KR20230061068A - System and method for matching and analyzing real-time process data of semiconductor equipment - Google Patents

Abstract

A system and method for matching and analyzing real-time process data of semiconductor equipment are disclosed. This system includes a plurality of semiconductor devices, an analysis server that collects real-time process data from the plurality of semiconductor devices, and matches and compares and analyzes the collected real-time process data for each semiconductor device, and matching/receiving process data received from the analysis server. It includes a plurality of GUI (Graphic User Interface) devices that visualize and output comparative analysis data.

Description

System and method for matching and analyzing real-time process data of semiconductor equipment}

The present invention relates to a system and method for matching and analyzing real-time process data of semiconductor equipment.

Currently, semiconductor/FPD (Flat Panel Display) equipment field operation of domestic companies is operated by monitoring and controlling the process status using the process control program installed in each equipment in front of the equipment on site. According to this method, when an error occurs in semiconductor/FPD equipment, it is possible to determine whether or not there is an error through a manufacturing execution system (MES) of a semiconductor/FPD manufacturer or a warning light/buzzer.

In the semiconductor/FPD facility process, after the process has been performed step by step, it is determined whether the product is defective in the measurement process, and when it is confirmed that the product has a defect, various log files (Log file), so a lot of time is wasted in analyzing the cause of the abnormality and deriving a solution to the problem. In addition, we are facing a reality in which yield and productivity depend on the ability of field engineers.

On the other hand, domestic semiconductor/FPD equipment is currently maintained and managed only with process control and FDC (Fault Detection and Classification) functions within the equipment. Therefore, semiconductor/FPD equipment is highly dependent on foreign markets, and in a situation where most semiconductor manufacturers rely on imports, the cost of maintaining equipment for major overseas manufacturers is also high. Overseas manufacturers provide and operate an Equipment Engineering System (EES) for equipment maintenance, and this system's main functions are process control, equipment productivity, and equipment abnormality monitoring and control, and maintenance costs are high.

The problem to be solved is to collect real-time process data from semiconductor equipment, analyze it through data mining, derive appropriate process parameters, and provide a system and method for providing data visualization before and after the occurrence of abnormalities in semiconductor equipment. .

According to one feature, a system for matching and analyzing real-time process data of semiconductor equipment, which collects a plurality of semiconductor devices and real-time process data from the plurality of semiconductor devices, and matches and compares the collected real-time process data for each semiconductor device. It includes an analysis server for analysis, and a plurality of GUI (Graphic User Interface) devices that visualize and output matching/comparison analysis data of the process data received from the analysis server.

The analysis server collects real-time process data from the plurality of semiconductor devices, matches and compares and analyzes the plurality of data collection modules that are dedicated interfaces for Ethernet communication with the plurality of semiconductor devices, and compares and analyzes the real-time process data. A plurality of data analysis modules respectively corresponding to the data collection modules of, and a plurality of GUI interface modules outputting matching and comparative analysis results of the real-time process data in the form of graphs or screens and corresponding to the plurality of data analysis modules, respectively. can do.

The plurality of data collection modules, the plurality of data analysis modules, and the plurality of GUI interface modules may perform internal communication using a message queue method.

The system is an RDBMS that stores standardized data having a relational structure of at least one of user information, semiconductor equipment information, process parameters, recipes, equipment setting information, events, and alarm information, and real-time time series such as process data and process element values. A NoSQLDB for storing unstructured data managed as information may be further included.

The plurality of data analysis modules express the value of each element of the process data stored in a predetermined time condition before/after the occurrence of the abnormality and the time of occurrence of the abnormality in a graph, and the GUI device corresponding to the graph through the GUI interface module. can be output as

The plurality of data analysis modules convert process data received and stored in real time from the semiconductor equipment into a packet format and expressed as a screen for checking a detailed state, and the screen corresponds to the screen through the GUI interface module. You can output to a GUI device.

The plurality of data analysis modules subdivide the process data of the semiconductor equipment into at least one unit of a lot or a substrate step to analyze trends and patterns, and based on the trends and patterns An error that does not meet the criteria (Nelson Rules) for determining a predetermined defect may be detected.

According to another feature, as a method for matching and analyzing real-time process data of semiconductor equipment by an analysis server, the step of collecting real-time process data from a plurality of semiconductor equipment, matching and comparative analysis of the collected real-time process data for each of a plurality of semiconductor equipment Generating one result data, expressing the result data in the form of a graph or screen, and outputting the result data in the form of a graph or screen to a plurality of GUI (Graphic User Interface) devices.

