Automatic particle testing method and system for PECVD equipment transmission platform

Abstract

The invention relates to the technical field of particle detection of semiconductor manufacturing equipment, in particular to an automatic particle testing method and system of a PECVD equipment transmission platform. The method comprises the following steps: constructing a reusable step unit with a unique ActionID and a standardized action library through action stepwise packaging, analyzing and generating a structured Sequence configuration file, establishing an independent test channel, and realizing parallel execution of test and production by adopting a hardware-level and software-level combined mutual exclusion lock mechanism and a production task priority strategy; a model configuration packet is loaded through a platform abstraction layer to shield hardware differences, particle concentration is collected in real time in combination with a sampling plan strongly bound with an action sequence, data is analyzed by using a quantification formula, overrun disposal is triggered, snapshots are stored during production preemption, follow-up running is performed when resources are idle, and a structured report is generated and pushed after circulation is completed. The test efficiency and the equipment utilization rate are greatly improved, the development cost and the pollution risk are reduced, and the method is suitable for stability detection and pre-detection scenes before production of PECVD (Plasma Enhanced Chemical Vapor Deposition) equipment.

Description

Automated particle testing method and system for PECVD equipment transport platform Technical Field

[0001] This invention relates to the field of particle detection technology in semiconductor manufacturing equipment, and more specifically to an automated particle testing method and system for a PECVD equipment transport platform. Background Technology

[0002] In semiconductor chip manufacturing, plasma-enhanced chemical vapor deposition (PECVD) equipment is the core equipment for thin film deposition on wafer surfaces. The cleanliness of its processing environment directly determines the film quality and device yield. Tiny particle contamination on the wafer surface can cause film defects, short circuits, and other problems, seriously affecting the performance stability of semiconductor devices. Therefore, it is necessary to regularly monitor the particle concentration in the PECVD equipment's transport platform and chamber to ensure that the process environment meets cleanliness standards.

[0003] Current particle testing methods in the industry generally rely on manually written scripts or sequential operations, which have many technical shortcomings and are no longer suitable for the large-scale, high-frequency, and parallel production needs of modern semiconductor manufacturing. Specific problems include: First, traditional particle testing requires manually writing scripts line by line to complete actions such as cavity vacuuming, argon purging, and particle sensor readings, lacking a unified action library. Each time a new or modified test item is added, developers need to write or rewrite a large amount of code from scratch, resulting in code redundancy, logical inconsistencies, and a single test script taking 4-6 hours to write, leading to high long-term maintenance costs.

[0004] Secondly, existing testing methods lack independent testing scheduling channels. The testing process shares control resources with production scheduling, necessitating a complete production halt during testing and resulting in prolonged equipment idleness. For example, if four hours of particle testing are scheduled daily, equipment utilization will drop from 80% to 60%, leading to an average annual capacity loss of up to 20%. Furthermore, malfunctions during testing may disrupt normal production processes, triggering additional production risks.

[0005] Third, single-action testing requires repeated manual parameter configuration and effect verification. The testing logic for combined actions is even more complex, and debugging requires tracing faults across multiple system modules. Typically, the debugging cycle for a complete test process takes 2-3 days, and after fine-tuning the parameters, the entire process needs to be run again, resulting in an overall debugging cycle of 1-2 weeks, which seriously affects production progress and the iteration efficiency of test solutions.

[0006] Fourth, traditional testing uses actual wafers as the testing medium. If testing errors occur, such as inadequate sealing or excessively long dust blowing times, particle contamination of the wafer surface can easily result. Furthermore, sudden changes in environmental parameters such as temperature, humidity, and vacuum levels during the switch between production and testing modes can introduce additional particles. According to feedback from typical semiconductor factories, the wafer scrap rate due to traditional particle testing can reach 1.2%, with batches exceeding particle limits accounting for approximately 4%, resulting in significant production cost losses for companies.

[0007] Fifth, different models of PECVD equipment differ significantly in terms of chamber structure, gas path configuration, and communication protocols. Traditional test programs are deeply coupled with the machine model and lack a universal adaptation mechanism. Each time the machine model is changed, the test program needs to be redeveloped or extensively rewritten, with an adaptation cycle of 5-10 days. The program reuse rate is less than 30%, which seriously restricts the large-scale promotion and application of the test solution.

