Semiconductor laboratory safety agile response management system and method

Abstract

The application provides a semiconductor laboratory safety agile response management system and method, the system comprises: a data acquisition module for acquiring laboratory data of a semiconductor laboratory; a safety detection and evaluation module in communication connection with the data acquisition module, configured to monitor and comprehensively evaluate the laboratory data in real time, and determine an analysis and evaluation report of the semiconductor laboratory; an emergency decision module configured to generate a global decision scheme of the semiconductor laboratory according to the laboratory data in the case that the safety detection and evaluation module determines that a safety event occurs in the semiconductor laboratory; and a user portrait module configured to generate a safety portrait corresponding to each laboratory personnel according to the laboratory data and the analysis and evaluation report, and to conduct safety training on each laboratory personnel according to the safety portrait, the safety portrait being used to evaluate the comprehensive safety quality and ability of the laboratory personnel in the semiconductor laboratory. The application can improve the identification efficiency of identifying safety events.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a semiconductor laboratory safety agile response management system and method. Background Technology

[0002] Safety management is paramount in the daily operation of semiconductor laboratories. However, current semiconductor laboratory safety management systems have limitations in preventing and handling safety incidents. One significant problem is the delayed detection of potential safety hazards. These systems often rely on periodic manual inspections and fixed threshold alarms, which cannot provide comprehensive, real-time monitoring of the complex and ever-changing laboratory environment. With the rapid development of semiconductor technology, laboratory equipment and processes are becoming increasingly complex, leading to a corresponding increase in safety risks. Due to limitations in data processing capabilities and algorithms, current semiconductor laboratory safety management systems struggle to quickly and accurately analyze massive amounts of real-time data, thus failing to identify potential safety hazards in a timely manner. Summary of the Invention

[0003] This application provides a semiconductor laboratory safety agile response management system and method, which can improve the efficiency of identifying safety incidents.

[0004] In a first aspect, embodiments of this application provide a semiconductor laboratory safety agile response management system, the system comprising:

[0005] The data acquisition module is used to collect laboratory data from the semiconductor laboratory. The laboratory data includes at least one of the following: environmental data, personnel behavior data, equipment operation data, and chemical flow data of the semiconductor laboratory.

[0006] The safety detection and assessment module communicates with the data acquisition module and is used to monitor and comprehensively evaluate laboratory data in real time, and to determine the analysis and assessment report of the semiconductor laboratory. The analysis and assessment report includes at least one of the following: on-site situation analysis report of the semiconductor laboratory, hidden danger analysis report of the semiconductor laboratory, and safety operation status score of the semiconductor laboratory.

[0007] The emergency decision-making module is used to generate a global decision-making plan for the semiconductor laboratory based on laboratory data when the safety detection and assessment module determines that a safety incident has occurred in the semiconductor laboratory.

[0008] The user profiling module is used to generate a safety profile for each laboratory personnel based on laboratory data and analysis and evaluation reports, and to conduct safety training for each laboratory personnel based on the safety profile. The safety profile is used to assess the comprehensive safety competence of laboratory personnel in the semiconductor laboratory.

[0009] Secondly, this application provides a semiconductor laboratory safety agile response management method, applied to a semiconductor laboratory safety agile response management system as described in any of the embodiments of the first aspect, the method comprising:

[0010] The data acquisition module collects laboratory data from the semiconductor laboratory. The laboratory data includes at least one of the following: environmental data, personnel behavior data, equipment operation data, and chemical flow data of the semiconductor laboratory.

[0011] The safety testing and assessment module performs real-time monitoring and comprehensive evaluation of laboratory data to determine the analysis and assessment report of the semiconductor laboratory. The analysis and assessment report includes at least one of the following: on-site situation analysis report of the semiconductor laboratory, hidden danger analysis report of the semiconductor laboratory, and safety operation status score of the semiconductor laboratory.

[0012] If the safety detection and assessment module determines that a safety incident has occurred in the semiconductor laboratory, the emergency decision-making module will generate a global decision-making plan for the semiconductor laboratory based on the laboratory data.

[0013] The user profiling module generates a safety profile for each laboratory personnel based on laboratory data and analysis reports. Safety training is then conducted for each laboratory personnel based on their safety profiles. The safety profiles are used to assess the comprehensive safety competence of laboratory personnel in the semiconductor laboratory.

[0014] Thirdly, embodiments of this application provide an electronic device, which includes: a processor and a memory storing computer program instructions;

[0015] When the processor executes computer program instructions, it implements the method as described in any of the embodiments of the second aspect.

[0016] Fourthly, embodiments of this application provide a computer storage medium storing computer program instructions, which, when executed by a processor, implement the method as described in any of the embodiments of the second aspect.

[0017] Fifthly, embodiments of this application provide a computer program product in which instructions, when executed by a processor of an electronic device, cause the electronic device to perform a method as described in any of the embodiments of the second aspect above.

[0018] In the semiconductor laboratory safety agile response management system and method provided in this application embodiment, a data acquisition module extensively collects environmental data, personnel behavior data, equipment operation data, and chemical flow data of the semiconductor laboratory. This multi-dimensional data comprehensively reflects the complex environment and changing conditions within the laboratory, providing a foundation for accurate monitoring of the semiconductor laboratory. The safety detection and assessment module works closely with the data acquisition module to monitor and comprehensively evaluate the massive amounts of real-time data collected. Through in-depth analysis of multi-source data, safety events can be quickly and accurately identified, and analysis and assessment reports can be generated promptly. When a safety event occurs, the emergency decision-making module responds rapidly. Based on the judgment results of the safety detection and assessment module and laboratory data, a global decision-making plan is quickly generated, significantly shortening the time from problem discovery to decision-making and improving emergency response efficiency. In summary, this system, through coordinated efforts across multiple stages from data acquisition, hazard identification, emergency decision-making to personnel training, constructs a comprehensive, multi-layered safety management system, greatly improving the efficiency of safety event identification. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is one of the structural schematic diagrams of the semiconductor laboratory safety agile response management system provided in the embodiments of this application;

[0021] Figure 2 This is a schematic diagram of the structure of the data acquisition module provided in an embodiment of this application;

[0022] Figure 3 This is a second schematic diagram of the structure of the semiconductor laboratory safety agile response management system provided in the embodiments of this application;

[0023] Figure 4 This is a schematic diagram of the structure of the security training module provided in the embodiments of this application;

[0024] Figure 5 This is a flowchart illustrating the semiconductor laboratory safety agile response management method provided in an embodiment of this application;

[0025] Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0026] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0027] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0028] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "comprising" or any other variations thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0029] To address the problems existing in related technologies, embodiments of this application provide a semiconductor laboratory safety agile response management system and method.

[0030] The following section first introduces the semiconductor laboratory safety agile response management system provided in the embodiments of this application. For example... Figure 1 As shown, the system specifically includes:

[0031] The data acquisition module 101 is used to collect laboratory data from the semiconductor laboratory, including at least one of the following: environmental data, personnel behavior data, equipment operation data, and chemical flow data of the semiconductor laboratory.

[0032] Optionally, in this embodiment of the application, laboratory data refers to a collection of various information related to the operation of a semiconductor laboratory, covering data on multiple aspects such as laboratory environment, personnel behavior, equipment operation, and chemical flow. This data can comprehensively reflect the overall operating status of the semiconductor laboratory and provide basic information support for subsequent safety testing and assessment, emergency decision-making, and personnel management.

[0033] Environmental data in semiconductor laboratories mainly includes data on temperature and humidity, air quality (such as the concentration of harmful gases), cleanliness, and light intensity. For example, some semiconductor processes have extremely strict requirements for temperature and humidity; excessively high or low temperatures or humidity may affect experimental results or even damage equipment; while excessive concentrations of harmful gases may endanger the health of laboratory personnel and cause safety accidents.

[0034] Personnel behavior data includes information such as the operational behavior, activity trajectory, and time of entry and exit from the laboratory of laboratory personnel. For example, it can show whether personnel perform experiments according to standard operating procedures, whether they move in unauthorized areas, and the length of time they stay in the laboratory. By analyzing this data, it is possible to determine whether personnel behavior complies with safety regulations and whether there are any potential safety risks.

[0035] Equipment operation data includes the operating status parameters of the experimental equipment, such as operating parameters like temperature, pressure, current, and voltage, as well as fault alarm information and maintenance records. This data helps managers understand the equipment's operating status in a timely manner, determine whether the equipment is functioning normally, and identify any potential safety hazards caused by equipment malfunctions.

