Semiconductor performance detection system based on environmental simulation

Abstract

The invention discloses a semiconductor performance detection system based on environmental simulation, which relates to the technical field of semiconductor detection and comprises an environmental simulation module, a parameter traversal module, an analog simulation module, a parameter traversal module, a data processing module, a data processing module and a data processing module, and is characterized in that the environmental simulation module is used for acquiring environmental simulation information and configuring an analog simulation environment for semiconductor detection based on the environmental simulation information; the parameter traversal module is used for carrying out real-time environment parameter traversal on an analogue simulation environment, screening out negative environment parameters influencing semiconductor performance detection and replacing the negative environment parameters, the integrated control module is connected with the parameter traversal module and used for controlling a mechanical arm to carry out automatic integrated control on a semiconductor in the analogue simulation environment, and the data analysis module is connected with the integrated control module. And the performance evaluation module is connected with the integrated control module and is used for evaluating the performance of the semiconductors after automatic integrated control and storing the semiconductors in different areas based on an evaluation result. According to the invention, the performance of the semiconductor can be detected in an environment simulation mode, and the semiconductor with different performances can be distinguished.

Description

Technical Field

[0001] The present invention relates to the technical field of semiconductor detection, and specifically to a semiconductor performance detection system based on environmental simulation. Background Technique

[0002] Semiconductor devices are the cornerstone of modern electronic technology, and their performance directly affects the stability and energy efficiency of electronic systems. Detecting the performance of semiconductors is an effective means to ensure that the quality of semiconductor devices meets the standards. With the rapid development of the semiconductor industry, the requirements for semiconductor performance detection are getting higher and higher.

[0003] Traditional semiconductor performance detection methods mainly rely on testing in the actual environment, which is not only time-consuming and laborious, but also difficult to comprehensively cover the influence of various environmental factors on semiconductor performance. In addition, there are many uncontrollable factors in the actual environment, resulting in large deviations in test results. To solve these problems, a semiconductor performance detection system based on environmental simulation has emerged. Summary of the Invention

[0004] In order to solve the above problems, the purpose of the present invention is to provide a semiconductor performance detection system based on environmental simulation.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A semiconductor performance detection system based on environmental simulation, including: An environmental simulation module, used to obtain environmental simulation information, configure a simulation environment for semiconductor detection based on the environmental simulation information. Among them, the simulation environment includes several simulation items, the simulation data and simulation monitoring scripts corresponding to each simulation item; perform environmental monitoring based on the simulation monitoring scripts; A parameter traversal module, connected to the environmental simulation module, used to perform real-time traversal of environmental parameters in the simulation environment, screen out negative environmental parameters that affect semiconductor performance detection, construct a set of positive parameters based on the negative environmental parameters, and replace the negative environmental parameters with the positive parameter set; An integrated control module, connected to the parameter traversal module, used to control the robotic arm to perform automated integrated control on the semiconductor in the simulation environment. The automated integrated control is carried out in cooperation with the corrected environmental parameters and the test script compiled by the robotic arm; A data analysis module, connected to the integrated control module, used to evaluate the performance of the semiconductor after the automated integrated control is completed, and store the semiconductor in different areas based on the evaluation results.

[0006] Furthermore, the environmental simulation module includes: An information acquisition unit, used to obtain environmental simulation information; A marking unit for marking and removing the exceeded standard information in the environment simulation information, where the exceeded standard information is data information that does not conform to the normal data range respectively; A configuration unit for configuring a simulation environment based on the environment simulation information; Construct a number of storage nodes, allocate a storage node for each simulation item, and use it to store the simulation data of each simulation item respectively; A monitoring unit for constructing a simulation monitoring script corresponding to each simulation item. The simulation monitoring script includes several simulation monitoring items, and the simulation monitoring items record the abnormal judgment conditions of the corresponding simulation item. It monitors different simulation items in the simulation environment in real time. When the simulation monitoring item meets the corresponding abnormal judgment condition, it is marked as an abnormal simulation item.

