Intelligent guarding system for large-scale micro-nano processing laboratory equipment

Abstract

The invention provides an intelligent guard system for large-scale micro-nano processing laboratory equipment, and the system comprises a data collection module, a risk early warning module, a fault positioning module and an operation and maintenance management module, the fault is traced by using the collected real-time environment data, real-time state data, experimental data, real-time behavior data and identity information, so that the details of the fault can be known in time, and fault maintenance, responsibility investigation and the like can be carried out; the operation and maintenance management module can carry out multi-dimensional operation and maintenance management on the laboratory according to the collected real-time environment data, real-time state data, experimental data, real-time behavior data and identity information, so that the efficiency, the performance and the service life of equipment are improved, the maintenance cost of the equipment is reduced, and effective utilization of social resources is facilitated.

Description

Technical Field

[0001] The present application relates to the field of laboratory intelligent monitoring technology, and in particular to an intelligent monitoring system for large-scale micro-nano processing laboratory equipment. Background Art

[0002] In recent years, traditional laboratories have faced challenges such as inefficient management, inadequate resource utilization, and safety risks. Although world-class research platforms have begun adopting intelligent management methods, many pressing issues remain, including inadequate monitoring, incomplete refinement, and imperfect digitization. This is particularly true for the oversight of high-precision, large-scale instruments.

[0003] For example, traditional laboratories rely on managers to manually count, register, allocate, and check instrument usage, status, and environmental conditions. This management approach not only wastes staff energy on complex and trivial tasks, but is also prone to errors and safety hazards. It also limits management efficiency and resource utilization, and makes it impossible to accurately manage process flows.

[0004] While modern laboratory intelligent management has made some progress, the safety monitoring methods employed are limited and lack refinement. These methods primarily monitor experimental teaching equipment, leaving relatively isolated facilities and inadequate management of high-precision, large-scale instruments. Most equipment failures caused by misoperation still require human oversight, detection, and assessment, lacking early warning and emergency response measures. Failure to promptly detect faults or safety hazards can lead to serious equipment damage, operational delays, and even accidents. Summary of the Invention

[0005] The purpose of this application is to solve at least one of the above-mentioned technical defects, especially the technical defects in the existing technology of incomplete management links supporting high-precision large-scale instruments, single safety monitoring means, and lack of early warning and abnormal handling measures.

[0006] The present application provides an intelligent monitoring system for large-scale micro-nano processing laboratory equipment, the system comprising:

[0007] The data collection module is used to collect the real-time environment data of the laboratory, the real-time status data of laboratory equipment, the experimental data of each operation link during the experiment, and the real-time behavior data and identity information of the experimenters in the laboratory;

[0008] The risk warning module is used to conduct real-time security risk analysis on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and determine the corresponding emergency plan based on the identification results when security risks are identified;

[0009] The fault location module is used to trace the source of the fault by using the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information when a related equipment fault is detected;

[0010] The operation and maintenance management module is used to perform multi-dimensional operation and maintenance management of the laboratory based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information.

[0011] Optionally, the system further comprises:

[0012] The experimental skills management module is used to build a user portrait corresponding to the experimental personnel based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and formulate a personalized training plan for the experimental personnel based on the user portrait.

[0013] Optionally, the system further comprises:

[0014] The laboratory management module is used to comprehensively evaluate the laboratory's operating efficiency and cost-effectiveness based on the collected real-time environmental data, real-time status data, experimental data, real-time behavioral data and identity information, and formulate optimization measures based on the evaluation results.

[0015] Optionally, the system further comprises:

[0016] The appointment management module is used to conduct project applications, safety assessments, process audits, equipment training, and appointment management for users who make appointments for experiments.

[0017] Optionally, the reservation management module includes a project application module, a security access module, a process review module, a training reservation module and an experiment reservation module;

[0018] The project application module is used to receive project information entered by the registered user under the selected project type;

[0019] The security access module is used to receive a security access application uploaded by a registered user after entering project information. The security access application includes a security access form, an HSE safety certificate, and an NFF safety certificate;

[0020] The process review module is used to receive process applications submitted by registered users who have passed the security review for designated instruments and review the submitted process applications;

[0021] The training reservation module is used to receive training registration applications initiated by registered users who have submitted process applications for instruments that have passed process review, and to conduct equipment training and assessment for the registered users;

[0022] The experiment reservation module is used to receive and review the experiment reservation application initiated by the registered user who has passed the training assessment for the instrument with the use permission, and send the review result to the corresponding registered user.

[0023] Optionally, the reservation management module further includes an account registration module;

[0024] The registration account module is used to receive registration / login requests initiated by on-campus users or off-campus users through different entrances, verify the registration / login requests, and grant different types of laboratory access permissions to on-campus users or off-campus users after the verification is passed.

[0025] Optionally, the system further comprises:

[0026] The data analysis module is used to perform statistical analysis of data in different dimensions based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and obtain statistical analysis results;

[0027] Among them, the statistical analysis results are used to assist machine operation and maintenance, procurement decisions, and comprehensive management decisions.

[0028] Optionally, when the risk warning module identifies a security risk, the process of determining a corresponding emergency plan based on the identification result includes:

[0029] When the risk warning module identifies a security risk, it determines the risk level based on the identification result and pushes corresponding alarm information and emergency response plans to the back-end management personnel according to the risk level;

[0030] Among them, the push methods of alarm information and emergency plans corresponding to different risk levels are different.

[0031] Optionally, the risk warning module is further configured to:

[0032] The entire process flow during the experiment is monitored in real time based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and process optimization suggestions are made to the corresponding experimenters based on the monitoring results.

[0033] Optionally, the operation and maintenance management module includes an experimental material management module, an experimental instrument management module, a hazardous chemicals management module and a laboratory environment management module;

[0034] The experimental material management module is used to manage the purchase, storage, use, scrapping, and abnormal use monitoring of experimental materials based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data, and identity information;

[0035] The laboratory instrument management module is used to manage the operation and maintenance of laboratory instruments, including timekeeping and billing, fault reporting, maintenance, and training, based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data, and identity information;

[0036] The hazardous chemicals management module is used to perform reagent cabinet management, reagent management, access control management, environmental monitoring, intelligent inventory management, and reagent usage traceability for hazardous chemicals based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data, and identity information;

[0037] The laboratory environment management module is used to perform abnormal early warning monitoring, abnormality tracing and special gas monitoring of the laboratory environment based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information.

