An energy digital twin simulation device and method for an adaptive semiconductor device

Abstract

The present invention discloses an adaptive digital twin simulation device and method for semiconductor equipment energy consumption. The device includes a data acquisition module, a simulation model construction and operation module, and a parameter update module connected by signals. The data acquisition module obtains production information and process parameter information of semiconductor products and obtains actual processing data in real time. The simulation model construction and operation module constructs a process equipment energy consumption simulation model based on preset process equipment configuration units, integrates the production information and process parameter information of semiconductor products, operates the process equipment energy consumption simulation model, and provides energy consumption simulation data in real time. The parameter update module is used to update the process parameter information in the process equipment energy consumption simulation model. By setting up the parameter update module and introducing a real-time data feedback mechanism, the process parameter information is dynamically updated, thereby improving the accuracy and real-time performance of the process equipment energy consumption simulation model.

Description

Technical Field

[0001] The present invention belongs to the technical field of device simulation, and specifically relates to an adaptive digital twin simulation device and method for energy consumption of semiconductor equipment. Background Art

[0002] Process equipment requires multiple power supplies during operation. Understanding the power consumption of each process equipment at different times and under different conditions can provide data reference for process parameter adjustment, equipment maintenance, energy saving and consumption reduction, etc.

[0003] Currently, power supply for process equipment is typically provided in zones, with each zone having only one overall monitoring instrument. The power usage of individual process equipment is not monitored. Furthermore, the process equipment in a zone may contain multiple functions and models, making it impossible to determine the power usage of each individual piece of equipment.

[0004] Patent CN116579273A discloses a method and system for dynamic simulation of semiconductor equipment power consumption. The method includes: determining the model and process of the process equipment; disassembling the process equipment power units; grouping the power units according to their power characteristics; establishing a power consumption data set based on the grouping of the power units; establishing a dynamic power consumption simulation model based on the production rhythm and processing flow of the process equipment and process, and inputting the power consumption data set into the dynamic power consumption simulation model; running the dynamic power consumption simulation model and performing real-time state capture to dynamically output the real-time power consumption of the semiconductor equipment. This method can realize dynamic simulation of the power consumption of process equipment, and can present the power consumption curve of the equipment over a certain period, facilitating data analysis.

[0005] On the one hand, the above simulation method only simulates electricity consumption data and is not applicable to process equipment including multiple power supplies; on the other hand, the above simulation method uses a simulation model with fixed parameters to simulate electricity consumption data, and the accuracy of the model is limited.

[0006] How to simulate the energy consumption of process equipment that adopts multiple power supplies while improving the accuracy of energy consumption simulation is a problem that needs to be solved at present. Summary of the Invention

[0007] In response to the defects in the above-mentioned prior art, the present invention provides an adaptive semiconductor equipment energy consumption digital twin simulation device and method, the device including a data acquisition module, a simulation model construction and operation module, and a parameter update module connected by signals; the data acquisition module is used to obtain the production information and process parameter information of semiconductor products, and to obtain the actual processing data of process equipment in real time; the simulation model construction and operation module is used to construct a process equipment energy consumption simulation model according to a preset process equipment configuration unit, integrate the production information and process parameter information of semiconductor products, operate the process equipment energy consumption simulation model, and provide energy consumption simulation data in real time; the parameter update module is used to update the process parameter information in the process equipment energy consumption simulation model, wherein the updated process parameter information is given based on the analysis of the actual processing data of the process equipment and combined with the energy consumption simulation data to update the process parameter information in the process equipment energy consumption simulation model. By setting up the parameter update module and introducing a real-time data feedback mechanism, the process parameters in the process equipment energy consumption simulation model are dynamically updated, thereby improving the accuracy and real-time performance of the process equipment energy consumption simulation model.

[0008] In a first aspect, the present invention provides an adaptive semiconductor equipment energy consumption digital twin simulation device, specifically comprising:

[0009] Data acquisition module, simulation model construction and operation module and parameter update module connected by signals;

[0010] The data acquisition module is used to obtain the production information and process parameter information of semiconductor products, as well as the actual processing data of process equipment in real time;

[0011] The simulation model construction and operation module is used to build a process equipment energy simulation model based on the preset process equipment configuration unit, integrate the production information and process parameter information of semiconductor products, run the process equipment energy simulation model, and provide energy simulation data in real time;

[0012] The parameter updating module is used to update the process parameter information in the process equipment energy consumption simulation model, wherein the updated process parameter information is given based on the analysis of the actual processing data of the process equipment.

[0013] Furthermore, the process equipment configuration unit includes a plurality of workstation subunits and a plurality of manipulator subunits;

[0014] According to the preset process equipment configuration unit, a process equipment energy consumption simulation model is constructed, which specifically includes:

[0015] Obtaining a preset process equipment configuration unit;

[0016] Combined with the connection relationship between each workstation sub-unit and each robot sub-unit in the process equipment configuration unit, the energy consumption logic of the process equipment is integrated to construct a process equipment energy consumption simulation model.

