Intelligent monitoring method and system and semiconductor production system

Abstract

The invention provides an intelligent monitoring method and system and a semiconductor production system, and the method comprises the steps: summarizing the original data of each control system, carrying out the intelligent calculation, and generating the information of each preset technological process with a technological region as a unit; monitoring the operation condition of a control system and the production condition of process equipment in each process area, displaying actual process flow state information, a currently executed instruction and a completion condition on a user interface corresponding to each process area, and prompting an instruction to be executed in the next step; judging whether the actual production condition is consistent with a preset production condition or not based on a comparison result of the duration of each process and the actual processing duration; and if not, determining an abnormal reason by taking the process flow sequence as a judgment logic and sending out an alarm signal. According to the invention, the system operation condition of each production scene of the automatic production line is intelligently planned and monitored from the perspective of AI, systematized arrangement and intelligent judgment are carried out in all directions, actions are indicated, rapid early warning is carried out, problems are solved, and the production target is achieved.

Description

Technical Field

[0001] This invention relates to the field of semiconductor wafer fabrication and manufacturing, and in particular to an intelligent monitoring method, system, and semiconductor manufacturing system. Background Technology

[0002] A fab (fabrication plant) is a factory that manufactures semiconductor devices, equipped with various devices that execute semiconductor manufacturing processes. Traditionally, fabs relied on manual operation of various production equipment, which resulted in low efficiency, the impact of dust generated by workers on product quality, and high labor costs. To improve production efficiency, output, product yield, and reduce costs, fabs have gradually shifted from manual to semi-automated operation, with increasing levels of automation.

[0003] However, the effect of semi-automation on improving production efficiency, output, product yield, and reducing costs is limited. How to achieve fully automated production in a fab plant and further improve system operating efficiency and production efficiency has become one of the problems that urgently need to be solved by those skilled in the art.

[0004] It should be noted that the above description of the technical background is only for the purpose of providing a clear and complete explanation of the technical solutions of the present invention and facilitating understanding by those skilled in the art. It should not be assumed that the above technical solutions are known to those skilled in the art simply because they have been described in the background section of this invention. Summary of the Invention

[0005] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide an intelligent monitoring method, system, and semiconductor manufacturing system to solve the problem that the system operating efficiency and production efficiency in the semiconductor device manufacturing process need to be improved in the prior art.

[0006] To achieve the above and other related objectives, the present invention provides an intelligent monitoring method, which includes at least:

[0007] 1) Summarize the raw data of each control system in the production process, perform intelligent calculations on the raw data, and generate preset process flow information for each process area by process area.

[0008] 2) When the process equipment is running, the operation status of the control system and the production status of the process equipment in each process area are monitored. At the same time, the actual process flow status information, the currently executed instructions and their completion status are displayed on the user interface corresponding to each process area, and the next instruction to be executed is prompted.

[0009] 3) Compare the duration of each process in the preset process flow information with the actual processing time, and determine whether the actual production status is consistent with the preset production status based on the comparison results; when the actual production status is inconsistent with the preset production status, the current process flow status is highlighted, the cause of the abnormality is determined by the process flow sequence, and an alarm signal is sent to the corresponding person in charge.

[0010] Optionally, the raw data of each control system includes at least one of the following: current equipment availability information, shipment information, process parameters, equipment condition information, equipment loading port status, POD location information, storage information, routine testing information, equipment maintenance information, equipment warm-up information, online product information, next destination information of goods, DUMMY wafer inventory information, and DUMMY wafer usage information.

[0011] Optionally, the actual process flow status information includes machine condition information, shipment information, work assignment information, and handling information.

[0012] Optionally, the operation of each process equipment in step 2) can be production operation, routine testing operation, or maintenance testing operation.

[0013] Alternatively, if the loading and unloading windows of the equipment are idle or occupied for a period of time exceeding the corresponding standard time, it is determined that there is a problem with the handling of goods;

[0014] When goods are located at the loading / unloading window, and the time during which the goods are waiting to be loaded exceeds the set time, it is determined that the corresponding device has a communication failure.