In the generating step, the process data of the semiconductor equipment is subdivided into at least one unit of a lot or a substrate step to analyze trends and patterns, and based on the trends and patterns, in advance Error data that does not meet the criteria (Nelson Rules) for determining a predetermined defect may be generated.

In the outputting, the value of each element of the process data stored in the pre-determined time condition before/after the occurrence of the abnormality and the time of occurrence of the abnormality may be expressed as a graph.

In the outputting, process data received and stored in real time from the semiconductor equipment may be converted into a packet format and displayed on a screen for checking a detailed state.

According to the embodiment, by collecting process data of each semiconductor equipment through real-time process data matching and analysis between semiconductor/FPD equipment, and analyzing data trends by process and time series, problems can be quickly identified and optimal recipes can be applied. possible.

In addition, when an abnormality occurs in semiconductor/FPD equipment, data before/after the abnormality can be visualized using process data collected in real time.

In addition, based on equipment master data, process data, and equipment log data already possessed by semiconductor/FPD equipment manufacturers, obstacle factors are derived through data analysis, and rules related to mass production yield are selected and applied. By doing so, it is possible to simulate basic demonstration results.

1 is a configuration diagram of a real-time process data matching/analysis system according to an embodiment.
2 is a block diagram showing an internal configuration of a semiconductor equipment (EQP) according to an embodiment.
3 is a block diagram showing the detailed configuration of an EQP according to an embodiment.
4 is a block diagram showing a detailed configuration of an analysis server according to an embodiment.
5 illustrates the configuration of an EQP optimal process condition derivation and application simulation system according to an embodiment.
6 shows a process of detecting errors and reference types through application of EQP process data rules according to an embodiment.
7 is an exemplary view illustrating analysis and visualization of characteristics of process parameter/process data matching result data between EQPs according to an embodiment.

Hereinafter, with reference to the accompanying drawings, embodiments of the present invention will be described in detail so that those skilled in the art can easily carry out the present invention. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a certain component is said to "include", it means that it may further include other components without excluding other components unless otherwise stated.

In addition, terms such as “…unit”, “…unit”, and “…module” described in the specification mean a unit that processes at least one function or operation, which may be implemented by hardware or software or a combination of hardware and software. can

Devices described in the present invention are composed of hardware including at least one processor, memory device, communication device, and the like, and a program to be executed in combination with the hardware is stored in a designated place. The hardware has the configuration and capability to implement the method of the present invention. The program includes instructions implementing the operating method of the present invention described with reference to the drawings, and implements the present invention in combination with hardware such as a processor and a memory device.

In this specification, "transmission or provision" may include not only direct transmission or provision, but also indirect transmission or provision through another device or by using a detour path.

Expressions written in the singular in this specification may be interpreted in the singular or plural unless an explicit expression such as “one” or “single” is used.

In this specification, like reference numerals refer to like elements, regardless of drawing, and "and/or" includes each and every combination of one or more of the recited elements.

In this specification, terms including ordinal numbers such as first and second may be used to describe various components, but the components are not limited by the terms. These terms are only used for the purpose of distinguishing one component from another. For example, a first element may be termed a second element, and similarly, a second element may be termed a first element, without departing from the scope of the present disclosure.

In the flowcharts described herein with reference to the drawings, the order of operations may be changed, several operations may be merged, certain operations may be divided, and certain operations may not be performed.

1 is a configuration diagram of a real-time process data matching/analysis system according to an embodiment, and FIG. 2 is a block diagram showing an internal configuration of a semiconductor equipment (EQP) according to an embodiment.

Referring to FIG. 1 , the real-time process data matching/analysis system matches and analyzes real-time process data between semiconductor/flat panel display (FPD) equipment. Here, the semiconductor/FPD equipment may be collectively referred to as semiconductor equipment (Equipment, hereinafter referred to as 'EQP'). Also, in this specification, equipment may refer to semiconductor equipment or EQP.

The real-time process data matching/analysis system includes a matching/analysis system 100 and a monitoring system 200. The matching/analysis system 100 includes a plurality (n) of EQPs 110, a switch hub 120, and an analysis server 130. The plurality of EQPs 110 are connected to the analysis server 130 through the switch hub 120.