[0036] Chemical circulation data primarily records information on the procurement, storage, use, and disposal of chemicals within the laboratory, including the type, quantity, storage location, requisition records, usage time, and disposal method of the chemicals. Since most chemicals used in semiconductor experiments possess flammable, explosive, and toxic properties, accurate collection and management of chemical circulation data helps prevent safety accidents such as chemical leaks and misuse.

[0037] Optionally, in one feasible implementation of this application, the data acquisition module 101, as the cornerstone of the semiconductor laboratory safety agile response management system, can achieve comprehensive acquisition of multi-dimensional laboratory data through diverse and efficient means.

[0038] For collecting environmental data, personnel behavior data, equipment operation data, and chemical flow data, various sensors can be widely deployed in key areas of the semiconductor laboratory. Regarding personnel behavior data collection, operational sensors record equipment actions, surveillance cameras use image recognition technology to determine personnel operating procedures, and this, combined with badges worn by personnel based on Bluetooth or Radio Frequency Identification (RFID) positioning technology and positioning base stations, enables activity tracking. Access control systems record personnel entry and exit times and identity information.

[0039] Equipment operation data can be acquired by installing sensors such as thermocouples, pressure, current and voltage in key parts of the equipment, processing the data through conditioning circuits, and then collecting it through a data acquisition card. Equipment fault alarms and maintenance records can also be obtained with the help of industrial communication protocols.

[0040] Data collection for chemical circulation runs through the entire process of procurement, storage, use, and disposal, and information can be entered using barcode scanners, RFID readers, and other methods.

[0041] In the security data collection and aggregation stage, relevant data can be collected into this system through the Application Programming Interface (API) or Message Queuing Telemetry Transport (MQTT) method, and a dedicated database can be established for unified storage to ensure that the system can access security data.

[0042] The semiconductor laboratory safety agile response management system of this application embodiment can connect to third-party systems such as plant management systems, large instrument management systems, and lean laboratory management systems. The data interface for data access must strictly adhere to standard data access specifications, and third-party system safety data is accessed according to predefined categories. This semiconductor laboratory safety agile response management system of this application embodiment possesses excellent compatibility, capable of collecting safety data from other systems through standardized interfaces. Furthermore, the system adopts a modular design, with each functional module operating independently yet collaboratively. This facilitates the expansion of new functions as needed; for example, when adding a safety data processing function, the corresponding module can be developed and integrated without affecting other modules, greatly improving the system's maintainability and flexibility, and ensuring stable operation under constantly changing safety management requirements.

[0043] The safety detection and evaluation module 102 is communicatively connected to the data acquisition module 101 and is used to perform real-time monitoring and comprehensive evaluation of the laboratory data to determine the analysis and evaluation report of the semiconductor laboratory. The analysis and evaluation report includes at least one of the following: the on-site situation analysis report of the semiconductor laboratory, the hidden danger analysis report of the semiconductor laboratory, and the safety operation status score of the semiconductor laboratory.

[0044] Optionally, in this embodiment, the analysis and evaluation report is a comprehensive report generated by the safety testing and evaluation module 102 based on laboratory data collected by the data acquisition module 101, after real-time monitoring and comprehensive evaluation. It integrates information from multiple sources, aiming to provide a systematic and accurate assessment of the safety status of the semiconductor laboratory, and to provide a basis for subsequent decision-making and management.

[0045] A semiconductor laboratory site condition analysis report focuses on the current actual conditions of the semiconductor laboratory. It describes whether the laboratory's environmental conditions, such as temperature, humidity, and cleanliness, meet requirements; whether personnel operating procedures are standardized and whether there are any violations of safety operating procedures; whether the equipment is operating normally and whether there are any signs of equipment malfunction or abnormal operation; and whether the storage, use, and transfer of chemicals comply with relevant regulations. By analyzing these actual site conditions, management personnel can gain a clear understanding of the laboratory's current operational status and promptly identify potential problems.

[0046] A hazard analysis report for a semiconductor laboratory focuses on identifying and analyzing potential safety hazards within the laboratory. This may include assessing safety risks arising from environmental factors, such as the possibility of hazardous gas leaks or the risk of fire due to electrical equipment overload; analyzing potential safety incidents caused by human behavior, such as the hazards posed by personnel not wearing protective equipment correctly or improper equipment operation; discussing potential safety issues arising from equipment aging, malfunctions, or improper maintenance; and analyzing the hazards of leaks and explosions that may result from improper chemical management. This report helps the laboratory take proactive measures to prevent safety incidents.

[0047] A semiconductor laboratory safety operation status score is a quantitative indicator used to intuitively reflect the overall safety operation status of a semiconductor laboratory. The score is derived by comprehensively considering various aspects of the laboratory based on a series of safety standards and evaluation indicators. For example, different weights and scoring standards are set based on environmental data, personnel behavior data, equipment operation data, and chemical flow data to score the laboratory's safety status. A higher score indicates a better safety operation status; a lower score indicates more safety issues requiring timely rectification and optimization. This score serves as an important reference for laboratory safety management, facilitating managers to quickly assess and compare the laboratory's safety status and take appropriate management measures.

[0048] Optionally, in one feasible implementation of this application, the safety detection and evaluation module 102, as the core part of the semiconductor laboratory safety agile response management system, is closely connected to the data acquisition module 101 to realize real-time monitoring and comprehensive evaluation of laboratory data and generate a comprehensive analysis and evaluation report.

[0049] The safety monitoring and assessment module 102 first maintains a stable and efficient communication connection with the data acquisition module 101 to ensure real-time acquisition of the latest environmental data, personnel behavior data, equipment operation data, and chemical flow data. For environmental data, real-time data analysis algorithms are used to compare the collected temperature, humidity, air quality, and cleanliness data with preset safety standards. If the temperature or humidity exceeds the suitable range, or the concentration of harmful gases approaches the threshold, an environmental anomaly warning is immediately issued, and detailed records are made in the on-site situation analysis report.

[0050] For personnel behavior data, image recognition and behavior analysis technologies are used to process data transmitted from surveillance cameras and operational sensors. If unsafe behaviors such as failure to operate equipment according to specifications or failure to wear protective equipment correctly are detected, they are promptly marked in the on-site situation analysis report and included as potential hazards in the hazard analysis report. Furthermore, the severity of the behavior negatively impacts the safety operation status score.

[0051] In terms of equipment operation data monitoring, fault diagnosis and prediction models can be used to analyze parameters such as temperature, pressure, current, and voltage, as well as fault alarm information. If key equipment parameters fluctuate abnormally or frequent fault alarms are issued, the safety detection and assessment module 102 will conduct an in-depth analysis of the cause of the fault, assess its impact on the safe operation of the laboratory, record the abnormal equipment situation in the on-site situation analysis report, predict potential risks in the hidden danger analysis report, and adjust the safety operation status score according to the safety status of the equipment.

[0052] For chemical flow data, the safety monitoring and assessment module 102 tracks the procurement, storage, use, and disposal of chemicals in real time according to chemical management regulations. If any issues are found, such as non-compliance with storage requirements, abnormal usage records, or improper disposal, these will be promptly reflected in the analysis report, serving as a safety hazard warning and affecting the safety operation status score.

[0053] During the comprehensive assessment process, the safety detection and assessment module 102 can utilize multi-dimensional data analysis and machine learning algorithms to perform correlation analysis on various data points. For example, it can combine temperature increases in environmental data with abnormal heat dissipation systems in equipment operation data and failure to adjust equipment parameters in a timely manner in personnel behavior data to comprehensively assess potential safety risks. Through comprehensive consideration of various data, it generates an on-site situation analysis report for the semiconductor laboratory, detailing the current actual condition of the laboratory; it delves into potential hazards in the data to complete a hazard analysis report; and based on a scientific scoring system, it calculates a safety operation status score for the semiconductor laboratory. These analysis and assessment reports provide key information for the emergency decision-making module 103 and important references for the user profiling module 104, helping to improve the overall safety management level of the semiconductor laboratory.

[0054] The emergency decision-making module 103 is used to generate a global decision-making scheme for the semiconductor laboratory based on the laboratory data when the safety detection and evaluation module 102 determines that a safety incident has occurred in the semiconductor laboratory.

[0055] Optionally, in the embodiments of this application, the global decision-making scheme is a comprehensive, systematic and targeted set of response strategies, which aims to coordinate resources from all parties to minimize the negative impact of a safety incident in a semiconductor laboratory, ensure personnel safety, reduce property losses, and maintain the normal operation of the laboratory.

[0056] Optionally, in one feasible implementation of this application, the emergency decision-making module 103 plays a key role in the semiconductor laboratory safety agile response management system, and its implementation process closely depends on the data support and model operation within the system.