[0038] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0039] The present application provides an intelligent on-duty monitoring system for large-scale micro-nano processing laboratory equipment, which includes a data acquisition module, a risk warning module, a fault location module, and an operation and maintenance management module. The data acquisition module of the present application can collect real-time laboratory environmental data, real-time status data of laboratory equipment, experimental data of each operation link during the experiment, and real-time behavior data and identity information of the experimenter in the laboratory through various security monitoring methods, thereby improving the refinement of data collection and the accuracy of subsequent data processing. The risk warning module can perform real-time security risk analysis on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data, and identity information, and when a security risk is identified, determine the corresponding emergency plan based on the identification result to ensure the safety of personnel and equipment. The process can also remotely monitor the process environment in real time and provide immediate guidance in emergency situations. In addition, the process can also adjust environmental conditions and equipment settings in real time during the sample preparation stage to ensure the stability and repeatability of experimental conditions, thereby improving the accuracy and credibility of experimental results. At the same time, the detailed data records provide a transparent chain of evidence for academic achievements, making the research process verifiable and traceable, and strengthening the verification and traceability of academic integrity. The fault location module of the present application can use the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information to trace the fault when a related equipment fault is detected, so as to timely understand the fault details and perform fault repair and accountability; finally, the operation and maintenance management module of the present application can perform multi-dimensional operation and maintenance management of the laboratory based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, thereby helping to improve the efficiency, performance and service life of the equipment, reduce the maintenance cost of the equipment, and thus facilitate the effective use of social resources. This application automatically collects important data by establishing a "smart Internet of Things" system in the laboratory scenario, thereby improving the timeliness, accuracy and fine granularity of the data, thereby improving the level of intelligent management, helping to reduce manual intervention, improving the efficiency and accuracy of data collection, and reducing management costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0041] Figure 1 A system architecture diagram of an intelligent on-call system for large-scale micro-nano processing laboratory equipment provided in an embodiment of the present application;

[0042] Figure 2 A visual display diagram for multi-dimensional monitoring of laboratory environments and different large instruments provided in the embodiment of the present application;

[0043] Figure 3 A system architecture diagram including an experimental skills management module and a laboratory management module provided in an embodiment of the present application;

[0044] Figure 4 A schematic diagram of the internal structure of the reservation management module provided in an embodiment of the present application;

[0045] Figure 5 This is a diagram showing basic information of the electron beam exposure equipment provided in an embodiment of the present application. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0047] In one embodiment, Figure 1 As shown, Figure 1 This is a system architecture diagram of an intelligent on-duty monitoring system for large-scale micro-nano processing laboratory equipment provided in an embodiment of the present application. The present application provides an intelligent on-duty monitoring system for large-scale micro-nano processing laboratory equipment, and the system may include:

[0048] The data acquisition module is used to collect the real-time environmental data of the laboratory, the real-time status data of laboratory equipment, the experimental data of each operation link in the experimental process, and the real-time behavior data and identity information of the experimenters in the laboratory.

[0049] The risk warning module is used to conduct real-time security risk analysis on the collected real-time environmental data, real-time status data, experimental data, real-time behavioral data and identity information, and when security risks are identified, determine the corresponding emergency plan based on the identification results.

[0050] The fault location module is used to trace the fault to its source when a related equipment fault is detected using the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information.

[0051] The operation and maintenance management module is used to perform multi-dimensional operation and maintenance management of the laboratory based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information.

[0052] In this embodiment, Figure 1 As shown, the smart on-duty system of the present application may include a data acquisition module, a risk warning module, a fault location module and an operation and maintenance management module, wherein the data acquisition module can collect detailed and comprehensive information, and the risk warning module, the fault location module and the operation and maintenance management module can adopt advanced technical means such as multimodal fusion to achieve all-round management of large-scale instrument process. For example, the present application can utilize the Internet of Things, big data and Internet technologies, through a variety of sensors and video monitoring, to conduct real-time, non-sensing, detailed and comprehensive automated data collection, statistics and analysis of equipment, and effectively grasp the operating status of the equipment. The collected information includes but is not limited to the temperature and humidity of the laboratory, equipment status and operation and maintenance information, and can achieve all-weather and all-round real-time data monitoring, predictive maintenance, safety warning, alarm and fault tracing, thereby avoiding serious damage to the equipment or safety accidents and ensuring laboratory safety. In addition, based on comprehensive perception, the present application combines rich user experience to customize smart on-duty solutions, optimize instrument maintenance strategies, optimize process parameters, and tap the potential value of equipment. This system not only greatly improves user experience and scientific research efficiency, but also improves management efficiency, allowing managers to focus their energy on providing technical support and maximize value. In addition, while ensuring laboratory safety, this application traces the source of faults through a fault location module, thereby clearly defining the rights and responsibilities of equipment failures, resolving concerns about open sharing, and building a pragmatic and dynamically perceptive smart laboratory.

[0053] Specifically, to address the technical shortcomings of existing technologies in large-scale micro-nanofabrication laboratories, the monitoring methods are relatively simple, the facilities are relatively independent, the information collected, the scope of control, and the risk identification are limited, and many emergencies still rely on human discovery and judgment. Furthermore, existing technologies only achieve basic data collection (instrument working environment, instrument core component status), and cannot accurately grasp equipment usage. Consequently, there is a lack of refined data management and analysis, and there is still room for improvement in data timeliness, accuracy, and fine granularity. In particular, there is room for improvement in the full lifecycle management of the experimental process and the efficient backtracking of the experimental process. Intelligent data-assisted decision-making has not yet been fully realized, and the potential of data cannot be fully utilized.

[0054] Based on this, this application configures a data acquisition module in the smart duty system, which can collect the real-time environmental data of the laboratory, the real-time status data of laboratory equipment, the experimental data of each operation link in the experiment process, and the real-time behavior data and identity information of the experimenters in the laboratory. This can not only achieve full life cycle management and remote maintenance guidance through the precise collection and analysis of multi-dimensional data, but also improve equipment utilization and fault tracing efficiency, and help optimize process parameters and provide a basis for process optimization.

[0055] Specifically, the data acquisition module of this application combines cameras and various sensors through Internet of Things technology to realize laboratory video monitoring, environmental monitoring, access control, power monitoring, operation monitoring and computer monitoring, and collects real-time laboratory environmental data, real-time status data of laboratory equipment, and experimental data of each operation link in the experiment process, real-time behavior data and identity information of experimenters in the laboratory, thereby comprehensively monitoring equipment and experimental environment to ensure stable experimental conditions.

[0056] For example, this application can use a visual camera monitoring system and a hard disk recorder to conduct video surveillance of the laboratory, thereby obtaining real-time behavioral data of the experimenters in the laboratory. This can not only effectively prevent collisions, misoperation, and the introduction of foreign objects, ensuring the safe operation of the equipment, but also use video processing technology to quickly analyze the recordings of key event points, and issue alarms when the experimenters break into specific areas, and timely intervene in abnormal behavior in the video. At the same time, this application can also realize automatic film playback and transmission functions through automated manipulators, thereby replacing manual operations, reducing operational errors and improving work efficiency.