[0017] Furthermore, the production information includes the production time, processing batch and process information of the semiconductor product, the process parameter information includes the set operating time and set energy consumption of each station in the process equipment during the processing of the semiconductor product, the actual processing data includes the actual processing time and actual energy consumption data, and the parameter update module includes a first update submodule, a second update submodule and a third update submodule;

[0018] A first updating submodule is configured to analyze actual processing data of the process equipment within a preset time period, update the set operating time and set energy consumption of each workstation in the process of processing semiconductor products in the current process parameter information, and provide first process parameter information;

[0019] A second updating submodule is configured to determine a current processing batch of the process equipment and, based on actual processing data of the process equipment of the associated processing batch corresponding to the current processing batch, update the set energy consumption and set operating time of each station in the semiconductor product processing process in the current process parameter information to provide second process parameter information;

[0020] The third updating submodule is used to determine the current processing time and update the current process parameter information in combination with the fixed updating strategy to provide the third process parameter information.

[0021] Furthermore, the actual processing data of the process equipment within the preset time period is analyzed, and the set operating time and set energy consumption of each station in the process of processing the semiconductor product in the current process parameter information are updated to provide the first process parameter information, which specifically includes:

[0022] Obtain actual energy consumption data of process equipment at each moment within a preset time period;

[0023] Perform data cleaning on the actual energy consumption data at each moment to obtain standard energy consumption data;

[0024] According to the changes in the standard energy consumption data at each moment, the standard energy consumption curve is obtained and the mean value of the standard energy consumption data is given;

[0025] Combined with the average value of the standard energy consumption data and the actual processing time of each station in the process equipment, the set operating time and set energy consumption of each station in the semiconductor product processing process in the current process parameter information are updated to obtain the first process parameter information.

[0026] Furthermore, the current processing batch of the process equipment is determined, and based on the actual processing data of the process equipment of the associated processing batch corresponding to the current processing batch, the set energy consumption and set operating time of each station in the semiconductor product processing process in the current process parameter information are updated to provide second process parameter information, specifically including:

[0027] Determine the current processing batch of process equipment;

[0028] According to the correlation relationship between each processing batch, the actual processing data of the process equipment corresponding to the current processing batch is given;

[0029] Perform data cleaning on the actual processing data of the process equipment associated with the processing batch, eliminate abnormal values and null values in the actual processing data, and provide standard processing data;

[0030] Based on the analysis of changes in the standard processing data, the set energy consumption and set operating time of each station in the semiconductor product processing process in the current process parameter information are updated to provide second process parameter information.

[0031] Furthermore, the current processing time is determined, and the current process parameter information is updated in combination with the fixed update strategy to provide third process parameter information, specifically including:

[0032] Determine the current processing time. If the current processing time is a time value in a preset update schedule, trigger a fixed update strategy. The fixed update strategy is to obtain the latest process parameter information.

[0033] The current process parameter information is updated to provide third process parameter information.

[0034] Furthermore, the energy consumption simulation model of the process equipment is run to provide real-time energy consumption simulation data, including:

[0035] According to the current process parameter information, the process equipment energy consumption simulation model is used to simulate the energy consumption of the process equipment and provide the initial energy consumption simulation data;

[0036] Combined with the actual energy consumption data of process equipment, the energy consumption simulation correction coefficient is given;

[0037] According to the energy consumption simulation correction coefficient, the initial energy consumption simulation data is corrected and the energy consumption simulation data is given in real time.

[0038] Furthermore, combined with the actual energy consumption data of the process equipment, the energy consumption simulation correction coefficient is given, including:

[0039] According to the actual energy consumption data of process equipment per unit time and the initial energy consumption simulation data, the difference between the actual energy consumption data and the initial energy consumption simulation data is analyzed and a sub-correction coefficient is given;

[0040] Combine all the sub-correction coefficients within the preset time period, analyze the changes in the sub-correction coefficients, and provide the energy consumption simulation correction coefficient.

[0041] Furthermore, the energy simulation correction coefficient can be expressed as:

[0042]

[0043] in, is the energy simulation correction coefficient, is the sub-correction coefficient of the nth unit time, is the initial energy consumption simulation data of the nth unit time, is the actual energy consumption data of the nth unit time.

[0044] In a second aspect, the present invention further provides an adaptive semiconductor device energy consumption digital twin simulation method, which is applied to any of the above-mentioned adaptive semiconductor device energy consumption digital twin simulation devices, including:

[0045] Obtaining production information and process parameter information of semiconductor products, as well as real-time acquisition of actual processing data of process equipment;

[0046] According to the preset process equipment configuration unit, a process equipment energy simulation model is constructed, which integrates the production information and process parameter information of semiconductor products, runs the process equipment energy simulation model, and provides energy simulation data in real time;

[0047] The process parameter information in the process equipment energy consumption simulation model is updated, wherein the updated process parameter information is given based on the analysis of actual processing data of the process equipment.

[0048] The present invention provides an adaptive semiconductor equipment energy consumption digital twin simulation device and method, which has at least the following beneficial effects:

[0049] (1) Through the data acquisition module and the simulation model construction and operation module, the energy consumption simulation model of the process equipment is constructed based on the preset process equipment configuration unit. Combined with the parameter update module, based on the analysis of the actual processing data and energy consumption simulation data of the process equipment, the process parameter information in the energy consumption simulation model of the process equipment is updated and the energy consumption simulation data is given; by setting the parameter update module to introduce a real-time data feedback mechanism, the current process parameter information in the energy consumption simulation model of the process equipment is dynamically updated to improve the accuracy and real-time performance of the energy consumption simulation model of the process equipment.