[0007] Further, the parameter traversal module includes: a traversal unit for completing the traversal of the environmental parameters in the simulation environment where the semiconductor is located. The environmental parameter traversal is set with corresponding traversal frequencies, traversal paths, and several items to be traversed corresponding to the simulation environment under the traversal path; Among them, several items to be traversed correspond to several simulation items in the simulation environment; A screening unit for performing value scoring on several items to be traversed in the simulation environment, obtaining the value score of each item to be traversed, and screening out the negative environmental parameters for semiconductor performance detection; A construction unit for analyzing the negative environmental parameters, obtaining the abnormal parameter path, abnormal details information, and abnormal data volume corresponding to the negative environmental parameters, combining them as the abnormal reference information set of the negative environmental parameters, and based on the abnormal reference information set, constructing positive correction parameters for correcting each negative environmental parameter and summarizing them as the positive parameter set; A replacement unit for replacing the negative environmental parameters in the current simulation environment where the semiconductor is located with the positive parameter set.

[0008] Further, the screening unit includes: a scoring unit for performing text similarity analysis on each item to be traversed and its preset standard reference item through the bag-of-words model, obtaining the text similarity between the corresponding item to be traversed and its standard reference item, and using the text similarity as the value score; A marking unit for marking some of the items to be traversed whose value scores do not meet the requirements, screening them as negative environmental parameters that have a negative impact on semiconductor performance detection, and marking the corresponding association of the negative environmental parameters as "Error"; Among them, it is judged whether the value score meets the requirements by setting a value determination interval, which is denoted as Ω, and the value score is denoted as Value; When Value ∈ Ω, no operation is performed; When Value Ω, screen the corresponding items to be traversed as negative environmental parameters.

[0009] Further, the integrated control module includes: a first control unit for debugging the robotic arm, defining several control response execution actions for the robotic arm to operate on the semiconductor, and the action types of the control response execution actions include basic motion control actions, physical interaction actions, testing and process actions, and intelligent cooperation actions; A script compilation unit for editing a script file for automatic integrated control of the robotic arm through a code platform, editing control instructions for each control response execution action, and after importing the control instructions into the script file, completing the final compilation to construct a corresponding test script; A second control unit for obtaining the corrected environmental parameters, and based on the corrected environmental parameters, parsing the test script for automatic integrated control of the robotic arm, and executing the script content recorded in the test script to perform automatic integrated control on the semiconductor.

[0010] Further, an evaluation unit for extracting key performance characteristics of the semiconductor that has completed automatic integrated control, obtaining historical data corresponding to the automatic integrated control, performing clustering analysis on the historical data through machine learning, and constructing a performance evaluation model for detecting the performance of the semiconductor; Input the extracted key performance characteristics into the performance evaluation model, and the performance evaluation model outputs the index values of the corresponding key performance characteristics of the semiconductor. Accumulate all the index values to generate a comprehensive performance detection and evaluation score; A picking unit for setting several levels of performance evaluation intervals, and dividing all the semiconductors that need to be subjected to performance detection into different performance levels according to the subordination relationship between the comprehensive performance detection and evaluation score and different performance evaluation intervals, and storing them in different areas.

[0011] Further, the specific process of obtaining the comprehensive performance detection and evaluation score includes: Record the comprehensive performance detection and evaluation score as Score: Score = \sum ^{n}_{i = 1} {Rr\left [ {i} \right ]} ; where n is the total number of items of the corresponding key performance characteristics of the semiconductor output by the performance evaluation model, label each item of key performance characteristic as i, i = 1, 2, 3,..., n, n is a natural number greater than 0, and Rr\left [ {i} \right ] represents the index value of the i-th key performance characteristic; The calculation method of the index value of the key performance characteristic is as follows: Set the reference value for each key performance characteristic and obtain the characteristic value of the key performance characteristic; ; Among them, the characteristic values of the key performance characteristics include the probe positioning accuracy rate, the wafer loading and unloading completion rate, the robot arm obstacle avoidance achievement rate, the expected force control completion rate, the dispensing qualification rate, the spraying qualification rate, and the cooperation success rate. The reference value corresponding to each key performance characteristic is the specification value that can achieve the expected effect.