[0008] In summary, traditional particle testing methods have significant problems in terms of efficiency, cost, yield assurance, and adaptability, and cannot meet the demands of modern semiconductor manufacturing for high-efficiency, low-risk, and highly adaptable particle detection. Summary of the Invention

[0009] The purpose of this invention is to propose an automated particle testing method and system for PECVD equipment transfer platforms, which improves particle testing efficiency and overall equipment utilization, effectively reduces testing development costs, wafer contamination risks, and machine adaptation costs, and ensures semiconductor manufacturing yield and production stability.

[0010] According to a first aspect of the embodiments of this disclosure, an automated particle testing method for a PECVD equipment transmission platform is provided, comprising the following steps: encapsulating test actions into reusable step units with unique ActionIDs, configuring execution parameters, verification rules, and exception strategies to form a dynamically loadable action library; selecting action combinations through a graphical interface or script, setting the number of loops and particle qualification thresholds, and parsing to generate a structured Sequence configuration file containing action IDs, sampling plans, and priorities; establishing an independent test channel, adopting a mutex lock mechanism combining hardware and software levels, following a production task priority strategy to achieve parallel execution of testing and production, suspending testing and saving snapshots when production tasks arrive; collecting particle concentrations at key action nodes according to the sampling plan, quantifying and analyzing data, and triggering retry, cleaning, or rollback strategies when limits are exceeded; resuming testing from snapshots after production idles, generating a structured report containing particle concentration curves after completing the loop, and pushing it to the production dashboard; loading configuration packages for different models through the platform abstraction layer to shield hardware differences and achieve rapid adaptation to multiple PECVD models.

[0011] In one embodiment, the step unit includes execution parameters Params, preconditions PreCond, success verification Verify, sampling plan SamplingPlan, exception policy OnFail, and cleanup action Cleanup. The execution parameters include speed v, positioning accuracy ε, vacuum target P_set, suction pressure P_s, purge duration t_purge, and rotation angle θ. The action library is stored in JSON or XML format.

[0012] In one embodiment, the Sequence configuration file includes at least SequenceId, Version number, Priority, MutexResources declaration, global threshold, sampling period, and Steps array. Each Step is associated with a unique ActionID and records parameters, verification conditions, and exception handling strategies.

[0013] In one embodiment, the hardware-level lock is implemented based on the lock register / coil of the EtherCAT / Modbus fieldbus, while the software-level lock uses a process / thread mutex or semaphore; the snapshot includes StepIndex, loop count, key sensor status, particle statistics, and number of retries.

[0014] In one embodiment, the quantification analysis data includes: sampling number: N = ⌊T_test / Δt⌋+1, where Δt is the sampling interval, and T_test is the duration of a single action (such as a robotic arm picking up a piece) or the entire test sequence (such as the combination of "picking up a piece → transferring → placing a piece"); average particle concentration: C_avg = (1 / N)·Σ_{i=1..N}C_i, where N is the sampling number, and C_i is the particle concentration data obtained from the i-th sampling; moving average (denoising): C_ma(i) = (1 / W)·Σ_{j=i-W+1..i}C_j, where W is the window length, and C_j is the average particle concentration. The particle concentration data obtained from the j-th sampling is used; Particle dose (equivalent exposure): D=Σ_{i=1..N}C_i·Δt, used to measure the cumulative contribution of a certain action to the contamination; Exceedance judgment: if C_ma(i)>C_limit and the number of consecutive times is ≥M, then the segment is judged as failed and OnFail (i.e., retry / clean / rollback) is triggered, where C_limit is the qualified particle threshold and C_ma(i) is the moving average particle concentration of the i-th sampling point; Confidence limit: UCL=μ+3σ, where the parameters μ and σ are obtained from the statistics of historical qualified batches; An alarm is triggered when C_avg>UCL.

[0015] In one embodiment, the platform abstraction layer includes a general interface ITransferPlatform and a configuration file import module. The general interface defines a unified method for robotic arm movement, FOUP door operation, and cavity vacuum control. The configuration package includes the number of arms, cavity coordinates, and communication protocol parameters for the model. The communication protocols include EtherCAT, Modbus, and SECS.