The monitoring system 200 includes an operation detection server (Fault Detection and Classification, hereinafter collectively referred to as 'FDC') 210 and a plurality of GUI (Graphic User Interface) devices 220 . The FDC server 210 is connected to the analysis server 130 and is connected to a plurality of GUI devices 200 .

Here, the analysis server 130 and the GUI device 220 may be computing devices having at least one processor, memory, and storage.

The EQP 110 is a device that performs a semiconductor manufacturing process, and may be a semiconductor device or FPD. The analysis server 130 may receive and store real-time process data from the EQP 110 and perform matching and comparison analysis. The GUI device 220 visualizes and outputs matching/comparison analysis data of process data collected from the analysis server 130 .

The EQP 110 may include an EQP interface module 111, a Cluster Tool Controller (CTC) 112, a Transfer Module Controller (TMC) 113, and a Process Module Controller (PMC) 114.

The EQP interface module 111 is connected to the analysis server 130 through the switch hub 120. The EQP interface module 111 transmits process data to the analysis server 130 through the switch hub 120.

The EQP interface module 111 is installed in the EQP 110 and interworks with the process control program.

The EQP control unit 115 transmits processing/table history/recipe/variable/data collection of parameters (DCOP) data of the EQP 110 to the analysis server 130. can

The CTC 112 outputs control data for operating each component of the semiconductor manufacturing equipment according to the operator's input of an operation command, receives the measured operating state data from each semiconductor manufacturing equipment, samples and stores it, and allows the operator to monitor it. displayed on the screen.

TMC 113 is an abbreviation of Transfer Module Controller, and is in charge of transferring wafers.

The PMC 114 is an abbreviation of a process module controller, and plays a role in overall control of vacuum, plasma, temperature, gas flow, etc. in order to control a process for a wafer.

The analysis server 130 collects process data including status and process speed data, alarm data, process parameters, etc. from the EQPs 110 in real time, and matches and compares each process data for each detailed process by time. can do.

The analysis server 130 is a real-time process data matching and comparative analysis technology, and may present an appropriate recipe or process parameters for improving the production yield of semiconductor/FPD equipment and apply them to each EQP 110 .

Referring to FIG. 2, the analysis server 130 includes a plurality of data collection modules 131, a plurality of data analysis modules 132, and a plurality of GUI (Graphic User Interface) interface modules. (133), a data storage module (Database Module) 134 and an analysis database (135).

The plurality of EQPs 110 include respective EQP interface modules 111 .

The plurality of GUI devices 220 include respective communication modules 221 and screen viewers 222 .

The plurality of data collection modules 131 receive real-time process data from the plurality of EQPs 110 through Ethernet communication and transmit the data to the plurality of data analysis modules 132 . At this time, the plurality of data collection modules 131 may collect and transmit real-time process data collection management and process result data, that is, process speed data, process parameters, detailed process data, and recipes to the plurality of data analysis modules 132. .

The plurality of data analysis modules 132 may generate data obtained by matching, comparing, and analyzing the received real-time process data. The plurality of data analysis modules 132 analyze real-time process data and process result data through data mining to derive appropriate process parameters, and analyze obstacles through data visualization before/after the EQP 110 abnormal occurrence point. can

Matching/comparison analysis data generated by the plurality of data analysis modules 132 may be stored in the analysis database 135 through the plurality of data storage modules 134 .

Matching/comparison analysis data generated by the plurality of data analysis modules 132 may be transmitted to the plurality of GUI devices 220 through the plurality of GUI interface modules 133 .

At this time, the analysis server 130 includes a plurality of data collection modules 131, a plurality of data analysis modules 132, and a plurality of GUI interface modules for processing each process data for each EQP 110 and the GUI device 220. (133).

The plurality of data collection modules 131 communicate with the plurality of EQP interface modules 111 through Ethernet. A plurality of data collection modules 131 may be provided for each EQP 110 . That is, the data collection module #1 (131) is dedicated to Ethernet communication with the EQP interface module #1 (111) of EQP #1 (110), and the data collection module #2 (131) is the EQP of EQP #2 (110). Ethernet communication with interface module #2 (111) is dedicated, and data collection module #n (131) is dedicated to Ethernet communication with EQP interface module #n (111) of EQP #n (110).