[0012] Furthermore, the picking unit includes: The performance evaluation interval includes an excellent performance level interval, a good performance level interval, a qualified performance level interval, and an unqualified performance level interval; They are respectively denoted as Δ 优秀、 Δ 良好、 Δ 合格 and Δ 不合格 ; When Score ∈ Δ 优秀 , mark the corresponding semiconductor as a high-quality product and pick it to the preset first storage area; When Score ∈ Δ 良好 , mark the corresponding semiconductor as a good product and pick it to the preset second storage area; When Score ∈ Δ 合格 , pick the corresponding semiconductor as a qualified product and pick it to the preset third storage area; When Score ∈ Δ 不合格 , pick the corresponding semiconductor as a non-conforming product and pick it to the preset fourth storage area.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: The environmental simulation module obtains environmental simulation information, configures a simulation environment for semiconductor detection based on the environmental simulation information, the parameter traversal module performs real-time environmental parameter traversal on the simulation environment, screens out negative environmental parameters that affect semiconductor performance detection, and constructs a positive parameter set to replace the negative environmental parameters. The integrated control module controls the robot arm to perform automated integrated control on the semiconductor in the simulation environment. The data analysis module evaluates the performance of the semiconductor after the automated integrated control is completed and stores the semiconductor in different areas based on the evaluation results. On the one hand, it realizes the simulation of the simulation environment in the virtual scene, can more accurately reproduce the detection scene and various environmental influence factors, and effectively improves the accuracy of semiconductor performance detection. On the other hand, the integrated control module, through the collaborative work with the robot arm, finely realizes the automated integrated control of semiconductor detection, greatly improves the detection efficiency, and also reduces the errors caused by manual operation. Description of the Drawings

[0014] Figure 1 This is the schematic diagram of the present invention. Specific Embodiments

[0015] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0016] Embodiment 1, as Figure 1 shown, the semiconductor performance detection system based on environmental simulation in this embodiment includes: an environmental simulation module for obtaining environmental simulation information and configuring a simulation environment for semiconductor detection based on the environmental simulation information. The simulation environment includes several simulation items, the simulation data and simulation monitoring scripts corresponding to each simulation item; performing environmental monitoring based on the simulation monitoring scripts; a parameter traversal module connected to the environmental simulation module for performing real-time traversal of environmental parameters in the simulation environment, screening out negative environmental parameters affecting semiconductor performance detection, constructing a positive parameter set based on the negative environmental parameters, and replacing the negative environmental parameters with the positive parameter set; an integrated control module connected to the parameter traversal module for controlling the robotic arm to perform automated integrated control on the semiconductor in the simulation environment. The automated integrated control is carried out in cooperation with the corrected environmental parameters and the test script compiled by the robotic arm; a data analysis module connected to the integrated control module for evaluating the performance of the semiconductor after the automated integrated control is completed, and storing the semiconductor in different zones based on the evaluation results.

[0017] In one embodiment, the environmental simulation module includes: an information acquisition unit for obtaining environmental simulation information, where the environmental simulation information includes temperature simulation information, humidity simulation information, cleanliness simulation information, electromagnetic simulation information, pressure simulation information, and vibration simulation information; a marking unit for marking the respective exceeding-standard information in the temperature simulation information, humidity simulation information, cleanliness simulation information, electromagnetic simulation information, pressure simulation information, and vibration simulation information, and removing the exceeding-standard information. The exceeding-standard information is data information that does not conform to the normal data range; Configuration unit, used to configure a simulation environment based on environmental simulation information. Among them, according to the temperature simulation information, configure the environmental temperature simulation item; according to the humidity simulation information, configure the environmental humidity simulation item; according to the cleanliness simulation information, configure the environmental cleanliness simulation item; according to the electromagnetic simulation information, configure the environmental electromagnetic simulation item; according to the pressure simulation information, configure the environmental pressure simulation item; according to the vibration simulation information, configure the environmental vibration simulation item.

