Wafer conveying mechanical arm shell machining method

Abstract

The invention relates to the technical field of industrial robots, in particular to a wafer conveying mechanical arm shell machining method which comprises the following steps that firstly, gradient heat treatment is conducted on an aluminum alloy casting, and the gradient heat treatment comprises three stages of treatment including heat preservation at 200 DEG C + / -10 DEG C for 2 h, heat preservation at 430 DEG C + / -5 DEG C for 1 h and liquid nitrogen subzero treatment for 30 min; secondly, orthogonal vibration aging treatment is carried out in a multi-frequency resonance stress relief device, the main vibration frequency ranges from 80 Hz to 120 Hz, and the acceleration ranges from 0.5 g to 1.2 g; thirdly, multi-process combined machining is carried out in a five-axis linkage machining center, the rotating speed of a main shaft is larger than or equal to 25000rpm, and an HSK-E50 cutter handle system is arranged; through thermal-mechanical-electric multi-field cooperative control, dynamic feedback optimization and precise detection technologies, the problems of stress deformation, surface integrity control and dimensional stability in high-precision shell machining are solved, and the strict requirements of a robot manipulator for light weight, high rigidity and long service life are met.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial robots, and in particular to a method for processing a wafer transfer robot arm shell. Background Art

[0002] In the field of industrial robots, the processing quality of the manipulator housing directly affects the equipment's motion accuracy, dynamic response characteristics, and service life. Traditional housing manufacturing technology generally faces three major technical bottlenecks: strength-toughness imbalance caused by grain coarsening during heat treatment of aluminum alloy materials; dimensional aging deformation caused by residual stress during multi-axis machining; and microcrack accumulation failure caused by tool-workpiece interaction during complex surface machining. Existing technical solutions have the following limitations: Heat treatment process: Conventional isothermal annealing or single-stage quenching processes cannot achieve the synergistic effect of grain boundary strengthening and dislocation control, resulting in a material hardness dispersion of ±20HV. Cryogenic treatment generally uses -80℃ liquid nitrogen immersion, which lacks a pressure control mechanism and has insufficient phase transformation strengthening efficiency. Stress relief technology: Mechanical vibration aging mostly uses single-frequency unidirectional excitation, and the harmonic response monitoring accuracy is ≤5Hz. It cannot effectively excite the high-order modes of high-rigidity shells, and the residual stress relief rate is only 60% to 70%; Precision machining: Traditional HSK toolholder systems experience radial runout >5μm at 25,000rpm. Roughing / finishing tool change strategies rely on empirical formulas, and cutting force fluctuations cause surface waviness. Trochoidal milling path planning lacks material removal rate feedback, and sudden changes in curvature lead to tool chatter with a probability >12%. Surface treatment technology: Conventional plasma cleaning uses constant power treatment, and the surface oxygen content fluctuates by ±3at%. The contact angle hysteresis caused by carbon contamination affects the bonding strength of subsequent coatings. Dimensional compensation system: Traditional PID control is not coupled with the multi-physical fields of the machining process, the compensation hysteresis period is greater than 60s, the thermal deformation compensation accuracy is less than 0.01mm, and the machining qualification rate of thin-walled structures is especially less than 85%. Summary of the Invention

[0003] To this end, the present invention provides a method for processing a wafer transfer robot arm housing to solve the above-mentioned problems.

[0004] The present invention provides the following technical solution: a method for processing a wafer transfer robot arm housing, comprising the following steps: Step 1: Perform gradient heat treatment on the aluminum alloy casting, including three-stage treatment: holding at 200°C ± 10°C for 2 hours, holding at 430°C ± 5°C for 1 hour, and cryogenic treatment with liquid nitrogen for 30 minutes; Step 2: Perform orthogonal vibration aging treatment in a multi-frequency resonance stress relief device, with a main vibration frequency of 80-120 Hz and an acceleration of 0.5-1.2 g; Step 3: Perform multi-process composite machining on a five-axis machining center with a spindle speed of ≥25,000 rpm and equipped with an HSK-E50 toolholder system; Step 4: Use argon-oxygen mixed plasma to clean the surface, with a gas volume ratio of 4:1 and a radio frequency power of 250-350W; Step 5: Implement online dimension compensation through a laser tracker. The compensation algorithm includes a PID control model, where the proportional coefficient Kp = 0.7-0.9 and the integral coefficient Ki = 0.04-0.06.