[0050] (2) Through the first updating submodule, the second updating submodule and the third updating submodule in the parameter updating module, the current process parameter information is updated in different dimensions, and the process equipment energy consumption simulation model is corrected, thereby further ensuring the simulation accuracy of the process equipment energy consumption simulation model.

[0051] (3) The initial energy consumption simulation data obtained by correcting the current process parameter information is combined with the energy consumption correction coefficient to correct the initial energy consumption simulation data and output the energy consumption simulation data, thereby improving the accuracy of the output prediction results of the process equipment energy consumption simulation model. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A structural block diagram of an adaptive semiconductor equipment energy usage digital twin simulation device provided by an embodiment of the present invention;

[0053] Figure 2 A flowchart of constructing a process equipment energy consumption simulation model provided by an embodiment of the present invention;

[0054] Figure 3 A schematic diagram of a wafer processing process according to an embodiment of the present invention;

[0055] Figure 4 A flowchart for determining first process parameter information provided by an embodiment of the present invention;

[0056] Figure 5 A flowchart for determining second process parameter information provided by an embodiment of the present invention;

[0057] Figure 6 A flowchart for determining third process parameter information provided by an embodiment of the present invention;

[0058] Figure 7 A schematic diagram of the operation of an adaptive semiconductor equipment energy usage digital twin simulation device provided by an embodiment of the present invention;

[0059] Figure 8 A flowchart of an adaptive semiconductor equipment energy usage digital twin simulation method provided in an embodiment of the present invention.

[0060] Among them, 10, data acquisition module; 20, simulation model construction and operation module; 30, parameter update module; 31, first update submodule; 32, second update submodule; 33, third update submodule. DETAILED DESCRIPTION

[0061] To better understand the above technical solution, the following will be described in detail with reference to the accompanying drawings and specific implementation methods. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0062] The terms used in the embodiments of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The singular forms "a," "an," "the," and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, and unless the context clearly indicates otherwise, "a plurality" generally includes at least two.

[0063] It should also be noted that the terms "include," "comprises," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a product or device comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such product or device. In the absence of further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the product or device comprising the element.

[0064] Energy costs account for a large proportion of an enterprise's production costs. Through energy consumption simulation of process equipment, energy demand can be predicted in advance, energy distribution can be optimized, and energy consumption can be reduced, thereby effectively controlling the enterprise's production costs.

[0065] The power consumption of process equipment is related to the commissioning of the machine and the setting of process parameters. The current energy simulation model has the following problems:

[0066] (1) There is a deviation between the process parameter setting value and the actual operating value;

[0067] (2) The process equipment will adjust the process parameters of a batch of products in real time according to the processing conditions during the operation of the machine, resulting in a large gap between the energy consumption prediction value output by the energy consumption simulation model and the actual value.

[0068] In summary, current energy simulation models can only make predictions based on fixed process parameters and cannot synchronize with the process parameters of on-site process equipment. If manual intervention is required to adjust process parameters in the energy simulation model, the model lacks self-learning or adaptive capabilities. When process equipment operating conditions are complex or dynamically changing, the simulation accuracy of the energy simulation model will significantly decrease.

[0069] Therefore, the present invention proposes an adaptive semiconductor equipment energy consumption digital twin simulation device, comprising a data acquisition module 10, a simulation model construction and operation module 20, and a parameter update module 30 connected by signals; the data acquisition module 10 is used to obtain the production information and process parameter information of semiconductor products, as well as to obtain the actual processing data of process equipment in real time; the simulation model construction and operation module 20 is used to construct a process equipment energy consumption simulation model based on a preset process equipment configuration unit, integrate the production information and process parameter information of semiconductor products, operate the process equipment energy consumption simulation model, and provide energy consumption simulation data in real time; the parameter update module 30 is used to update the process parameter information in the process equipment energy consumption simulation model, wherein the updated process parameter information is provided based on an analysis of the actual processing data of the process equipment. By setting up the parameter update module 30, a real-time data feedback mechanism is introduced to dynamically update the process parameters in the process equipment energy consumption simulation model, thereby improving the accuracy and real-time performance of the process equipment energy consumption simulation model.

[0070] like Figure 1 As shown, an embodiment of the present invention provides an adaptive digital twin simulation device for semiconductor equipment energy usage, specifically comprising a data acquisition module 10, a simulation model construction and operation module 20, and a parameter update module 30 connected via signals. The data acquisition module 10 acquires semiconductor product launch information and process parameter information, as well as actual processing data of the process equipment in real time. The launch information includes the launch time, processing batch, and process information of the semiconductor product. The process parameter information includes the set operating time and set energy consumption of each workstation in the process equipment during the semiconductor product processing. The actual processing data includes actual processing time and actual energy consumption data. The simulation model construction and operation module 20 constructs a process equipment energy usage simulation model based on a preset process equipment configuration unit, integrates the semiconductor product launch information and process parameter information, runs the process equipment energy usage simulation model, and generates real-time energy usage simulation data. The process equipment configuration unit includes multiple workstation sub-units and multiple robot sub-units. The parameter update module 30 updates the process parameter information in the process equipment energy usage simulation model, wherein the updated process parameter information is generated based on an analysis of the actual processing data of the process equipment.