[0018] The above-mentioned simulation items configured based on environmental simulation information act together on the simulation environment for performance testing of semiconductors, laying a good data foundation for the detection of semiconductors. The influence degrees of environmental temperature, environmental humidity, environmental air cleanliness, environmental electric and magnetic fields, environmental atmospheric pressure, and vibrations of different types, amplitudes, and frequencies on semiconductors are comprehensively considered, making the simulation environment closer to the detection scenario in the real environment.

[0019] The simulation functions of specific simulation items are explained as follows: Environmental temperature simulation item: Set the temperature range from -60°C to 125°C to simulate the environmental temperature in extreme conditions, and the single - time temperature change amplitude is maintained at ±1°C; Environmental humidity simulation item: Set the relative humidity range from 45% to 65% to keep the semiconductor in a suitable environmental humidity. Unsuitable environmental humidity will have a negative impact on the chip. For example, too high humidity will cause condensation on the chip surface, affecting the test accuracy; too low humidity may generate static electricity and damage the chip; Environmental cleanliness simulation item: Set the air monitoring indicator level to ISO - Class - 5 and above. Pollutants such as particles and dust in the air will cause physical damage to the chip, thereby affecting the electrical performance of the chip. Maintaining good air cleanliness is beneficial to the chip test; Environmental electromagnetic simulation item: Simulate the corresponding environmental electric field and environmental magnetic field according to the set electric field strength and magnetic field strength, and change the directions of the environmental electric field and environmental magnetic field to test the electromagnetic compatibility of the semiconductor; Environmental pressure simulation item: Simulate different atmospheric pressure conditions, control the pressure change rate, and test the performance of the semiconductor under high or low pressure; Environmental vibration simulation item: Specifically divided into two types: mechanical vibration and acoustic vibration. Set vibrations of different amplitudes and frequencies for simulation to test the mechanical stability and reliability of the semiconductor; Construct several storage nodes, allocate a storage node for each simulation item, and use it to store the simulation data corresponding to each simulation item; The monitoring unit is used to construct a simulation monitoring script corresponding to each simulation item. The simulation monitoring script includes a number of simulation monitoring items, and the simulation monitoring items record the abnormal determination conditions of the corresponding simulation items. It monitors different simulation items in the simulation environment in real time. When a simulation monitoring item meets the corresponding abnormal determination condition, it is marked as an abnormal simulation item.

[0020] It should be noted that the environment simulation module realizes the reproduction of the real detection environment. By accurately configuring various simulation items, it simulates the actual application scenarios of semiconductors to ensure that the detection results are closer to the real working conditions, improve the detection credibility, and expose potential performance defects in advance through the coverage of extreme environmental conditions, and verify the reliability of semiconductors in complex scenarios.

[0021] In one embodiment, the parameter traversal module includes: The traversal unit is used to complete the traversal of environmental parameters in the simulation environment where the semiconductor is located. The traversal of environmental parameters is set with corresponding traversal frequencies, traversal paths, and a number of items to be traversed corresponding to the simulation environment under the traversal path; Among them, a number of items to be traversed correspond to a number of simulation items in the simulation environment; The screening unit is used to perform value scoring on a number of items to be traversed in the simulation environment, and then obtain the value score corresponding to each item to be traversed. According to the value score, negative environmental parameters that have a negative impact on the semiconductor performance detection are screened out; The construction unit is used to analyze the negative environmental parameters to obtain the abnormal parameter path, abnormal details information, and abnormal data volume corresponding to the negative environmental parameters, and combine them as the abnormal reference information set of the negative environmental parameters. Based on the abnormal reference information set, positive correction parameters for correcting each negative environmental parameter are constructed and summarized as the positive parameter set; The replacement unit is used to replace the negative environmental parameters in the current simulation environment where the semiconductor is located with the positive parameter set. Each positive correction parameter in the positive parameter set is used to match and repair the negative environmental parameters corresponding to the corresponding item to be traversed, so as to filter out all negative environmental parameters in the simulation environment.