[0057] This application can also collect information related to the use of "water, electricity, and gas" of the equipment by connecting with the factory system. In addition, this application can also select data in the usage information that can reflect the working status of the equipment for real-time monitoring and response. For example: from the smart meter system, the constantly updated instantaneous power of the equipment can be obtained. Through a period of data accumulation and the guidance of operation and maintenance managers, the instantaneous power can reflect whether the equipment is in "shutdown", "standby", or "working" status. For some equipment that may be dangerous if it works at full load for too long (especially heating equipment such as ovens), this information can help to discover safety hazards in advance.

[0058] This application can also install "client management software" on the operating terminal used for instrument and equipment control, so as to manage the use of instruments and equipment through the management and control of the use of the operating terminal. The client has the following three important functions: 1. Personnel using the operating terminal need to log in and unlock through the school's unified identity authentication. The unlocking conditions may include: whether authorized by the administrator, whether within the appointment period, etc.; 2. In non-confidential situations, the operations on the operating terminal are recorded to facilitate subsequent tracing of software use; 3. For key equipment, the log files in the operating terminal can also be connected to increase the monitoring of the equipment by monitoring file changes, identifying content, and uploading new events.

[0059] Schematically, as Figure 2 As shown, Figure 2 A visual display diagram for multi-dimensional monitoring of laboratory environments and different large instruments provided in the embodiment of the present application; Figure 2 In this application, a variety of sensors can be used to monitor the laboratory environment. For example, this application can install PM2.5, volatile organic compound, temperature, and humidity detection sensors at various locations in the laboratory. In this way, the laboratory environment can be monitored through the real-time environmental data monitored by the sensors, so that timely intervention and processing can be carried out when the environment is abnormal. This application can also track key indicators such as power supply, air supply, cooling water temperature, air compressor status, power consumption, VOC concentration, etc. of each large instrument, so as to timely grasp the real-time status data of laboratory equipment. This application can also monitor the experimental process of the experimenter, such as sampling, opening and closing the hatch, etc., and can also record the computer logged in by the experimenter and the instruments used, so as to obtain the experimental data generated by each operation link in the experimental process. In addition, this application can also obtain the identity information of the experimenter and the entry and exit time of the experimenter through access control monitoring, or use UWB technology to accurately locate and authenticate the experimenter to ensure the safety of the experiment and the traceability of the data.

[0060] In addition, this application can also screen out possible on-duty requirements through past operating experience, and adopt different monitoring methods for different instruments to collect corresponding signals (such as status, action information, etc.), so as to collect the information required for on-duty requirements. This information can form an event record in the intelligent on-duty system, and can send out alarm push or assist in subsequent efficient traceability according to pre-set rules. This application collects key parameters and steps in real time, and through intelligent analysis and decision-making assistance, effectively improves the repeatability of the experiment and ensures that the experimental results are true and reliable. For example, this application can divide laboratory instruments into expensive / precise / large / imported equipment, necessary / medium-sized / domestic / imported equipment, and simple / small equipment / measurement equipment, and adopt different on-duty plans for different equipment.

[0061] For example, this application can classify electron beam exposure equipment into expensive / precision / large / imported equipment categories, and adopt the following on-duty plan for electron beam exposure equipment:

[0062] 1. If the device encounters an error, it will provide feedback in the form of a buzzer alarm. Install a decibel sensor to monitor possible alarm sounds (the alarm content needs to be transmitted through screen information).

[0063] 2. Use a video stream recorder in conjunction with a hard disk recorder to achieve scrolling recording of screen information and push real-time video streams. In particular, while pushing alarm information, it can provide administrators with a way to remotely view real-time screen information.

[0064] 3. For the log files that can be exported by the device, a log import module is customized and developed. Based on the operation and maintenance management personnel's experience in comparing and interpreting log information, the imported log files can be stored and interpreted as event history, making it easier to trace specific events within the system.

[0065] 4. For the cabin opening action, an optocoupler sensor can be placed on the side of the cabin to record the opening and closing actions.

[0066] This application can also classify fully automatic offline coating and developing equipment into essential / medium-sized / domestic / imported equipment categories, and adopt the following on-duty plan for fully automatic offline coating and developing equipment:

[0067] 1. The main power switch monitors the human power on / off. An optocoupler sensor can be placed to monitor the human power on / off. If the hatch is accidentally opened during unauthorized periods, an alarm will be issued in time.

[0068] 2. Emergency stop switch, you can place an optocoupler sensor to monitor emergency stop and push alarm information online.

[0069] 3. Monitor all exposed and openable doors (12), monitor the opening and closing status, and push alarm information when someone opens a specific door without authorization.

[0070] 4. The device computer can be installed with client management software, which can provide unified identity authentication and login verification. Screen recording can be performed for non-confidential experiments to facilitate subsequent review.

[0071] 5. Connect with the data of the equipment control system, record the alarm information and operation process information of the equipment, and then monitor the VOC data and developer level status in the main cabin to prevent overflow, etc.

[0072] This application can also classify dual-beam electron microscopes (similar to scanning electron microscopes and scanning probes) as simple / small equipment / measurement equipment, and adopt the following duty plan for dual-beam electron microscopes:

[0073] 1. Optocoupler sensors are placed in the equipment's small exchange compartment and main compartment for monitoring of opening and closing. If the compartment door is accidentally opened during unauthorized periods, an alarm will be triggered in time. If the compartment door is opened for too long, the user will be reminded and warned to avoid moisture and air adsorption.

[0074] 2. Use an optocoupler sensor to monitor whether the energy spectrum probe has entered the working position.

[0075] 3. The working indicator light of the femtosecond laser is monitored by a light sensor, which records the power on and off status and provides data for duration statistics.

[0076] 4. The device computer can be installed with client management software, which can provide unified identity authentication and login verification. Screen recording can be performed for non-confidential experiments to facilitate subsequent review.

[0077] 5. By monitoring the log files in the equipment computer, the operation information of the equipment's electron beam system and ion beam system can be recorded.

[0078] 6. Add a set of redundant environmental sensors between the auxiliary equipment and supervise the deployment and improvement of existing water immersion sensors.

[0079] This application uses a data acquisition module to conduct all-round data collection, from experimental preparation to sample processing, to data storage and upload. Each important node is accurately monitored and recorded to form a complete experimental process data chain, and adopts multiple-dimensional on-duty plans for different experimental equipment, such as user on-and-off duty, equipment key parts duty, and equipment power and environment duty. This not only provides three-dimensional data support for experimental operations and ensures the accurate execution and management of the process, but also can realize fault warning and abnormal alarm through real-time analysis of these data, timely discover potential problems, and prevent risks from occurring. This management model that starts from the process not only greatly improves the quality of the experiment, but also provides strong data support and guarantee for the realization of quality management. In addition, this application can realize 24-hour unmanned operation of equipment through intelligent linkage technology and personalized rule formulation, and can remotely monitor equipment status and maintenance guidance, thereby effectively improving management efficiency and monitoring accuracy.