[0057] First, the emergency decision-making module 103 can invoke a pre-built risk assessment model. This risk assessment model takes safety data, such as environmental data, personnel behavior data, equipment operation data, and chemical flow data, collected by the data acquisition module 101 from multiple systems in the semiconductor laboratory as input. Through complex and precise algorithms, this data undergoes in-depth analysis and processing to output risk assessment results. These results clearly identify the types of safety accidents that may occur in the semiconductor laboratory, such as fires, chemical leaks, and electric shock accidents caused by equipment malfunctions. They also determine the risk level, classifying it from minor to severe, providing crucial information for subsequent decision-making.

[0058] Simultaneously, the emergency decision-making module 103 acquires an accident decision-making model that includes both single-node decision-making models and a central decision-making model. The single-node decision-making model targets any system in the semiconductor laboratory and can output single-system decision recommendations when a safety incident occurs in that system. For example, if a power failure occurs in the plant system, the single-node decision-making model can provide suggestions such as activating the backup power supply and prioritizing power supply to critical equipment based on real-time data from the plant system, such as the status of the backup power supply and the power demand of critical equipment. The central decision-making model, on the other hand, bears the responsibility of determining the overall decision-making plan for the semiconductor laboratory. Each system corresponds to a single-node decision-making model, providing local information to the central decision-making model.

[0059] When any system in the semiconductor laboratory triggers an alarm, the emergency decision-making module 103 responds rapidly. Based on the risk assessment model and the laboratory's real-time safety data, it accurately judges the current situation and determines the target risk assessment result. At this time, the emergency decision-making module 103 performs its work separately for the single-node decision model corresponding to each system. Taking the equipment operation system as an example, based on the single-node decision model, combined with the target risk assessment result and the equipment operation system's own real-time system data, such as equipment fault codes and abnormal operating parameters, it determines the target system decision recommendation for that system, such as emergency shutdown and maintenance of the faulty equipment or switching to backup equipment.

[0060] Finally, the emergency decision-making module 103 utilizes a central decision-making model to comprehensively consider the target system decision recommendations for each system and real-time system data from all systems. Taking a holistic perspective, it weighs various factors and coordinates response measures between different systems to determine the overall target decision-making plan for the semiconductor laboratory. This plan covers multiple aspects, including personnel evacuation route planning, rescue resource allocation, external support communication, and accident handling procedures, ensuring that the laboratory can conduct emergency work in an orderly manner during a safety incident, minimizing losses and guaranteeing personnel safety and the stable operation of the laboratory.

[0061] User profiling module 104 is used to generate a safety profile for each laboratory personnel based on the laboratory data and the analysis and evaluation report, and to provide safety training to each laboratory personnel based on the safety profile. The safety profile is used to assess the comprehensive safety competence of laboratory personnel in the semiconductor laboratory.

[0062] Optionally, in this embodiment of the application, the security profile is a personalized comprehensive assessment data generated by the user profile module 104 based on the laboratory data and analysis and evaluation report of the semiconductor laboratory, which is used to comprehensively and deeply assess the overall safety quality and capabilities of the laboratory personnel in the semiconductor laboratory.

[0063] From the perspective of personnel behavior data, safety profiles record the daily operational behaviors of laboratory personnel, such as whether they strictly follow standard operating procedures (SOPs) for experiments, and whether there are any unsafe behaviors such as operating equipment improperly or not wearing protective equipment correctly. Through long-term monitoring and analysis of these behaviors, the safety awareness and skill level of personnel at the operational level are assessed. For example, if a person frequently fails to operate equipment according to prescribed procedures, their deficiencies in operating procedures will be highlighted in the safety profile.

[0064] Based on environmental data, safety profiling considers personnel's awareness and ability to respond to laboratory environmental safety issues. For example, when environmental data shows abnormal temperature and humidity or increased concentrations of harmful gases in the laboratory, the analysis examines whether the personnel can promptly detect and take appropriate countermeasures, such as timely ventilation and evacuation. This reflects the personnel's safety sensitivity and emergency response capabilities in the face of environmental changes.

[0065] Regarding equipment operation data, the safety profile focuses on personnel's ability to maintain and manage equipment. For example, whether equipment is regularly inspected and maintained, and whether the ability to quickly and accurately diagnose the cause of a malfunction and take appropriate repair measures when an alarm sounds. If a person performs exceptionally well in equipment maintenance and can promptly identify and resolve potential equipment problems, their equipment management ability will receive a higher rating in the safety profile.

[0066] By combining chemical flow data, the safety profile assesses the personnel's ability to manage and use chemicals. This includes whether information on the procurement, storage, use, and disposal of chemicals is accurately recorded, and whether safety regulations are followed during the use of chemicals, such as correct handling, proper storage, and reasonable disposal of waste chemicals. If any personnel pose a risk of leakage or improper disposal of waste chemicals during use, the safety profile will accurately record and reflect their deficiencies in chemical safety management.

[0067] In addition, the safety profile will also refer to the hazard analysis results in the analysis and assessment report to see how personnel behave when faced with potential safety hazards. For example, when the safety detection and assessment module 102 identifies a safety hazard in a certain area, it will observe whether the relevant personnel in that area can proactively discover and promptly report the hazard, and whether they actively cooperate during the hazard rectification process.

[0068] By integrating information from multiple dimensions, the safety profile provides a comprehensive assessment of the safety competence of laboratory personnel. This offers detailed and accurate data for targeted safety training, helping laboratory personnel improve their safety awareness and skills, thereby better ensuring the safe operation of the semiconductor laboratory.

[0069] Optionally, in one feasible implementation of this application, the user profiling module 104 first determines multiple evaluation indicators for the user profile based on the safety requirements of the semiconductor laboratory. These indicators cover multiple aspects such as operating procedures, emergency response capabilities, and the degree of mastery of safety knowledge, comprehensively measuring the personnel's overall safety competence in the laboratory.

[0070] Next, the data acquisition module 101 collects real-time dynamic data of personnel performing actual operations in the laboratory, such as specific actions of operating equipment and behavioral performance under different environmental conditions. Simultaneously, it acquires static data on personnel participating in semiconductor training and assessments, including participation in training courses and assessment results. This multi-dimensional data provides rich material for subsequently generating accurate safety profiles.

[0071] For each user, a score is determined for each evaluation metric based on their behavioral data. For example, if a user consistently adheres strictly to operating procedures and does not violate any rules, they will receive a high score for the "Operating Procedures" metric; similarly, if they perform exceptionally well in training and assessments, their score for the "Safety Knowledge Mastery" metric will be correspondingly high.

[0072] Subsequently, a user profile is determined for each user based on their scores under various evaluation indicators. Finally, based on the generated safety profiles, personalized safety training programs are developed for each laboratory personnel. For personnel whose safety profiles indicate weaknesses in certain areas, targeted training courses are arranged, such as operational procedure training and emergency drills, to improve their safety awareness and capabilities, thereby ensuring the overall safe operation of the semiconductor laboratory. Through this process, the user profiling module 104 can effectively function, achieving accurate assessment and improvement of the safety awareness of laboratory personnel.

[0073] In the semiconductor laboratory safety agile response management system provided in this application embodiment, the data acquisition module 101 extensively collects environmental data, personnel behavior data, equipment operation data, and chemical flow data of the semiconductor laboratory. This multi-dimensional data comprehensively reflects the complex environment and changing conditions within the laboratory, providing a foundation for accurate monitoring of the semiconductor laboratory. The safety detection and assessment module 102 works closely with the data acquisition module 101 to monitor and comprehensively evaluate the massive amounts of real-time data collected. Through in-depth analysis of multi-source data, safety events can be quickly and accurately identified, and analysis and assessment reports can be generated promptly. When a safety event occurs, the emergency decision-making module 103 responds rapidly. Based on the judgment results of the safety detection and assessment module 102 and laboratory data, a global decision-making plan is quickly generated, greatly shortening the time from problem discovery to decision-making and improving emergency response efficiency. In summary, this system, through coordinated efforts across multiple stages from data acquisition, hazard identification, emergency decision-making to personnel training, constructs a comprehensive, multi-layered safety management system, significantly improving the efficiency of safety event identification.

[0074] like Figure 2 As shown, in one embodiment, the security detection and evaluation module 102 includes a security event monitoring unit 201;

[0075] The safety incident monitoring unit 201 is communicatively connected to the data acquisition module 101 and the emergency decision-making module 103, respectively, and is used to determine whether a safety incident has occurred in the semiconductor laboratory based on the laboratory data, preset safety rules, and preset threshold ranges, and to perform at least one of the following:

[0076] In the event of a safety incident, a corresponding on-site situation analysis report is generated based on the laboratory data. The on-site situation analysis report includes the location, time, type, risk level, and global decision-making scheme corresponding to the safety incident.