[0071] It should be understood that the actual processing time is the processing time of each workstation or robot during the semiconductor product processing process, and the actual energy consumption data is the energy consumption of each workstation or robot during the semiconductor product processing process. The set operating time is the processing time of each robot subunit or workstation subunit in the process equipment energy simulation model, and the set energy consumption is the energy consumption of each robot subunit or workstation subunit in the process equipment energy simulation model. The above-mentioned set operating time and set energy consumption can be data set by relevant personnel based on actual conditions, or can be data obtained after updating by the parameter update module 30, and there is no limitation on this.

[0072] In the embodiment provided by the present invention, the manufacturing execution system (MES) and resource management system (RMS) in the factory are used to obtain data including production information and process parameter information, and the parameter update module 30 is used to update the process parameter information. This is combined with the intelligent equipment system (IES), the fault detection and classification (FDC) system, and the advanced process control (APC) system. Finally, by acquiring and analyzing the actual energy consumption data provided by the supervisory control and data acquisition (SCADA) system, an energy consumption simulation correction coefficient is given to obtain energy consumption simulation data. The present invention constructs a dynamic process equipment twin system through the above-mentioned device, and is able to provide energy consumption simulation data of the power of each process equipment in different time periods.

[0073] Among them, MES is a system used to monitor and manage the manufacturing process. It connects the semiconductor factory's Enterprise Resource Planning (ERP) system with the shop floor equipment, allowing real-time tracking of production progress, quality, and equipment status to optimize production efficiency. The semiconductor factory ERP system is management software designed specifically for semiconductor companies. It integrates multiple core modules, including supply chain, production control, quality management, and financial management. It helps semiconductor factories achieve refined management of production processes, intelligent inventory control, and integrated financial operations. This helps companies optimize resource allocation, improve operational efficiency, strengthen cost control, and provide real-time, accurate data support for business decision-making. RMS is a production process recipe management system that sets up and controls the entire process equipment, including manpower, equipment, and materials, ensuring efficient resource utilization and supporting production planning and scheduling. APC is an advanced control technology used in industrial automation designed to optimize the performance of complex industrial processes. It improves production efficiency, product quality, and resource utilization by real-time monitoring, analysis, and adjustment of key parameters in the production process. IES and FDC systems collect and analyze equipment sensor data in real time to monitor the energy consumption of equipment within a specific time window during the production process. This monitoring monitors the actual processing time and energy usage of process equipment during the production process. SCADA is used in factory management systems to monitor and control industrial processes, collecting data in real time and providing a visual interface to support remote operation and automated control. Factory management systems encompass the various infrastructure and working environments supporting chip production, including water, electricity, gas supply, wastewater treatment, and HVAC systems (heating, ventilation, and air conditioning). Through real-time data collection and analysis, they ensure the normal operation of equipment and that environmental parameters meet production requirements, thereby guaranteeing the quality and output of semiconductor products.

[0074] Reference Figure 2 , according to the preset process equipment configuration unit, build a process equipment energy simulation model, specifically including:

[0075] Obtaining a preset process equipment configuration unit;

[0076] Combined with the connection relationship between each workstation sub-unit and each robot sub-unit in the process equipment configuration unit, the energy consumption logic of the process equipment is integrated to construct a process equipment energy consumption simulation model.

[0077] In the embodiments provided herein, a process equipment energy simulation model is constructed using the simulation software PlantSimulation. The process equipment energy simulation model simulates the power and energy consumption of process equipment during processing and monitors the actual energy usage data of the process equipment. The process equipment energy simulation model is constructed by obtaining a preset process equipment configuration unit, combining the connection relationships between each workstation sub-unit and each robot sub-unit within the process equipment configuration unit, and integrating the energy usage logic of the process equipment. The parameter update module 30 updates the process parameter information in the process equipment energy simulation model based on the actual energy usage data of the process equipment, thereby enabling dynamic operation of the process equipment energy simulation model. Energy usage logic refers to the energy consumption patterns of process equipment under different operating states. Specifically, it describes the rules and patterns for how process equipment consumes energy (such as electricity, gas, chemicals, etc.) under different operating stages and process conditions during the semiconductor product manufacturing process. The energy usage logic includes the energy requirements of process equipment during different stages such as startup, operation, standby, and maintenance, as well as the energy consumption patterns under different process parameters.

[0078] The process equipment energy simulation model primarily embeds all the factory's machines and the rules governing the products they process (i.e., the actual process equipment configuration units of each machine) into the model to simulate a real machine system. The process equipment simulation model simulates actual machine processing steps and operational logic, consisting of different workstation modules and robotic modules. The machine operates according to input settings, ultimately outputting simulated energy usage data.

[0079] Taking wafer processing as an example, refer to Figure 3 During wafer processing, wafers enter the process equipment's loadport, where they are grabbed by a robot and placed at a workstation for processing. The machine contains different numbers and types of workstations, each with different power consumption points. Each point has a corresponding sensor, which monitors the power consumption at each point in real time. After a wafer completes processing at a workstation, it is transferred by the robot to the next processing station. Once all processing is complete, it leaves the equipment through the loadport. Machine processing is triggered by commissioning information. Commissioning information includes wafer process information, allowing the machine to be commissioned according to a specific wafer launch time. In the process equipment energy simulation model, configure workstations of different types and numbers, enter the processing time for each workstation, and enter the set operating time and energy consumption for each point at each workstation to complete the configuration and construction of the process equipment energy simulation model.

