Gas flow control method and device, electronic equipment and storage medium

Abstract

The present disclosure relates to a gas flow control method and device, electronic equipment and computer readable storage medium, and relates to the technical field of semiconductor production and manufacturing, and can be applied to the use scene of nitrogen related machine in semiconductor process. The method comprises: in response to a product arrival event that a product to be processed arrives at a target loading port, determining a to-be-processed production batch corresponding to the product to be processed; obtaining machine configuration parameters; the machine configuration parameters comprise a gas flow prediction value corresponding to at least one production batch in the machine loading port; determining a target flow prediction value corresponding to the to-be-processed production batch arriving at the target loading port from the machine configuration parameters; and controlling the machine to blow gas to the product to be processed arriving at the target loading port according to the target flow prediction value. The present disclosure can automatically configure the gas blowing amount of the machine loading port, without manual pre-setting, realizing the automatic control of the machine blowing gas, effectively shortening the process time, and improving the product yield.

Description

Technical Field

[0001] This disclosure relates to the field of semiconductor manufacturing technology, and more specifically, to a gas flow control method, a gas flow control device, an electronic device, and a computer-readable storage medium. Background Technology

[0002] Gases are a crucial component of semiconductor manufacturing because they generate the chemical reactions necessary to shape the electrical properties of semiconductors. Due to their complexity, the gases used at each stage of the manufacturing process need to be precise and accurate to properly configure the semiconductor.

[0003] Take nitrogen as an example. Due to its availability and inertness, nitrogen is a core gas used in various steps of the semiconductor manufacturing process, but its primary use is in the purging stage. In this stage, nitrogen is used to flush each channel and pipeline to remove any oxygen from the machines and tools, thus protecting them from other gases that could contaminate the process.

[0004] In the semiconductor industry, nitrogen is used for various purposes, including testing and maintenance. Currently, the nitrogen usage mechanism requires manual pre-setting of the nitrogen purging volume (N2Purge) at the equipment end, which is time-consuming and labor-intensive.

[0005] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this disclosure is to provide a gas flow control method, a gas flow control device, an electronic device, and a computer-readable storage medium, thereby overcoming, at least to some extent, the problems of existing semiconductor gas usage mechanisms that cannot automatically adjust the gas purging volume corresponding to the loading port and cannot automatically control the gas purging.

[0007] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part by practice of the invention.

[0008] According to a first aspect of this disclosure, a gas flow control method is provided, comprising: in response to a product arrival event of a product to be processed arriving at a target loading port, determining a production batch to be processed corresponding to the product to be processed; acquiring machine configuration parameters; the machine configuration parameters including a gas flow prediction value corresponding to at least one production batch at the machine loading port; determining a target flow prediction value corresponding to the production batch to be processed arriving at the target loading port from the machine configuration parameters; and controlling the machine to purge gas onto the product to be processed arriving at the target loading port according to the target flow prediction value.

[0009] In one exemplary embodiment of this disclosure, the gas flow prediction value is obtained through the following steps: acquiring at least one loading port included in the machine; determining all production batches corresponding to the products to be processed that are about to arrive at each loading port; acquiring the production batch number corresponding to each production batch; and determining the gas flow prediction value corresponding to each production batch in sequence according to the production batch number.

[0010] In one exemplary embodiment of this disclosure, the step of determining the gas flow prediction value corresponding to each production batch according to the production batch number includes: determining the production batch to be predicted based on the production batch number; obtaining a pre-configured number of reference production batches, and determining a set of production batches corresponding to the production batch to be predicted based on the number of reference production batches; the set of production batches includes at least one reference production batch; obtaining the actual gas flow value corresponding to each of the reference production batches; and determining the gas flow prediction value corresponding to the production batch to be predicted based on the obtained actual gas flow value.

[0011] In one exemplary embodiment of this disclosure, the number of reference production batches is multiple, and the step of determining the production batch set corresponding to the production batch to be predicted based on the number of reference production batches includes: obtaining the batch end numbers of the multiple reference production batches; determining the corresponding batch start number based on the number of reference production batches and the batch end number; and taking the reference production batches between the batch start number and the batch end number as the production batch set.

[0012] In one exemplary embodiment of this disclosure, the number of actual gas flow rates is multiple. Determining the predicted gas flow rate value corresponding to the production batch to be predicted based on the obtained actual gas flow rates includes: calculating the average of the multiple actual gas flow rates to obtain the predicted gas flow rate value; the predicted gas flow rate value... Among them, MA LPi (i = 1, 2, ..., n) represents the predicted gas flow rate for each loading port, n represents the number of loading ports on the machine, N represents the number of reference production batches, Xt represents the actual gas flow rate of the reference production batch corresponding to the batch end number, t represents the batch end number, and t-N+1 represents the batch start number.