[0022] In one embodiment, the screening unit includes: The scoring unit is used to perform text similarity analysis on each item to be traversed and the preset standard reference item corresponding to the item to be traversed through the bag-of-words model, and then obtain the text similarity between the corresponding item to be traversed and its preset standard reference item; use the text similarity as the value score of the corresponding item to be traversed, and the value range of the value score is the interval (0, 1); A marking unit, used to mark the parts of the items to be traversed whose value score does not meet the requirements, and filter them as negative environmental parameters that have an adverse impact on the semiconductor performance detection. The negative environmental parameters are correspondingly marked as "Error". Among them, it is determined whether the value score meets the requirements by setting a value measurement interval. The value measurement interval is denoted as Ω, and Ω = [0.6, 1). The value score is denoted as Value. When Value ∈ Ω, no operation is performed. When Value ∉Ω, the corresponding items to be traversed are filtered as negative environmental parameters.

[0023] In one embodiment, the integrated control module includes: A first control unit, used to debug the robotic arm, define several control response execution actions for the robotic arm to operate on the semiconductor, and the action types of the control response execution actions include basic motion control actions, physical interaction actions, test and process actions, and intelligent collaboration actions. The basic motion control actions include point-to-point motion and linear interpolation. Through point-to-point motion, the robotic arm is moved to the command coordinates at a preset moving speed, such as positions like the wafer stage or the probe card, for wafer loading and unloading and test probe positioning, and the accuracy of the robotic arm is controlled within ±0.001 mm. Through linear interpolation, the robotic arm is moved uniformly along a pre-planned straight path to avoid the vibration of the robotic arm, for path planning of the cutting blade and glue coating on the packaged semiconductor. The basic motion control actions also include rotation and attitude adjustment, rotating the end effector configured on the robotic arm, and adjusting the angles of the gripper or the probe to match the semiconductor, for flip-chip alignment and three-dimensional stacking packaging related to the semiconductor. For a multi-axis robotic arm, control the movement of the multi-axis robotic arm in the semiconductor chamber to avoid obstacles in the chamber.

[0024] The physical interaction actions include grasping and placing actions and force control operations. Through the grasping and placing actions, wafers, chips, and packaging substrates are transported, and the gripper of the robotic arm is controlled to open and close to adapt to the objects to be grasped with different sizes; through force control operations, constant force contact and compliant assembly are achieved; constant force contact: when the probe of the robotic arm contacts the pad, a constant pressure is maintained (for example: 5 g ± 0.2 g); through compliant assembly, the cover plate and the substrate are fitted together after packaging. The test and process actions include probe control operations and process execution operations. The probe control operation is used to synchronously contact several probe test points to shorten the test time, and plan the anti-collision path corresponding to the movement of the probe, and adjust the probe position and related parameters of the probe control in real time.

[0025] The process execution operation includes dispensing, spraying, and laser trimming; Perform dispensing or spraying. Among them, dispensing is performed according to the preset glue volume control accuracy of ±0.1 μL, spraying is performed according to the preset spraying speed range, and the preset spraying speed range is 0.1 - 10 mm / s. Perform laser trimming, where the robotic arm carries a laser head to correct the resistance value of the semiconductor; The intelligent collaborative actions include multi-robot intelligent collaboration and adaptive collaboration; Among them, multi-robot intelligent collaboration includes task relay and human-robot collaboration; Perform task relay. After a robotic arm finishes the current process operation on the wafer, it transfers the processed wafer to the next robotic arm to perform the process operation corresponding to the next robotic arm; for task relay, the control time error < 10 ms, and the control position error < 0.1 mm; Perform human-robot collaboration. Within the planned safe working area, the collaborative operation of the staff and the robotic arm is carried out synchronously; for human-robot collaboration, a force perception emergency stop mechanism is provided. The force perception emergency stop mechanism is: when the robotic arm senses an external force outside the preset force range, it means that the robotic arm encounters an unexpected event, and the current operation of the robotic arm is stopped immediately.