[0080] In a specific implementation method, the present application can perform real-time security risk analysis on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information through a risk warning module, and when a security risk is identified, determine the corresponding emergency plan based on the identification results; it can also use the fault location module to trace the source of the fault when a related equipment fault is detected using the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information; it can also use the operation and maintenance management module to perform multi-dimensional operation and maintenance management of the laboratory based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information.

[0081] For example, the present application can use a data acquisition module to collect information such as laboratory temperature, humidity, hazardous gas concentration, and equipment operating parameters, and use a risk warning module to monitor the safety status of the process in real time. The risk warning module can analyze this data and identify whether the current data is in an abnormal mode. If it is in an abnormal mode, it automatically triggers warnings and alarms, and initiates response measures to intervene in time during the experiment to ensure the safety of personnel and equipment. In addition, the smart on-call system of the present application can synchronize user operation logs, monitor infrastructure (such as power and gas supply) data, and track key indicators such as cooling water temperature, air compressor status, power consumption, and VOC concentration to the risk warning module. The risk warning module can use big data analysis technology to mine the massive data generated by the equipment, identify hidden risk points, and optimize the equipment's use and maintenance plan based on these risk points. This process not only helps provide users with accurate process optimization suggestions and timely adjust maintenance strategies according to changes in equipment operating conditions to achieve predictive maintenance, but also reduces equipment failures and downtime, improving operation and maintenance efficiency. In addition, after integrating environmental monitoring data (such as temperature and humidity, VOC, PM2.5, oxygen content, etc.) with equipment operation data (including host power consumption, software operation records, sample chamber door status, high-voltage indication, vacuum pump and air compressor power consumption, etc.), this application can perform safety risk analysis through the risk warning module, and then adjust the environmental conditions and equipment settings in real time during the sample preparation stage to ensure the stability and repeatability of the experimental conditions, thereby improving the accuracy and credibility of the experimental results. At the same time, this application has achieved the traceability of the entire process of experimental data for the first time, ensuring the repeatability of the experiment and academic norms; detailed data records can also provide a transparent chain of evidence for academic achievements, making the research process verifiable and traceable, and strengthening the verification and traceability of academic integrity. In addition, this application uses the technical means of multimodal fusion to achieve all-round perception and refined management of the experimental process of large-scale instruments.

[0082] Furthermore, the fault location module can determine whether there is a faulty device based on the relevant data collected by the data acquisition module. If a relevant device fault is detected, the real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information collected can be used to trace the fault so as to locate the fault point in time. For example, the fault location module of the present application can be based on the digital twin technology of the IOT log to trace the fault scene and reproduce the operation log, laboratory environment, sensor status, video monitoring, client screen recording, and fault moment in multiple dimensions, thereby quickly realizing fault location tracing. The process also supports arbitrary dragging and tracing back of the event timeline, thereby accurately locating the fault and effectively improving the safety and quality management level of the laboratory. In addition, the present application can easily and efficiently trace back and reproduce the experimental process, and can also provide unprecedented evidence for the verification of data authenticity and academic norms, thereby helping to improve the standardization and credibility of academic research. In addition, the present application combines manufacturer cooperation, multimodal monitoring and technical personnel experience to collect key data, achieve efficient fault tracing and rapid repair, extend equipment life, and improve scientific research efficiency.

[0083] Furthermore, the operation and maintenance management module of the present application can not only use the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information to carry out fine-grained management of various aspects of laboratory equipment operating status, performance, energy consumption, etc., thereby helping laboratory managers to more accurately understand the operating status and management of the equipment, and timely adjust and optimize equipment operating parameters to avoid potential risks; it can also realize the full life cycle management and monitoring mechanism of hazardous chemicals such as procurement and warehousing, access tracking, and waste management through the intelligent Internet of Things system, which not only helps to improve the safety and quality management level of the laboratory, but also can reduce the economic losses caused by safety accidents and quality problems.

[0084] This application uses a groundbreaking management model to comprehensively guarantee scientific research efficiency and safety, and for the first time proposes the concepts of lean management and full life cycle management. It uses digital resources as support to achieve real-time fault monitoring, predictive maintenance, all-round dynamic perception, refined operation and maintenance, and scientific research assistance, greatly improving scientific research efficiency, saving scientific research resources, and ensuring laboratory safety.

[0085] In the above embodiment, the system includes a data acquisition module, a risk warning module, a fault location module and an operation and maintenance management module, wherein the data acquisition module of the present application can collect the real-time environmental data of the laboratory, the real-time status data of the laboratory equipment, the experimental data of each operation link in the experimental process, the real-time behavior data and identity information of the experimenter in the laboratory through a variety of security monitoring means, thereby improving the degree of refinement of data collection and improving the accuracy of subsequent data processing; the risk warning module can perform real-time security risk analysis on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and when a security risk is identified, determine the corresponding emergency plan based on the identification result to ensure the safety of personnel and equipment, and the process can also remotely monitor the process environment in real time and provide immediate guidance in emergency situations. In addition, the process can also adjust the environmental conditions and equipment settings in real time during the sample preparation stage to ensure the stability and repeatability of the experimental conditions, thereby improving the accuracy and credibility of the experimental results; at the same time, the detailed data records provide a transparent chain of evidence for academic achievements, making the research process verifiable and traceable, and strengthening the verification and traceability of academic integrity. The fault location module of the present application can use the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information to trace the fault when a related equipment fault is detected, so as to timely understand the fault details and perform fault repair and accountability; finally, the operation and maintenance management module of the present application can perform multi-dimensional operation and maintenance management of the laboratory based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, thereby helping to improve the efficiency, performance and service life of the equipment, reduce the maintenance cost of the equipment, and thus facilitate the effective use of social resources. This application automatically collects important data by establishing a "smart Internet of Things" system in the laboratory scenario, thereby improving the timeliness, accuracy and fine granularity of the data, thereby improving the level of intelligent management, helping to reduce manual intervention, improving the efficiency and accuracy of data collection, and reducing management costs.

[0086] In one embodiment, Figure 3 As shown, Figure 3 A system architecture diagram including an experimental skills management module and a laboratory management module provided in an embodiment of the present application; the system may also include:

[0087] The experimental skills management module is used to build a user portrait corresponding to the experimental personnel based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and formulate a personalized training plan for the experimental personnel based on the user portrait.