[0013] In one exemplary embodiment of this disclosure, the method further includes: determining the standard deviation of the gas flow rate for each loading port based on the reference production batch quantity corresponding to each loading port, multiple actual gas flow rate values, and multiple predicted gas flow rate values; determining a corresponding gas flow rate range based on the predicted gas flow rate value for each loading port and the standard deviation of the gas flow rate; the standard deviation of the gas flow rate... in, The standard deviation of the gas flow rate corresponding to the loading port is represented by N; N represents the reference production batch quantity; MA LPi (i = 1, 2, ..., n) represents the predicted gas flow rate for each loading port, and n represents the number of loading ports included on the machine. t represents the initial gas flow rate corresponding to each loading port; t represents the batch end number.

[0014] In one exemplary embodiment of this disclosure, the gas flow rate range includes a maximum predicted value and a minimum predicted value. The method further includes: obtaining the gas flow rate prediction value corresponding to the production batch to be predicted; if the gas flow rate prediction value is less than the minimum predicted value, then the minimum predicted value is used as the gas flow rate prediction value; if the gas flow rate prediction value is greater than the maximum predicted value, then the maximum predicted value is used as the gas flow rate prediction value.

[0015] In one exemplary embodiment of this disclosure, the machine configuration parameters are generated through the following steps: obtaining a pre-built flow parameter configuration template; and assigning parameters to the gas flow parameters of each loading port of the machine based on the flow parameter configuration template to obtain the machine configuration parameters.

[0016] In one exemplary embodiment of this disclosure, the flow parameter configuration template includes a combination of any one or more parameters among machine characteristics, flow rate level, and gas flow purging value.

[0017] In one exemplary embodiment of this disclosure, based on the flow parameter configuration template, the gas flow parameters of each loading port of the machine are assigned parameters to obtain the machine configuration parameters. This includes: determining the machine characteristic value corresponding to the machine characteristic in the flow parameter configuration template; if the machine characteristic is a recipe control machine, then the default gas flow parameter value is used to assign parameters to the gas flow parameter to obtain the machine configuration parameters; if the machine characteristic is a parameter control machine, then the calculated gas flow parameter value is used to assign parameters to the gas flow parameter to obtain the machine configuration parameters.

[0018] In one exemplary embodiment of this disclosure, controlling the machine to purge gas onto the product to be processed arriving at the target loading port based on the target flow prediction value includes: generating a flow control command for the target loading port based on the target flow prediction value; sending the flow control command to the machine; controlling the machine to purge gas onto the product to be processed arriving at the target loading port based on the target flow prediction value, and recording the actual purge flow value.

[0019] In one exemplary embodiment of this disclosure, the method further includes: obtaining the actual purging flow rate value of the machine purging the target loading port; comparing the actual purging flow rate value with the target flow rate prediction value to obtain a flow rate comparison result; and locating a gas purging fault if the flow rate comparison result is inconsistent.

[0020] According to a second aspect of this disclosure, a gas flow control device is provided, comprising: an event response module, configured to determine a production batch corresponding to the product to be processed in response to a product arrival event at a target loading port; a parameter acquisition module, configured to acquire machine configuration parameters, the machine configuration parameters including a gas flow prediction value corresponding to at least one production batch at the machine loading port; a target prediction value determination module, configured to determine a target flow prediction value corresponding to the production batch to be processed arriving at the target loading port from the machine configuration parameters; and a control module, configured to control the machine to purge gas onto the product to be processed arriving at the target loading port according to the target flow prediction value.

[0021] In one exemplary embodiment of this disclosure, the gas flow control device further includes a flow prediction value determination module, configured to: acquire at least one loading port included in the machine; determine all production batches corresponding to the products to be processed that are about to arrive at each loading port; acquire the production batch number corresponding to each production batch; and determine the gas flow prediction value corresponding to each production batch in sequence according to the production batch number.

[0022] In one exemplary embodiment of this disclosure, the flow prediction value determination module includes a flow prediction unit, configured to: determine the production batch to be predicted based on the production batch number; obtain a pre-configured number of reference production batches; determine a set of production batches corresponding to the production batch to be predicted based on the number of reference production batches; the set of production batches includes at least one reference production batch; obtain the actual gas flow value corresponding to each of the reference production batches; and determine the gas flow prediction value corresponding to the production batch to be predicted based on the obtained actual gas flow value.

[0023] In one exemplary embodiment of this disclosure, the number of reference production batches is multiple, and the traffic prediction unit includes a batch set determination subunit, which is used to obtain the batch end number of the multiple reference production batches; determine the corresponding batch start number according to the number of reference production batches and the batch end number; and take the reference production batches between the batch start number and the batch end number as the production batch set.