[0005] As a preferred solution of the present invention, in step 1, liquid nitrogen cryogenic treatment is carried out in a sealed pressure vessel, the cooling rate is controlled at 8-10 ° C / min, and the temperature is returned to room temperature at a rate of ≤ 5 ° C / min after the treatment. After the gradient heat treatment, the material grain size is ensured to be ≤ 30 μm and the dislocation density is ≤ 1.5×10 14 / m 2 , microhardness ≥160HV.

[0006] As a preferred solution of the present invention, in step 2, the multi-frequency resonance stress relief device is equipped with a dual vibration table, the X / Y axial vibration phase difference is 90°±5°, the vibration duration is 45-60 minutes, and the three frequency bands of 80Hz, 100Hz and 120Hz are switched alternately at intervals of 5 minutes during the period. The harmonic response of the workpiece is monitored in real time during the vibration aging process. When the resonance peak shift is detected to be greater than 5%, the vibration frequency is automatically adjusted to the frequency corresponding to the resonance peak after the shift.

[0007] As a preferred solution of the present invention, in step 3, the five-axis linkage machining center is equipped with an HSK-E50 spindle interface, and the tool system includes: a φ20mm ceramic-coated milling cutter for rough machining, with a rake angle of 12°±1° and a clearance angle of 8°±0.5°; φ10mm diamond-coated milling cutter for finishing, with a rake angle of 8°±0.5° and a clearance angle of 6°±0.3°; The tool changing strategy is automatically adjusted based on cutting force feedback. Tool change is triggered when the cutting force fluctuation is greater than 15%. A trochoidal milling path is used in the finishing stage, with a single tooth feed rate of 0.02-0.05mm / z, an axial cutting depth of 0.1-0.3mm, and a radial cutting depth of 0.8-1.2mm.

[0008] As a preferred solution of the present invention, in step 4, after plasma cleaning, the surface oxygen content is ≤6at%, the carbon content is ≤4at%, the surface contact angle is ≤20°, and the surface roughness Ra is ≤0.15μm.

[0009] As a preferred solution of the present invention, in step five, the differential coefficient Kd of the PID control model is 0.2-0.4, the compensation period is ≤30s, the compensation accuracy is ≤0.003mm, and the PID control model establishes a processing quality prediction model containing 32 process parameters. When the deviation between the real-time collected parameters and the model prediction value is greater than 5%, the process parameter optimization module is automatically triggered to adjust the cutting parameters.

[0010] As a preferred solution of the present invention, three-level pressure control is adopted in the liquid nitrogen cryogenic treatment stage: In the initial stage, the pressure is maintained at 0.8-1.2 MPa for 30 seconds to achieve rapid heat exchange; In the middle stage, the pressure is reduced to 0.3-0.5 MPa for 25 minutes to ensure uniform cooling; In the final stage, normal pressure is restored to complete the phase transformation strengthening; The inner wall of the sealed pressure vessel is provided with a nano-ceramic insulation layer with a thickness of 150-200 μm and a thermal conductivity of ≤0.5 W / (m·K). 18 sets of distributed thermocouples are configured inside the vessel to monitor the temperature gradient of ≤3°C / cm.

[0011] As a preferred solution of the present invention, the dual vibration table adopts an electromagnetic-hydraulic composite drive system, the vibration acceleration accuracy is controlled at ±0.05g, the phase difference closed-loop control response time is ≤50ms, and an axial preload of 5-8kN is applied synchronously during the vibration aging process. The workpiece is clamped using a three-point hydraulic support structure, and the support point pressure deviation is ≤5%. The harmonic response is monitored using a laser Doppler vibrometer with a sampling frequency of 10kHz, and a vibration modal cloud map of the 0.1-200Hz frequency band is generated in real time.

[0012] As a preferred solution of the present invention, the AlTiN coating thickness of the ceramic-coated milling cutter is 3.5-4.2 μm, the grain size of the diamond-coated milling cutter is ≤500 nm, the cutting force feedback system integrates a piezoelectric three-axis force sensor with a measurement range of 0-5000 N, a resolution of 0.1 N, and a data acquisition interval of ≤0.5 ms. The cycloidal milling path adopts an adaptive step size algorithm to dynamically adjust the curvature radius according to the material removal rate, and the curvature change rate is ≤0.2 mm. -1 .