[0016] In one embodiment, the action types of the step unit include FOUP door opening and closing, robotic arm picking up / placing wafers, transfer, cavity vacuuming, purging, rotation, waiting, returning to zero, and particle collection.

[0017] According to a second aspect of the present disclosure, an automated particle testing system for a PECVD equipment transmission platform is provided, comprising: an action unit encapsulation and library construction module, which encapsulates test actions into reusable step units with unique ActionIDs, configures execution parameters, verification rules, and exception policies, and forms a dynamically loadable action library; an action combination and sequence configuration module, which selects action combinations through a graphical interface or script, sets the number of loops and particle qualification thresholds, and parses and generates a structured Sequence configuration file containing action IDs, sampling plans, and priorities; and a parallel scheduling and resource arbitration module, which establishes independent test channels and performs parallel scheduling and resource arbitration. A mutex mechanism combining hardware and software levels is used to prioritize production tasks, enabling parallel execution of testing and production. When a production task arrives, testing is suspended and a snapshot is saved. The particle monitoring and over-limit handling module collects particle concentration at key action nodes according to the sampling plan, quantifies and analyzes the data, and triggers retry, cleanup, or rollback strategies when limits are exceeded. The test continuation and report output module resumes testing from the snapshot after production idles, generates a structured report containing particle concentration curves after the loop is completed, and pushes it to the production dashboard. The cross-model adaptation and deployment module loads configuration packages for different models through the platform abstraction layer, shielding hardware differences and enabling rapid adaptation to multiple PECVD models.

[0018] According to a third aspect of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and running on the memory, wherein the processor executes the program to implement the automated particle testing method of the PECVD equipment transfer platform.

[0019] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the automated particle testing method of the PECVD equipment transfer platform.

[0020] Compared with existing technologies, the above-mentioned technical solutions adopted in this invention have the following advantages: 1. By leveraging the step-by-step encapsulation and visual configuration interface, the configuration time for a single action is reduced from the traditional 4-6 hours to minutes, and the construction time for combined actions is compressed from several days to tens of minutes, completely eliminating the tedious process of manual programming. It also supports the configuration of single actions and arbitrary combinations of actions, and can quickly switch between templates for various scenarios such as pre-production inspection and stability testing, flexibly meeting different testing needs.

[0021] 2. By adopting a parallel scheduling mechanism, testing and production can be executed synchronously without downtime. Testing time no longer occupies capacity, and daily additional capacity can be increased by 20-30%. Through independent invocation of action sets and resource arbitration strategies, equipment utilization has been restored from the traditional 60% to over 80%, maximizing the filling of production gaps and optimizing equipment operation rhythm.

[0022] 3. Based on a unified action library and platform abstraction layer, when switching device models, only configuration needs to be updated without rewriting test logic. The adaptation cycle is shortened from 5-10 days to 1-2 days, and the program reusability rate is increased to over 80%. Debug script reuse and parameterized management reduce the development cost of a single test program from 5,000 yuan to several hundred yuan, significantly reducing enterprise R&D investment.

[0023] 4. Adopting a modular architecture and universal interface specifications, the functional modules have low coupling, eliminating the need for overall reconstruction when adding new actions, detection points, or hardware. The dedicated test control layer is separated from the production scheduling layer, minimizing system upgrade and maintenance risks, and allowing for smooth deployment of later functional iterations without impacting production.

[0024] 5. During the test, key indicators such as particle concentration and success rate of actions are collected in real time, and structured test reports and statistical analyses are automatically generated, providing accurate quantitative basis for equipment maintenance, process improvement and quality control, and helping enterprises achieve data-driven continuous optimization.

[0025] In summary, this invention constructs a highly efficient, parallel, low-pollution, and easily scalable particle testing system, comprehensively improving testing quality and production efficiency, reducing costs and risks, and demonstrating significant value for widespread application. Attached Figure Description

[0026] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an undue limitation of this application.