[0024] In one exemplary embodiment of this disclosure, the number of actual gas flow rates is multiple, and the flow prediction unit further includes a flow prediction subunit for calculating the average of the multiple actual gas flow rates to obtain the predicted gas flow rate; the predicted gas flow rate... Among them, MA LPi (i = 1, 2, ..., n) represents the predicted gas flow rate for each loading port, n represents the number of loading ports on the machine, N represents the number of reference production batches, Xt represents the actual gas flow rate of the reference production batch corresponding to the batch end number, t represents the batch end number, and t-N+1 represents the batch start number.

[0025] In one exemplary embodiment of this disclosure, the flow prediction value determination module further includes a flow range determination unit, configured to determine the gas flow standard deviation corresponding to each loading port based on the reference production batch quantity corresponding to each loading port, multiple actual gas flow values, and multiple gas flow prediction values; and to determine the corresponding gas flow value range based on the gas flow prediction value corresponding to each loading port and the gas flow standard deviation; the gas flow standard deviation in, The standard deviation of the gas flow rate corresponding to the loading port is represented by N; N represents the reference production batch quantity; MA LPi (i = 1, 2, ..., n) represents the predicted gas flow rate for each loading port, and n represents the number of loading ports included on the machine. t represents the initial gas flow rate corresponding to each loading port; t represents the batch end number.

[0026] In one exemplary embodiment of this disclosure, the gas flow rate range includes a maximum predicted value and a minimum predicted value. The flow rate prediction value determination module further includes a prediction value adjustment unit, used to obtain the gas flow rate prediction value corresponding to the production batch to be predicted; if the gas flow rate prediction value is less than the minimum predicted value, then the minimum predicted value is used as the gas flow rate prediction value; if the gas flow rate prediction value is greater than the maximum predicted value, then the maximum predicted value is used as the gas flow rate prediction value.

[0027] In one exemplary embodiment of this disclosure, the flow prediction value determination module further includes a machine parameter configuration unit, used to obtain a pre-built flow parameter configuration template; based on the flow parameter configuration template, to perform parameter assignment processing on the gas flow parameters of each loading port of the machine to obtain the machine configuration parameters.

[0028] In one exemplary embodiment of this disclosure, the machine parameter configuration unit includes a machine parameter configuration subunit, used to perform parameter assignment processing on the gas flow parameters of each loading port of the machine based on the flow parameter configuration template to obtain the machine configuration parameters, including: determining the machine characteristic value corresponding to the machine characteristic in the flow parameter configuration template; if the machine characteristic value is a recipe control machine, then the default gas flow parameter value is used to perform parameter assignment processing on the gas flow parameter to obtain the machine configuration parameters; if the machine characteristic value is a parameter control machine, then the calculated gas flow parameter value is used to perform parameter assignment processing on the gas flow parameter to obtain the machine configuration parameters.

[0029] In one exemplary embodiment of this disclosure, the control module includes a control unit, configured to generate a flow control command for the target loading port based on the target flow prediction value; send the flow control command to the machine tool; control the machine tool to purge gas onto the product to be processed arriving at the target loading port based on the target flow prediction value, and record the actual purging flow value.

[0030] In one exemplary embodiment of this disclosure, the gas flow control device further includes a fault location module, configured to acquire the actual purging flow rate value of the machine purging the target loading port; compare the actual purging flow rate value with the target flow rate prediction value to obtain a flow rate comparison result; and locate a gas purging fault if the flow rate comparison result is inconsistent.

[0031] According to a third aspect of this disclosure, an electronic device is provided, comprising: a processor; and a memory storing computer-readable instructions that, when executed by the processor, implement the gas flow control method according to any one of the preceding claims.

[0032] According to a fourth aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the gas flow control method according to any one of the preceding claims.

[0033] The technical solution provided in this disclosure may include the following beneficial effects:

[0034] The gas flow control method in the exemplary embodiments of this disclosure, during machine operation, testing, or maintenance, can shorten process time, increase machine utilization, and save labor costs by automatically calculating the predicted gas flow rate for each loading port, eliminating the need for manual setting of gas purging parameters. Furthermore, when the product to be processed arrives at the loading port, the automatic control of the machine to purge gas into the loading port can effectively improve processing efficiency and product yield.

[0035] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0036] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0037] Figure 1 A flowchart illustrating the nitrogen usage mechanism in the existing semiconductor industry is shown in the illustration.

[0038] Figure 2 A flowchart illustrating an exemplary embodiment of a gas flow control method according to the present disclosure is shown schematically.

[0039] Figure 3 An overall flowchart of a gas flow control mechanism according to an exemplary embodiment of the present disclosure is illustrated schematically;

[0040] Figure 4 The diagram illustrates the results of determining the predicted gas flow rates for different production batches according to an exemplary embodiment of the present disclosure.