The plurality of data analysis modules 132 receive real-time process data from the plurality of EQP interface modules 111 and transmit the received real-time process data to the plurality of data analysis modules 132 and the plurality of data storage modules 134. can

The plurality of data analysis modules 132 collect real-time process data of each EQP from the plurality of data collection modules 131 . That is, the data analysis module #1 (132) receives real-time process data of the EQP #1 (110) from the data collection module #1 (131) and transfers it to the GUI interface module #1 (133). Data analysis module #2 (132) receives real-time process data of EQP #2 (110) from data collection module #2 (131) and transfers it to GUI interface module #2 (133). Data analysis module #n (132) receives real-time process data of EQP #n (110) from data collection module #n (131) and transfers it to GUI interface module #n (133).

According to an embodiment, the plurality of data analysis modules 132 may use Tool To Tool Match (TTTM) technology. TTTM is a technology developed for analysis of logs and data created in equipment based on .NET Frameworks 4.0, and a plurality of data analysis modules 132 execute TTTM programs to analyze each used in a plurality of EQPs 110. It can provide a function to compare Recipe, FA Variable, and process data in a 1:1 ratio.

The plurality of data analysis modules 132 collect and store each real-time process data and recipe of the process for each EQP 110, and use real-time or stored data to simultaneously collect and store data time series of several EQPs 110. A comparative analysis can be performed. Conventionally, it is difficult to collect process data in real time, so log files and recipes written in semiconductor/FPD equipment are read from semiconductor/FPD equipment and the data is compared and analyzed, so only at the site where semiconductor/FPD equipment is installed it is possible to check For external use, after copying the corresponding log file and recipe from the semiconductor/FPD equipment, it could be used after saving to a separate computer where the TTTM program was installed. Therefore, comparison between semiconductor/FPD equipment is a structure in which only 1:1 comparison is possible. However, in an embodiment of the present invention, time-series comparative analysis of data of several EQPs 110 may be performed at the same time.

In this way, the plurality of data analysis modules 132 compare/match information of key parameters and recipes of process data collected from multiple EQPs 110 and log files recorded in equipment between equipment. and can be analyzed. Conventionally, EQP provides only information managed by the manufacturer's MES or FDC, so to collect accurate process data, interworking with process control programs installed in the equipment and the contents of the log file are required. However, the embodiment of the present invention can derive optimal process conditions through process data comparison/matching analysis between EQPs 110 and apply them to the EQPs 110.

The plurality of data analysis modules 132 may generate a specification model by applying a statistical technique based on process reference data and process information, and detect a change in process information of each single EQP 110 among the EQPs 110. .

The plurality of data analysis modules 132 may provide graphs showing data state monitoring and comparison of main state values using process data.

In addition, the data analysis module 132 derives obstacles through data analysis based on the equipment master data, process data, and equipment log data of the EQP 110, and selects rules related to mass production yield By applying it, it is possible to provide a basic demonstration result simulation.

The communication modules 221 mounted in a plurality of GUI 220 devices communicate with independent dedicated GUI interface modules 133 . The communication modules 221 receive data obtained by matching/comparing and analyzing real-time process data from each of the GUI interface modules 133 .

The communication modules 221, based on the matching/comparison analysis data received from the GUI interface modules 133, show the entire EQP operating situation visualizing the state of the EQPs 110 through screen viewers 222 connected to each other. can be printed out. The entire EQP operation situation may be implemented in a graph form optimized for time series matching data between EQPs 110.

The communication modules 221 may provide an alarm function when an event occurs based on matching/comparison analysis data received from the GUI interface modules 133 . The communication modules 221 access the analysis database 135 through the GUI interface modules 133 and provide query and search functions for each stored EQP 110 by condition, such as process data, process parameters, and recipes. can do.

3 is a block diagram showing a detailed configuration of an EQP according to an embodiment, and shows a detailed configuration of the EQP 110 described in FIGS. 1 and 2 .

Referring to FIG. 3 , the EQP 110 may include an EQP interface module 111, a CTC 112, a TMC 113, a PMC 114, and an EQP control device 115. Since the EQP interface module 111, the CTC 112, the TMC 113, and the PMC 114 have been described in FIGS. 1 and 2, their descriptions are omitted.

The EQP control unit 115 includes a viewer 115-1, an analyzer 115-2, a local connector 115-3, a remote connector 115-4, a remote receiver 115-5, and an equipment database 115-3. 6) may be included.