[0088] In this embodiment, the intelligent duty system may also include an experimental skills management module, which can construct a user portrait corresponding to the experimenter based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and formulate personalized training plans for the experimenter based on the user portrait. This can enhance scientific research assistance capabilities and has far-reaching significance for cultivating top talents in this field.

[0089] Specifically, this application can use big data technology or artificial intelligence technology to comprehensively analyze multi-source information, such as laboratory environment data, video surveillance information, access control records, instrument operation logs, equipment operating status, operation and maintenance data, user operation behavior and its feedback and experimental results, etc., to build a comprehensive portrait of the user, and capture the user's behavior pattern and skill level in the laboratory through a comprehensive portrait, revealing their specific experimental operation habits and technical capabilities. Then, this application can also use data analysis technology to identify the user's experimental operation proficiency, safety awareness, problem-solving ability and innovation potential. Based on the information obtained from the above analysis, personalized training programs can also be formulated for users, such as experimental skills training, safety standard education, theoretical knowledge reinforcement, and scientific research innovation methodology guidance. It aims to fill the user's skill gaps, give full play to their advantages, and enhance their experimental skills and scientific research innovation capabilities.

[0090] In the above examples, this application utilizes intelligent monitoring and precise analysis for the first time to help instructors develop personalized training plans. Through digital technology and intelligent analysis, it is possible to evaluate and improve the operational level of researchers, optimize process parameters, provide process steps, and improve research efficiency. By systematically analyzing data, instructors can develop personalized training plans, promoting the rapid growth of researchers.

[0091] In one embodiment, the system may further include:

[0092] The laboratory management module is used to comprehensively evaluate the laboratory's operating efficiency and cost-effectiveness based on the collected real-time environmental data, real-time status data, experimental data, real-time behavioral data and identity information, and formulate optimization measures based on the evaluation results.

[0093] In this embodiment, Figure 3 As shown, the smart duty system of the present application may also include a laboratory management module, which can comprehensively evaluate the laboratory's operating efficiency and cost-effectiveness based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and formulate optimization measures based on the evaluation results to improve the laboratory's resource utilization.

[0094] In a specific implementation, this application can reveal the correlation and influence between different data through cross-analysis and fusion technology of data, and gain insight into the advantages and disadvantages of resource allocation and potential room for improvement. This application can also use statistical analysis, machine learning and other methods to conduct in-depth mining and pattern recognition of various types of collected indicator data, thereby providing data support for making accurate management decisions and optimization measures, and helping to improve the utilization rate of instruments and equipment, reduce operating costs, promote the economic sustainability of the laboratory, and achieve efficient use of resources.

[0095] In one embodiment, the system may further include:

[0096] The appointment management module is used to conduct project applications, safety assessments, process audits, equipment training, and appointment management for users who make appointments for experiments.

[0097] In this embodiment, the smart duty system can also include an appointment management module. The appointment management system can provide safety, environment, health, equipment and other aspects of training to users who have scheduled experiments before the experiment, and review the upcoming process applications to further eliminate safety hazards and ensure the safety of personnel and equipment.

[0098] In a specific implementation method, in this application, the user can make an appointment for the machine time of the relevant equipment before the experiment, and arrive at the laboratory at the scheduled time after the appointment is successful, wherein the user enters the experimental area and the route of action before arriving at the equipment, the user logs in to the client control software and starts the equipment operation software, the relevant software preparation work and parameter setting of the equipment, the user's hardware preparation work, opens the exchange chamber, puts in the sample table, vacuumizes, opens and closes the hatch in the exchange chamber, etc., opens and closes the electron beam, opens and closes the laser, opens and closes the ion source, takes out the relevant process actions of the sample, stores and uploads the data, ends the experiment and logs out of the system, the personnel leave the experimental area, etc. This complete process containing necessary important nodes will be automatically recorded without human intervention. At the same time, for some special events in the link that exceed the threshold and violate the preset logic and rules, the risk warning module can also be used to identify and push alarm information in real time. This application brings about the improvement of the quality of laboratory intelligence on-duty through a precise and detailed process management method, thereby achieving an improvement in the level of quality management.

[0099] In one embodiment, Figure 4 As shown, Figure 4 Schematic diagram of the internal structure of the appointment management module provided in the embodiment of the present application; the appointment management module includes a project application module, a security access module, a process review module, a training appointment module and an experiment appointment module.

[0100] The project application module is used to receive project information entered by a registered user under a selected project type.

[0101] The security access module is used to receive a security access application uploaded by a registered user after entering project information. The security access application includes a security access form, an HSE safety certificate, and an NFF safety certificate.

[0102] The process review module is used to receive process applications submitted by registered users who have passed the security review for designated instruments, and to review the submitted process applications.

[0103] The training reservation module is used to receive training registration applications initiated by registered users who have submitted process applications for instruments that have passed process review, and to conduct equipment training and assessment for the registered users.

[0104] The experiment reservation module is used to receive and review the experiment reservation application initiated by the registered user who has passed the training assessment for the instrument with the use permission, and send the review result to the corresponding registered user.

[0105] In this embodiment, after the user successfully registers, the project information can be entered into the project application module. The project application module can receive the project information entered by the registered user under the selected project type, which includes but is not limited to project group projects and unit projects, etc. The project information includes but is not limited to project name, project number, and which project funds are selected before the experiment appointment to pay for the security access assessment fee and the experimental fee, etc. For example, among the registered users of this application, if there is a registered user who is currently participating in a project group project or is about to participate in a project group project, the registered user can first click "Apply to Join" in the system to apply to join the project group. Applying for a project group requires the approval of the project group leader or project group administrator. After approval, click "Project Application" to choose to join a project under the project group. If there is no project, please contact the project group leader to create a project. When the project group leader creates the project, the system will send a relevant notification to the registered user so that the registered user can log in to the system and join the created project. After the subsequent experiment is completed, the experimental data can be uploaded to the folder corresponding to the project. This makes it convenient to find the experimental data and to record multiple experiments conducted under the same project so that statistical analysis can be performed on all experiments conducted on the project later. In addition, registered users can also choose the settlement method for the assessment fees and experimental fees generated after the experiment, such as settling the assessment fees and experimental fees through the entered research group projects or unit projects.

[0106] It should be noted that the registered users participating in the research group project in this application can be on-campus users or off-campus users. The off-campus users can be users cooperating with a research group on campus, or users participating in research group projects in other cooperating schools. The specific choice can be made based on actual circumstances and is not restricted here. The registered users participating in the unit project in this application can be external unit users. Such users can also enter their unit projects so that they can be classified, counted and charged according to the project type in the future.