[0041] Figure 5 The diagram illustrates the results of gas flow rate values ​​for nearly 30 production batches of a machine according to an exemplary embodiment of the present disclosure.

[0042] Figure 6 A flowchart illustrating a control unit blowing purge gas onto a product to be processed at a loading port according to an exemplary embodiment of the present disclosure is shown.

[0043] Figure 7 A block diagram of a gas flow control device according to an exemplary embodiment of the present disclosure is shown schematically;

[0044] Figure 8 A block diagram of an electronic device according to an exemplary embodiment of the present disclosure is shown schematically;

[0045] Figure 9 The illustration shows a schematic diagram of a computer-readable storage medium according to an exemplary embodiment of the present disclosure. Detailed Implementation

[0046] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted.

[0047] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details described, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known structures, methods, apparatuses, implementations, materials, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0048] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, or in one or more software-hardened modules, or in different network and / or processor devices and / or microcontroller devices.

[0049] Gases are a crucial component of semiconductor manufacturing. For example, when wafers are transferred to the equipment for processing such as etching and cleaning, or when the equipment needs testing or maintenance, the nitrogen purging rate needs to be manually set in advance at the equipment level. (Reference) Figure 1 , Figure 1 A flowchart illustrating the nitrogen usage mechanism in the existing semiconductor industry is shown.

[0050] In step S110, the machine settings are manually configured. During semiconductor manufacturing, if nitrogen purging of the product to be processed is required, the nitrogen purging volume of the nitrogen purging machine can be preset. After the machine settings are completed, in step S120, the front-opening unified pod (FOUP) is moved to the machine; and in step S130, the machine is manually configured to purge the incoming wafer with nitrogen. In step S140, the nitrogen purging volume is recorded. After nitrogen purging is completed, in step S150, the FOUP is removed, ending the nitrogen purging process.

[0051] The entire process described above requires human intervention at each stage. Furthermore, the nitrogen purging rate can only be set according to a pre-defined value. If the nitrogen purging rate needs to be changed, it will need to be manually set again, making the entire operation time-consuming and labor-intensive.

[0052] Based on this, in this example embodiment, a gas flow control method is first provided. The gas flow control method of this disclosure can be implemented using a server or using a terminal device. The terminal described in this disclosure can include mobile terminals such as mobile phones, tablets, laptops, handheld computers, and personal digital assistants (PDAs), as well as fixed terminals such as desktop computers. Figure 1 A schematic diagram illustrating a gas flow control method flow according to some embodiments of the present disclosure is shown. Reference Figure 2 The gas flow control method may include the following steps:

[0053] Step S210: In response to the product arrival event of the product to be processed arriving at the target loading port, determine the production batch to be processed corresponding to the product to be processed.

[0054] According to some exemplary embodiments of this disclosure, the product to be processed can be a product awaiting processing in a semiconductor manufacturing process. A load port (LP) can be a device port in a machine that supports the product to be processed. A target load port can be a specific load port on the machine where the product to be processed arrives. A product arrival event can be an event in which the product to be processed arrives at the target load port on the machine. A production batch to be processed can be different production batches of the product to be processed arriving at the target load port in a sequential order.

[0055] In semiconductor manufacturing, when wafers need to undergo specific production processes on a machine, or when they are running, testing, or undergoing maintenance, FOUP can transfer a batch of wafers to be processed to the machine's loading port. Due to the actual needs of the production process, the wafers to be processed may arrive at different loading ports of the machine in different sequences. Arriving at the loading port in different sequences will generate corresponding production batches. Therefore, all production batches of products to be processed that arrive at the machine's loading port can be determined according to the production process requirements.

[0056] Step S220: Obtain the machine configuration parameters; the machine configuration parameters include the predicted gas flow rate corresponding to at least one production batch in the machine loading port.

[0057] According to some exemplary embodiments of this disclosure, the machine configuration parameters may be parameters related to the purge gas that the machine blows to each loading port. The predicted gas flow rate may be a pre-predicted value of the amount of purge gas that the machine will blow to each loading port.

[0058] Before the product arrival event occurs and gas purging is performed, pre-configured machine configuration parameters can be obtained. Since the machine can include one or more loading ports, the machine can perform gas purging on each loading port. The machine configuration parameters can include the predicted gas flow rate for purging all production batches that are about to arrive at the loading port.

[0059] Step S230: Determine the target flow prediction value corresponding to the production batch to be processed that arrives at the target loading port from the machine configuration parameters.

[0060] According to some exemplary embodiments of this disclosure, the target flow rate prediction value may be the amount of purge gas that the machine will blow into the target loading port in advance.

[0061] After a product arrival event occurs, the target flow prediction value corresponding to the production batch to be processed that arrives at the target loading port can be determined from the machine configuration parameters.