The viewer 115-1 outputs processing data, table history data, recipes, variables, and DCOP collected from the semiconductor process modules CTC 112, TMC 113, and PMC114 to the analyzer 115-2.

The analyzer 115-2 transmits the processing data, table history data, recipe, variable, and DCOP collected from the viewer 115-1 to the local connector 115-3, the remote connector 115-4, and the remote receiver 115-2. 5) through the EQP interface module 111. These processing data, table history data, recipes, variables, and DCOP are transmitted to the analysis server 130 through the EQP interface module 111.

The analyzer 115-2 stores processing data, table history data, recipes, variables, and DCOP collected from the viewer 115-1 in the equipment database 115-6.

4 is a block diagram showing a detailed configuration of an analysis server according to an embodiment.

At this time, Figure 4 shows a detailed configuration of the embodiment of the analysis server 130 described in Figures 1 and 2.

Referring to FIG. 4, the analysis server 130 includes a plurality of data collection modules 131, a plurality of data analysis modules 132, a plurality of GUI interface modules 133, a data storage module 134, a relational database (RDBMS) Management System) 135a, NoSQLDB 135b, main processor 136, batch processor 137, and message queue handler 138.

As described in FIG. 2, the plurality of data collection modules 131, the plurality of data analysis modules 132, and the plurality of GUI interface modules 133 are connected to the plurality of EQPs 110 and the plurality of GUI devices 220, respectively. interlock

At this time, in order to prevent message bottlenecks, each EQP is interlocked with an independent dedicated interface, that is, a plurality of data collection modules 131, and a plurality of data collection modules 131 and a plurality of data analysis modules 132 are connected to a message queue (Message Queue). Queue) method internal communication can be performed.

The plurality of data analysis modules 132 may compare and analyze real-time large-capacity data processing techniques, for example, a distributed processing method or a streaming method, and apply a data processing method suitable for operation for each EQP.

The data storage module 134 transmits standardized data collected from the EQPs 110 by the plurality of data collection modules 131, for example, equipment information, process parameters, recipes, etc. to the message queue handler 138. It is received by the main processor 136 through and stores such standardized data in the RDBMS 135a, which is a relational database system.

The RDBMS 135a stores information requiring a relational structure such as user information, EQP information, process parameters, equipment setting information, recipe information, events, and alarms.

The plurality of data analysis modules 132 may store unstructured data, eg, process data, variables, etc., in the NoSQLDB 135b that does not define a schema.

The NoSQLDB 135b stores data to be managed as real-time time series information, such as process data and process factor values, and can be stored in a key value format or column family format.

The plurality of data analysis modules 132 may simultaneously perform matching of process parameters and/or process data of several EQPs 110 based on Tool To Tool Match (TTTM) technology.

The plurality of data analysis modules 132 may select process data matching factors. At this time, the data to be matched may include Processing, Table History, Recipe, Variable, DCOP (Data Collection of Parameters), and the like, and a process data element to be added may be selected.

Unlike the prior art, the plurality of data analysis modules 132 may store data to be matched in a separate database table.

The plurality of data analysis modules 132 may display different data and display detailed item graphs when matching data is analyzed. The plurality of data analysis modules 132 may display different data as a result of data matching with separate shades, select an item requiring detailed analysis among matching data, and display it as a graph. The plurality of data analysis modules 132 may perform correlation analysis between EQPs through matching data mining.

The plurality of data analysis modules 132 may detect errors and standard types through application of EQP process data rules, and model failure types.

The plurality of data analysis modules 132 may provide a rule service for determining defects. The plurality of data analysis modules 132 subdivide the process data of each EQP 110 in Lot/Substrate Step units, analyze trends and patterns, and determine defects (Nelson Rules) can be reflected to detect errors in problematic sections and standard types.

The plurality of data analysis modules 132 may detect errors that do not meet predetermined criteria for determining defects based on the analyzed trends and patterns. By repeating this process, the plurality of data analysis modules 132 may collect various errors and criterion types, and may model process failure types that may occur in various situations.

The plurality of data analysis modules 132 may analyze characteristics of process parameters and/or process data matching result data between the EQPs 110 .

The plurality of data analysis modules 132 may perform statistical logic suitable for EQP matching data mining, for example, statistical logic for data characteristic analysis and test verification of at least one of univariate statistics, model-based selection, and iterative selection.

The plurality of data analysis modules 132 may apply statistical logic to process parameters and/or process data matching data between EQPs 110 to calculate failure threshold standards according to process data characteristic analysis.