[0015] When the actual running time of the equipment exceeds or falls below the preset ratio of the process standard running time, the corresponding equipment is determined to be faulty.

[0016] Alternatively, in step 3), when a problem occurs in the handling of goods, the alarm signal is sent to the production personnel; when a communication failure occurs in the equipment, the alarm signal is sent to the machine automation duty personnel; when a equipment malfunctions, the alarm signal is sent to the machine process engineer.

[0017] To achieve the above and other related objectives, the present invention also provides an intelligent monitoring system, which includes at least:

[0018] Watchdog logic module, intelligent monitoring database, user interface and alarm management module;

[0019] The watchdog logic module is connected to each control system in the production process, monitors the operation status of the control systems in each process area and the production status of the process equipment, and makes early warning judgments based on the original data of each control system and the process sequence as the logical judgment basis.

[0020] The intelligent monitoring database is connected to the watchdog logic module and is used to aggregate data from various control systems and store the computational data of the watchdog logic module.

[0021] The user interface communicates with the intelligent monitoring database, reads data from the intelligent monitoring database, displays the actual process flow status information, the currently executed instructions and their completion status, and prompts the next instruction to be executed.

[0022] The alarm management module is connected to the watchdog logic module and sends alarm signals to the corresponding responsible person based on the early warning from the watchdog logic module.

[0023] Optionally, the user interface communicates with the intelligent monitoring database based on the WebSocket protocol.

[0024] To achieve the above and other related objectives, the present invention also provides a semiconductor manufacturing system, the semiconductor manufacturing system comprising:

[0025] At least one process equipment, control system, and the aforementioned intelligent monitoring system;

[0026] Each piece of equipment is used to execute the various technological steps in the production process;

[0027] The control system is connected to each process device and is used to control the operation of each process device;

[0028] The intelligent monitoring system is connected to the control system and is used to monitor the production process.

[0029] Optionally, the control system includes at least one of a manufacturing execution system, a material control system, a dispatching system, an equipment automation system, a standard machine interface, and an electronic shelf system.

[0030] As described above, the intelligent monitoring method, system, and semiconductor manufacturing system of the present invention have the following beneficial effects:

[0031] This invention develops an intelligent monitoring system based on process areas and provides a visual interface. The system displays the current instructions and next steps for each machine, derived from intelligent calculations. This allows monitoring personnel (production staff) in each process area of ​​the production line to intuitively and quickly see the system's operational status and actual production status in their assigned area. The system automatically displays the instructions issued to each machine and their completion status on the interface, along with information on the next steps to be taken.

[0032] This invention enables production personnel to monitor whether the current instructions and decisions given by the control system match reality and whether there are any abnormalities through visualized information. If an abnormality is found, the system can remind production personnel to quickly contact the relevant person in charge for resolution. The system will also automatically notify the relevant person in charge by phone to handle the issue in a timely manner, thereby improving system operating efficiency and production efficiency, reducing abnormality handling time, reducing machine idle time, and further increasing machine capacity. Attached Figure Description

[0033] Figure 1 The diagram shown is a flowchart of the intelligent monitoring method of the present invention.

[0034] Figure 2 A schematic diagram showing the user interface of the present invention is displayed.

[0035] Figure 3 The diagram shown is a structural schematic of the intelligent monitoring system of the present invention.

[0036] Figure 4 The diagram shown is a schematic representation of the semiconductor manufacturing system of the present invention.