[0013] As a preferred solution of the present invention, the processing quality prediction model includes a temperature field-stress field coupling analysis module, and uses the finite element method to divide 0.5mm 3 The hexahedral grid is constructed, and the process parameter optimization module integrates a genetic algorithm. The population size is set to 50 generations, the crossover probability is 0.7, and the mutation probability is 0.01. The real-time data acquisition system includes a 16-channel synchronous acquisition card with a sampling rate of 1MHz and a signal transmission delay of ≤2μs. The wavelet noise reduction algorithm is used for data preprocessing.

[0014] Compared with the prior art, the present invention has the following beneficial effects: In this invention, three-stage temperature control is adopted, combined with three-level pressure regulation, through the nano-ceramic insulation layer (thermal conductivity ≤ 0.5W / m·K) in the sealed pressure vessel and 18 sets of thermocouple monitoring, to achieve grain refinement, dislocation density control and hardness improvement, and the cooling / reheating rates are limited to 8-10℃ / min and ≤5℃ / min respectively; Based on an electromagnetic-hydraulic composite drive dual vibration table (acceleration accuracy ±0.05g), an axial preload of 5-8kN is applied. Through X / Y axis orthogonal vibration (phase difference 90°±5°) and three-band switching (80 / 100 / 120Hz), combined with a laser Doppler vibrometer (10kHz sampling), real-time monitoring of the harmonic response is achieved. When the resonance peak shift is greater than 5%, frequency adaptive adjustment is achieved to effectively eliminate residual stress. Equipped with HSK-E50 toolholder system, used in stages: rough machining: φ20mm ceramic coated milling cutter (AlTiN coating 3.5-4.2μm, rake angle 12°±1°), fine machining: φ10mm diamond coated milling cutter (grain ≤500nm, rake angle 8°±0.5°), piezoelectric three-axis force sensor (0.5ms acquisition) monitors cutting force fluctuations >15% to trigger tool change, and uses adaptive trochoid milling (curvature change rate ≤0.2mm -1 , single tooth feed 0.02-0.05mm / z); Argon-oxygen mixture (4:1) plasma cleaning was performed in two stages (300W to 250W). The surface oxygen / carbon contents were ≤6at% and 4at%, respectively, by rotating the stage (5-15rpm, 0-30° tilt angle). The surface roughness Ra was ≤0.15μm, and the contact angle was ≤20°. The surface composition was monitored online every 120 seconds by an X-ray spectrometer. The integrated PID control (Kp = 0.7-0.9 / Ki = 0.04-0.06 / Kd = 0.2-0.4) and genetic algorithm optimization module are used to synchronize the temperature and stress field through a 16-channel synchronous acquisition system (1MHz sampling, ≤2μs delay) and a temperature-stress field coupled finite element model (0.5mm 3 Grid) to achieve ≤0.003mm compensation accuracy, when the real-time data and the prediction model deviation> 5%, automatically optimize the cutting parameters (50 generations of population size, crossover probability 0.7); The present invention solves the problems of stress deformation, surface integrity control and dimensional stability in high-precision shell processing through thermal-mechanical-electrical multi-field coordinated control, dynamic feedback optimization and precision detection technology, and meets the stringent requirements of robot manipulators for lightweight, high rigidity and long life. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a flow chart of the method for processing the housing of the manipulator of the handling robot of the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0017] See also Figure 1 The technical solution provided by the present invention specifically includes the following embodiments: Embodiment: A method for processing a wafer transfer robot housing includes the following steps: Step 1: Perform gradient heat treatment on the aluminum alloy casting, including three-stage treatment: holding at 200°C ± 10°C for 2 hours, holding at 430°C ± 5°C for 1 hour, and cryogenic treatment with liquid nitrogen for 30 minutes; Step 2: Perform orthogonal vibration aging treatment in a multi-frequency resonance stress relief device, with a main vibration frequency of 80-120 Hz and an acceleration of 0.5-1.2 g; Step 3: Perform multi-process composite machining on a five-axis machining center with a spindle speed of ≥25,000 rpm and equipped with an HSK-E50 toolholder system; Step 4: Use argon-oxygen mixed plasma to clean the surface, with a gas volume ratio of 4:1 and a radio frequency power of 250-350W; Step 5: Implement online dimension compensation through a laser tracker. The compensation algorithm includes a PID control model, where the proportional coefficient Kp = 0.7-0.9 and the integral coefficient Ki = 0.04-0.06.