[0027] Figure 1 is a flowchart of the automated particle testing method for the PECVD equipment transfer platform. Detailed Implementation

[0028] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0029] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0030] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0031] It should be noted that the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and systems according to various embodiments of this disclosure. It should be noted that each block in a flowchart or block diagram may represent a module, segment, or portion of code, which may include one or more executable instructions for implementing the logical functions specified in the various embodiments. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutively represented blocks may actually be executed substantially in parallel, or they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, may be implemented using a dedicated hardware-based system that performs the specified functions or operations, or using a combination of dedicated hardware and computer instructions.

[0032] Example 1: This example provides an automated particle testing method for a PECVD equipment transfer platform, including the following steps: S1. Encapsulate test actions into reusable step units with unique ActionIDs, configure execution parameters, verification rules, and exception strategies to form a dynamically loadable action library; specifically, basic actions such as FOUP door opening and closing, robotic arm wafer picking / placing, transfer, cavity vacuuming, purging, rotation, waiting, zeroing, and particle collection are abstracted into step units with a unified data structure, and a unique ActionID is assigned to each step unit. The step unit includes at least execution parameters (Params), preconditions (PreCond), success verification rules (Verify), sampling plan (SamplingPlan), exception handling strategy (OnFail), and cleanup action (Cleanup) to achieve action reuse, version management, and cross-process calling, ultimately building a standardized action library.

[0033] For each step unit, execution parameters are configured, including speed v, positioning accuracy ε, vacuum target P_set, vacuum timeout T_vac, suction cup pressure P_s, purge duration t_purge, and rotation angle θ. Machine-readable success verification conditions are also defined, including a position sensor feedback of 1, vacuum degree ≤ P_set, normal suction cup vacuum status, and particle count drop relative to baseline ≥ ΔC_min. Timeout thresholds for each action are also specified. The configured step units are stored in JSON or XML format, and a dynamically loadable data interface is constructed, supporting runtime retrieval and retrieval via a unique ActionID.

[0034] S2. Select action combinations via a graphical interface or script, set the number of loops and particle qualification threshold, and parse to generate a structured Sequence configuration file containing action IDs, sampling plans, and priorities. Specifically, users can select single or multiple step units as actions through drag-and-drop operations in the graphical interface or by using scripts such as Python. Configure the execution order of actions, the number of loops N_loop, conditional branching logic (e.g., particle concentration exceeding the limit → execute the PURGE cleaning action → retry the original action → re-detect), and the particle qualification threshold C_limit. Save the configured action combinations as reusable test templates, supporting quick switching between different test scenarios such as "stability testing, pre-production inspection, and maintenance verification," improving test adaptation efficiency.

[0035] The configured action combination is parsed into a standardized Sequence configuration file. This file contains at least the SequenceId (unique sequence identifier), Version number, Priority, MutexResources declaration, global threshold, sampling period, and a Steps array arranged in a preset order. Each Step in the Steps array corresponds to and records core fields such as ActionID (unique step unit identifier), execution parameters Params, success verification rule Verify, sampling plan, exception handling strategy OnFail, and cleanup action Cleanup.

[0036] By storing the Sequence configuration file on disk in JSON or XML format, the test process becomes traceable, comparable, and portable, laying the foundation for cross-device deployment.

[0037] S3. Establish an independent test channel, employing a mutex mechanism combining hardware and software levels, and following a production task priority strategy to achieve parallel execution of testing and production. When a production task arrives, the test is suspended and a snapshot is saved. Specifically, the Sequence configuration file is submitted to an independent task queue of the test scheduling module, forming a dedicated test channel that is logically isolated from the production channel of the production scheduling module. The test scheduling module does not directly occupy the internal control resources of the production scheduling module; it only initiates a transmission platform control request to the production scheduling module through a standardized resource request interface, ensuring that particle testing can be executed in parallel without interruption of production tasks, avoiding equipment downtime.