[0037] Component designation explanation

[0038] 1. Intelligent monitoring system

[0039] 11 Watchdog Logic Module

[0040] 12 Intelligent Monitoring Database

[0041] 13 User Interface

[0042] 14 Alarm Management Module

[0043] 101 MES Backup Database

[0044] 102 DISPATCH Backup Database

[0045] 103 EAP Backup Database

[0046] 104 SMIF Backup Database

[0047] 105 E-RACK Backup Database

[0048] 106 MCS Backup Database

[0049] 2 Control System

[0050] 3. Process Equipment Detailed Implementation

[0051] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0052] Please see Figures 1-4 It should be noted that the illustrations provided in this embodiment are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0053] Taking an 8-inch semiconductor fab as an example, which is a semi-automated factory, if an anomaly occurs during the automated system's workflow, an alarm management system (AMS) will send emails or SMS messages to the corresponding designated responsible groups to remind personnel to check and handle the issue. However, this reminder is usually a group message that notifies production personnel (TA), machine process engineers (owners), and machine automation operators. Because the cause of the anomaly is unclear, the responsible personnel cannot determine whether they need to check the problem themselves, and there is no system or personnel to track whether the anomaly was handled in a timely manner. The general process is that the corresponding machine process engineer and production personnel arrive at the equipment site, need to check the system and standard operating procedure (SOP) documentation based on past experience, and then look for setting problems in the corresponding production system interfaces. If the process engineer or production personnel cannot identify the problem, they then notify the machine automation operator to check the system function settings by analyzing the production log (LOG) to troubleshoot and handle the problem, which is time-consuming and labor-intensive.

[0054] Furthermore, production personnel cannot monitor the specific operation of the entire production process. If the actions determined by the system do not match the actual situation, the on-site personnel cannot know it in time. For example, if a handling abnormality occurs, the current system mechanism will not promptly remind the relevant person in charge to handle it, resulting in the machine remaining idle. The problem will only be discovered when the production personnel check the corresponding production report. This failure to notify the relevant personnel in time to check and handle the problem greatly affects the efficiency of handling automation faults and the improvement of machine capacity.

[0055] Based on the above reasons, this invention proposes an intelligent monitoring method, system, and semiconductor manufacturing system. Through AI, it intelligently plans and monitors the system operation status of various production scenarios on an automated production line, comprehensively arranges and intelligently judges the system, instructs actions, and quickly notifies the relevant responsible persons to solve problems and achieve production goals.

[0056] Example 1

[0057] This embodiment provides an intelligent monitoring method, including:

[0058] 1) Summarize the raw data of each control system in the production process, perform intelligent calculations on the raw data, and generate preset process flow information for each process area by process area.

[0059] Specifically, the first step is to acquire the raw data from each control system in the production process (for example, data from the last three months is used; the specific duration can be set according to actual needs). These control systems cooperate to automate the entire production line, including but not limited to MES (Manufacturing Execution System; responsible for monitoring and controlling the production process, including production planning, equipment management, and quality control), DISPATCH (distribution system; responsible for scheduling and distributing wafers or other materials between different stages of the production line), EAP (Equipment Automation Program; responsible for controlling production equipment, collecting production data, and interacting with upper-level management systems (such as MES), SMIF (Standard Mechanical Interface; used for automated transmission and processing), E-RACK (electronic racking; a system used in the semiconductor industry for material management and storage; typically using RFID technology to achieve real-time tracking and management of sensitive materials such as wafers), and MCS (Material Control System; used to monitor, control, and manage the flow and storage of materials throughout the production line). The data in each control system contains all the information of each device executing the corresponding process, including but not limited to the current inventory information of the machine, the running information, process parameters, machine status information, the status of the machine loading port, the location information of POD (the box for holding the wafer boat and the wafer), storage information, routine testing information, machine maintenance information, machine warm-up information, online product information, the next destination information of the goods, DUMMY wafer (wafers without function, called test wafers or dummy wafers) inventory information, and DUMMY wafer usage information, which will not be elaborated here.