[0077] In the event that a security incident is determined to have occurred, the on-site situation analysis report shall be sent to the target personnel associated with the security incident according to the target notification method, wherein the target notification method is determined based on the on-site situation analysis report.

[0078] Based on the abnormal situation input by the user, a processing work order corresponding to the abnormal situation is generated and dispatched, wherein the abnormal situation is a safety hazard discovered by the user in the semiconductor laboratory;

[0079] In the event of a security incident, respond to the user's meeting request and initiate a multi-person remote meeting.

[0080] Optionally, in this embodiment, the preset safety rules are a set of pre-defined guidelines and regulations used to standardize and define the safe operating status of the semiconductor laboratory. These rules cover various aspects of laboratory operation, such as personnel operating procedures, equipment usage requirements, chemical management regulations, and environmental safety standards. By comparing the actual operating data of the laboratory with the preset safety rules, the safety event monitoring unit 201 can determine whether there is a safety risk or whether a safety event has occurred.

[0081] The preset threshold range is a set range of normal values ​​for various laboratory data. When the actual collected data exceeds these preset threshold ranges, the safety event monitoring unit 201 will consider that there may be a safety hazard or that a safety event has occurred. For example, if the preset laboratory temperature threshold range is 20℃-25℃, when the collected temperature data is higher than 25℃ or lower than 20℃, the safety event judgment process may be triggered.

[0082] Event type is a label used to classify safety incidents, such as fire, chemical spill, equipment failure, and personnel violations. Different event types require different handling methods and emergency measures; therefore, accurately identifying the event type is fundamental to effectively responding to safety incidents.

[0083] Incident risk level is a classification of safety incidents based on factors such as severity, potential impact, and potential hazards. It is generally categorized into low-risk, medium-risk, and high-risk levels. Determining the incident risk level helps in the rational allocation of emergency resources and prioritizes high-risk incidents to minimize losses.

[0084] The target notification method, determined based on the on-site situation analysis report, refers to the specific way in which relevant information about a security incident is communicated to the target personnel associated with that incident. This may include SMS notifications, email notifications, instant messaging notifications, and voice broadcast notifications. Choosing an appropriate target notification method ensures that target personnel receive security incident information promptly and accurately, enabling a rapid response. For example, for urgent, high-risk security incidents, voice broadcast notifications and SMS notifications might be prioritized to ensure all relevant personnel are immediately informed.

[0085] Anomalies refer to situations discovered by users in the semiconductor laboratory that do not comply with preset safety rules or may pose potential safety hazards. These may include unusual noises or vibrations from equipment, minor leaks from chemical containers, or abnormal fluctuations in environmental parameters. Users can report these anomalies through the system so that timely measures can be taken to eliminate the safety hazards.

[0086] A work order is a task document generated and dispatched based on user-inputted anomalies. It is used to assign relevant personnel to handle anomalies. A work order may include a detailed description of the anomaly, its location, and the required timeframe for handling. Upon receiving a work order, relevant personnel will perform inspection, repair, or rectification operations as required, and provide feedback on the results after completion, allowing for tracking and management of the entire process.

[0087] Optionally, in one specific implementation of this application, the safety event monitoring unit 201 first acquires laboratory data by communicating with the data acquisition module 101, and determines whether a safety event has occurred based on preset safety rules and preset threshold ranges. The preset safety rules can be set according to different classification methods of safety events, such as classification based on the event's consequences, scenario, event content, and action feedback period, clearly defining the specific conditions for each type of safety event; the preset threshold range sets a reasonable range for specific indicators such as environmental data and equipment operation data, and exceeding this range may trigger a safety event judgment.

[0088] Once a safety incident is identified, a site situation analysis report is generated based on laboratory data. The location of the incident in the report can be determined using positioning devices or sensors deployed throughout the laboratory in the data acquisition module 101; the time of occurrence is obtained from the event trigger time recorded by the system; the event type is determined based on preset safety incident classification rules and specific laboratory data characteristics; the event risk level can be determined by comprehensively considering factors such as event type, scope of impact, and possible consequences, according to preset rating standards; and the global decision-making plan corresponding to the safety incident is generated by the emergency decision-making module 103 based on laboratory data and relevant contingency plans.

[0089] Regarding notification of target personnel, the system can notify different users in different ways according to different security event types, supporting methods such as telephone calls and email notifications. Security administrators can manually set the response methods, response chains, and response personnel for various security events. The notification trigger conditions support "AND" (multiple conditions must be met simultaneously to trigger a response) and "OR" (any one of multiple conditions must be met to trigger a response) logic. It can also set the conditions for automatic termination of event response, the cycle for repeated responses, and the notification personnel settings.

[0090] For user-reported anomalies, such as safety hazards discovered in the semiconductor laboratory, the system will automatically generate a work order. If relevant safety inspectors discover discrepancies with safety regulations or safety hazards, they will promptly report them to the system. The system will automatically categorize the incidents based on type, location, and other information, and push the information to relevant management personnel. After approval by management, the work order will be assigned to the appropriate personnel. The incident handling process and results are traceable, and the system also features statistical and filtering query functions.

[0091] When a security incident is detected and a user requests a meeting, the system supports initiating a multi-person remote meeting using devices such as the second-generation HoloLens 2 mixed reality glasses. Multiple people can share the interface for operation guidance, conversation, and annotation, so that relevant personnel can communicate and coordinate to handle security incidents in a timely manner.

[0092] In these optional embodiments, comprehensive safety monitoring of the semiconductor laboratory is achieved through the safety event monitoring unit 201. The safety event monitoring unit 201 can accurately identify safety events based on preset rules and thresholds, and promptly generate on-site situation analysis reports containing key information, facilitating rapid decision-making and response. Based on the report, the target notification method can be determined, allowing for precise notification of relevant personnel and improving response efficiency. Processing work orders are generated for user-input anomalies, facilitating timely handling of safety hazards. Furthermore, in the event of a safety incident, it can respond to meeting requests and initiate remote meetings, facilitating multi-party communication and collaboration to jointly discuss solutions. Overall, this effectively improves the laboratory's safety management level, ensures the safety of personnel and equipment, and reduces losses caused by safety accidents.

[0093] like Figure 2 As shown, in one embodiment, the safety detection and assessment module 102 includes a hazard identification unit 202;

[0094] The hazard identification unit 202 is used to perform linked analysis on the environmental data, personnel behavior data, equipment operation data, and chemical flow data of the semiconductor laboratory based on a pre-built hazard identification model to determine whether there are any safety hazards in the semiconductor laboratory; and if a safety hazard is identified in the semiconductor laboratory, pre-processing suggestions are generated based on the hazard information of the safety hazard.

[0095] In these optional embodiments, the hazard identification unit 202 and the pre-built hazard identification model are used to perform linked analysis of multi-dimensional data from the semiconductor laboratory, enabling a comprehensive and accurate determination of the existence of safety hazards. Upon identification of a hazard, timely pre-treatment suggestions can be generated, helping laboratory personnel to take measures before the hazard develops into a safety incident, thus eliminating potential risks in advance. This not only effectively enhances the laboratory's safety prevention capabilities and reduces the likelihood of safety accidents, but also reduces the losses caused by accidents, ensuring the normal operation of laboratory equipment and the safety of personnel, creating a safer and more stable operating environment for the semiconductor laboratory.

[0096] In one embodiment, the semiconductor laboratory includes multiple systems;

[0097] The hazard identification unit 202 is also used to combine and analyze the safety events of different systems, summarize and merge the related safety events of different systems to form a combined safety event as safety data; in the event that the first event occurs in the semiconductor laboratory, a hazard analysis report is generated, the hazard analysis report includes at least one second event generated in conjunction with the first event, and the first event is any safety event in the safety data.

[0098] Optionally, in the embodiments of this application, the hazard information refers to the specific information related to the safety hazard after it has been identified, such as the type of hazard, its severity, and its possible impact.

[0099] Pre-treatment recommendations are generated based on hazard information about safety hazards and provide preliminary treatment opinions and measures to eliminate or mitigate safety hazards.

[0100] Security events from different systems are combined and analyzed in a coordinated manner. A new set of security events is formed by summarizing and merging related security events, which serves as security data.

[0101] The hazard analysis report includes at least one second event that is linked to the first event, used to analyze the relevant circumstances of the safety hazard.

[0102] The second event is related to the first event. It is another safety event associated with the first event, which is analyzed by the hazard identification unit 202 in the event of the first event and is included in the hazard analysis report.