[0080] According to the production information, wafers are put into production at different times, and the energy consumption simulation model of the process equipment is run. According to the process information of the wafer, the corresponding workstation sub-unit is entered for processing, and the usage point is opened. The daily average of the output power energy consumption is monitored through indicators to complete the model simulation.

[0081] It can be understood that Loadport (wafer loader / wafer loader) is a key automation equipment in wafer processing, mainly used for the transmission and loading and unloading of wafers between different equipment.

[0082] The initial inputs (production information and process parameter information) of the process equipment energy simulation model are automatically obtained from the MES system and RMS system within the factory. The production information of the machine is obtained from the MES system, including information such as the time for each wafer to be put into production and the corresponding process. This information serves as the production input of the process equipment energy simulation model to determine the production of the machine. In addition, the machine process parameters (i.e., process parameter information) are automatically obtained from the RMS system, including the set operation and set energy consumption corresponding to different processes of the machine. Under different processes, the machine's operating station and station processing time determine the machine's processing operation time. In addition, different stations have multiple power energy usage points. Based on the usage time and energy consumption corresponding to each usage point, the dynamic superposition of the energy consumption of all processes of the machine is the energy consumption of the process equipment.

[0083] The running results of the process equipment energy consumption simulation model include the instantaneous energy consumption, daily average energy consumption, and monthly average energy consumption of the process equipment at all simulation moments.

[0084] Referring to Table 1 and Table 2, taking the input of production information and process parameter information as an example, a wafer wafer1 enters the machine for processing based on the wafer input time in the production information and the corresponding process recipe1. According to the process parameter information, process recipe1 will start the CH1~CHn stations to start processing the wafer in sequence. The processing time is T1~Tn respectively. The usage points corresponding to station CH1 are nozzle1~nozzle n. The superposition of the usage time and usage corresponding to each usage point is the kinetic energy consumption of the station in that period. The instantaneous energy consumption is the superposition of the energy consumption of the process equipment energy simulation model at that moment at different stations. The daily average is the average of the instantaneous values of each day, and the monthly average is the average of the daily average values. It is specifically expressed as:

[0085]

[0086] in, is the daily average, is the nth instantaneous energy consumption value, is the monthly average, is the daily average value corresponding to the mth day, m is the number of daily average values in a month, and n is the number of instantaneous energy consumption values in a day.

[0087] Table 1 Production information

[0088]

[0089] Table 2 Process parameter information

[0090]

[0091] Furthermore, the parameter updating module 30 includes a first updating submodule 31 , a second updating submodule 32 and a third updating submodule 33 ;

[0092] The first updating submodule 31 is configured to analyze actual processing data of the process equipment within a preset time period, update the set operating time and set energy consumption of each workstation in the process of processing semiconductor products in the current process parameter information, and provide first process parameter information;

[0093] The second updating submodule 32 is configured to determine the current processing batch of the process equipment and, based on actual processing data of the process equipment of the associated processing batch corresponding to the current processing batch, update the set energy consumption and set operating time of each station in the semiconductor product processing process in the current process parameter information to provide second process parameter information;

[0094] The third updating submodule 33 is used to determine the current processing time and update the current process parameter information in combination with the fixed updating strategy to provide third process parameter information.

[0095] Further, refer to Figure 4 , providing the first process parameter information, specifically including:

[0096] Obtain actual energy consumption data of process equipment at each moment within a preset time period;

[0097] Perform data cleaning on the actual energy consumption data at each moment to obtain standard energy consumption data;

[0098] According to the changes in the standard energy consumption data at each moment, the standard energy consumption curve is obtained and the mean value of the standard energy consumption data is given;

[0099] Combined with the average value of the standard energy consumption data and the actual processing time of each station in the process equipment, the set operating time and set energy consumption of each station in the semiconductor product processing process in the current process parameter information are updated to obtain the first process parameter information.

[0100] In a specific embodiment, the IES system and the FDC system will regularly update and adjust the process parameter information of the process equipment energy simulation model based on the actual machine operation conditions and energy consumption, so that the results output by the process equipment energy simulation model are closer to the actual values. In a specific example, the preset time period is that the process parameter information is adjusted once every preset time period through the IES system and the FDC system to give a first process parameter information. The specific process is: obtain the actual energy consumption data at each moment within the corresponding preset time period, and then perform data cleaning on the actual energy consumption data, eliminate abnormal values and null values in the actual energy consumption data, and obtain standard energy consumption data. According to the changes in the standard energy consumption data at each moment, a standard energy consumption curve is obtained. Then the average value of the standard energy consumption data within the preset time period is calculated to give the first process parameter information. The current process parameter information is updated based on the first process parameter information, thereby correcting the process equipment energy simulation model. Average value Specifically expressed as:

[0101]

[0102] in, for The standard energy consumption data corresponding to the t-th moment, for The number of internal moments.

[0103] Further, refer to Figure 5 , providing the second process parameter information, specifically including:

[0104] Determine the current processing batch of process equipment;

[0105] According to the correlation relationship between each processing batch, the actual processing data of the process equipment corresponding to the current processing batch is given;

[0106] Perform data cleaning on the actual processing data of the process equipment associated with the processing batch, eliminate abnormal values and null values in the actual processing data, and provide standard processing data;

[0107] Based on the analysis of changes in the standard processing data, the set energy consumption and set operating time of each station in the semiconductor product processing process in the current process parameter information are updated to provide second process parameter information.