[0026] The adaptive collaboration includes visual servo and AI path optimization; Dynamically track the wafer alignment mark through visual servo; Generate an obstacle avoidance path for the robotic arm through AI path optimization.

[0027] The script compilation unit is used to edit a script file for automatic integrated control of the robotic arm through a code platform, and edit the control instructions corresponding to each control response execution action. After importing the control instructions into the script file, the final compilation is completed to construct the corresponding test script; The second control unit is used to obtain the corrected environmental parameters, and parse the test script for automatic integrated control of the robotic arm based on the corrected environmental parameters, and execute the script content recorded in the test script to perform various operations for automatic integrated control of the semiconductor.

[0028] It should be noted that by editing corresponding control instructions for each action that the robotic arm needs to perform, and importing all the control instructions into a script file, the construction of the final test script is achieved. According to the content recorded in the final test script, the robotic arm is subjected to efficient automated integrated control to complete the precise processing of semiconductors.

[0029] In one embodiment, the data analysis module includes: An evaluation unit, which is used to extract the key performance characteristics of the semiconductor that has completed automated integrated control, obtain the historical data corresponding to the automated integrated control, perform clustering analysis on the historical data through machine learning, and construct a performance evaluation model for detecting the performance of the semiconductor; Input the extracted key performance characteristics into the performance evaluation model. The performance evaluation model outputs the index values of the corresponding key performance characteristics of the semiconductor, and accumulates all the index values to generate a comprehensive performance detection and evaluation score.

[0030] Denote the comprehensive performance detection and evaluation score as Score, and the calculation formula of Score is as follows: ; Where n is the total number of items of the corresponding key performance characteristics of the semiconductor output by the performance evaluation model. Each item of key performance characteristic is labeled as i, i = 1, 2, 3,..., n, and n is a natural number greater than 0. represents the index value of the i-th key performance characteristic.

[0031] The calculation method of the index value of the key performance characteristic is as follows: Set the respective reference values for each item of key performance characteristic, obtain the characteristic values of the key performance characteristic. The characteristic values are used to reflect the characteristic state corresponding to the current key performance characteristic. The closer the characteristic value is to the reference value, the more the corresponding key performance characteristic meets the expectation, and the characteristic state is qualified. ; Among them, the characteristic values corresponding to the key performance characteristics include but are not limited to probe positioning accuracy rate, wafer loading and unloading completion rate, robotic arm obstacle avoidance achievement rate, expected force control completion rate, dispensing qualification rate, spraying qualification rate, and cooperation success rate. The reference values corresponding to the above-mentioned key performance characteristics are the specification values that can achieve the expected effects respectively. For example, the minimum allowable accuracy rate of probe positioning, the minimum allowable completion rate of wafer loading and unloading, the minimum obstacle avoidance rate of robotic arm obstacle avoidance, the lower limit completion rate of expected force control, the qualification thresholds of dispensing qualification rate and spraying qualification rate respectively, and the minimum success rate corresponding to the cooperation success rate.