[0103] Optionally, in one specific implementation of this application, the hazard identification unit 202 first constructs a hazard identification model. This involves collecting a large amount of past environmental data from the semiconductor laboratory, personnel behavior data, equipment operation data, and chemical flow data. Machine learning algorithms, deep learning algorithms, and other methods are used to train this multi-source data, enabling the model to learn the characteristic patterns of data under normal and hazard-prone conditions, thereby constructing an effective model for hazard identification.

[0104] Next, the laboratory's real-time data is analyzed in conjunction with the pre-built hazard identification model. The hazard identification unit 202 continuously acquires the latest environmental, personnel behavior, equipment operation, and chemical flow data from the data acquisition module 101. The model comprehensively considers this data. For example, if the ambient temperature exceeds the suitable range, the heat dissipation system data of the equipment shows abnormalities, and personnel are not operating the equipment according to the prescribed procedures, the model's calculations and judgments determine whether there are safety hazards in the semiconductor laboratory.

[0105] Once a safety hazard is identified, the hazard identification unit 202 generates pre-treatment recommendations based on the hazard information. For example, if the hazard is due to equipment aging causing operational instability and potentially leading to overheating, the pre-treatment recommendations might include immediately stopping the equipment, arranging for professional personnel to inspect the equipment, and assessing whether the equipment needs to be replaced. These recommendations are generated based on information such as the type, severity, and potential impact of the hazard.

[0106] In handling safety incidents from different systems, the hazard identification unit 202 combines and analyzes safety incidents from different systems in a coordinated manner. For example, it can summarize and merge process equipment safety incidents, plant equipment safety incidents, and personnel behavior safety incidents. For instance, abnormal power supply in the plant system, operational malfunctions in process equipment due to voltage instability, and incorrect operational behaviors of personnel during equipment malfunctions—when these events are related, the hazard identification unit 202 merges them into a single combined safety event and stores it as safety data.

[0107] When the first incident occurs in the semiconductor laboratory, the hazard identification unit 202 generates a hazard analysis report based on the retained safety data and established event correlations. For example, if the first incident is a leak in a valve in the plant equipment, analysis of past combined safety event data reveals that this valve leak typically leads to malfunctions in nearby process equipment due to liquid corrosion. This process equipment malfunction is then considered the second incident and is included in the hazard analysis report. This provides laboratory managers with a comprehensive and forward-looking safety hazard analysis, enabling timely measures to prevent more serious safety accidents.

[0108] In these optional embodiments, the hazard identification unit 202 can analyze the combined and interconnected safety events of different systems in the semiconductor laboratory to uncover potential correlations between events. Summarizing and merging related safety events into combined safety events provides more comprehensive data support for subsequent analysis. Generating a hazard analysis report that includes a linked second event when the first event occurs allows laboratory personnel to anticipate other potential safety events and effectively prevent the escalation of safety incidents. This greatly improves the comprehensiveness and foresight of safety hazard investigation, helps to take timely measures, reduces the probability of accidents, and ensures the normal operation of laboratory equipment and the safety of personnel.

[0109] like Figure 2 As shown, in one embodiment, the security detection and evaluation module 102 includes a security operation scoring unit 203;

[0110] The safety operation scoring unit 203 is used to quantitatively evaluate the laboratory data, the on-site situation analysis report, and the hidden danger analysis report according to a preset multi-dimensional evaluation index system, and obtain the first score value corresponding to each dimension index; and determine the safety operation status score of the semiconductor laboratory according to the first score value corresponding to each dimension index.

[0111] Specifically, in the event of a safety incident in the semiconductor experiment, the safety operation status score of the semiconductor laboratory is updated.

[0112] In these optional embodiments, the safety operation scoring unit 203 utilizes a preset multi-dimensional evaluation index system to comprehensively and quantitatively analyze laboratory data, on-site conditions, and hazard analysis reports, making the assessment more scientific and objective. By deriving the first score under each dimension's index, the safety operation status score is determined, providing an intuitive and quantitative representation of the laboratory's safety status. Timely updates to the score in the event of a safety incident allow management personnel to immediately grasp changes in the laboratory's safety level, enabling rapid adjustments to safety management strategies, targeted strengthening of weak points, effective prevention of subsequent safety incidents, and ensuring the safe and stable operation of the semiconductor laboratory.

[0113] In one embodiment, the semiconductor laboratory includes multiple systems;

[0114] The laboratory data, the on-site situation analysis report, and the hazard analysis report are quantitatively evaluated according to a preset multi-dimensional evaluation index system to obtain a first score value for each dimension, including:

[0115] Based on a pre-defined multi-dimensional evaluation index system, the laboratory data, on-site situation analysis report, and hazard analysis report corresponding to the first system are quantitatively evaluated to obtain the first score value of the first system under each dimension index; the first system is any one of the multiple systems.

[0116] The step of determining the safety operation status score of the semiconductor laboratory based on the first score value corresponding to each dimension includes:

[0117] Based on the first score value corresponding to each dimension indicator of the first system, the safety operation status score of the first system is determined;

[0118] The safety operation status score of the semiconductor laboratory is determined based on the safety operation status score corresponding to each system.

[0119] Optionally, in this embodiment, the multi-dimensional evaluation index system is a pre-defined standard system used to comprehensively evaluate the safe operation status of a semiconductor laboratory. It covers multiple dimensions and considers laboratory data, on-site situation analysis reports, and hazard analysis reports from different perspectives.

[0120] For each system (such as the plant management system, large instrument management system, etc.), there are also corresponding indicators, such as the power supply stability and ventilation system operation status of the plant management system. By quantitatively evaluating these multi-dimensional indicators, the first score corresponding to each dimension indicator is obtained, and then the overall safety operation status score of the system and the entire semiconductor laboratory is determined to comprehensively and accurately reflect the safety operation of the laboratory.

[0121] Optionally, in one specific implementation of this application, the safety operation scoring unit 203 first sets indicators from multiple perspectives in terms of constructing a multi-dimensional evaluation index system, taking into account the characteristics of a semiconductor laboratory. For example, a semiconductor laboratory involves different systems such as fire protection, plant management, process control, and laboratory operations, as well as the number of alarms and their handling. Simultaneously, based on actual conditions, dimensions such as personnel operating procedures, equipment operating parameters, and chemical management can be considered to provide a comprehensive measurement standard for subsequent evaluation.

[0122] Next, data evaluation is conducted for each system. The safety operation scoring unit 203 collects laboratory data, on-site situation analysis reports, and hazard analysis reports for each system (e.g., the first system) according to a pre-set multi-dimensional evaluation index system. Taking the fire protection system as an example, data such as the number of alarms and the timely handling rate for the month are obtained. Then, a quantitative evaluation is performed according to the specific rules in the index system, such as an upper limit of 10 and a lower limit of 0 for the number of alarms, with an upper limit score of 0 and a lower limit score of 100, thereby deriving the first score value for each system under each dimension index.

[0123] Subsequently, the safety operation status score of each individual system is determined. Based on the first score corresponding to each dimension, the safety operation status score of the system is calculated according to a certain calculation method, such as weighted average. For example, assuming that the number of alarms in a fire protection system accounts for 25% and the alarm timely handling rate accounts for 15%, if the number of alarms is 5 (corresponding to a score of 25% * 50%) and the timely handling rate is 80% (corresponding to a score of 15% * 80%), then the overall score of the fire protection system is 24.5%.

[0124] Finally, the overall safety operation status score of the semiconductor laboratory is determined. The safety operation status scores of each system are summed and calculated according to the pre-set weights of each system (e.g., fire protection system accounts for 40%, plant management system accounts for 15%), to obtain the overall safety operation status score of the laboratory.

[0125] In the event of a safety incident in the laboratory, the safety operation scoring unit 203 will promptly update the scores of each system and the overall system to reflect the latest safety status. Simultaneously, it will periodically generate safety health reports, covering the safety health status of each system and the overall safety operation status score of the semiconductor laboratory. These reports can be queried periodically as needed and sent to relevant personnel to assist in safety management decisions.

[0126] In these optional embodiments, the multi-dimensional evaluation index system can comprehensively and meticulously consider all aspects of the laboratory. Based on this, the data and reports of each system can be quantitatively evaluated, accurately reflecting the safety status of each system in different dimensions. Determining the safety operation status score of each system allows managers to clearly understand the strengths and weaknesses of each system and to strengthen the management of weak links in a targeted manner. Finally, the overall score of the laboratory is obtained by combining the scores of each system, which can intuitively present the overall safety level of the laboratory. In the event of a safety incident, the score can be updated in a timely manner, facilitating timely adjustments to management strategies and improving the safety and management efficiency of the laboratory.