[0108] It is understandable that the recipes of wafers produced in different batches may be the same or different, but the power consumption data for wafers produced with the same or similar recipes are also similar. Therefore, the second process parameter information provided in the embodiment of the present invention is obtained by associating the actual energy consumption data of the batches, thereby completing the correction of the energy consumption simulation model of the process equipment and improving the accuracy of the model simulation.

[0109] In one specific embodiment, the association between each processing batch is obtained through an equipment automation program (EAP) system. When the current processing batch is obtained, the corresponding associated batches are also obtained. Therefore, the actual energy usage data of the associated batches is first cleaned to remove outliers and null values, thereby obtaining standard energy usage data. In one specific example, the standard energy usage data is then averaged to provide the set energy usage in the second process parameter information. In other examples, different methods are used to determine the second process parameter information based on the fluctuation of the standard energy usage data. For example, when the standard energy usage data fluctuates relatively smoothly, the mode or median of the standard energy usage data is used as the set energy usage in the second process parameter information. Conversely, the mean or average of the extreme values is used as the set energy usage in the second process parameter information, without limitation. The actual energy usage data of the associated batches allows for real-time adjustment of the process parameter information. Adjustments are made to the process parameter information for the current batch on a batch-by-batch basis, with real-time adjustments made only for the current batch, and the next batch automatically recovers. It is understandable that when the associated processing batch is the current processing batch, the process parameter information in the associated processing batch will also be adjusted in real time, and the next batch will be automatically restored.

[0110] The above process is a process of determining the set energy consumption. It can be understood that the update of the set running time can be completed in the same way, which will not be described in detail here.

[0111] Among them, the EAP system is a key system used to realize equipment automation control and data acquisition in semiconductor product manufacturing.

[0112] Further, refer to Figure 6 , determine the current processing time, and combine the fixed update strategy to update the current process parameter information and give the third process parameter information, specifically including:

[0113] Determine the current processing time. If the current processing time is a time value in a preset update schedule, trigger a fixed update strategy. The fixed update strategy is to obtain the latest process parameter information.

[0114] The current process parameter information is updated to provide third process parameter information.

[0115] In the embodiments provided herein, a fixed update strategy is used to periodically update the current process parameter information at specified times, further modifying the process equipment energy simulation model. When the fixed update strategy is triggered, the latest process parameter information is read from the RMS system. The process parameter information in the RMS system is set or adjusted by relevant personnel based on actual conditions. It is understood that the latest process parameter information is the process parameter information currently read from the RMS system, and the latest process parameter information may be the same as or different from the current process parameter information.

[0116] The preset update schedule includes multiple time values. These time values can be set by the staff based on experience or randomly generated by a random function, with no limitation. The current processing time is obtained in real time. If the current processing time is a time value in the update schedule, the fixed update strategy is triggered, and the latest process parameter information is read from the RMS system. The current process parameter information in the process equipment energy simulation model is updated to provide the third process parameter information.

[0117] It can be understood that the first process parameter information, the second process parameter information and the third process parameter information are all parameters for correcting the current process parameter information. Depending on the actual situation, the process equipment energy consumption simulation model can use any one or more of these methods to correct the current process parameter information, and there is no limitation on this.

[0118] In the first specific example, the current process parameter information is corrected only by the first process parameter information, that is, the current process parameter information is corrected once every preset time period. The preset time period may only include the actual energy consumption data of a certain processing batch, or may include the actual energy consumption data of multiple processing batches. The number of processing batches within the preset time period does not affect the correction of the process parameter information by the first process parameter information.

[0119] Taking the first update submodule 31 as an example, the current process parameter information in the process equipment energy simulation model is updated based on the actual processing time and actual energy consumption data of a certain process equipment. When a certain wafer enters the process equipment according to the wafer input time in the production information, wafers of different process steps enter the corresponding workstation subunits and start processing in sequence. After the process equipment energy simulation model runs for a certain period of time, it outputs the initial energy simulation data a1 and the set running time T1 of the process equipment. After a preset time period, the initial energy simulation data a1 and the set running time T1 of the process equipment in this time period are compared and analyzed with the actual energy consumption data b1 and the actual processing time T1'. Each recipe processed by the equipment will obtain the corresponding initial energy simulation data and actual energy consumption data. When the next stage of simulation begins, the process parameter information is updated again, and the average value of the actual energy consumption data b1 in the preset time period is used as the input value of the new stage of process parameter information to update the process equipment energy simulation model. When the simulation enters the next time interval, the process parameter information is updated in sequence, so that the output results of the process equipment energy consumption simulation model gradually approach the actual value of the process equipment, and the process equipment energy consumption simulation model gradually approaches the actual operation of the process equipment, thereby realizing the correction of the model.

[0120] In the second specific example, the process parameter information is modified solely using the second process parameter information. Specifically, actual energy usage data for batches associated with the current processing batch is obtained, and the process parameter information for the current processing batch (including the set run time and set energy usage) is modified to produce the second process parameter information. After the current processing batch is completed, the process parameter information does not affect the next processing batch and can be restored to its initial value or modified to the process parameter information corresponding to the next batch.

[0121] In a third specific example, the current process parameter information is modified solely using the third process parameter information. Specifically, when the time value in the update schedule is reached, the latest process parameter information is read from the RMS system, and the third process parameter information is provided to complete the modification of the current process parameter information. The determination of the third process parameter information is solely related to the time value in the update schedule and is not affected by other factors.