[0060] Specifically, in semiconductor manufacturing processes, the production line is divided into process areas (By areas, mainly used to implement key manufacturing steps). For example, these include photolithography (PHOTO), epitaxial growth (EPI), thermal processing, ion implantation (IMP), thin film deposition (TF), and chemical mechanical polishing (CMP). In practical applications, the corresponding process areas can be determined based on the actual process flow. Historical data acquired from each control system is intelligently calculated and summarized (AI) to obtain preset process flow information for each process area. This preset process flow information includes, but is not limited to, the steps to be executed (corresponding execution instructions and corresponding status information) and the duration of each step. The calculated steps and corresponding durations serve as theoretical values.

[0061] It should be noted that due to differences in the characteristics of product handling, daily machine testing, machine maintenance information, and machine warm-up information across different process areas, the corresponding intelligent calculation logic required also differs. Therefore, intelligent calculation based on each process area ensures that each process area has an appropriate intelligent calculation logic, thereby improving the accuracy of the calculations. Simultaneously, in the monitoring system developed based on process areas, the operating procedures of each process area remain independent, with no interference between them. Furthermore, the calculation and judgment rules of the corresponding process area can be switched promptly according to the actual situation of the production line, greatly improving flexibility.

[0062] 2) When the process equipment is running, the operation status of the control system and the production status of the process equipment in each process area are monitored. At the same time, the actual process flow status information, the currently executed instructions and their completion status are displayed on the user interface corresponding to each process area, and the next instruction to be executed is prompted.

[0063] Specifically, in this embodiment, the operation of the process equipment includes, but is not limited to, operation for production purposes, operation for routine daily testing, and operation for preventive maintenance (PM). Any type of operation for any purpose is applicable to this invention, and will not be described in detail here.

[0064] Specifically, once the process equipment is running, the actual operating status of each process piece of equipment is obtained based on the current raw data from each control system. According to the sequence of the process flow, the progress information of the production process (including the preset entire process flow, the current process flow, and the production data corresponding to the current process flow) is displayed on the user interface corresponding to each process area, so as to intuitively reflect the operating status of the control system and the production status of the process equipment in the corresponding process area. Further, in this embodiment, the production flow of each process area is divided into a pre-send stage, an equipment operation stage (EQ Run), and a post-send stage. For example... Figure 2 As shown, the instructions for the forward delivery stage include, but are not limited to, the continuous execution of wafer allocation and handling. That is, when the next point performs processing on the i-th wafer, the previous point performs processing on the (i+1)-th wafer. Handling includes moving wafers from the warehouse stocker to the electronic shelf overhead buffer (OHB). Instructions for the equipment operation stage include, but are not limited to, the equipment's process duration (provided by the equipment automation system EAP), determining the next destination (provided by the allocation system DISPATCH), unloading from the machine (provided by the material control system MCS), and handling (provided by the material control system MCS). Instructions for the backward delivery stage include, but are not limited to, determining the lot (LOT) and handling. Specifically, the lot is determined and moved from the equipment to the electronic shelf overhead buffer. Then, the next destination site and equipment information are obtained from the dispatch system, and finally, the lot is determined again and moved from the equipment location system LOC to the next equipment. Clicking the corresponding command will also display the current production data, including but not limited to the hourly output of the machine (WPH, Wafer Per Hour), actual processing time (APT, Actual Process Time), dispatch sequence information, and handling information; among which, actual processing time includes but is not limited to the time when the first wafer starts processing, the time when the last wafer starts processing, transmission time, and buffer time; handling information includes but is not limited to batch status information and location information; these will not be elaborated here.

[0065] 3) Compare the duration of each process in the preset process flow information (including but not limited to machine processing time and loading / unloading waiting time) with the actual processing time, and determine whether the actual production status is consistent with the preset production status based on the comparison results; when the actual production status is inconsistent with the preset production status, the current process flow status is highlighted, the cause of the abnormality is determined by the process flow sequence, and an alarm signal is sent to the corresponding person in charge.

[0066] Specifically, this invention uses the process flow sequence as the judgment logic, analyzes the reasons for abnormalities based on the differences between the instructions (and production status) that should theoretically be executed and the actual instructions (and production status), and identifies the corresponding responsible persons.

