avoided.

[0131] 2. At the angle Location (paracrystalline / softest point):

[0132] Resistance factor .

[0133] System command speed .

[0134] Effect: The rotation speed automatically increases, and the processing efficiency is improved by taking advantage of the easy-to-remove properties of the material.

[0135] 3. At the angle Location (center of the Notch gap):

[0136] Although that place The calculated rotational speed should be 19 rpm.

[0137] However, due to the triggering of the Notch protection logic ( The system forcibly clamps the speed at 5.0 rpm and sets the feed rate to 30%.

[0138] Effect: Achieve a "soft landing" and completely eliminate the impact of the gap.

[0139] The continuous speed change command generated through the above calculation process (such as...) Figure 5(As shown in the waveform), the control system can precisely direct the machine tool to be in the optimal cutting state every millisecond, thereby realizing the "adaptive grinding" described in the claims.

[0140] Other implementation methods

[0141] Those skilled in the art will understand that although this embodiment uses a silicon carbide (SiC) focused ring as an example, the method of the present invention is also applicable to the processing of rings made of other hard and brittle materials with lattice anisotropy, such as sapphire and GaN nitride. Furthermore, the lattice symmetry coefficient n in step S2 can be adjusted according to the crystal structure of the specific material (for example, for cubic materials, n can be 4).

[0142] Example 4

[0143] This embodiment also provides a readable storage medium storing a computer program, the computer program including program code for controlling a process to execute the process, the process including the silicon carbide semiconductor focusing ring adaptive grinding control method based on lattice vector mapping according to Embodiment 1.

[0144] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0145] Generally, various embodiments can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. Some aspects of the invention can be implemented in hardware, while others can be implemented by firmware or software executed by a controller, microprocessor, or other computing device, but the invention is not limited thereto. Although various aspects of the invention may be shown and described as block diagrams, flowcharts, or using some other graphical representation, it should be understood that, by way of non-limiting example, these blocks, apparatuses, systems, techniques, or methods described herein can be implemented in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0146] Embodiments of the present invention can be implemented by computer software, which may be executable by a data processor of a mobile device, such as a processor entity, or by hardware, or by a combination of software and hardware. Computer software or programs (also referred to as program products) including software routines, applets, and / or macros can be stored in any device-readable data storage medium, and they include program instructions for performing specific tasks. The computer program product may include one or more computer-executable components configured to perform the embodiments when the program is run. The one or more computer-executable components may be at least one piece of software code or a portion thereof. Additionally, it should be noted in this respect that, as Figure 2Any box in the logical flow can represent a program step, or interconnected logic circuits, boxes and functions, or a combination of program steps and logic circuits, boxes and functions. Software can be stored on physical media such as memory chips or blocks of storage implemented within a processor, magnetic media such as hard disks or floppy disks, and optical media such as DVDs and their data variants, CDs, etc. The physical medium is a non-transient medium.

[0147] Those skilled in the art should understand that 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 have been described. 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.

[0148] The above embodiments are merely illustrative of several implementations of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the appended claims.

Claims

1. An adaptive grinding control method for silicon carbide semiconductor focusing rings, characterized in that, Includes the following steps: Step S1: Construct a geometry-lattice composite coordinate system; Geometric notch position data of the silicon carbide focusing ring is acquired through a visual monitoring system to establish a physical coordinate system; lattice growth principal axis direction data of the silicon carbide focusing ring is acquired through an X-ray orientation device to establish a lattice coordinate system; the phase deviation angle between the geometric notch position and the lattice growth principal axis direction is calculated. Step S2: Generate an anisotropic material removal model; based on the phase deviation angle and the lattice symmetry characteristics of silicon carbide material, construct an equivalent grinding resistance model that varies with the circumferential angle; the equivalent grinding resistance model The calculation formula is as follows: Where θ is the current circular rotation angle. Remove resistance from the reference material. Where n is the anisotropy coefficient of the material and n is the lattice symmetry coefficient. The phase deviation angle; Step S3: Generate variable parameter interpolation instructions; based on the equivalent grinding resistance model, calculate the target grinding parameters corresponding to each angular position on the full circumferential grinding path, and generate machining code containing dynamic spindle speed and dynamic feed rate; The dynamic feed rate and the equivalent grinding resistance model There is a negative correlation; Step S4: Perform adaptive grinding; control the actuator of the CNC grinding machine to run the machining code, improve grinding efficiency when the grinding point is in the para-crystalline region, and reduce grinding impact when the grinding point is in the anti-crystalline or cleavage region.