[0107] After the registered user in this application enters the project information through the project application module, the security access module can accept the security access application uploaded by the registered user and review the security access application. After the review is passed, the next step can be entered. If the review fails, the registered user will be informed of the reason for failure and wait for the registered user's further action. Among them, the security access application uploaded by the registered user in this application includes but is not limited to the security access form, HSE safety certificate and NFF safety certificate. The security access form can be filled out and uploaded according to the template provided by the system. The HSE safety certificate and NFF safety certificate can be trained and tested according to the relevant guidelines in the system. After passing the test, the HSE safety certificate and NFF safety certificate can be obtained. At this time, the two certificates can be uploaded together with the security access form. In addition, for the relevant expenses incurred by the registered user during the examination, this application can register the project information pre-entered by the registered user and settle them uniformly at a specific time. During the settlement, the settlement can be made according to the source of the project funds in the project information filled in by the registered user.

[0108] Among them, the HSE safety certificate of this application is a certification certificate related to health, safety and environmental management. The HSE safety certificate usually indicates that a person has certain knowledge, skills and abilities in the field of HSE, and can effectively implement and manage HSE-related matters in the workplace. Registered users with HSE safety certificates can be recognized as being able to operate equipment more standardizedly, reduce the accident rate, and ensure the safety and stability of the experimental process. The NFF safety certificate of this application is a certificate related to the safety of micro-nano system laboratories. Registered users with this certificate can be recognized as being familiar with the safety knowledge of micro-nano system laboratories. This application conducts an overall health, safety and environmental management access audit on registered users and a laboratory-level safety access audit in order to strengthen the safety awareness of registered users who make appointments for experiments and the operating specifications of large instruments from multiple dimensions.

[0109] Furthermore, after the registered user passes the security review after entering the project information, this application can receive the process application submitted by the registered user who has passed the security review for the designated instrument through the process review module, and review the submitted process application. If the existing large-scale instrument does not match the process application submitted by the registered user, such as there is a mismatch in process parameter requirements, related function implementation, etc., in order to prevent the use of the process flow for experiments from causing large-scale instrument failure or a certain degree of safety hazards, a notification of process review failure can be sent to the user at this time, and the reason for failure can also be attached in the notification so that the user can perform other operations based on the reason; if the existing large-scale instrument matches the process application submitted by the registered user, a notification of process review approval can be sent to the user so that the user can proceed to the next step.

[0110] For example, when the registered user of this application applies for a process review in the system, he can first click "Process Review" to enter the new process review page, click "Add" to add a process application, and submit the application for review by the administrator. It is worth noting that the instrument information displayed on the training appointment page of this application is related to the instruments submitted for process review. Only instruments that have passed the process review will be displayed on the training appointment page, and the review time for process reviews of different instruments submitted at different times will also be different. Therefore, when the process review of a certain instrument is passed, the user can log in to the system according to the relevant notification and view the instruments that have passed the process review on the training appointment page in order to make training appointments for them.

[0111] Furthermore, when the training assessment is completed, the experiment reservation module of this application can receive and review the experiment reservation application initiated by the registered user who has passed the training assessment for the instrument with use permission, and send the review result to the corresponding registered user. It is understandable that since it takes a certain amount of time for the registered user to conduct training assessment for different instruments, and the assessment time is also different, the registered user who has passed the training assessment can log in to the system to view the instrument with use permission, and initiate the experiment reservation application corresponding to the instrument according to his own needs. After receiving the experiment reservation application, the administrator can review it and send the review result to the corresponding registered user so that the registered user can perform subsequent operations.

[0112] For example, when a registered user who has passed the training assessment logs into the system, he can click "Experimental Appointment" to enter the instrument appointment page. This page only displays the instrument information of the current user who has passed the instrument training assessment. Then, the registered user can click "I want to make an appointment" to enter the "Appointment Calendar" page, select the time period required for the appointment, and submit it. Of course, in this application, the administrator can also set different ways of accessing the computer according to different instrument types, such as appointment, on-demand access, and queuing. Different appointment methods can be used for different on-boarding methods. For example, when making an appointment to access the computer, the user can log in to the system on the web or mobile terminal to make an appointment; when on-demand access, the user can scan the code directly in the laboratory to access the computer; when queuing for the computer, the user can queue offline or online. Different on-boarding methods correspond to different types of instruments. The specific settings can be made according to the laboratory situation and are not restricted here.

[0113] In addition, since the working hours of different large instruments in the micro-nano system laboratory of this application are different, in order to better maintain the instrument performance of large instruments and to balance reservation resources, this application can pre-establish the same or different reservation rules according to different instruments. Figure 5 As shown, Figure 5 A diagram showing basic information of the electron beam exposure equipment provided in an embodiment of the present application; Figure 5 In the basic information of the electron beam exposure equipment, the instrument description, precautions, reservation rules and charging standards of the equipment are displayed. The reservation rules may be that the reservation duration shall not exceed the preset duration, the number of reservations on the same working day shall not exceed the preset number, no reservations shall be made 12 hours before the experiment, and other rules related to the performance of large instruments and the use of resources are not restricted here. When a registered user clicks "I want to make an appointment" to enter the "Appointment Calendar" page and selects the time period for the appointment, in order to prevent the user from being unclear or not reviewing the appointment rules, the appointment rules can also be displayed to the user through a system pop-up window, or through a specific area, so that the user can make an appointment based on the appointment rules, thereby improving the appointment management efficiency of the laboratory and improving the resource utilization of the laboratory.

[0114] In one embodiment, the reservation management module may further include an account registration module.

[0115] The registration account module is used to receive registration / login requests initiated by on-campus users or off-campus users through different entrances, verify the registration / login requests, and grant different types of laboratory access permissions to on-campus users or off-campus users after the verification is passed.

[0116] In this embodiment, the reservation management module can include not only a security access module, a project application module, a process review module, a training reservation module, and an experiment reservation module, but also a registration account module, which can receive registration / login requests from on-campus users or off-campus users through different entrances, and verify the registration / login requests, and give different types of access control permissions to on-campus users or off-campus users after the verification is passed. This can provide laboratory resources for both on-campus and off-campus users at the same time, thereby maximizing value, and can also make flexible reservations through a variety of permission types. In addition, by building a refined Internet of Things system with rich parameters, this application can not only realize the digital management of personnel and equipment, but also solve problems such as machine time allocation and rule implementation, thereby avoiding missed reports and false reports, and preventing billing losses.

