Intelligent electronic bulk gas station quality and safety management CQC analysis system

Abstract

The present invention discloses an intelligent electronic bulk gas station quality and safety management CQC analysis system, including an on-site gas analyzer, a CQC analyzer, a controller, a fault alarm unit, a data collection unit and a data processing background, wherein the fault alarm unit includes a data acquisition module, a data classification module, a data cleaning module and a data analysis module. The present invention analyzes, monitors and manages the key data of the gas used through artificial intelligence technology and algorithms, so as to facilitate real-time monitoring of gas quality, flow pressure, spare reserves and safety status, and can associate the main data of the gas and the direct underlying data with the direct alarm rules, upgrade to multi-dimensional data parameters and analysis, and form on-site gas linkage, interactive mass analysis and optimization of quality, efficiency and safety through artificial intelligence models and algorithm optimization.

Description

Technical Field

[0001] The present invention belongs to the technical field of safety management, and in particular relates to an intelligent electronic bulk gas station quality and safety management CQC analysis system. Background Art

[0002] Bulk electronic gas is an indispensable basic supporting source material in the development of integrated circuits, optoelectronics, microelectronics, especially in the manufacturing process of ultra-large-scale integrated circuits, liquid crystal display devices, semiconductor light-emitting devices and semiconductor materials, and fundamentally restricts the precision and accuracy of circuits and devices. It can be divided into three categories according to its category: pure gas, high-purity gas and semiconductor special material gas. Special material gas is mainly used in epitaxy, doping and etching processes, and high-purity gas is mainly used as diluent gas and carrier gas. Bulk electronic gas is a key material for semiconductor integrated circuit manufacturing. The uninterrupted and safe production of electronic gas plays a key role in semiconductor integrated circuit manufacturing. Among them, the reading of CQC analyzer plays a decisive role in the stability, reliability, quality and safety of the entire system.

[0003] The traditional solution is for operators to set simple OOC or OOS alarms for numerical values. When a problem occurs, the personnel will analyze and judge the event and handle the post-fault analysis and processing. However, this method is difficult to determine the cause of the fault, and the maintenance time is relatively long. At the same time, serious accidents may occur during the processing. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent electronic bulk gas station quality and safety management CQC analysis system to solve the problems raised in the above background technology that it is difficult to determine the cause of the fault in the prior art, the maintenance time is long, and accidents may occur during the processing.

[0005] To achieve the above object, the present invention adopts the following technical scheme: an intelligent electronic bulk gas station quality and safety management CQC analysis system, including an on-site gas analyzer, a CQC analyzer, a controller, a fault alarm unit, a data collection unit and a data processing background, wherein the fault alarm unit includes a data acquisition module, a data classification module, a data cleaning module and a data analysis module;

[0006] The data collection unit includes a pressure sensor, a flow sensor and a temperature sensor;

[0007] The data processing backend is pre-installed with fault prediction software, which includes model building, model training, model reasoning and model application functions;

[0008] The data acquisition module, data classification module, data cleaning module and data analysis module are all connected to the controller, the on-site gas analyzer, CQC analyzer, pressure sensor, flow sensor and temperature sensor are all connected to the data acquisition module, and the data analysis module is connected to the data processing background.

[0009] Preferably, the on-site gas analyzer and CQC analyzer monitor the gas, and monitor the pressure, flow and temperature inside the gas in real time through pressure sensors, flow sensors and temperature sensors, and send the reading data to the data acquisition module, and then the data acquisition module sends these data to the data classification module, and the data classification module classifies the characteristic data parameters in these data and associates alarms.

[0010] Preferably, the data classification module classifies and arranges the data in chronological order, removes useless data and garbled characters, calibrates the characteristic data, and stores the characteristic data in a separate space. After the data classification is completed, the data classification module sends the data to the data cleaning module.

[0011] Preferably, the data cleaning module can screen these data, first screen out the calibrated feature data and store them separately, then analyze the remaining data to form a systematic data stream for analysis, and then send the data stream to the data analysis module.