[0122] In the fourth specific example, the first process parameter information, the second process parameter information and the third process parameter information are integrated to modify the process parameter information. That is, the first updating submodule 31, the second updating submodule 32 and the third updating submodule 33 are run simultaneously to modify the current process parameter information.

[0123] It is important to understand what specific information the process parameter information includes. The current process parameter information refers to the data actually used during the construction and operation of the process equipment energy consumption simulation model. The first process parameter information, the second process parameter information, and the third process parameter information are updated from the current process parameter information at different time points or stages. The current process parameter information is one of the first process parameter information, the second process parameter information, the third process parameter information, and the initial process parameter information. The initial process parameter information is the initially set, unupdated process parameter information.

[0124] Reference Figure 7 At preset intervals, actual energy usage data is read from the IES and FDC systems to update current process parameters. Combined with the APC system, these parameters are updated based on the current processing batch. The RMS system updates according to the time value (e.g., T2) set in the time update table. The process equipment energy simulation model obtains the latest process parameter information and simulates the process based on the commissioning information, outputting results to complete the revision of the process equipment energy simulation model.

[0125] Furthermore, the energy consumption simulation model of the process equipment is run to provide real-time energy consumption simulation data, including:

[0126] According to the current process parameter information, the process equipment energy consumption simulation model is used to simulate the energy consumption of the process equipment and provide the initial energy consumption simulation data;

[0127] Combined with the actual energy consumption data of process equipment, the energy consumption simulation correction coefficient is given;

[0128] According to the energy consumption simulation correction coefficient, the initial energy consumption simulation data is corrected and the energy consumption simulation data is given in real time.

[0129] Furthermore, combined with the actual energy consumption data of the process equipment, the energy consumption simulation correction coefficient is given, including:

[0130] According to the actual energy consumption data of process equipment per unit time and the initial energy consumption simulation data, the difference between the actual energy consumption data and the initial energy consumption simulation data is analyzed and a sub-correction coefficient is given;

[0131] Combine all the sub-correction coefficients within the preset time period, analyze the changes in the sub-correction coefficients, and provide the energy consumption simulation correction coefficient.

[0132] The energy simulation correction coefficient is specifically expressed as:

[0133]

[0134] in, is the energy simulation correction coefficient, is the sub-correction coefficient of the nth unit time, is the initial energy consumption simulation data of the nth unit time, is the actual energy consumption data of the nth unit time.

[0135] In the embodiment provided by the present invention, the initial energy consumption simulation data is corrected by the SCADA system, and the unit time is day. That is, the sub-correction coefficient of the day is calculated based on the actual energy consumption data and the initial energy consumption simulation data of each day. The energy consumption simulation correction coefficient of n days can be obtained from the sub-correction coefficient of each day. , based on the energy simulation correction coefficient and the initial energy simulation data Output energy consumption simulation data , thereby achieving correction and calibration of simulation output results.

[0136] Energy consumption simulation data is specifically expressed as follows:

[0137] ;

[0138] in, is the energy simulation correction coefficient, is the initial energy consumption simulation data corresponding to the nth unit time, is the energy consumption simulation data of the nth unit time.

[0139] Reference Figure 8 , an embodiment of the present invention provides an adaptive semiconductor device energy consumption digital twin simulation method, comprising:

[0140] Obtaining production information and process parameter information of semiconductor products, as well as real-time acquisition of actual processing data of process equipment;

[0141] According to the preset process equipment configuration unit, a process equipment energy simulation model is constructed, which integrates the production information and process parameter information of semiconductor products, runs the process equipment energy simulation model, and provides energy simulation data in real time;

[0142] The process parameter information in the process equipment energy consumption simulation model is updated, wherein the updated process parameter information is given based on the analysis of actual processing data of the process equipment.

[0143] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described steps can refer to the corresponding process in the aforementioned device embodiment, and will not be repeated here.

[0144] Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they are aware of the basic inventive concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the invention. Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the invention. Thus, the present invention is intended to include such changes and modifications as fall within the scope of the claims and their equivalents.

Claims

1. An adaptive digital twin simulation device for semiconductor equipment energy consumption, characterized in that: include: a data acquisition module, a simulation model construction and operation module, a first updating submodule, a second updating submodule, and a third updating submodule connected by signals; A data acquisition module is used to obtain production information and process parameter information of semiconductor products, as well as to obtain actual processing data of process equipment in real time. The production information includes the production time, processing batch and process information of the semiconductor products. The process parameter information includes the set operating time and set energy consumption of each station in the process equipment during the processing of semiconductor products. The actual processing data includes actual processing time and actual energy consumption data. The simulation model construction and operation module is used to build a process equipment energy simulation model based on the preset process equipment configuration unit, integrate the production information and process parameter information of semiconductor products, run the process equipment energy simulation model, and provide energy simulation data in real time; A first updating submodule is configured to analyze actual processing data of the process equipment within a preset time period, update the set operating time and set energy consumption of each workstation in the process of processing semiconductor products in the current process parameter information, and provide first process parameter information; A second updating submodule is configured to determine a current processing batch of the process equipment and, based on actual processing data of the process equipment of the associated processing batch corresponding to the current processing batch, update the set energy consumption and set operating time of each station in the semiconductor product processing process in the current process parameter information to provide second process parameter information; The third updating submodule is used to determine the current processing time and update the current process parameter information in combination with the fixed updating strategy to provide the third process parameter information.