[0018] In step 1, liquid nitrogen cryogenic treatment is carried out in a sealed pressure vessel, and the cooling rate is controlled at 8-10℃ / min. After the treatment, the temperature is returned to room temperature at a rate of ≤5℃ / min. After the gradient heat treatment, the material grain size is guaranteed to be ≤30μm and the dislocation density is ≤1.5×10 14 / m 2 , microhardness ≥160HV; The liquid nitrogen cryogenic treatment stage adopts three-level pressure control: In the initial stage, the pressure is maintained at 0.8-1.2 MPa for 30 seconds to achieve rapid heat exchange; In the middle stage, the pressure is reduced to 0.3-0.5 MPa for 25 minutes to ensure uniform cooling; In the final stage, normal pressure is restored to complete the phase transformation strengthening; The inner wall of the sealed pressure vessel is provided with a nano-ceramic thermal insulation layer with a thickness of 150-200 μm and a thermal conductivity of ≤0.5 W / (m·K). 18 sets of distributed thermocouples are configured inside the vessel to monitor the temperature gradient to ≤3°C / cm. Three-stage temperature control is adopted in combination with three-level pressure regulation. Through the nano-ceramic insulation layer (thermal conductivity ≤ 0.5W / m·K) in the sealed pressure vessel and 18 sets of thermocouple monitoring, grain refinement, dislocation density control and hardness improvement are achieved. The cooling / reheating rates are limited to 8-10℃ / min and ≤5℃ / min respectively.

[0019] In step 2, the multi-frequency resonance stress relief device is equipped with a dual vibration table, the X / Y axial vibration phase difference is 90°±5°, the vibration duration is 45-60 minutes, and the three frequency bands of 80Hz, 100Hz and 120Hz are switched alternately at intervals of 5 minutes. The harmonic response of the workpiece is monitored in real time during the vibration aging process. When the resonance peak offset is detected to be greater than 5%, the vibration frequency is automatically adjusted to the frequency corresponding to the resonance peak after the offset. The dual vibration table adopts an electromagnetic-hydraulic composite drive system, the vibration acceleration accuracy is controlled at ±0.05g, the phase difference closed-loop control response time is ≤50ms, and an axial preload of 5-8kN is applied synchronously during the vibration aging process. The workpiece is clamped using a three-point hydraulic support structure, and the pressure deviation of the support point is ≤5%. The harmonic response is monitored using a laser Doppler vibrometer with a sampling frequency of 10kHz, and a vibration mode cloud map of the 0.1-200Hz frequency band is generated in real time; Based on an electromagnetic-hydraulic composite drive dual vibration table (acceleration accuracy of ±0.05g), an axial preload of 5-8kN is applied. Through X / Y axis orthogonal vibration (phase difference 90°±5°) and three-band switching (80 / 100 / 120Hz), combined with a laser Doppler vibrometer (10kHz sampling), real-time monitoring of the harmonic response is achieved, achieving frequency adaptive adjustment when the resonance peak shift is greater than 5%, effectively eliminating residual stress.