[0117] For example, in this application, on-campus users can register and log in using the school's unified identity authentication (SSO) account; off-campus users can register and log in by filling in information such as name, mobile phone number, and login password. When registering and logging in, you can register and log in through the web page or through the mini-program. There is no restriction on the specific login method. Successfully registered users can be given different types of access control permissions based on different user types. For example, for on-campus users, since the user's identity information is uniformly authenticated by the school, such users can directly enter the laboratory through face recognition. For off-campus users, in order to ensure the safety of personnel entering and exiting, such users can apply for a visitor card. After the experiment reservation is successful, the access control permission for the corresponding time period will be automatically issued, and the user can enter the laboratory with the visitor card. This not only makes it convenient for on-campus and off-campus users to conduct experiments, but also reduces safety risks and realizes flexible appointment management.

[0118] In one embodiment, the system may further include:

[0119] The data analysis module is used to perform statistical analysis of data in different dimensions based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and obtain statistical analysis results.

[0120] Among them, the statistical analysis results are used to assist machine operation and maintenance, procurement decisions, and comprehensive management decisions.

[0121] In this embodiment, the smart duty system can not only establish a "smart Internet of Things" system in the laboratory scenario, but also automatically collect important data through the system. This not only improves the timeliness, accuracy and granularity of the data, but also improves the level of intelligent management, helps reduce manual intervention, improves the efficiency and accuracy of data collection, and reduces management costs.

[0122] Furthermore, this application can also perform statistical analysis of data in different dimensions based on the collected real-time environmental data, real-time status data, experimental data, real-time behavioral data and identity information, and obtain statistical analysis results. The statistical analysis results can assist machine operation and maintenance, procurement decisions, comprehensive management decisions, etc., thereby further improving the intelligence and digitalization level of this system.

[0123] For example, this application can comprehensively analyze the number of laboratory reservations, computer hours, instruments with the most reservations, instruments with the most computer hours, subjects with the most reservations, subjects with the most computer hours, etc. based on the identity information of the laboratory personnel and the equipment status information of the laboratory equipment. In this way, the reservation strategy can be adjusted in time according to the analysis, and the equipment status of related equipment can be monitored in detail to reduce equipment failures and downtime, and improve operation and maintenance efficiency and reservation management level.

[0124] This application can also use the data reported by the data acquisition module to count the number of sensors, the total number of instruments, the number of sensor reports, the number of instruments in use, the number of idle instruments, the number of instruments under maintenance, and the number of trigger events, thereby achieving visual on-duty monitoring. In addition, this application can also support comprehensive statistical data analysis at the school level, department level, research group level, and instrument level, thereby providing users with data analysis strategies of different granularity.

[0125] In one embodiment, when the risk warning module identifies a security risk, the process of determining a corresponding emergency plan based on the identification result may include:

[0126] When the risk warning module identifies a security risk, it determines the risk level based on the identification result and pushes corresponding alarm information and emergency response plans to the back-end management personnel according to the risk level;

[0127] Among them, the push methods of alarm information and emergency plans corresponding to different risk levels are different.

[0128] In this embodiment, the risk warning module can perform real-time security risk analysis on the collected real-time environmental data, real-time status data, experimental data, real-time behavioral data and identity information. The analysis process can be implemented through neural networks or big data technologies. When a security risk is identified, the risk level of the security risk can be determined based on the identification results, so that the corresponding alarm information and emergency plans can be pushed to the background management personnel based on the risk level.

[0129] Specifically, when the present application identifies a security risk, it can determine the risk level based on the identification result, and the present application presets different push methods for different risk levels, so as to push corresponding alarm information and emergency plans according to different push methods. For example, the present application can pre-collect the processing speed of the relevant information pushed by each back-end manager for different push methods, and set the corresponding risk level according to the processing speed. For example, information with a higher risk level can be pushed through a push method with a faster processing speed, while information with a lower risk level can be pushed through a push method with a relatively slower processing speed. This can avoid the situation where the back-end manager cannot find the information with a higher risk level in a large number of push information in a timely manner after pushing through the same push method, thereby effectively improving the efficiency of information processing, and can notify the back-end manager to take emergency plans in a timely manner through message push, thereby minimizing the risk of equipment failure, avoiding delays in scientific research progress and major economic losses, and has important practical value and significance.

[0130] In one embodiment, the risk warning module may also be used to:

[0131] The entire process flow during the experiment is monitored in real time based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and process optimization suggestions are made to the corresponding experimenters based on the monitoring results.

[0132] In this embodiment, the risk warning module not only analyzes the relevant data collected by the data acquisition module and identifies whether the current data is in an abnormal mode, but also automatically triggers warnings and alarms if so, initiating countermeasures to ensure timely intervention during the experiment and ensure the safety of personnel and equipment. It also synchronizes user operation logs, monitors infrastructure data (such as power and gas supply), and tracks key indicators such as cooling water temperature, air compressor status, power consumption, and VOC concentration. Using big data analysis techniques, it mines the massive amount of data generated during the experiment to monitor the entire process in real time and, based on the monitoring results, provides process optimization suggestions to the corresponding experimenters.

[0133] For example, the risk warning module of this application can use big data, artificial intelligence and virtual simulation technology to analyze and mine the massive data (process parameters, process and results) generated during the use of large-scale instruments, and establish a process library corresponding to different large-scale instruments and different process flows, thereby providing users with process guidance during the experiment, such as recommending process flows and process parameters, etc. This can not only improve scientific research efficiency and process stability, but also optimize equipment use and maintenance strategies. In addition, this application uses multimodal fusion technology to comprehensively monitor laboratory safety, quickly discover and deal with dangerous situations, and reduce losses.

[0134] In one embodiment, the operation and maintenance management module includes an experimental material management module, an experimental instrument management module, a hazardous chemicals management module and a laboratory environment management module.

[0135] The experimental material management module is used to perform operation and maintenance management on the purchase, warehousing, use, scrapping, and abnormal use monitoring reminders of experimental materials based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information.

[0136] The experimental instrument management module is used to perform operation and maintenance management of the experimental instruments including time billing, fault reporting, maintenance and training based on the collected real-time environment data, real-time status data, experimental data, real-time behavior data and identity information.

[0137] The hazardous chemicals management module is used to perform reagent cabinet management, reagent management, access control management, environmental monitoring, intelligent inventory management and reagent usage traceability for hazardous chemicals based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information.

[0138] The laboratory environment management module is used to perform abnormal early warning monitoring, abnormality tracing and special gas monitoring of the laboratory environment based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information.

[0139] In this embodiment, the operation and maintenance management module can not only use the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information to carry out fine management of the operating status, performance, energy consumption and other aspects of laboratory equipment, thereby helping laboratory managers to more accurately understand the operating status and management of the equipment, timely adjust and optimize the equipment operating parameters, and avoid potential risks; it can also realize the full life cycle management and monitoring mechanism of the procurement, warehousing, access tracking, and waste management of hazardous chemicals through the intelligent Internet of Things system, which not only helps to improve the safety and quality management level of the laboratory, but also reduces the economic losses caused by safety accidents and quality problems. In addition, this application realizes the standardized management of experimental consumables through the combination of software and hardware, solves the problems of waste and responsibility, and facilitates statistical reporting. Moreover, this application comprehensively records and analyzes the use and maintenance of instruments, conducts multi-dimensional analysis of data, and then guides operation and maintenance decisions and saves costs; digital technology can solve the repetitive and inefficient work in equipment management, release the energy of managers, and play a high-level technical support role.