2. The adaptive semiconductor equipment energy usage digital twin simulation device according to claim 1, characterized in that: The process equipment configuration unit includes a plurality of workstation subunits and a plurality of manipulator subunits; According to the preset process equipment configuration unit, a process equipment energy consumption simulation model is constructed, which specifically includes: Obtaining a preset process equipment configuration unit; Combined with the connection relationship between each workstation sub-unit and each robot sub-unit in the process equipment configuration unit, the energy consumption logic of the process equipment is integrated to construct a process equipment energy consumption simulation model.

3. The adaptive semiconductor equipment energy usage digital twin simulation device according to claim 1, characterized in that: Analyze the actual processing data of the process equipment within a preset time period, update the set operating time and set energy consumption of each station in the process of processing semiconductor products in the current process parameter information, and provide first process parameter information, specifically including: Obtain actual energy consumption data of process equipment at each moment within a preset time period; Perform data cleaning on the actual energy consumption data at each moment to obtain standard energy consumption data; According to the changes in the standard energy consumption data at each moment, the standard energy consumption curve is obtained and the mean value of the standard energy consumption data is given; Combined with the average value of the standard energy consumption data and the actual processing time of each station in the process equipment, the set operating time and set energy consumption of each station in the semiconductor product processing process in the current process parameter information are updated to obtain the first process parameter information.

4. The adaptive semiconductor equipment energy usage digital twin simulation device according to claim 1, characterized in that: Determine the current processing batch of the process equipment, and update the set energy consumption and set operating time of each station in the semiconductor product processing process in the current process parameter information based on the actual processing data of the process equipment of the associated processing batch corresponding to the current processing batch, and provide second process parameter information, specifically including: Determine the current processing batch of process equipment; According to the correlation relationship between each processing batch, the actual processing data of the process equipment corresponding to the current processing batch is given; Perform data cleaning on the actual processing data of the process equipment associated with the processing batch, eliminate abnormal values and null values in the actual processing data, and provide standard processing data; Based on the analysis of changes in the standard processing data, the set energy consumption and set operating time of each station in the semiconductor product processing process in the current process parameter information are updated to provide second process parameter information.

5. The adaptive semiconductor equipment energy usage digital twin simulation device according to claim 1, characterized in that: Determine the current processing time, and combine the fixed update strategy to update the current process parameter information to provide the third process parameter information, including: Determine the current processing time. If the current processing time is a time value in a preset update schedule, trigger a fixed update strategy. The fixed update strategy is to obtain the latest process parameter information. The current process parameter information is updated to provide third process parameter information.

6. The adaptive semiconductor equipment energy usage digital twin simulation device according to claim 1, characterized in that: Run the energy consumption simulation model of process equipment and provide real-time energy consumption simulation data, including: According to the current process parameter information, the process equipment energy consumption simulation model is used to simulate the energy consumption of the process equipment and provide the initial energy consumption simulation data; Combined with the actual energy consumption data of process equipment, the energy consumption simulation correction coefficient is given; According to the energy consumption simulation correction coefficient, the initial energy consumption simulation data is corrected and the energy consumption simulation data is given in real time.

7. The adaptive semiconductor equipment energy usage digital twin simulation device according to claim 6, characterized in that: Combined with the actual energy consumption data of process equipment, the energy consumption simulation correction coefficient is given, including: According to the actual energy consumption data of process equipment per unit time and the initial energy consumption simulation data, the difference between the actual energy consumption data and the initial energy consumption simulation data is analyzed and a sub-correction coefficient is given; Combine all the sub-correction coefficients within the preset time period, analyze the changes in the sub-correction coefficients, and provide the energy consumption simulation correction coefficient.

8. The adaptive semiconductor equipment energy usage digital twin simulation device according to claim 7, characterized in that: The energy simulation correction coefficient is specifically expressed as: ； in, is the energy simulation correction coefficient, is the sub-correction coefficient of the nth unit time, is the initial energy consumption simulation data of the nth unit time, is the actual energy consumption data of the nth unit time.

9. An adaptive digital twin simulation method for semiconductor equipment energy consumption, characterized in that: The adaptive semiconductor equipment energy consumption digital twin simulation device as claimed in any one of claims 1 to 8 comprises: Obtaining production information and process parameter information of semiconductor products, as well as real-time actual processing data of process equipment, wherein the production information includes the production time, processing batch and process information of the semiconductor products; the process parameter information includes the set operating time and set energy consumption of each station in the process equipment during the processing of semiconductor products; and the actual processing data includes actual processing time and actual energy consumption data; According to the preset process equipment configuration unit, a process equipment energy simulation model is constructed, which integrates the production information and process parameter information of semiconductor products, runs the process equipment energy simulation model, and provides energy simulation data in real time; Analyze actual processing data of the process equipment within a preset time period, update the set operating time and set energy consumption of each station in the process of processing the semiconductor product in the current process parameter information, and provide first process parameter information; Determine a current processing batch of the process equipment, and update the set energy consumption and set operating time of each station in the semiconductor product processing process in the current process parameter information based on actual processing data of the process equipment of the associated processing batch corresponding to the current processing batch, and provide second process parameter information; Determine the current processing time, and combine the fixed update strategy to update the current process parameter information to provide the third process parameter information.

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