[0067] More specifically, when a problem occurs in the handling of goods, an alarm signal is sent to the production personnel. In this embodiment, a problem is determined to have occurred when the loading / unloading window of the equipment is idle or occupied for a period exceeding the corresponding standard time (for example, the SPEC time). For example, if the loading / unloading window of the preceding equipment is idle for a period exceeding the set SPEC time, an alarm signal is sent to the production personnel to notify them to load the goods. If the goods have been processed on the machine and have completed their normal operation, but are delivered to the loading / unloading window for a period exceeding the set SPEC time, an alarm signal is sent to the production personnel to notify them to remove the goods as soon as possible.

[0068] More specifically, when a communication failure occurs in the equipment, an alarm signal is sent to the machine automation operator. In this embodiment, when goods are located at the loading / unloading window and the waiting time for loading exceeds a set time, a communication failure is determined to have occurred in the corresponding equipment. As an example, if goods have been moved to the machine loading / unloading window, but the LOT status still shows a waiting time for loading after the set time has elapsed, an alarm signal will be automatically sent to the EAP (Equipment Automation) operator (in this example, the alarm signal is sent by telephone) so that the EAP operator can check whether the communication between the EAP system and the equipment is abnormal.

[0069] More specifically, when equipment malfunctions, an alarm signal is sent to the machine process engineer. In this embodiment, when the actual running time of the equipment exceeds or falls below a preset percentage of the standard running time, the corresponding equipment is determined to have malfunctioned. As an example, if goods are continuously running within the machine, and the running time of these goods has exceeded or fallen below 20% of the standard running time (which can also be set to 5%, 8%, 10%, 13%, 15%, 17%, or 25%), then an alarm signal is sent to the machine process engineer to notify them to check for any abnormalities in the machine.

[0070] It should be noted that the setting standards for the duration and preset ratio are set by the machine equipment and process engineers according to the actual production needs, as long as fault detection can be achieved, and are not limited here.

[0071] The intelligent monitoring method of the present invention monitors the operation status of each link and displays the progress information of the production process and anomaly monitoring according to the actual delivery process.

[0072] Example 2

[0073] like Figure 3 As shown, this embodiment provides an intelligent monitoring system 1, which includes:

[0074] Watchdog logic module 11, intelligent monitoring database 12, user interface 13, and alarm management module 14.

[0075] like Figure 3 As shown, the watchdog logic module 11 is connected to each control system in the production process, monitors the operation status of the control systems in each process area and the production status of the process equipment, and makes early warning judgments based on the original data of each control system and the process sequence as the logical judgment basis.

[0076] Specifically, the watchdog logic module 11 acquires raw data and performs intelligent calculations (which can be set to be executed once every minute, with the execution frequency set as needed) to achieve functions such as monitoring, sending early warnings, and updating the intelligent monitoring database 12. In this embodiment, the watchdog logic module 11 acquires raw data from the standby databases of each control system, including but not limited to the MES standby database 101, DISPATCH standby database 102, EAP standby database 103, SMIF standby database 104, E-RACK standby database 105, and MCS standby database 106.

[0077] Specifically, when an abnormal situation occurs, the watchdog logic module 11 makes a judgment based on the process flow sequence, analyzes and confirms the specific problem of the abnormal situation and the corresponding person in charge, and then triggers the alarm management module 14 to notify the corresponding person in charge to handle it quickly.

[0078] like Figure 3 As shown, the intelligent monitoring database 12 is connected to the watchdog logic module 11, which is used to summarize the data of each control system and store the calculation data of the watchdog logic module 11.

[0079] like Figure 3 As shown, the user interface 13 communicates with the intelligent monitoring database 12, reads data from the intelligent monitoring database 12, displays the actual process flow status information, the currently executed instructions and their completion status, and prompts the next instruction to be executed.