[0032] The picking unit is used to set several levels of performance evaluation intervals. According to the subordination relationship between the comprehensive performance detection and evaluation scores and different performance evaluation intervals, all semiconductors that need to be subjected to performance detection are divided into different performance levels and stored in different areas. The performance evaluation intervals include excellent performance level interval, good performance level interval, qualified performance level interval, and unqualified performance level interval, which are respectively denoted as Δ 优秀、 Δ 良好、 Δ 合格 and Δ 不合格 ; When Score ∈ Δ 优秀 , mark the corresponding semiconductor as an excellent product and pick it to the preset first storage area; When Score ∈ Δ 良好 , mark the corresponding semiconductor as a good product and pick it to the preset second storage area; When Score ∈ Δ 合格 , pick the corresponding semiconductor as a qualified product and pick it to the preset third storage area; When Score ∈ Δ 不合格 , pick the corresponding semiconductor as an unqualified product and pick it to the preset fourth storage area.

[0033] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A semiconductor performance detection system based on environmental simulation, characterized in that, Including: An environment simulation module, configured to obtain environment simulation information, configure a simulation environment for semiconductor detection based on the environment simulation information, where the simulation environment includes a number of simulation items, corresponding simulation data and simulation monitoring scripts for each simulation item; perform environment monitoring based on the simulation monitoring scripts; A parameter traversal module, connected to the environment simulation module, configured to perform real-time traversal of environment parameters in the simulation environment, screen out negative environment parameters that affect semiconductor performance detection, construct a positive parameter set based on the negative environment parameters, and replace the negative environment parameters with the positive parameter set; An integrated control module, connected to the parameter traversal module, configured to control a robotic arm to perform automated integrated control on a semiconductor in the simulation environment, where the automated integrated control is coordinated by the corrected environment parameters and the test script compiled corresponding to the robotic arm; A data analysis module, connected to the integrated control module, configured to evaluate the performance of the semiconductor after the automated integrated control is completed, and store the semiconductor in different areas based on the evaluation results.

2. The semiconductor performance detection system based on environmental simulation according to claim 1, wherein, The environment simulation module includes: An information acquisition unit, configured to obtain environment simulation information; A marking unit, configured to mark and remove the excessive information in the environment simulation information, where the excessive information is data information that does not conform to the normal data range; A configuration unit, configured to configure the simulation environment based on the environment simulation information; Construct a number of storage nodes, allocate a storage node for each simulation item, and use it to store the respective simulation data of each simulation item; A monitoring unit, configured to construct a simulation monitoring script corresponding to each simulation item, where the simulation monitoring script includes a number of simulation monitoring items, and the simulation monitoring items record the abnormal determination conditions of the corresponding simulation item, perform real-time monitoring on different simulation items in the simulation environment, and mark it as an abnormal simulation item when the simulation monitoring item meets the corresponding abnormal determination conditions.

3. The semiconductor performance detection system based on environmental simulation according to claim 2, characterized in that The parameter traversal module includes: a traversal unit, configured to complete the traversal of environment parameters in the simulation environment where the semiconductor is located. The traversal of environment parameters is set with corresponding traversal frequencies, traversal paths, and a number of items to be traversed corresponding to the simulation environment under the traversal path; Among them, the number of items to be traversed corresponds to a number of simulation items in the simulation environment; A screening unit, configured to perform value scoring on a number of items to be traversed in the simulation environment, obtain the value score of each item to be traversed, and screen out the negative environment parameters for semiconductor performance detection; A construction unit, configured to analyze the negative environment parameters, obtain the abnormal parameter path, abnormal details information, and abnormal data volume corresponding to the negative environment parameters, merge them as the abnormal reference information set of the negative environment parameters, construct a positive correction parameter for correcting each negative environment parameter based on the abnormal reference information set, and summarize it as the positive parameter set; A replacement unit, configured to replace the negative environment parameters in the current simulation environment where the semiconductor is located with the positive parameter set.