[0062] Step S240: Based on the target flow prediction value, control the machine to blow purge gas onto the product to be processed that has reached the target loading port.

[0063] According to some exemplary embodiments of this disclosure, after obtaining the target flow rate prediction value, the machine can be controlled to purge gas onto the product to be processed arriving at the target loading port according to the target flow rate prediction value, so as to achieve the product processing and production purpose. For example, when the machine is controlled to purge nitrogen into the wafer at the loading port, it can prevent the wafer from being oxidized, thereby further improving the product yield.

[0064] According to the gas flow control method in this example embodiment, during machine operation, testing, or maintenance, on the one hand, by automatically calculating the predicted gas flow rate for each loading port, there is no need to manually set gas purging parameters, which can shorten process time, increase machine utilization, and save labor costs. On the other hand, when the product to be processed arrives at the loading port, the automatic control of the machine to purge gas into the loading port can effectively improve processing efficiency and increase product yield.

[0065] The gas flow control method in this example embodiment will be further described below.

[0066] To achieve automated control of gas purging, this disclosure proposes a gas flow control method, referencing... Figure 3 , Figure 3A schematic flowchart illustrating the overall flow control mechanism according to an exemplary embodiment of the present disclosure is shown. In step S310, the machine configuration parameters are automatically configured. The control system can obtain the predicted gas flow rate corresponding to each loading port in the machine through the parameter configuration step. Specifically, as follows:

[0067] In one exemplary embodiment of this disclosure, at least one loading port of the machine is obtained; all production batches corresponding to the products to be processed that are about to arrive at each loading port are determined; the production batch number corresponding to each production batch is obtained; and the gas flow prediction value corresponding to each production batch is determined sequentially according to the production batch number.

[0068] In this context, a production batch can refer to different batches of products transported to the loading port of the machine by the product transport equipment. The production batch number can be a unique number corresponding to each different production batch, and the production batch number can be determined according to the order in which the products arrive at the loading port.

[0069] For a production machine, all loading ports within that machine can be identified; each machine may contain one or more loading ports. Once the loading ports are determined, multiple production batches corresponding to the products to be processed that will subsequently arrive at that loading port can be obtained. For example, in semiconductor manufacturing, wafers may undergo etching. Before the etching process, the wafers are placed in the machine's loading ports, which are equipped with robotic arms that place them into corresponding chambers. At this point, many wafers are waiting. During this period, the wafers may oxidize; therefore, nitrogen gas can be used to purge the wafers for oxidation protection.

[0070] During the production process, the products to be processed can be divided into different production batches and sent to the loading port to determine the predicted gas flow rate of different production batches of products to be processed in each loading port. Specifically, the predicted gas flow rate of different production batches of products to be processed is determined by the following steps: Before determining the predicted gas flow rate, the production batches of products to be processed that will arrive at the loading port later can be determined first, and the production batch numbers corresponding to each of the multiple production batches can be determined. For example, the production batch numbers can be determined according to the order in which the products to be processed arrive at the loading port. The resulting production batch numbers can be 1, 2, 3, ..., N, etc.

[0071] After obtaining the production batch numbers corresponding to multiple production batches, the predicted gas flow rate for each production batch can be determined sequentially based on these batch numbers. For example, if there are five production batches of products awaiting processing arriving at the first loading port, the predicted gas flow rate for each of production batches 1 through 5 can be determined sequentially. By predicting the predicted gas flow rate for the next production batch of products awaiting processing in advance, the specific amount of purging gas to be injected into that production batch can be determined based on the predicted gas flow rate.

[0072] In one exemplary embodiment of this disclosure, the production batch to be predicted is determined based on the production batch number; a pre-configured number of reference production batches is obtained, and a set of production batches corresponding to the production batch to be predicted is determined based on the number of reference production batches; the set of production batches includes at least one reference production batch; the actual gas flow rate value corresponding to each reference production batch is obtained; and the predicted gas flow rate value corresponding to the production batch to be predicted is determined based on the obtained actual gas flow rate value.

[0073] The production batch to be predicted can be a batch of products about to arrive at the machine loading port for processing. The number of reference production batches can be the number of reference production batches used to calculate the predicted gas flow rate of the production batch to be predicted, which can be represented as N. The set of production batches can be a set consisting of at least one reference production batch. The reference production batch can be a production batch whose actual gas flow rate is used as a reference when calculating the predicted gas flow rate of the production batch to be predicted. The actual gas flow rate can be the actual value of the purge gas corresponding to the reference production batch.