The plurality of data analysis modules 132 may perform correlation analysis between EQPs 110 through process failure type modeling and process data characteristic analysis and visualization. The plurality of data analysis modules 132 may derive a reference condition for predicting a situation before an equipment failure occurs by modeling the failure type.

The plurality of data analysis modules 132 may compare production efficiencies between equipments by analyzing and visualizing process data characteristics. By identifying the correlation between production efficiency and process conditions, it is possible to suggest optimal process conditions (recipe, variables, etc.).

The plurality of data analysis modules 132 may verify and verify the production process result by applying the optimal process conditions to the EQP 110 .

The plurality of data analysis modules 132 may perform obstacle factor analysis through data visualization before/after the point of occurrence of an abnormality between the EQPs 110. In this case, the plurality of data analysis modules 132 may visualize data before/after the EQP abnormality occurs.

The plurality of data analysis modules 132 collects real-time EQP status data and process data, and at the time of EQP abnormality, the data is stored in a separate alarm table along with alarm occurrence time and corresponding alarm information. Together, real-time status data and process data can be stored. Based on the stored data, the plurality of data analysis modules 132 may search the EQP abnormal occurrence data history under conditions for each period (month/week/day).

The plurality of data analysis modules 132 may check visualization content by selecting search result data. The plurality of data analysis modules 132 may perform obstacle factor analysis through visualization of data before/after the point of occurrence of the EQP abnormality.

According to one embodiment, the plurality of data analysis modules 132 may graph the value of each element of the process data stored in the time condition before/after the occurrence of the abnormality set by the user and the time of occurrence of the abnormality in a graph.

According to another embodiment, the plurality of data analysis modules 132 convert the process data received and stored in real time from the EQP 110 into a packet format so that the user checks the detailed state of the actual EQP 110. It can be expressed on the screen in the same way as

The plurality of data analysis modules 132 can analyze the cause of the EQP abnormality through visualization data expressed in graphs or screens, and derive the correlation of process data and the influence between elements based on the consultation data input from the EQP expert. there is.

The plurality of data analysis modules 132 may derive EQP optimal process conditions and perform application simulation.

The main processor 136 operates in conjunction with the message queue handler 138 and the GUI interface module 133, and in conjunction with the data storage module 134.

The main processor 136 may transfer the standardized data collected from the message queue handler 138 to the data storage module 134.

The main processor 136 may transmit standardized data and unstructured data collected from the message queue handler 138 to the GUI device 220 through the GUI interface module 133 .

The batch processor 137 may perform a batch function of data stored in the NoSQLDB 135b.

5 illustrates the configuration of an EQP optimal process condition derivation and application simulation system according to an embodiment.

Referring to FIG. 5 , a plurality of EQP simulators 300 are connected to the analysis server 130, and the analysis server 130 is connected to the GUI device 220.

The EQP simulator 300 is an EQP for test verification and performs a simulation function by the analysis server 130 .

The data collection module 131 of the analysis server 130 performs EQP interface, state data collection, process data collection, EQP event collection, and setting parameter collection.

The data analysis module 132 of the analysis server 130 may perform EQP data trend analysis, alarm/state relationship analysis, and job/process/recipe relationship analysis.

The data storage module 133 of the analysis server 130 stores EQP reference information, EQP operation information, status data, process data, EQP events, setting parameters, and various histories generated by the data analysis module 132, and It can perform information management and periodic data backup.

The data analysis module 132 of the analysis server 130 may perform a simulation function. At this time, the data analysis module 132 may collect data transmitted/received in real time during the process of the EQP 110 . The data analysis module 132 may generate situation analysis data that may occur during the process of the EQP 110 . The data analysis module 132 may generate situation analysis data such as process parameters in a normal operation/failure situation.

The data analysis module 132 may create scenarios for each situation based on data collected during the process and situation analysis data that may occur. The data analysis module 132 may implement a setting editor for changing scenarios and recipes, changing process data values, and the like.

The data analysis module 132 may perform system verification using the EQP simulator 300 . The data analysis module 132 may vary the data transmission/reception speed of the EQP simulator 300 to verify the system data processing speed.