2. The adaptive grinding control method for silicon carbide semiconductor focusing rings as described in claim 1, characterized in that, In step S3, for the geometric gap region of the focusing ring, the generation of variable parameter interpolation instructions also includes a "virtual soft landing" strategy: The preset angle range on both sides of the physical edge of the geometric notch is defined as a high-risk zone; In the generated machining code, when the grinding trajectory enters the high-risk zone, the feed rate multiplier is forcibly rewritten to 30% to 50% of the preset standard speed; Simultaneously, a C-axis micro-deflection command is generated to control the force direction vector at the grinding contact point to always deflect towards the solid side of the focusing ring, so as to form a compressive stress cutting state.

3. The adaptive grinding control method for silicon carbide semiconductor focusing rings as described in claim 1, characterized in that, The specific process for obtaining the principal axis direction data of lattice growth in step S1 is as follows: The C-axis turntable is controlled to drive the focusing ring to rotate, and the edge of the focusing ring is diffracted and scanned using an X-ray orientation device. Record the C-axis angular position when the X-ray diffraction intensity reaches its peak. The angular position is determined as the normal vector direction of the principal cleavage plane of the crystal lattice, and serves as the zero-point reference of the crystal coordinate system.

4. The adaptive grinding control method for silicon carbide semiconductor focusing rings as described in claim 3, characterized in that, The method does not rely on real-time force or temperature feedback sensors during the grinding process for parameter correction. The machining code is calculated and generated once based on the phase deviation angle before grinding begins.

5. A system for performing the adaptive grinding control method for silicon carbide semiconductor focusing rings according to claim 1, characterized in that, include: The multi-source data acquisition module is equipped with a visual monitoring interface and an X-ray orientation interface, which are used to acquire the geometric contour data and internal lattice angle data of the focusing ring, respectively. The vector mapping calculation module is used to receive the geometric contour data and lattice angle data, calculate the phase deviation angle between the geometric notch and the lattice principal axis, and construct a full-circumference grinding resistance distribution model based on the characteristics of silicon carbide crystal. The interpolation control module is used to decompose the standard circular motion trajectory into variable speed motion commands that vary with angle, based on the grinding resistance distribution model. The drive module is used to connect to and drive the spindle motor and feed axis motor of the grinding machine to execute the speed change motion command.

6. The system as described in claim 5, characterized in that, The mechanical body controlled by the execution drive module includes: The dual-spindle assembly includes a horizontal spindle for grinding the outer diameter and a vertical spindle for grinding the end face and notch. The C-axis direct-drive rotary table is used to support the focusing ring for precise indexing rotation. The interpolation control module is configured to coordinate the feed of the dual-spindle assembly and the rotation speed of the C-axis direct-drive rotary table based on the phase deviation angle.

7. The system as described in claim 5, characterized in that, The interpolation control module has a pre-set notch protection logic unit. The notch protection logic unit is configured to automatically trigger the feed rate limiting function when it is determined that the current machining position is within a preset distance of the edge of the geometric notch, and set the spindle load threshold. Once the load exceeds the threshold, a slight retraction is triggered.

8. The system as described in claim 5, characterized in that, It also includes a materials and processes database; The database stores the anisotropy coefficient λ and the benchmark removal resistance K for different types of silicon carbide materials. base ; The vector mapping calculation module retrieves the corresponding coefficients from the database to construct the model based on the workpiece material type input by the user.

9. A readable storage medium, characterized in that, The readable storage medium stores a computer program, the computer program including program code for controlling a process to execute the process, the process including the adaptive grinding control method for silicon carbide semiconductor focusing rings according to any one of claims 1 to 4.

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