[0074] After obtaining the production batch number, the production batch to be predicted can be determined based on the production batch number. Before performing traffic prediction on the production batch to be predicted, a pre-configured number of reference production batches can be obtained, for example, the number of reference production batches can be configured as 3, 5, 6, etc. Based on the number of reference production batches, a set of production batches corresponding to the production batch to be predicted can be determined. This set of production batches can consist of one or more reference production batches corresponding to the production batch to be predicted.

[0075] Once the set of production batches consisting of reference production batches is determined, the actual gas flow rate value corresponding to each reference production batch can be obtained. The actual gas flow rate value can be determined based on historical production experience, such as the actual gas purging value determined by various influencing factors such as the placement of the products to be processed, their specific quantity, and processing requirements. After obtaining one or more actual gas flow rate values, these values ​​can be used as the basis for calculations to determine the predicted gas flow rate value corresponding to the production batch to be predicted.

[0076] In one exemplary embodiment of this disclosure, batch end numbers of multiple reference production batches are obtained; a corresponding batch start number is determined based on the number of reference production batches and the batch end number; and the reference production batches between the batch start number and the batch end number are used as a set of production batches.

[0077] The batch end number can be the end number of the reference production batch, and can be represented by 't'. The batch start number can be the start number of the reference production batch, and can be represented by 't-N+1'.

[0078] When determining the set of production batches used for gas flow prediction of the production batch to be predicted, the batch end number of the corresponding reference production batch can be determined first. Since the batch end number can be the batch number of the production batch to be predicted itself (for example, when the batch number corresponding to the production batch to be predicted is 3), the batch end number can be 3. In this case, based on the number of reference production batches and the batch end number, the batch start number corresponding to the production batch to be predicted can be determined, i.e., t-N+1=3-3+1=1. After determining the batch start number, the reference production batches between the batch start number and the batch end number can be used as the set of production batches.

[0079] For example, if the current production batch to be predicted is production batch 3 in machine loading port 1, then the batch end number is 3. When the reference production batch quantity is set to 3, the reference production batches corresponding to production batch 3 in machine loading port 1 will be production batch 1, production batch 2, and production batch 3, respectively. A production batch set is generated based on the determined reference production batches, and subsequent gas flow prediction processing is performed based on the obtained production batch set.

[0080] In one exemplary embodiment of this disclosure, the average of multiple actual gas flow rates is calculated to obtain a predicted gas flow rate; the predicted gas flow rate... Among them, MA LPi (i = 1, 2, ..., n) represents the predicted gas flow rate for each loading port, where n can represent the number of loading ports on the machine; N represents the number of reference production batches; Xt represents the actual gas flow rate of the reference production batch corresponding to the batch end number; t represents the batch end number; and t-N+1 represents the batch start number.

[0081] When multiple reference production batches are identified for the production batch to be predicted, the actual gas flow rate for each reference production batch can be obtained. Figure 4 , Figure 4 The diagram illustrates the results of determining the predicted gas flow rates for different production batches according to an exemplary embodiment of the present disclosure. Figure 4In this process, FOUP delivers 10 production batches of products to be processed to the loading port. For example, if the batch number of the current production batch to be predicted is 3, then the actual gas flow rates corresponding to production batches 1, 2, and 3 are obtained respectively. The average of the obtained actual gas flow rates is calculated to obtain the predicted gas flow rate, as shown in Formula 1.

[0082]

[0083] Among them, MA LPi (i = 1, 2, ..., n) can represent the predicted gas flow rate for each loading port, n can represent the number of loading ports on the machine; N can represent the number of reference production batches; Xt can represent the actual gas flow rate for the reference production batch corresponding to the batch end number; t can represent the batch end number; t-N+1 can represent the batch start number.

[0084] Similarly, the predicted gas flow rates for production batches 3 through 10 can be calculated separately. This processing method effectively improves the accuracy of the predicted gas flow rates.

[0085] Those skilled in the art will readily understand that the number of reference production batches corresponding to the production batch to be predicted can be one. In this case, a matching mathematical model will be used to calculate the predicted gas flow rate of the production batch to be predicted. For example, the predicted gas flow rate of the reference production batch can be used as the predicted gas flow rate of the production batch to be predicted.

[0086] In one exemplary embodiment of this disclosure, the standard deviation of the gas flow rate for each loading port is determined based on the reference production batch quantity corresponding to each loading port, multiple actual gas flow rate values, and multiple predicted gas flow rate values; the corresponding gas flow rate range is determined based on the predicted gas flow rate value and the standard deviation of the gas flow rate for each loading port; the standard deviation of the gas flow rate... in, Indicates the standard deviation of gas flow rate corresponding to the loading port; N represents the reference production batch quantity; MA LPi (i = 1, 2, ..., n) represents the predicted gas flow rate for each loading port, and n can represent the number of loading ports included on the machine. This represents the initial gas flow rate for each loading port; t represents the batch end number.