[0080] Specifically, in this embodiment, the user interface 13 uses the JAVA language tool (or other programming languages) to further generate the intelligent calculation results of each process area into a corresponding visualization system for on-site production personnel to monitor and view. The user interface 13 communicates with the intelligent monitoring database 12 based on the WebSocket protocol. The client is set to actively call the web service middleware every few seconds to read the real-time machine status data in the intelligent monitoring database 12 and return it to the user interface 13 for automatic data refresh and display. As an example, the user interface 13 displays the production process status information for three stages (pre-feed stage, equipment operation stage, and post-feed stage) of production operation, routine testing operation, and maintenance testing operation. When an alarm occurs in the current step, the current process status will be highlighted in color. Production personnel can click to enter the next level of detailed information, view detailed information, and push it to the relevant responsible person for timely handling.

[0081] like Figure 3 As shown, the alarm management module 14 is connected to the watchdog logic module 11, and sends alarm signals to the corresponding responsible persons based on the early warning of the watchdog logic module 11.

[0082] Specifically, alarm signals include, but are not limited to, SMS messages and telephone calls; any method that can trigger an alarm is applicable.

[0083] It should be noted that the intelligent monitoring system 1 in this embodiment can be used to implement the intelligent monitoring method of embodiment one, and the specific principles will not be elaborated here.

[0084] like Figure 4 As shown, this embodiment also provides a semiconductor manufacturing system, including:

[0085] At least one process equipment 3, control system 2, and intelligent monitoring system 1 of the present invention.

[0086] like Figure 4 As shown, each process device 3 is used to execute each process step in the production process.

[0087] Specifically, the number N of process equipment 3 is set according to the specific process flow requirements. Process equipment 3 includes, but is not limited to, photo equipment, diffusion equipment, thin film deposition equipment, etching equipment, wet process equipment, ion implantation equipment, chemical mechanical polishing equipment, wafer sorting equipment, measurement equipment, wafer acceptance test equipment (WAT) / wafer inspection equipment (CP), which will not be elaborated here.

[0088] like Figure 4As shown, the control system 2 connects to each process device 3 and is used to control the operation of each process device 3. The control system 2 includes at least one of a manufacturing execution system, a material control system, a dispatching system, an equipment automation system, a standard machine interface, and an electronic shelf system, as shown in Example 1.

[0089] like Figure 4 As shown, the intelligent monitoring system 1 is connected to the control system 2 to monitor the production process and send alarm signals to the corresponding person in charge of the corresponding process area when an abnormality occurs.

[0090] In this embodiment, the semiconductor manufacturing system is an 8-inch production line to improve the efficiency and capacity of the 8-inch production line and reduce costs. In actual use, any production line can adopt the semiconductor manufacturing system of the present invention, and is not limited to this embodiment.

[0091] This invention enables production personnel in the monitoring room to intelligently monitor the operation of each link in the production system. When any link node has an abnormality or alarm, the system will intelligently and quickly locate the problem and automatically notify the relevant person in charge to respond and handle it in a timely manner. Production personnel in the monitoring room can also remind the corresponding person in charge to handle the abnormality in a timely manner.

[0092] In summary, this invention provides an intelligent monitoring method, system, and semiconductor manufacturing system, comprising: summarizing raw data from each control system in the production process; performing intelligent calculations on the raw data to generate preset process flow information for each process area; monitoring the operating status of the control systems and the production status of the process equipment in each process area during operation; simultaneously displaying the actual process flow status information, currently executed instructions, and completion status on the user interface corresponding to each process area, and prompting the next instruction to be executed; comparing the duration of each process step in the preset process flow information with the actual processing time, and determining whether the actual production status is consistent with the preset production status based on the comparison results; when the actual production status is inconsistent with the preset production status, highlighting the current process flow status, determining the cause of the anomaly based on the process flow sequence, and issuing an alarm signal to the corresponding responsible person. This invention intelligently plans and monitors the system operation status of each production scenario of an automated production line from an AI perspective, comprehensively and systematically arranging and intelligently judging, instructing actions, quickly warning and solving problems, and achieving production goals. Therefore, this invention effectively overcomes the various shortcomings of the prior art and has high industrial application value.