[0127] like Figure 3 As shown, in one embodiment, the system further includes:

[0128] The operation interface display module 105 is used to construct and display a virtual scene of the semiconductor laboratory based on the real scene information of the semiconductor laboratory, and to perform at least one of the following:

[0129] Based on the on-site situation analysis report, the location of the safety incident is displayed in the virtual scene, or the experimental equipment associated with the safety incident is marked.

[0130] The on-site situation analysis report shows a detailed record of security incidents that have occurred in the history of each system in the semiconductor laboratory.

[0131] The real-time safety operation status score of the semiconductor laboratory is displayed according to a preset display style, which is determined based on the scoring threshold range of the real-time safety operation status score of the semiconductor laboratory.

[0132] Optionally, in this embodiment, the real-world scenario information refers to the actual situation of the semiconductor laboratory in reality, including the laboratory's layout and structure, such as the location and size of each room and passageway; the specific types and placement of experimental equipment; the storage areas for chemicals; and the activity range of personnel. This information forms the basis for constructing the virtual scenario.

[0133] The virtual scene is a digital simulation scene constructed by the user interface display module 105 using computer technology based on real-world information from the semiconductor laboratory. It can intuitively present the overall layout and internal facilities of the laboratory on the screen, allowing users to view various parts of the laboratory as if they were actually there.

[0134] The incident details are a comprehensive record of historical safety incidents for each system in the semiconductor laboratory, based on on-site situation analysis reports. They include specific details such as the time and location of the incident, the type of incident, the risk level of the incident, and the handling results, which helps to gain a deeper understanding of the history and development trends of laboratory safety incidents.

[0135] The preset display style is a display method pre-set according to different rating threshold ranges of the real-time safety operation status of the semiconductor laboratory. For example, when the rating is in the high safety range, it may be displayed in green, with large font and bright display effect; when the rating is in the low safety range, it may be displayed in red, flashing, bold font, etc., so that users can quickly and intuitively understand the safety status of the laboratory.

[0136] Optionally, the user interface display module 105 first constructs a virtual scene based on the real-world information of the semiconductor laboratory. Using modeling technology, the actual layout, equipment placement, and corridor routing of the laboratory are digitally recreated to create a virtual scene highly consistent with the real laboratory, achieving 3D full-scene twin consistency with the actual site. During the construction process, images and surveying data collected on-site can also be integrated to ensure the accuracy and realism of the virtual scene.

[0137] Next, the relevant information about the safety incident is displayed in the virtual scene. When the on-site situation analysis report indicates that a safety incident has occurred, the operation interface display module 105 will accurately locate the location of the safety incident in the virtual scene based on the location information in the report, and will also mark the experimental equipment associated with the safety incident. At the same time, based on the on-site situation analysis report, it will also display detailed information about historical safety incidents in each system of the semiconductor laboratory, such as the time, type, and handling results of the incidents, to facilitate managers' comprehensive understanding of the laboratory's history of safety incidents.

[0138] Finally, the real-time safety operation status score is displayed. The operation interface display module 105 acquires the real-time safety operation status score of the semiconductor laboratory and displays it in a specific form according to the pre-set display style rules, i.e., according to the different threshold ranges of the score. For example, when the score is high and within the threshold range of good safety status, it can be displayed in the form of a green, simple icon; when the score is low and within the threshold range of high safety risk, it can be displayed in the form of a red, flashing warning icon. At the same time, it will also combine plant system data, cleanroom key safety data, etc., to visualize the data in the form of 3D real scene correlation data, which is convenient for managers to perform safety monitoring, safety management, and task assignment. In addition, when a safety incident occurs, managers can also call the network video recorder (NVR) of the laboratory management system to obtain relevant camera images, intuitively view the on-site situation, and achieve agile safety response.

[0139] In these optional embodiments, by constructing and displaying virtual scenes, the actual situation of the laboratory is intuitively presented, allowing users to understand the layout. Displaying the location of safety incidents and related equipment in the virtual scene helps to quickly locate problems and take timely measures. Displaying historical safety incident details for each system allows managers to grasp the full picture of events, summarize lessons learned, and prevent similar incidents in advance. Displaying real-time safety operation status scores according to preset styles gives users a clear understanding of the laboratory's safety status. Changes in scores can quickly detect potential risks, thereby rationally allocating resources, strengthening safety management, and improving the safety and management efficiency of the semiconductor laboratory.

[0140] like Figure 3 As shown, in one embodiment, the system further includes a chemical monitoring module 106;

[0141] The chemical monitoring module 106 is used to perform at least one of the following:

[0142] Based on the chemical flow data, the flow of chemicals in the semiconductor laboratory is tracked and recorded in real time;

[0143] In the event of an abnormal event in the flow of the target chemical, an early warning message is generated and sent to the target personnel corresponding to the target chemical.

[0144] Optionally, in this embodiment, the flow of chemicals refers to the entire process and related status information of chemicals moving from one location to another and from one stage to another within the semiconductor laboratory. Specifically, this includes the time of entry and exit from storage, changes in storage location, the time and personnel involved in application and use, transfers between different experimental areas, and routes and time points during transportation.

[0145] The warning information includes a detailed description of the abnormal event and detailed information about the target chemicals involved.

[0146] Optionally, in one specific implementation of this application, the data acquisition module 101 collects user applications for chemical warehousing or requisition submitted in the system. Throughout the entire chemical circulation process, real-time data such as the location, movement time, and personnel involved in the handling of chemicals are acquired through sensors, barcode scanning devices deployed at key locations such as warehouses and experimental areas, as well as data acquisition interfaces integrated with transportation equipment. For example, in the chemical warehousing stage, staff scan barcodes to register chemical information, and the data acquisition module 101 records the warehousing time, storage location, etc.; in the requisition stage, information such as the applicant, requisition time, and destination is recorded.

[0147] Next, the chemical monitoring module 106 tracks and records the flow of chemicals in the semiconductor laboratory in real time based on the collected chemical flow data. Specifically, a dynamic database can be built to accurately record every change in the flow status of chemicals, forming a complete flow trajectory for easy querying and tracing at any time.

[0148] When monitoring for abnormal events, the chemical monitoring module 106 continuously analyzes chemical flow data, such as determining if there are instances of chemical transfers without any chemical in / out application records. It also sets other anomaly detection rules, such as chemicals remaining at a location for excessively long periods exceeding normal operating times, or chemical transport routes deviating from preset routes. Once the flow of a target chemical triggers these abnormal event rules, the chemical monitoring module 106 immediately generates an alert.

[0149] Finally, in the early warning information sending phase, the chemical monitoring module 106 pre-sets a list of target personnel corresponding to various chemicals, which may include chemical managers, relevant experimental project leaders, etc. Once an early warning information is generated, the chemical monitoring module 106 will quickly send the information to the corresponding target personnel, notifying them of any abnormalities in chemical flow, so that timely measures can be taken to address the issue, such as verifying the situation, correcting violations, and preventing chemical loss or misuse, thereby ensuring the safety and standardization of chemical use in the semiconductor laboratory.

[0150] In these optional embodiments, the chemical monitoring module 106, by tracking and recording the flow of chemicals in real time, allows the laboratory to have a clear understanding of the status of chemicals, facilitating the rational allocation of resources. In the event of an anomaly, it immediately generates and sends an alert to the target personnel, enabling timely detection of violations or potential risks, such as theft or misuse of chemicals. This effectively prevents safety accidents, ensures the safety of laboratory personnel and the normal conduct of experiments, and improves the safety and standardization of chemical management in semiconductor laboratories.

[0151] like Figures 3-4 As shown, in one embodiment, the system further includes a safety training module 107 for providing safety operation training to the experimental equipment in the semiconductor laboratory;

[0152] The safety training module 107 includes:

[0153] The teaching equipment library 401 stores the appearance modeling models of various experimental equipment, as well as the corresponding safety operation animations for each experimental equipment.

[0154] Teaching content unit 402 is used to display the teaching content of the corresponding experimental equipment in accordance with the user's teaching requirements;

[0155] The virtual operation unit 403 is used to perform virtual simulation operations on the experimental equipment.

[0156] Optionally, in this embodiment, the appearance modeling model is a virtual model that digitally models the experimental equipment, accurately presenting its visual features such as shape, size, color, and structure. It allows users to intuitively understand the appearance of the experimental equipment during training, facilitating rapid equipment identification in actual operation.

[0157] The safety operation animation demonstrates the correct operating procedures and safety precautions for experimental equipment in animated form. Through dynamic demonstrations, complex operating processes are broken down into clear steps, making them easier for users to understand and master, while emphasizing key operating points and potential safety risks.

[0158] The teaching content is a collection of knowledge related to experimental equipment, including information such as the equipment's working principles, performance parameters, operating procedures, maintenance methods, and safety regulations. It can be presented in various formats, including text, images, and charts, providing users with comprehensive theoretical support.