[0140] Specifically, the operation and maintenance management module of the present application may include an experimental material management module, an experimental instrument management module, a hazardous chemicals management module and a laboratory environment management module; wherein the experimental material management module can perform operation and maintenance management on the purchase, warehousing, use, scrapping and abnormal use monitoring reminders of experimental materials based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information. The experimental materials include but are not limited to experimental tables and chairs, lockers, power sockets, various sensors, video surveillance equipment, etc.; the experimental instrument management module can perform operation and maintenance management on the timekeeping and billing, fault reporting, maintenance and training of experimental instruments based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, which helps to improve the efficiency, performance and service life of the equipment. life, and reduce equipment maintenance costs; the hazardous chemicals management module can perform reagent cabinet management, reagent management, access control management, environmental monitoring, intelligent inventory and reagent usage traceability for hazardous chemicals based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, which helps to improve the laboratory's safety and quality management level and meet the safety and quality management requirements of modern laboratories; the laboratory environment management module can perform abnormal early warning monitoring, abnormality traceability and special gas monitoring for the laboratory environment based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, which can not only ensure the personal safety of experimental personnel, but also ensure the equipment safety of laboratory equipment, and improve the laboratory's intelligent management level through abnormality tracing.

[0141] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0142] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referenced to each other.

[0143] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent monitoring system for large-scale micro-nano processing laboratory equipment, characterized in that: The system comprises: The data collection module is used to collect the real-time environment data of the laboratory, the real-time status data of the laboratory equipment, the experimental data of each operation link in the experimental process, and the real-time behavior data and identity information of the experimenters in the laboratory; The risk warning module is used to conduct real-time security risk analysis on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and determine the corresponding emergency plan based on the identification results when security risks are identified; The fault location module is used to trace the fault source by using the collected real-time environment data, real-time status data, experimental data, real-time behavior data and identity information when a relevant equipment fault is detected; The operation and maintenance management module is used to perform multi-dimensional operation and maintenance management of the laboratory based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information.

2. The intelligent on-duty system for large-scale micro-nano processing laboratory equipment according to claim 1 is characterized in that: The system further comprises: The experimental skill management module is used to build a user portrait corresponding to the experimenter based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and formulate a personalized training plan for the experimenter based on the user portrait.

3. The intelligent on-duty system for large-scale micro-nano processing laboratory equipment according to claim 1 is characterized in that: The system further comprises: The laboratory management module is used to comprehensively evaluate the laboratory's operating efficiency and cost-effectiveness based on the collected real-time environmental data, real-time status data, experimental data, real-time behavioral data and identity information, and formulate optimization measures based on the evaluation results.

4. The intelligent on-duty system for large-scale micro-nano processing laboratory equipment according to claim 1 is characterized in that: The system further comprises: The appointment management module is used to conduct project application, safety assessment, process review, equipment training and appointment management for users who make appointments for experiments.

5. The intelligent on-duty system for large-scale micro-nano processing laboratory equipment according to claim 4 is characterized in that: The appointment management module includes a project application module, a security access module, a process review module, a training appointment module and an experiment appointment module; The project application module is used to receive project information entered by the registered user under the selected project type; The safety access module is used to receive a safety access application uploaded by a registered user after entering project information, wherein the safety access application includes a safety access form, an HSE safety certificate and an NFF safety certificate; The process review module is used to receive process applications submitted by registered users who have passed the security review for designated instruments, and review the submitted process applications; The training reservation module is used to receive training registration applications initiated by registered users who have submitted process applications for instruments that have passed process review, and to conduct equipment training and assessment for registered users who have registered; The experiment reservation module is used to receive and review the experiment reservation application initiated by the registered user who has passed the training assessment for the instrument with the use permission, and send the review result to the corresponding registered user.

6. The intelligent on-duty system for large-scale micro-nano processing laboratory equipment according to claim 5 is characterized in that: The reservation management module also includes an account registration module; The registration account module is used to receive registration / login requests initiated by on-campus users or off-campus users through different entrances, verify the registration / login requests, and grant different types of laboratory access rights to on-campus users or off-campus users after the verification is passed.

7. The intelligent on-duty system for large-scale micro-nano processing laboratory equipment according to claim 1 is characterized in that: The system further comprises: The data analysis module is used to perform statistical analysis of data in different dimensions based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, and obtain statistical analysis results; Among them, the statistical analysis results are used to assist machine operation and maintenance, procurement decisions, and comprehensive management decisions.

8. The intelligent on-duty system for large-scale micro-nano processing laboratory equipment according to any one of claims 1 to 7, characterized in that: When the risk warning module identifies a security risk, the process of determining a corresponding emergency plan based on the identification result includes: When the risk warning module identifies a security risk, it determines the risk level according to the identification result, and pushes corresponding alarm information and emergency plans to the back-end management personnel according to the risk level; Among them, the push methods of alarm information and emergency plans corresponding to different risk levels are different.

9. The intelligent on-duty system for large-scale micro-nano processing laboratory equipment according to any one of claims 1 to 7, characterized in that: The risk warning module is also used for: Based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information, the entire process flow during the experiment is monitored in real time, and process optimization suggestions are made to the corresponding experimenters based on the monitoring results.

10. The intelligent on-duty system for large-scale micro-nano processing laboratory equipment according to any one of claims 1 to 7, characterized in that: The operation and maintenance management module includes an experimental material management module, an experimental instrument management module, a hazardous chemicals management module and a laboratory environment management module; The experimental material management module is used to perform operation and maintenance management on the purchase, warehousing, use, scrapping, and abnormal use monitoring reminders of experimental materials based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data, and identity information; The experimental instrument management module is used to perform operation and maintenance management on the timekeeping and billing, fault reporting, maintenance and training of the experimental instruments based on the collected real-time environment data, real-time status data, experimental data, real-time behavior data and identity information; The hazardous chemicals management module is used to perform reagent cabinet management, reagent management, access control management, environmental monitoring, intelligent inventory management and reagent use traceability for hazardous chemicals based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information; The laboratory environment management module is used to perform abnormal early warning monitoring, abnormal source tracing and special gas monitoring of the laboratory environment based on the collected real-time environmental data, real-time status data, experimental data, real-time behavior data and identity information.

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