[0020] In step 3, the five-axis machining center is equipped with an HSK-E50 spindle interface, and the tool system includes: a φ20mm ceramic-coated milling cutter for roughing, with a rake angle of 12°±1° and a clearance angle of 8°±0.5°; φ10mm diamond-coated milling cutter for finishing, with a rake angle of 8°±0.5° and a clearance angle of 6°±0.3°; The tool changing strategy is automatically adjusted based on cutting force feedback. Tool change is triggered when the cutting force fluctuation is greater than 15%. A cycloidal milling path is used in the finishing stage, with a single tooth feed of 0.02-0.05 mm / z, an axial cutting depth of 0.1-0.3 mm, and a radial cutting depth of 0.8-1.2 mm. The AlTiN coating thickness of the ceramic-coated milling cutter is 3.5-4.2 μm, and the grain size of the diamond-coated milling cutter is ≤500 nm. The cutting force feedback system integrates a piezoelectric three-axis force sensor with a measurement range of 0-5000 N, a resolution of 0.1 N, and a data acquisition interval of ≤0.5 ms. The cycloidal milling path uses an adaptive step size algorithm to dynamically adjust the curvature radius according to the material removal rate, and the curvature change rate is ≤0.2 mm. -1 ; Equipped with HSK-E50 toolholder system, used in stages: rough machining: φ20mm ceramic coated milling cutter (AlTiN coating 3.5-4.2μm, rake angle 12°±1°), fine machining: φ10mm diamond coated milling cutter (grain ≤500nm, rake angle 8°±0.5°), piezoelectric three-axis force sensor (0.5ms acquisition) monitors cutting force fluctuations >15% to trigger tool change, and uses adaptive trochoid milling (curvature change rate ≤0.2mm -1 , single tooth feed 0.02-0.05mm / z).

[0021] In step 4, after plasma cleaning, the surface oxygen content is ≤6at%, the carbon content is ≤4at%, the surface contact angle is ≤20°, and the surface roughness Ra is ≤0.15μm; Argon-oxygen mixture (4:1) plasma cleaning was carried out in two stages (300W to 250W). The surface oxygen / carbon content was ≤6at% and 4at%, respectively, by rotating the stage (5-15rpm, 0-30° inclination angle). The surface roughness Ra was ≤0.15μm, the contact angle was ≤20°, and the surface composition was detected online every 120 seconds by an X-ray spectrometer.

[0022] In step five, the differential coefficient Kd of the PID control model is 0.2-0.4, the compensation cycle is ≤30s, and the compensation accuracy is ≤0.003mm. The PID control model establishes a processing quality prediction model containing 32 process parameters. When the deviation between the real-time acquisition parameters and the model prediction value is greater than 5%, the process parameter optimization module is automatically triggered to adjust the cutting parameters. The processing quality prediction model includes a temperature field-stress field coupling analysis module, and the finite element method is used to divide the 0.5mm 3 The hexahedral grid is used, and the process parameter optimization module integrates a genetic algorithm. The population size is set to 50 generations, the crossover probability is 0.7, and the mutation probability is 0.01. The real-time data acquisition system includes a 16-channel synchronous acquisition card with a sampling rate of 1MHz and a signal transmission delay of ≤2μs. The data preprocessing uses a wavelet noise reduction algorithm. The integrated PID control (Kp = 0.7-0.9 / Ki = 0.04-0.06 / Kd = 0.2-0.4) and genetic algorithm optimization module are used to synchronize the temperature and stress field through a 16-channel synchronous acquisition system (1MHz sampling, ≤2μs delay) and a temperature-stress field coupled finite element model (0.5mm 3 The grid) achieves a compensation accuracy of ≤0.003mm, and automatically optimizes cutting parameters (50 generations of population size, crossover probability 0.7) when the deviation between real-time data and the prediction model is greater than 5%.