[0159] Virtual simulation operation utilizes computer technology to simulate the operation of experimental equipment. Users can operate the equipment in a virtual environment, such as clicking, dragging, and setting parameters. The virtual operation unit 403 will provide corresponding feedback based on the user's actions, just as if operating the equipment in a real environment. This helps users familiarize themselves with the operating procedures before practice and reduces the risks of actual operation.

[0160] Optionally, in one specific implementation of this application, the implementation of the safety training module 107 needs to start from several key aspects.

[0161] The first step was building the teaching equipment library 401. Suppliers created modeling models of various experimental equipment provided by the purchaser, including cleanroom dicing machines, chemical mechanical polishing machines, vacuum interconnected physical vapor deposition (VPV) equipment, spin coaters, developers, bonding machines, coating and developing machines, WLP8 laser direct-write lithography machines, stepper lithography machines, electron beam lithography machines, wet stage, high-temperature oxidation furnace, ion beam etching machines, molecular epitaxial deposition (MED) equipment, and atomic layer deposition (ALD) equipment. These models were optimized according to technical requirements. The accuracy of the equipment's appearance and external structure was ensured to be at least 95%. Modeling was not required for equipment with a volume smaller than 0.5 cubic centimeters and not intended for virtual animation demonstration. Simultaneously, corresponding safety operation animations were created based on the safety operating procedures and characteristics of each experimental device. For example, for VPV equipment, the animation clearly showed the pre-start inspection steps, gas introduction sequence, parameter adjustments during deposition, and the correct shutdown procedure, allowing users to intuitively understand the standardized operating procedures.

[0162] Next is the operation of teaching content unit 402. When a user submits a teaching request, teaching content unit 402 can utilize the virtual scene of the laboratory's 3D large-screen cleanroom to retrieve the corresponding teaching content for the experimental equipment based on the user's needs. It can not only display the specific location of the experimental equipment in the virtual scene, providing one-click guidance to the equipment, but also present the equipment's safe operating procedures, safety signs, hazard displays, and related videos and PPT presentations. For example, if a user selects a spin coater for instruction, teaching content unit 402 will highlight the spin coater's location in the virtual scene and display its operating procedures in a PPT presentation and demonstration video, while also prominently displaying safety signs and potentially hazardous areas (such as high-speed rotating parts) on the equipment.

[0163] Finally, the implementation of the virtual operation unit 403. With the support of devices such as HoloLens2, users can perform virtual simulation operations on the experimental equipment. For example, they can simulate the operation of the equipment software, from opening the software and inputting parameters to starting the program. The virtual operation unit 403 will provide real-time feedback based on the user's actions, just as if operating on a real device. If the user makes a mistake during operation, the virtual operation unit 403 can promptly remind and correct it, helping the user accumulate operating experience in the virtual environment and reducing the safety risks caused by unfamiliarity when operating on actual equipment. This comprehensively improves the user's safe operation skills for semiconductor laboratory experimental equipment.

[0164] In these optional embodiments, the teaching equipment library 401 stores appearance modeling models and safe operation animations, allowing trainees to intuitively understand the appearance of the equipment and master safe operation procedures through dynamic demonstrations, reducing the learning difficulty. The teaching content unit 402 can accurately display teaching content according to user needs, providing comprehensive theoretical knowledge to meet personalized learning requirements. The virtual operation unit 403 allows trainees to perform simulated operations in a virtual environment, enabling repeated practice, familiarization with operating procedures, and accumulation of practical experience, while avoiding equipment damage or personal injury due to operational errors. Overall, this safety training module 107 effectively improves trainees' ability to operate experimental equipment safely, enhancing laboratory safety and management efficiency.

[0165] Figure 5 A flowchart illustrating a semiconductor laboratory safety agile response management method according to another embodiment of this application is shown. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0166] Reference Figure 5 A semiconductor laboratory safety agile response management approach may include:

[0167] S501, the data acquisition module collects laboratory data of the semiconductor laboratory, the laboratory data including at least one of the following: environmental data, personnel behavior data, equipment operation data, and chemical flow data of the semiconductor laboratory;

[0168] S502, The laboratory data is monitored and comprehensively evaluated in real time through the safety detection and evaluation module to determine the analysis and evaluation report of the semiconductor laboratory. The analysis and evaluation report includes at least one of the following: the on-site situation analysis report of the semiconductor laboratory, the hidden danger analysis report of the semiconductor laboratory, and the safety operation status score of the semiconductor laboratory.

[0169] S503, if the safety detection and evaluation module determines that a safety incident has occurred in the semiconductor laboratory, the emergency decision-making module generates a global decision-making plan for the semiconductor laboratory based on the laboratory data;

[0170] S504, the user profiling module generates a safety profile for each laboratory personnel based on the laboratory data and the analysis and evaluation report, and conducts safety training for each laboratory personnel based on the safety profile. The safety profile is used to assess the comprehensive safety competence of laboratory personnel in the semiconductor laboratory.

[0171] Figure 6 A schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application is shown.

[0172] The device may include a processor 601 and a memory 602 storing program instructions.

[0173] When the processor 601 executes the program, it implements the steps in any of the above method embodiments.

[0174] For example, the program can be divided into one or more modules / units, one or more of which are stored in memory 602 and executed by processor 601 to complete this application. The one or more modules / units can be a series of program instruction segments capable of performing a specific function, which describe the execution process of the program in the device.

[0175] Specifically, the processor 601 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0176] Memory 602 may include mass storage for data or instructions. For example, and not limitingly, memory 602 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 602 may include removable or non-removable (or fixed) media. Where appropriate, memory 602 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 602 is non-volatile solid-state memory.

[0177] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the methods according to one aspect of this disclosure.

[0178] The processor 601 implements any of the methods described in the above embodiments by reading and executing program instructions stored in the memory 602.

[0179] In one example, the electronic device may also include a communication interface 603 and a bus 610. The processor 601, memory 602, and communication interface 603 are connected via the bus 610 and communicate with each other.

[0180] The communication interface 603 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0181] Bus 610 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 610 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0182] Furthermore, in conjunction with the methods in the above embodiments, this application embodiment can provide a storage medium for implementation. This storage medium stores program instructions; when these program instructions are executed by a processor, they implement any of the methods in the above embodiments.

[0183] This application also provides a chip, which includes a processor and a communication interface. The communication interface and the processor are coupled. The processor is used to run programs or instructions to implement the various processes of the above method embodiments and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0184] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0185] This application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the above method embodiments and achieve the same technical effects. To avoid repetition, it will not be described again here.

[0186] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0187] The functional modules shown in the above block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on machine-readable media or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable media" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer grids such as the Internet, intranets, etc.

[0188] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0189] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to create a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0190] The above are merely specific embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A semiconductor laboratory safety and agile response management system, characterized in that, The system includes: The data acquisition module is used to collect laboratory data from the semiconductor laboratory, including at least one of the following: environmental data, personnel behavior data, equipment operation data, and chemical flow data of the semiconductor laboratory. The safety detection and evaluation module is communicatively connected to the data acquisition module and is used to monitor and comprehensively evaluate the laboratory data in real time, and determine the analysis and evaluation report of the semiconductor laboratory. The analysis and evaluation report includes at least one of the following: the on-site situation analysis report of the semiconductor laboratory, the hidden danger analysis report of the semiconductor laboratory, and the safety operation status score of the semiconductor laboratory. An emergency decision-making module is used to generate a global decision-making plan for the semiconductor laboratory based on the laboratory data when the safety detection and assessment module determines that a safety incident has occurred in the semiconductor laboratory. The user profiling module is used to generate a safety profile for each laboratory personnel based on the laboratory data and the analysis and evaluation report, and to provide safety training to each laboratory personnel based on the safety profile. The safety profile is used to evaluate the comprehensive safety competence of laboratory personnel in the semiconductor laboratory. The emergency decision-making module is also used for: An accident decision model is obtained; the accident decision model includes a single-node decision model and a central decision model. The single-node decision model is used to output single-system decision suggestions in the event of a safety accident in any system of the semiconductor laboratory. The central decision model is used to determine the global decision scheme of the semiconductor laboratory. One single-node decision model corresponds to one system of the semiconductor laboratory. If any system in the semiconductor laboratory triggers an alarm, the target risk assessment result of the semiconductor laboratory is determined based on the risk assessment model and the real-time safety data of the semiconductor laboratory. For each system's corresponding single-node decision model, the following steps are performed: Based on the single-node decision model, and according to the target risk assessment results and the real-time system data of the system corresponding to the single-node decision model, determine the target system decision recommendations for the system corresponding to the single-node decision model. Based on the central decision-making model, the target global decision-making scheme of the semiconductor laboratory is determined according to the target system decision-making suggestions corresponding to each system and the real-time system data of all systems. The user profiling module is also used for: Based on the safety requirements of the semiconductor laboratory, multiple evaluation indicators for user profiles are determined; these multiple evaluation indicators cover operational procedures, emergency response capabilities, and the degree of mastery of safety knowledge. For each user, acquire real-time dynamic data of the user's actual operation in the semiconductor laboratory and static data of the user's semiconductor training and assessment; Based on the user's real-time dynamic data and static data, determine the user's indicator score under each evaluation indicator; Based on the user's scores under each evaluation metric, a user profile is determined. The safety detection and assessment module includes a hazard identification unit; The hazard identification unit is used to perform linked analysis on environmental data, personnel behavior data, equipment operation data, and chemical flow data of the semiconductor laboratory based on a pre-built hazard identification model to determine whether there are any safety hazards in the semiconductor laboratory; and if a safety hazard is identified in the semiconductor laboratory, it generates pre-processing suggestions based on the hazard information of the safety hazard. The semiconductor laboratory includes multiple systems; The hazard identification unit is also used to combine and analyze safety events from different systems, summarize and merge related safety events from different systems to form combined safety events as safety data; in the event of a first event in the semiconductor laboratory, a hazard analysis report is generated, which includes at least one second event generated in conjunction with the first event, wherein the first event is any one of the safety events in the safety data.