[0087] The standard deviation of gas flow rate can be the standard deviation of the predicted gas flow rate when purging a certain loading port in the machine. The range of gas flow rate values ​​can be the range of purging amounts for purging a certain loading port in the machine.

[0088] For a specific loading port of a machine, the batch of products to be processed that subsequently arrive at that loading port can be determined. (Reference) Figure 5 , Figure 5 The diagram schematically illustrates the gas flow rate values ​​for approximately 30 production batches of a machine according to an exemplary embodiment of this disclosure. Specifically, the flow rate reaches... Figure 5 There are a total of 30 production batches at the loading port. The gas flow prediction value corresponding to each production batch can be determined by the above calculation method.

[0089] Obtain the preset initial gas flow rate value. Based on the reference production batch quantity corresponding to each loading port, multiple initial gas flow rates, and multiple predicted gas flow rates, determine the standard deviation of the gas flow rate corresponding to each loading port, as shown in Formula 2.

[0090]

[0091] in, This can represent the standard deviation of the gas flow rate corresponding to the loading port; N can represent the reference production batch quantity; MA LPi (i = 1, 2, ..., N) can represent the predicted gas flow rate for each production batch, and n can represent the number of loading ports on the machine. It can represent the initial gas flow rate for each production batch; t can represent the batch end number.

[0092] After determining the standard deviation of the gas flow rate for each loading port, the corresponding gas flow rate range can be determined based on the predicted gas flow rate and the standard deviation of the gas flow rate. The gas flow rate range can be expressed as follows: in, It can represent the standard deviation of the gas flow rate corresponding to the loading port; MA LPi (i = 1, 2, ..., N) can represent the predicted gas flow rate for each production batch. By defining the gas flow rate range, the range of purge gas flow rates for each production batch at the loading port is limited.

[0093] It should be noted that the equipment used in the semiconductor manufacturing process includes equipment controlled by recipe and equipment controlled by equipment constant. The scheme of controlling the purging gas of the equipment based on the predicted gas flow rate in this embodiment is applicable to equipment controlled by equipment constant. For such equipment, it is only necessary to set parameters at the equipment end, which is applicable to scenarios that are unrelated to the recipe.

[0094] In one exemplary embodiment of this disclosure, the predicted gas flow rate corresponding to the production batch to be predicted is obtained; if the predicted gas flow rate is less than the minimum predicted value, the minimum predicted value is used as the predicted gas flow rate; if the predicted gas flow rate is greater than the maximum predicted value, the maximum predicted value is used as the predicted gas flow rate.

[0095] The maximum predicted value can be the largest value within the range of gas flow rates. The minimum predicted value can be the smallest value within the range of gas flow rates.

[0096] After obtaining the predicted gas flow rate for the production batch to be predicted, the predicted gas flow rate for the production batch can be compared with the maximum and minimum predicted values ​​within the gas flow rate range. If the predicted gas flow rate is less than the minimum predicted value, it is considered that the predicted flow rate of the purging gas may be insufficient due to the calculation method or other factors. Therefore, the minimum predicted value can be used as the predicted gas flow rate, and the purging gas for the production batch to be processed should be based on the minimum predicted value.

[0097] Similarly, if the predicted gas flow rate is greater than the maximum predicted value, it is considered that the gas flow rate purging the product to be processed is too high. In this case, the maximum predicted value can be used as the predicted gas flow rate. This method of revising the gas flow rate can reduce the error rate in calculating the predicted gas flow rate.

[0098] In one exemplary embodiment of this disclosure, the machine configuration parameters are generated through the following steps: obtaining a pre-built flow parameter configuration template; and assigning parameters to the gas flow parameters of each loading port of the machine based on the flow parameter configuration template to obtain the machine configuration parameters.

[0099] The flow parameter configuration template can be a general parameter template used for configuring purging parameters when purging the loading port of the machine. The parameter assignment process can be the process of assigning values ​​to one or more parameters contained in the flow parameter configuration template.

[0100] After calculating the predicted gas flow rate for each production batch, a pre-configured flow parameter template can be obtained. When configuring the machine configuration parameters, the flow parameter configuration template can be used as the basis.

[0101] In one exemplary embodiment of this disclosure, the flow parameter configuration template includes a combination of any one or more parameters among machine characteristics, flow rate level, and gas flow purging value.

[0102] Among these, machine characteristics can refer to the parameter control type of the machine during the production process. These characteristics determine whether the machine is controlled by the production process formula or by equipment constants. Flow rate levels can be categorized based on the amount of gas flow rate used for purging the loading port of the machine. The gas flow purging value is the numerical value of the gas flow rate used for purging the loading port.