[0038] A dual-layer protection mechanism of "hardware-level lock + software-level mutual exclusion" is adopted for control of the transmission platform: the hardware-level lock realizes the acquisition and release of control rights through the lock register or coil of fieldbus such as EtherCAT / Modbus; the software-level mutual exclusion uses process / thread mutex or semaphores to protect the critical action sending segment and prevent concurrent conflicts. The priority arbitration rule is set so that production tasks have priority and test tasks have low priority. When a production task arrives, it can directly preempt the test lock, and the test task will automatically enter a suspended state. It will resume execution when the production resources are idle, ensuring that the test and production processes do not interfere with each other.

[0039] When a production task triggers resource preemption, the test module persists the current execution state as a snapshot. The snapshot contains core information such as the current step index (StepIndex), loop count (k), key sensor status, particle statistics of the nearest window, and the number of retries completed. Subsequently, the test module releases the hardware-level lock and the software-level mutex lock and enters a suspended state.

[0040] S4. Collect particle concentration at key action nodes according to the sampling plan, quantify and analyze the data, and trigger retry, cleanup, or rollback strategies when limits are exceeded. Specifically, after gaining control of the transmission platform, execute each step unit in the order preset in the Sequence configuration file: before executing each step unit, verify whether its preconditions (PreCond) are met; after execution, confirm whether the action meets the standard according to the success verification rule (Verify). At the sampling points defined by the sampling plan (SamplingPlan) associated with the step unit (such as PRE before action execution, POST after execution, or a specified time window), collect particle concentration data C(t) in real time at the set sampling interval Δt, and dynamically calculate key indicators such as average particle concentration C_avg, moving average concentration C_ma, and cumulative particle dose D=ΣC_i・Δt during the test run. If the moving average concentration C_ma exceeds the particle qualification threshold C_limit for M consecutive times, or the cumulative particle dose D exceeds the preset dose threshold, then the pre-set exception handling strategy (OnFail) in the step unit will be followed to perform retry, PURGE cleaning, or process rollback operations, and the result information of each exception handling will be recorded in detail.

[0041] S5. After production idles, the test resumes from the snapshot. After completing the loop, a structured report containing particle concentration curves is generated and pushed to the production dashboard. Specifically, after the production task is completed and the transmission platform resources are idle, the test module re-initiates the mutex lock request. After the request is approved, the entire execution state is restored from the snapshot to ensure that the test sequence is reentrant, the particle concentration statistics are uninterrupted, and the counts are not duplicated. After completing all test loops, a structured test report is automatically generated based on the particle qualification threshold C_limit and confidence upper limit UCL and other judgment rules. This report includes core information such as the action-particle concentration change curve, particle concentration exceeding the limit segment record, number of abnormal retries, number of online cleaning executions, and test lock occupancy time U_lock, and is simultaneously pushed to the production dashboard and log system for real-time monitoring and traceability.

[0042] S6. By loading configuration packages for different models through the platform abstraction layer, hardware differences are masked, enabling rapid adaptation to multiple PECVD models.

[0043] Specifically, through the platform abstraction layer's general interface ITransferPlatform and machine configuration package, parameter mapping for different PECVD machine models in terms of the number of robotic arms, cavity coordinates, and communication protocols (including EtherCAT, Modbus, SECS, etc.) is completed. The motion library, sequence configuration files, and executable instructions are stored in a read-write medium, enabling rapid deployment and version rollback of test solutions across multiple machine models without requiring modifications to the upper-layer test logic.

[0044] Example 2: This example provides an automated particle testing system for a PECVD equipment transmission platform, including: an action unit encapsulation and library construction module, which encapsulates test actions into reusable step units with unique ActionIDs, configures execution parameters, verification rules, and exception policies, forming a dynamically loadable action library; an action combination and sequence configuration module, which selects action combinations through a graphical interface or script, sets the number of loops and particle qualification thresholds, and parses and generates a structured Sequence configuration file containing action IDs, sampling plans, and priorities; and a parallel scheduling and resource arbitration module, which establishes independent test channels and uses hardware... The system employs a mutex mechanism combining software and platform levels, prioritizing production tasks to enable parallel execution of testing and production. When a production task arrives, testing is suspended and a snapshot is saved. The particle monitoring and over-limit handling module collects particle concentration data at key action nodes according to the sampling plan, quantifies and analyzes the data, and triggers retry, cleanup, or rollback strategies when limits are exceeded. The test continuation and report output module resumes testing from the snapshot after production idles, generates a structured report containing particle concentration curves after the loop is completed, and pushes it to the production dashboard. The cross-model adaptation and deployment module loads configuration packages for different models through the platform abstraction layer, shielding hardware differences and enabling rapid adaptation to multiple PECVD models.