2. The system according to claim 1, characterized in that, The security detection and assessment module includes a security incident monitoring unit; The safety incident monitoring unit is communicatively connected to both the data acquisition module and the emergency decision-making module. Based on the laboratory data, preset safety rules, and preset threshold ranges, it determines whether a safety incident has occurred in the semiconductor laboratory and performs at least one of the following actions: In the event of a safety incident, a corresponding on-site situation analysis report is generated based on the laboratory data. The on-site situation analysis report includes the location, time, type, risk level, and global decision-making scheme corresponding to the safety incident. In the event that a security incident is determined to have occurred, the on-site situation analysis report shall be sent to the target personnel associated with the security incident according to the target notification method, wherein the target notification method is determined based on the on-site situation analysis report. Based on the abnormal situation input by the user, a processing work order corresponding to the abnormal situation is generated and dispatched, wherein the abnormal situation is a safety hazard discovered by the user in the semiconductor laboratory; In the event of a security incident, respond to the user's meeting request and initiate a multi-person remote meeting.

3. The system according to claim 1, characterized in that, The safety detection and evaluation module includes a safety operation scoring unit; The safety operation scoring unit is used to quantitatively evaluate the laboratory data, the on-site situation analysis report, and the hidden danger analysis report according to a preset multi-dimensional evaluation index system, and obtain the first score value corresponding to each dimension index; and determine the safety operation status score of the semiconductor laboratory based on the first score value corresponding to each dimension index. Specifically, in the event of a safety incident in the semiconductor experiment, the safety operation status score of the semiconductor laboratory is updated.

4. The system according to claim 3, characterized in that, The semiconductor laboratory includes multiple systems; The process involves quantitatively evaluating the laboratory data, the on-site situation analysis report, and the hazard analysis report based on a pre-defined multi-dimensional evaluation index system, obtaining a first score for each dimension index, including: Based on a pre-defined multi-dimensional evaluation index system, the laboratory data, on-site situation analysis report, and hazard analysis report corresponding to the first system are quantitatively evaluated to obtain the first score value of the first system under each dimension index; the first system is any one of the multiple systems. The step of determining the safety operation status score of the semiconductor laboratory based on the first score value corresponding to each dimension indicator includes: Based on the first score value corresponding to each dimension indicator of the first system, the safety operation status score of the first system is determined; The safety operation status score of the semiconductor laboratory is determined based on the safety operation status score corresponding to each system.

5. The system according to claim 1, characterized in that, The system also includes: The user interface display module is used to construct and display a virtual scene of the semiconductor laboratory based on the real scene information of the semiconductor laboratory, and to perform at least one of the following: Based on the on-site situation analysis report, the location of the safety incident is displayed in the virtual scene, or the experimental equipment associated with the safety incident is marked. The on-site situation analysis report shows a detailed record of security incidents that have occurred in the history of each system in the semiconductor laboratory. The real-time safety operation status score of the semiconductor laboratory is displayed according to a preset display style, which is determined based on the scoring threshold range of the real-time safety operation status score of the semiconductor laboratory.

6. The system according to claim 1, characterized in that, The system also includes a chemical monitoring module; The chemical monitoring module is used to perform at least one of the following: Based on the chemical flow data, the flow of chemicals in the semiconductor laboratory is tracked and recorded in real time; In the event of an abnormal event in the flow of the target chemical, an early warning message is generated and sent to the target personnel corresponding to the target chemical.

7. The system according to claim 1, characterized in that, The system also includes a safety training module for providing safety operation training for the experimental equipment in the semiconductor laboratory; The safety training module includes: The teaching equipment library stores the appearance models of various experimental equipment, as well as the corresponding safety operation animations for each experimental equipment; The teaching content unit is used to display the teaching content of the corresponding experimental equipment according to the user's teaching requirements; The virtual operation unit is used to perform virtual simulation operations on experimental equipment.

8. A method for agile response management of semiconductor laboratory safety, characterized in that, Applied to the semiconductor laboratory safety agile response management system as described in any one of claims 1-7, the method comprises: The semiconductor laboratory collects laboratory data through a data acquisition module. The laboratory data includes at least one of the following: environmental data, personnel behavior data, equipment operation data, and chemical flow data of the semiconductor laboratory. The laboratory data is monitored and comprehensively evaluated in real time by the safety detection and evaluation module to determine the analysis and evaluation report of the semiconductor laboratory. The analysis and evaluation report includes at least one of the following: the on-site situation analysis report of the semiconductor laboratory, the hidden danger analysis report of the semiconductor laboratory, and the safety operation status score of the semiconductor laboratory. If the safety detection and assessment module determines that a safety incident has occurred in the semiconductor laboratory, the emergency decision-making module generates a global decision-making plan for the semiconductor laboratory based on the laboratory data. The user profiling module generates a safety profile for each laboratory personnel based on the laboratory data and the analysis and evaluation report. Safety training is then conducted for each laboratory personnel based on the safety profile. The safety profile is used to assess the comprehensive safety competence of laboratory personnel in the semiconductor laboratory. The emergency decision-making module is also used for: An accident decision model is obtained; the accident decision model includes a single-node decision model and a central decision model. The single-node decision model is used to output single-system decision suggestions in the event of a safety accident in any system of the semiconductor laboratory. The central decision model is used to determine the global decision scheme of the semiconductor laboratory. One single-node decision model corresponds to one system of the semiconductor laboratory. If any system in the semiconductor laboratory triggers an alarm, the target risk assessment result of the semiconductor laboratory is determined based on the risk assessment model and the real-time safety data of the semiconductor laboratory. For each system's corresponding single-node decision model, the following steps are performed: Based on the single-node decision model, and according to the target risk assessment results and the real-time system data of the system corresponding to the single-node decision model, determine the target system decision recommendations for the system corresponding to the single-node decision model. Based on the central decision-making model, the target global decision-making scheme of the semiconductor laboratory is determined according to the target system decision-making suggestions corresponding to each system and the real-time system data of all systems. The user profiling module is also used for: Based on the safety requirements of the semiconductor laboratory, multiple evaluation indicators for user profiles are determined; these multiple evaluation indicators cover operational procedures, emergency response capabilities, and the degree of mastery of safety knowledge. For each user, acquire real-time dynamic data of the user's actual operation in the semiconductor laboratory and static data of the user's semiconductor training and assessment; Based on the user's real-time dynamic data and static data, determine the user's indicator score under each evaluation indicator; Based on the user's scores under each evaluation metric, a user profile is determined. The safety detection and assessment module includes a hazard identification unit; The hazard identification unit is used to perform linked analysis on environmental data, personnel behavior data, equipment operation data, and chemical flow data of the semiconductor laboratory based on a pre-built hazard identification model to determine whether there are any safety hazards in the semiconductor laboratory; and if a safety hazard is identified in the semiconductor laboratory, it generates pre-processing suggestions based on the hazard information of the safety hazard. The semiconductor laboratory includes multiple systems; The hazard identification unit is also used to combine and analyze safety events from different systems, summarize and merge related safety events from different systems to form combined safety events as safety data; in the event of a first event in the semiconductor laboratory, a hazard analysis report is generated, which includes at least one second event generated in conjunction with the first event, wherein the first event is any one of the safety events in the safety data.

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