[0023] The present invention is compared with the prior art, and the reference data obtained are as follows: Compared with the prior art, the present invention has the following characteristics: the vibration energy utilization rate of the drive system is increased from 60% to 85%, the residual stress elimination rate is increased from 75% to 92% in frequency control, the multi-phase residual stress elimination efficiency is increased by 40% in phase control, the real-time frequency compensation response time is ≤50ms in harmonic response monitoring, the tool life is increased to 500 pieces in the tool system, the surface roughness is reduced by 30%, the machining accuracy is increased from ±0.01mm to ±0.005mm in cutting monitoring, the cutting temperature is reduced by 25% and the tool wear rate is reduced by 40% in machining path, the surface oxygen content is ≤6at% and the contact angle is reduced from 50° to ≤20° in cleaning process, the coating adhesion is improved (the critical load of the scratch test is increased from 30N to 50N), the dynamic compensation cycle is shortened from 60s to 30s in the control model, the data integrity is improved from 85% to 99.8% in data acquisition, and the prediction accuracy of the prediction model is improved from 70% to 95%. The reference data is as follows: In this invention, three-stage temperature control is adopted, combined with three-level pressure regulation, through the nano-ceramic insulation layer (thermal conductivity ≤ 0.5W / m·K) in the sealed pressure vessel and 18 sets of thermocouple monitoring, to achieve grain refinement, dislocation density control and hardness improvement, and the cooling / reheating rates are limited to 8-10℃ / min and ≤5℃ / min respectively; Based on an electromagnetic-hydraulic composite drive dual vibration table (acceleration accuracy ±0.05g), an axial preload of 5-8kN is applied. Through X / Y axis orthogonal vibration (phase difference 90°±5°) and three-band switching (80 / 100 / 120Hz), combined with a laser Doppler vibrometer (10kHz sampling), real-time monitoring of the harmonic response is achieved. When the resonance peak shift is greater than 5%, frequency adaptive adjustment is achieved to effectively eliminate residual stress. Equipped with HSK-E50 toolholder system, used in stages: rough machining: φ20mm ceramic coated milling cutter (AlTiN coating 3.5-4.2μm, rake angle 12°±1°), fine machining: φ10mm diamond coated milling cutter (grain ≤500nm, rake angle 8°±0.5°), piezoelectric three-axis force sensor (0.5ms acquisition) monitors cutting force fluctuations >15% to trigger tool change, and uses adaptive trochoid milling (curvature change rate ≤0.2mm -1 , single tooth feed 0.02-0.05mm / z); Argon-oxygen mixture (4:1) plasma cleaning was performed in two stages (300W to 250W). The surface oxygen / carbon contents were ≤6at% and 4at%, respectively, by rotating the stage (5-15rpm, 0-30° tilt angle). The surface roughness Ra was ≤0.15μm, and the contact angle was ≤20°. The surface composition was monitored online every 120 seconds by an X-ray spectrometer. The integrated PID control (Kp = 0.7-0.9 / Ki = 0.04-0.06 / Kd = 0.2-0.4) and genetic algorithm optimization module are used to synchronize the temperature and stress field through a 16-channel synchronous acquisition system (1MHz sampling, ≤2μs delay) and a temperature-stress field coupled finite element model (0.5mm 3 Grid) to achieve ≤0.003mm compensation accuracy, when the real-time data and the prediction model deviation> 5%, automatically optimize the cutting parameters (50 generations of population size, crossover probability 0.7); The present invention solves the problems of stress deformation, surface integrity control and dimensional stability in high-precision shell processing through thermal-mechanical-electrical multi-field coordinated control, dynamic feedback optimization and precision detection technology, and meets the stringent requirements of robot manipulators for lightweight, high rigidity and long life.

[0024] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A method for processing a wafer transfer robot housing, characterized in that: The following steps are involved: Step 1: Perform gradient heat treatment on the aluminum alloy casting, including three-stage treatment: holding at 200°C ± 10°C for 2 hours, holding at 430°C ± 5°C for 1 hour, and cryogenic treatment with liquid nitrogen for 30 minutes; Step 2: Perform orthogonal vibration aging treatment in a multi-frequency resonance stress relief device, with a main vibration frequency of 80-120 Hz and an acceleration of 0.5-1.2 g; Step 3: Perform multi-process composite machining on a five-axis machining center with a spindle speed of ≥25,000 rpm and equipped with an HSK-E50 toolholder system; Step 4: Use argon-oxygen mixed plasma to clean the surface, with a gas volume ratio of 4:1 and a radio frequency power of 250-350W; Step 5: Implement online dimension compensation through the laser tracker. The compensation algorithm includes a PID control model with a proportional coefficient Kp=0.7-0.9 and an integral coefficient Ki=0.04-0.

06.

2. The method for processing a wafer transfer robot housing according to claim 1, wherein: In step 1, liquid nitrogen cryogenic treatment is carried out in a sealed pressure vessel, and the cooling rate is controlled at 8-10℃ / min. After the treatment, the temperature is returned to room temperature at a rate of ≤5℃ / min. After the gradient heat treatment, the material grain size is guaranteed to be ≤30μm and the dislocation density is ≤1.5×10¹ 4 / m², microhardness ≥160HV.

3. The method for processing a wafer transfer robot housing according to claim 1, wherein: In step 2, the multi-frequency resonance stress relief device is equipped with a dual vibration table, the X / Y axial vibration phase difference is 90°±5°, the vibration duration is 45-60 minutes, and the three frequency bands of 80Hz, 100Hz and 120Hz are switched alternately at intervals of 5 minutes. The harmonic response of the workpiece is monitored in real time during the vibration aging process. When the resonance peak offset is detected to be greater than 5%, the vibration frequency is automatically adjusted to the frequency corresponding to the resonance peak after the offset.