[0045] The above modules can be deployed on the same device or distributed devices; the division of modules is only a functional logic description and does not limit the specific physical boundaries or implementation order.

[0046] Example 3: An electronic device for running the above-mentioned "Automated Particle Testing Method for PECVD Equipment Transfer Platform". The electronic device includes: a processor, a memory, and optional communication interfaces / display devices / input devices, etc.; the memory stores a computer program that can run on the processor. When the processor executes the program, it implements steps S1 to S6 of the method described in Example 1, specifically including but not limited to: S1. Encapsulating test actions into reusable step units with unique ActionIDs, configuring execution parameters, verification rules, and exception policies to form a dynamically loadable action library; S2. Selecting action combinations through a graphical interface or script, setting the number of loops and particle qualification thresholds, and parsing to generate a result containing action IDs, sampling plans, and priorities. S3. Establish an independent test channel, adopting a mutex mechanism combining hardware and software levels, following a production task priority strategy to achieve parallel execution of testing and production. When a production task arrives, the test is suspended and a snapshot is saved; S4. Collect particle concentration at key action nodes according to the sampling plan, quantify and analyze the data, and trigger retry, cleanup, or rollback strategies when limits are exceeded; S5. Resume testing from the snapshot after production idles, generate a structured report containing particle concentration curves after the loop is completed, and push it to the production dashboard; S6. Load configuration packages for different models through the platform abstraction layer to shield hardware differences and achieve rapid adaptation of multiple PECVD models.

[0047] The electronic device hardware can be one of a server, personal computer, workstation, industrial controller, edge computing device, or mobile terminal; the processor can be a general-purpose CPU, GPU, NPU, FPGA, or a combination thereof; the memory can be RAM, ROM, flash memory, or disk array. The device can interact with local / remote data storage (acquiring observation data and outputting inversion results) through a communication interface. The above hardware configuration does not constitute a limitation of the present invention.

[0048] Example 4: A computer-readable storage medium storing a computer program, which, when run on a processor of an electronic device, causes the program to execute the method steps S1 to S6 described in Example 1; the storage medium may be a disk, optical disk, flash memory, solid-state drive, read-only memory, random access memory, or any combination of the above media.

[0049] Those skilled in the art will understand that the modules or steps described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, which can then be stored in a storage device for execution by a computer device. Alternatively, they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. This disclosure is not limited to any particular combination of hardware and software.

[0050] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0051] While the specific embodiments of this disclosure have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of this disclosure. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this disclosure are still within the scope of protection of this disclosure.

Claims

1. An automated particle testing method for a PECVD equipment transport platform, characterized in that, Includes the following steps: Test actions are encapsulated into reusable step units with unique ActionIDs, and execution parameters, verification rules and exception policies are configured to form a dynamically loadable action library. Action combinations are selected through a graphical interface or script, the number of loops and particle qualification thresholds are set, and a structured Sequence configuration file containing action ID, sampling plan and priority is generated. An independent testing channel is established, employing a mutex mechanism combining hardware and software levels. Following a production task priority strategy, testing and production are executed in parallel. When a production task arrives, testing is suspended and a snapshot is saved. Particle concentration is collected at key action nodes according to the sampling plan, and the data is quantitatively analyzed. When limits are exceeded, retry, cleanup, or rollback strategies are triggered. After production idles, testing resumes from the snapshot. After the cycle is completed, a structured report containing particle concentration curves is generated and pushed to the production dashboard. Different machine configuration packages are loaded through the platform abstraction layer to shield hardware differences and achieve rapid adaptation to multiple PECVD models.

2. The automated particle testing method for the PECVD equipment transport platform according to claim 1, characterized in that, The step unit includes execution parameters Params, preconditions PreCond, success verification Verify, sampling plan SamplingPlan, exception policy OnFail, and cleanup action Cleanup. Execution parameters include velocity v, positioning accuracy ε, vacuum target P_set, suction pressure P_s, purge duration t_purge, and rotation angle θ. The action library is stored in JSON or XML format.