[0012] Preferably, the data analysis module performs secondary analysis on the data stream, associates the data collected by the secondary pressure sensor, temperature sensor and flow sensor in each on-site gas analyzer with the data of the CQC analyzer, uses and optimizes GMS rules to establish an analysis system, and then sends the analyzed data to the data processing background.

[0013] Preferably, the data processing background will analyze the data again through the fault prediction software, import the data into the AI ​​model for model building, and display the synchronous design fault prediction through AI intelligent analysis.

[0014] Preferably, the fault prediction software will train and infer the constructed model, continuously optimize the model, and repeatedly perform cycle tuning to complete the application of the model. Then the fault prediction software will associate the mature model with the on-site GMS system, process and analyze the on-site data, and output early warning and alarm signals to the corresponding system, which will eventually be processed by different on-site systems.

[0015] Preferably, the data processing background will deploy the trained model on the field system according to the application, and the data processing background will provide a communication interface according to the TCP / IP protocol and provide signals compatible with the customer's GMS operating software.

[0016] Technical effects and advantages of the present invention: The intelligent electronic bulk gas station quality and safety management CQC analysis system proposed by the present invention has the following advantages compared with the prior art:

[0017] 1. The present invention uses artificial intelligence technology and algorithms to analyze, monitor and manage the key data of the gas used, so as to monitor the gas quality, flow pressure, spare reserve and safety status in real time, and can associate the main data of the gas and the direct underlying data with the direct alarm rules, upgrade to multi-dimensional data parameters and analysis, and form on-site gas linkage, interactive mass analysis and optimization of quality, efficiency and safety through artificial intelligence models and algorithm optimization;

[0018] 2. The present invention can digitize and make real-time traditional paper data and fault analysis reports, and can provide the site with system visualization, rules, real-time supervision, classification control, machine learning, deep learning and artificial intelligence functions, to achieve intelligent, predictable and dynamic elastic manufacturing. At the same time, it can combine peripheral environmental data to form real-time monitoring and prediction of factory-level quality, efficiency, power consumption and safety, thereby upgrading the safe operation and maintenance of on-site personnel to intelligent and highly reliable operation and maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A block diagram of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0021] The present invention provides Figure 1 The intelligent electronic bulk gas station quality and safety management CQC analysis system includes on-site gas analyzer, CQC analyzer, controller, fault alarm unit, data collection unit and data processing background;

[0022] The fault alarm unit includes a data acquisition module, a data classification module, a data cleaning module and a data analysis module;

[0023] The data collection unit includes a pressure sensor, a flow sensor, and a temperature sensor;

[0024] The data processing backend is pre-installed with fault prediction software, which includes model building, model training, model reasoning and model application functions;

[0025] The data acquisition module, data classification module, data cleaning module and data analysis module are all connected to the controller, the field gas analyzer, CQC analyzer, pressure sensor, flow sensor and temperature sensor are all connected to the data acquisition module, and the data analysis module is connected to the data processing background;

[0026] The on-site gas analyzer and CQC analyzer monitor the gas, and monitor the pressure, flow and temperature inside the gas in real time through the pressure sensor, flow sensor and temperature sensor, and send the reading data to the data acquisition module, and then the data acquisition module sends these data to the data classification module, and the data classification module classifies the characteristic data parameters in these data and associates alarms;

[0027] The data classification module classifies and arranges these data in chronological order, removes useless data and garbled codes, calibrates the feature data, and stores these feature data in a separate space. After the data classification is completed, the data classification module sends these data to the data cleaning module;

[0028] The data cleaning module can filter these data, first filter out the calibrated feature data and store them separately, then analyze the remaining data to form a systematic data stream for analysis, and then send the data stream to the data analysis module;

[0029] The data analysis module performs secondary analysis on the data stream, associates the data collected by the secondary pressure sensor, temperature sensor and flow sensor in each on-site gas analyzer with the data of the CQC analyzer, uses and optimizes the GMS rules to establish an analysis system, and then sends the analyzed data to the data processing background;

[0030] The data processing background will analyze the data again through the fault prediction software, import the data into the AI ​​model for model building, and display the synchronous design fault prediction through AI intelligent analysis;

[0031] The fault prediction software will train and infer the built model, continuously optimize the model, and repeatedly perform cycle tuning to complete the application of the model. Then the fault prediction software will associate the mature model with the on-site GMS system, process and analyze the on-site data, and output early warning and alarm signals to the corresponding system, which will eventually be processed by different systems on site;

[0032] The data processing background will deploy the trained model on the on-site system according to the application, and the data processing background will provide a communication interface according to the TCP / IP protocol and provide signals that are compatible with the customer's GMS operating software.