[0093] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. An intelligent monitoring method, characterized in that, The intelligent monitoring method includes at least: 1) Summarize the raw data of each control system in the production process, perform intelligent calculations on the raw data, and generate preset process flow information for each process area by process area. 2) When the process equipment is running, the operation status of the control system and the production status of the process equipment in each process area are monitored. At the same time, the actual process flow status information, the currently executed instructions and their completion status are displayed on the user interface corresponding to each process area, and the next instruction to be executed is prompted. 3) Compare the duration of each process in the preset process flow information with the actual processing time, and determine whether the actual production status is consistent with the preset production status based on the comparison results; when the actual production status is inconsistent with the preset production status, the current process flow status is highlighted, the cause of the abnormality is determined by the process flow sequence, and an alarm signal is sent to the corresponding person in charge.

2. The intelligent monitoring method according to claim 1, characterized in that: The raw data of each control system includes at least one of the following for each process area: current inventory information of the machine, running information, process parameters, machine condition information, machine loading port status, POD location information, storage information, routine testing information, machine maintenance information, machine warm-up information, online product information, next destination information of goods, DUMMY wafer inventory information, and DUMMY wafer usage information.

3. The intelligent monitoring method according to claim 1, characterized in that: The actual process status information includes machine condition information, shipment information, work assignment information, and handling information.

4. The intelligent monitoring method according to claim 1, characterized in that: In step 2), the operation of each process equipment is either production operation, routine testing operation, or maintenance testing operation.

5. The intelligent monitoring method according to any one of claims 1-4, characterized in that: When the loading and unloading windows of the equipment are idle or occupied for a period of time exceeding the corresponding standard time, it is determined that there is a problem with the handling of goods. When goods are located at the loading / unloading window, and the time during which the goods are waiting to be loaded exceeds the set time, it is determined that the corresponding device has a communication failure. When the actual running time of the equipment exceeds or falls below the preset ratio of the process standard running time, the corresponding equipment is determined to be faulty.

6. The intelligent monitoring method according to claim 5, characterized in that: In step 3), When a problem occurs during cargo handling, the alarm signal is sent to the production personnel; When a communication failure occurs in the equipment, the alarm signal is sent to the machine automation duty personnel; When the equipment malfunctions, the alarm signal is sent to the machine process engineer.

7. An intelligent monitoring system, characterized in that, The intelligent monitoring system includes at least: Watchdog logic module, intelligent monitoring database, user interface and alarm management module; The watchdog logic module is connected to each control system in the production process, monitors the operation status of the control systems in each process area and the production status of the process equipment, and makes early warning judgments based on the original data of each control system and the process sequence as the logical judgment basis. The intelligent monitoring database is connected to the watchdog logic module and is used to aggregate data from various control systems and store the computational data of the watchdog logic module. The user interface communicates with the intelligent monitoring database, reads data from the intelligent monitoring database, displays the actual process flow status information, the currently executed instructions and their completion status, and prompts the next instruction to be executed. The alarm management module is connected to the watchdog logic module and sends alarm signals to the corresponding responsible person based on the early warning from the watchdog logic module.

8. The intelligent monitoring system according to claim 7, characterized in that: The user interface communicates with the intelligent monitoring database based on the WebSocket protocol.

9. A semiconductor manufacturing system, characterized in that, The semiconductor manufacturing system includes: At least one process equipment, a control system, and an intelligent monitoring system as described in any one of claims 7-8; Each piece of equipment is used to execute the various technological steps in the production process; The control system is connected to each process device and is used to control the operation of each process device; The intelligent monitoring system is connected to the control system and is used to monitor the production process.

10. The semiconductor manufacturing system according to claim 9, characterized in that: The control system includes at least one of the following: manufacturing execution system, material control system, dispatching system, equipment automation system, standard machine interface, and electronic shelf system.

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