The data analysis module 132 generates a failure situation using the EQP simulator 300 to perform system failure recognition function confirmation and failure factor analysis, correlation analysis between EQPs, and production volume prediction using the EQP simulator 300. . At this time, the data analysis module 132 may transmit normal process data and discontinuous event data from the EQP simulator 300 to predict the production amount according to the maximum production amount and the number of failures.

6 shows a process of detecting errors and reference types through application of EQP process data rules according to an embodiment, and FIG. 7 is an exemplary diagram illustrating analysis and visualization of characteristics of data as a result of matching process parameters/process data between EQPs according to an embodiment. .

Referring to FIG. 6 , the data analysis module 132 analyzes the raw data collected from the EQPs 110 (S101) and analyzes trends/patterns of process data based on this (S102).

The data analysis module 132 may apply a predefined rule service to the trend/pattern analysis data (S103) and perform error detection and confirmation (S104).

Referring to FIG. 7 , the data analysis module 132 may apply a rule service that expresses trend/pattern analysis in a graph form and sets threshold values according to statistical logic.

The embodiments of the present invention described above are not implemented only through devices and methods, and may be implemented through programs that realize functions corresponding to the configuration of the embodiments of the present invention or a recording medium on which the programs are recorded.

Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements made by those skilled in the art using the basic concept of the present invention defined in the following claims are also included in the scope of the present invention. that fall within the scope of the right.

Claims (11)

A system that matches and analyzes real-time process data of semiconductor equipment,
a plurality of semiconductor equipment;
An analysis server that collects real-time process data from the plurality of semiconductor devices, matches and compares and analyzes the collected real-time process data for each semiconductor device; and
A plurality of GUI (Graphic User Interface) devices that visualize and output matching/comparison analysis data of process data received from the analysis server
Including, system. In paragraph 1,
The analysis server,
A plurality of data collection modules that collect real-time process data from the plurality of semiconductor devices and are dedicated interfaces for Ethernet communication with the plurality of semiconductor devices;
A plurality of data analysis modules that match and compare and analyze the real-time process data and respectively correspond to the plurality of data collection modules, and
A plurality of GUI interface modules that output matching and comparative analysis results of the real-time process data in the form of graphs or screens and respectively correspond to the plurality of data analysis modules.
Including, system. In paragraph 2,
The plurality of data collection modules, the plurality of data analysis modules, and the plurality of GUI interface modules,
A system that performs internal communication of the Message Queue method. In paragraph 2,
An RDBMS that stores standardized data having a relational structure of at least one of user information, semiconductor equipment information, process parameters, recipes, equipment setting information, event, and alarm information, and
NoSQLDB that stores unstructured data managed as real-time time series information, such as process data and process factor values
Further comprising a system. In paragraph 2,
The plurality of data analysis modules,
A system that expresses the value of each element of process data stored in a pre-determined time condition before/after the occurrence of an abnormality and the time of occurrence of an anomaly as a graph, and outputs the graph to a corresponding GUI device through the GUI interface module. In paragraph 2,
The plurality of data analysis modules,
A system that converts the process data received and stored in real time from the semiconductor equipment into a packet format, expresses it as a screen for checking a detailed state, and outputs the screen to a corresponding GUI device through the GUI interface module. In paragraph 2,
The plurality of data analysis modules,
Criteria for analyzing trends and patterns by subdividing the process data of semiconductor equipment into at least one unit of Lot or Substrate Step, and determining predetermined defects based on the trends and patterns A system that detects errors that do not satisfy the (Nelson Rules). As a method for an analysis server to match and analyze real-time process data of semiconductor equipment,
Collecting real-time process data from a plurality of semiconductor equipment;
generating data as a result of matching and comparative analysis of the collected real-time process data for each of a plurality of semiconductor equipment; and
Expressing the result data in the form of a graph or screen, and outputting the result data in the form of a graph or screen to a plurality of GUI (Graphic User Interface) devices.
Including, method. In paragraph 8,
The generating step is
Criteria for analyzing trends and patterns by subdividing the process data of semiconductor equipment into at least one unit of Lot or Substrate Step, and determining predetermined defects based on the trends and patterns A method for generating error data that does not satisfy (Nelson Rules). In paragraph 8,
The outputting step is
A method of graphing the value of each element of the process data stored in a pre-determined time condition before/after the occurrence of an anomaly and the time of occurrence of an anomaly. In paragraph 8,
The outputting step is
A method of converting the process data received and stored in real time from the semiconductor equipment into a packet format and expressing it on a screen for checking a detailed status.

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