4. The semiconductor performance detection system based on environmental simulation according to claim 3, wherein The screening unit includes: a scoring unit for performing text similarity analysis on each item to be traversed and its preset standard reference item through a bag-of-words model, obtaining the text similarity between the item to be traversed and its standard reference item, and using the text similarity as the value score; a marking unit for marking some of the items to be traversed whose value scores do not meet the requirements, screening them as negative environmental parameters that have a negative impact on the semiconductor performance detection, and marking the corresponding association of the negative environmental parameters as "Error"; wherein, it is determined whether the value score meets the requirements by setting a value determination interval, denoted as Ω, and the value score is denoted as Value; When Value ∈ Ω, no operation is performed; When Value Ω, screen the corresponding items to be traversed as negative environmental parameters.

5. The semiconductor performance detection system based on environment simulation according to claim 4, wherein The integrated control module includes: a first control unit for debugging the robotic arm, defining several control response execution actions for the robotic arm to operate on the semiconductor, and the action types of the control response execution actions include basic motion control actions, physical interaction actions, testing and process actions, and intelligent collaboration actions; a script compilation unit for editing a script file for automated integrated control of the robotic arm through a code platform, and editing the control instructions for each control response execution action. After importing the control instructions into the script file, the final compilation is completed to construct the corresponding test script; a second control unit for obtaining the corrected environmental parameters, and based on the corrected environmental parameters, parsing the test script for automated integrated control of the robotic arm, and executing the script content recorded in the test script to perform automated integrated control on the semiconductor.

6. The semiconductor performance detection system based on environment simulation according to claim 5, characterized in that The data analysis module includes: an evaluation unit for extracting the key performance characteristics of the semiconductor that has completed automated integrated control, obtaining the historical data corresponding to the automated integrated control, and performing clustering analysis on the historical data through machine learning to construct a performance evaluation model for detecting the semiconductor performance; inputting the extracted key performance characteristics into the performance evaluation model, and the performance evaluation model outputs the index values of the corresponding key performance characteristics of the semiconductor, and accumulates all the index values to generate a comprehensive performance detection and evaluation score; a sorting unit for setting several levels of performance evaluation intervals, and dividing all the semiconductors that need to be subjected to performance detection into different performance levels according to the subordination relationship between the comprehensive performance detection and evaluation score and different performance evaluation intervals, and storing them in partitions.

7. The semiconductor performance detection system based on environmental simulation according to claim 6, wherein The specific process of obtaining the comprehensive performance detection and evaluation score includes: Record the comprehensive performance detection and evaluation score as Score: Score = \sum ^{n}_{i=1} {Rr\left [ {i} \right ]} ; Among them, n is the total number of key performance characteristics of the semiconductor output by the performance evaluation model. Each key performance characteristic is labeled as i, where i = 1, 2, 3, ……, n, and n is a natural number greater than 0. Rr represents the index value of the i-th key performance characteristic; The calculation method of the index value of the key performance characteristic is as follows: Setting the benchmark value of each key performance characteristic, and obtaining the characteristic value of the key performance characteristic; ； wherein, the characteristic values of the key performance characteristics include probe positioning accuracy rate, wafer loading and unloading completion rate, robotic arm obstacle avoidance achievement rate, expected force control completion rate, dispensing qualification rate, spraying qualification rate, and collaboration success rate, and the benchmark value corresponding to each key performance characteristic is the specification value that can achieve the expected effect.

8. The semiconductor performance detection system based on environmental simulation according to claim 7, wherein, The sorting unit includes: The performance evaluation intervals include excellent performance level interval, good performance level interval, qualified performance level interval, and unqualified performance level interval; Denoted as Δ respectively 优秀、 Δ 良好、 Δ 合格 and Δ 不合格 ; When Score ∈ Δ 优秀 mark the corresponding semiconductor as a high-quality product and select it to the preset first storage area to be stored; When Score ∈ Δ 良好 mark the corresponding semiconductor as a qualified product and select it to a preset second storage area; When Score ∈ Δ 合格 select the corresponding semiconductor as a qualified product and select it to the preset third storage area; When Score ∈ Δ 不合格 Select the corresponding semiconductor as a non-conforming product and select it to the preset fourth storage area to be stored.

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