[0033] This system not only connects the analyzer readings to the GMS system, but also outputs all other parameters inside the analyzer such as temperature, pressure, flow and other data, and connects to the advanced upgraded intelligent MES system and the customer's FMCS (factory monitoring system) system to realize electronic and intelligent processing of data. Changing passive management to active management and increasing real-time safety detection will prevent the occurrence of faults from the root. At the same time, it can identify hidden faults through artificial intelligence, improve production efficiency and reliability, and improve the level of management in real time and efficiently.

[0034] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. Intelligent electronic bulk gas station quality and safety management CQC analysis system, including on-site gas analyzer, CQC analyzer, controller, fault alarm unit, data collection unit and data processing background, characterized by: The fault alarm unit includes a data acquisition module, a data classification module, a data cleaning module and a data analysis module; The data collection unit includes a pressure sensor, a flow sensor and a temperature sensor; The data processing backend is pre-installed with fault prediction software, which includes model building, model training, model reasoning and model application functions; The data acquisition module, data classification module, data cleaning module and data analysis module are all connected to the controller, the on-site gas analyzer, CQC analyzer, pressure sensor, flow sensor and temperature sensor are all connected to the data acquisition module, and the data analysis module is connected to the data processing background; The on-site gas analyzer and CQC analyzer monitor the gas, and monitor the pressure, flow and temperature inside the gas in real time through pressure sensors, flow sensors and temperature sensors, and send the reading data to the data acquisition module, and then the data acquisition module sends these data to the data classification module, and the data classification module classifies the characteristic data parameters in these data and associates alarms.

2. The intelligent electronic bulk gas station quality and safety management CQC analysis system according to claim 1 is characterized by: The data classification module classifies and arranges the data in chronological order, removes useless data and garbled codes, calibrates the feature data, and stores the feature data in a separate space. After the data classification is completed, the data classification module sends the data to the data cleaning module.

3. The intelligent electronic bulk gas station quality and safety management CQC analysis system according to claim 1 is characterized by: The data cleaning module can screen these data, first screen out the calibrated feature data and store them separately, then analyze the remaining data to form a systematic data stream for analysis, and then send the data stream to the data analysis module.

4. The intelligent electronic bulk gas station quality and safety management CQC analysis system according to claim 1 is characterized by: The data analysis module performs secondary analysis on the data stream, associates the data collected by the secondary pressure sensor, temperature sensor and flow sensor in each on-site gas analyzer with the data of the CQC analyzer, uses and optimizes the GMS rules to establish an analysis system, and then sends the analyzed data to the data processing background.

5. The intelligent electronic bulk gas station quality and safety management CQC analysis system according to claim 1 is characterized by: The data processing background will analyze the data again through the fault prediction software, import the data into the AI ​​model for model building, and display the synchronous design fault prediction through AI intelligent analysis.

6. The intelligent electronic bulk gas station quality and safety management CQC analysis system according to claim 1 is characterized by: The fault prediction software will train and infer the built model, continuously optimize the model, and repeatedly perform cycle tuning to complete the application of the model. The fault prediction software will then associate the mature model with the on-site GMS system, process and analyze the on-site data, and output early warning and alarm signals to the corresponding systems, which will ultimately be processed by different on-site systems.

7. The intelligent electronic bulk gas station quality and safety management CQC analysis system according to claim 1 is characterized by: The data processing background will deploy the trained model on the field system according to the application, and the data processing background will provide a communication interface according to the TCP / IP protocol, and provide signals compatible with the customer's GMS operating software.

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