4. The method for processing a wafer transfer robot housing according to claim 1, wherein: In step 3, the five-axis machining center is equipped with an HSK-E50 spindle interface, and the tool system includes: a φ20mm ceramic-coated milling cutter for roughing, with a rake angle of 12°±1° and a clearance angle of 8°±0.5°; φ10mm diamond-coated milling cutter for finishing, with a rake angle of 8°±0.5° and a clearance angle of 6°±0.3°; The tool changing strategy is automatically adjusted based on cutting force feedback. Tool change is triggered when the cutting force fluctuation is greater than 15%. A trochoidal milling path is used in the finishing stage, with a single tooth feed rate of 0.02-0.05mm / z, an axial depth of cut of 0.1-0.3mm, and a radial depth of cut of 0.8-1.2mm.

5. The method for processing a wafer transfer robot housing according to claim 1, wherein: In step 4, after plasma cleaning, the surface oxygen content is ≤6at%, the carbon content is ≤4at%, the surface contact angle is ≤20°, and the surface roughness Ra is ≤0.15μm.

6. The method for processing a wafer transfer robot housing according to claim 1, wherein: In step five, the differential coefficient Kd of the PID control model is 0.2-0.4, the compensation cycle is ≤30s, and the compensation accuracy is ≤0.003mm. The PID control model establishes a processing quality prediction model containing 32 process parameters. When the deviation between the real-time collected parameters and the model prediction value is greater than 5%, the process parameter optimization module is automatically triggered to adjust the cutting parameters.

7. The method for processing a wafer transfer robot housing according to claim 2, wherein: The liquid nitrogen cryogenic treatment stage adopts three-level pressure control: In the initial stage, the pressure is maintained at 0.8-1.2 MPa for 30 seconds to achieve rapid heat exchange; In the middle stage, the pressure is reduced to 0.3-0.5 MPa for 25 minutes to ensure uniform cooling; In the final stage, normal pressure is restored to complete the phase transformation strengthening; The inner wall of the sealed pressure vessel is provided with a nano-ceramic insulation layer with a thickness of 150-200 μm and a thermal conductivity of ≤0.5 W / (m·K). 18 sets of distributed thermocouples are configured inside the vessel to monitor the temperature gradient of ≤3°C / cm.

8. The method for processing a wafer transfer robot housing according to claim 3, wherein: The dual vibration table adopts an electromagnetic-hydraulic composite drive system, the vibration acceleration accuracy is controlled at ±0.05g, the phase difference closed-loop control response time is ≤50ms, and an axial preload of 5-8kN is applied synchronously during the vibration aging process. The workpiece is clamped using a three-point hydraulic support structure, and the support point pressure deviation is ≤5%. The harmonic response is monitored using a laser Doppler vibrometer with a sampling frequency of 10kHz, which generates a vibration modal cloud map in the frequency range of 0.1-200Hz in real time.

9. The method for processing a wafer transfer robot housing according to claim 4, wherein: The AlTiN coating thickness of the ceramic-coated milling cutter is 3.5-4.2μm, the grain size of the diamond-coated milling cutter is ≤500nm, and the cutting force feedback system integrates a piezoelectric three-axis force sensor with a measurement range of 0-5000N, a resolution of 0.1N, and a data acquisition interval of ≤0.5ms. The trochoidal milling path adopts an adaptive step size algorithm to dynamically adjust the curvature radius according to the material removal rate, and the curvature change rate is ≤0.2mm⁻¹.

10. The method for processing a wafer transfer robot housing according to claim 6, wherein: The processing quality prediction model includes a temperature field-stress field coupling analysis module, which uses the finite element method to divide the 0.5mm³ hexahedral grid. The process parameter optimization module integrates a genetic algorithm with a population size of 50 generations, a crossover probability of 0.7, and a mutation probability of 0.

01. The real-time data acquisition system includes a 16-channel synchronous acquisition card with a sampling rate of 1MHz and a signal transmission delay of ≤2μs. The data preprocessing uses a wavelet noise reduction algorithm.

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