3. The automated particle testing method for the PECVD equipment transport platform according to claim 1, characterized in that, The Sequence configuration file contains at least SequenceId, Version number, Priority, MutexResources declaration, global threshold, sampling period, and Steps array. Each Step is associated with a unique ActionID and records parameters, verification conditions, and exception handling strategies.

4. The automated particle testing method for the PECVD equipment transport platform according to claim 1, characterized in that, The hardware-level lock is implemented based on the lock register / coil of the EtherCAT / Modbus fieldbus, while the software-level lock uses process / thread mutex or semaphore; the snapshot includes StepIndex, loop count, key sensor status, particle statistics and retry count.

5. The automated particle testing method for the PECVD equipment transport platform according to claim 1, characterized in that, The quantitative analysis data includes: Number of samplings: N = ⌊T_test / Δt⌋ + 1, where Δt is the sampling interval and T_test is the duration of a single action or the entire test sequence; Average particle concentration: C_avg = (1 / N)·Σ_{i=1..N}C_i, where N is the number of samplings and C_i is the particle concentration data obtained from the i-th sampling; Moving average: C_ma(i) = (1 / W)·Σ_{j=i-W+1..i}C_j, where W is the window length and C_j is the particle concentration data obtained from the j-th sampling. Particle concentration data; Particle dose: D=Σ_{i=1..N}C_i·Δt, used to measure the cumulative contribution of a certain action to pollution; Exceeding limit judgment: if C_ma(i)>C_limit and the number of consecutive times is ≥M, then the segment is judged as failed and OnFail is triggered, where C_limit is the qualified threshold for particles and C_ma(i) is the moving average particle concentration of the i-th sampling point; Confidence limit: UCL=μ+3σ, where the parameters μ and σ are obtained from the statistics of historical qualified batches; An alarm is triggered when C_avg>UCL.

6. The automated particle testing method for the PECVD equipment transport platform according to claim 1, characterized in that, The platform abstraction layer includes a general interface ITransferPlatform and a configuration file import module. The general interface defines a unified method for robotic arm movement, FOUP door operation, and cavity vacuum control. The configuration package includes the number of arms, cavity coordinates, and communication protocol parameters for the model. The communication protocols include EtherCAT, Modbus, and SECS.

7. The automated particle testing method for the PECVD equipment transport platform according to claim 1, characterized in that, The action types of the step unit include FOUP door opening and closing, robotic arm picking / placing wafers, transmission, cavity vacuuming, purging, rotation, waiting, returning to zero, and particle collection.

8. An automated particle testing system for a PECVD equipment transport platform, characterized in that, include: The action unit encapsulation and library construction module encapsulates test actions into reusable step units with unique ActionIDs, configures execution parameters, verification rules and exception policies, and forms a dynamically loadable action library; the action combination and sequence configuration module allows users to select action combinations through a graphical interface or script, set the number of loops and particle qualification thresholds, and parse and generate a structured Sequence configuration file containing action IDs, sampling plans and priorities. The parallel scheduling and resource arbitration module establishes an independent test channel, adopts a mutex lock mechanism combining hardware and software levels, follows the production task priority strategy, and enables parallel execution of testing and production. When a production task arrives, the test is suspended and a snapshot is saved. The particle monitoring and over-limit handling module collects particle concentration at key action nodes according to the sampling plan, quantifies and analyzes the data, and triggers retry, cleanup, or rollback strategies when limits are exceeded. The test continuation and report output module resumes the test from the snapshot after production idles, generates a structured report containing particle concentration curves after the loop is completed, and pushes it to the production dashboard. The cross-model adaptation and deployment module loads configuration packages for different models through the platform abstraction layer, shielding hardware differences and enabling rapid adaptation to multiple PECVD models.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and running thereon, characterized in that, When the processor executes the program, it implements the automated particle testing method of the PECVD equipment transfer platform according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the automated particle testing method for the PECVD equipment transfer platform as described in any one of claims 1-7.

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