[0103] In certain manufacturing processes, products can be processed using pre-set production configurations. In this case, the machine can be pre-programmed with a corresponding production recipe; such machines are recipe-controlled. Additionally, there are machines that are not recipe-controlled. Therefore, machine characteristics can be categorized as follows: recipe-controlled machines are identified as "Recipe," and unrecipe-controlled machines are identified as "NoRecipe."

[0104] When purging the loading port with gas, the flow rate can be classified according to the purging gas flow rate. For example, the Load Port can be divided into three levels: High, Middle, and Low. Assuming there are 5 loading ports in the machine, the flow rate classification for each of the 5 loading ports can result in LP1 to LP5 being any combination of one or more flow rates. For example, LP1 to LP5 could all be high, medium, or low flow rates; or LP1 to LP5 could be any two or three of the high, medium, and low flow rates.

[0105] The gas flow purging value can be the specific flow rate of the machine purging the production batch at that loading port. Based on the above three parameters, the flow parameter can be obtained in a unified format: N2Purge_{Recipe / NoRecipe}_{Low / Middle / High}_{Value}EC Control. In other gas applications, N2Purge can be replaced with the corresponding gas according to process requirements.

[0106] Based on a pre-configured, standardized flow parameter format, parameter values ​​are assigned to each loading port of the machine to obtain the machine configuration parameters. During the parameter assignment process, values ​​can be assigned to several characteristics, flow rates, and gas flow purging values ​​to obtain the machine configuration parameters.

[0107] In one exemplary embodiment of this disclosure, the machine characteristic value corresponding to the machine characteristic in the flow parameter configuration template is determined; if the machine characteristic value is a recipe control machine, the default gas flow parameter value is used to assign a parameter value to the gas flow parameter to obtain the machine configuration parameter; if the machine characteristic value is a parameter control machine, the calculated gas flow parameter value is used to assign a parameter value to the gas flow parameter to obtain the machine configuration parameter.

[0108] Among these, the machine characteristic value can be the specific value of the machine characteristic. A formula-controlled machine can be a machine controlled by a formula. A parameter-controlled machine can be a machine controlled by equipment constants.

[0109] After configuring the machine parameters based on the flow parameter configuration template, the specific values ​​of the machine characteristics in the flow parameter configuration template can be obtained, i.e., the machine characteristic values. If the machine characteristic value is a recipe-controlled machine, it is assumed that the machine is controlled by the pre-configured recipe. Therefore, the machine will be configured using the recipe's default parameters, i.e., the default gas flow parameter values ​​will be used to assign values ​​to the gas flow parameters to obtain the machine configuration parameters.

[0110] If the machine characteristic value is a parameter-controlled machine, it is considered that the machine uses the gas flow parameter value calculated in this disclosure for gas purging. That is, the calculated gas flow parameter value is used to assign a parameter value to the gas flow parameter to obtain the machine configuration parameter. Subsequently, gas purging will be performed based on the machine configuration parameter. The calculated gas flow parameter value can be well adapted to the scenario of equipment constant control, achieving the purpose of independent parameter prediction, high prediction efficiency and accurate prediction.

[0111] After configuring the machine parameters, you can send the configuration parameters to the machine for further reference. Figure 3 In step S320, if a product arrival event is detected, then in step S330, the machine is controlled to purge nitrogen. In response to the product arrival event, the machine is controlled to purge nitrogen into the loading port. In step S340, the actual gas purging volume is recorded. During the process of purging gas into the loading port, the equipment will automatically record the actual purging flow rate value for subsequent comparison of inventory and material consistency. In step S350, the nitrogen purging is automatically terminated. After the nitrogen purging is completed based on the actual purging flow rate value, the nitrogen purging will be automatically terminated, eliminating the need for manual stopping of the nitrogen purging and effectively saving manpower and resources.

[0112] In one exemplary embodiment of this disclosure, a flow control command for the target loading port is generated based on the target flow prediction value; the flow control command is sent to the machine tool; the machine tool is controlled to purge gas onto the product to be processed arriving at the target loading port based on the target flow prediction value, and the actual purging flow value is recorded.

[0113] The flow control command can be a control command that controls the machine to purge gas to a certain loading port. The actual purging flow rate value can be the actual value of the gas purged by the machine to the loading port.

[0114] refer to Figure 6 , Figure 6 A flowchart illustrating the process of a control unit purging gas onto the product to be processed at the loading port, according to an exemplary embodiment of this disclosure, is shown. The Material Management (MM) system can send flow control-related data to the Equipment Automation Program (EAP) via a transmission interface and perform corresponding Equipment Constant (EC) control. For example, the MM system can send flow parameters in a standardized format to the EAP via the transmission interface to generate unit configuration parameters. Which units require gas purging can be determined based on the standardized unit characteristics derived from the flow parameters.

[0115] After receiving the standardized flow parameters and having the FOUP automatically transport them to the machine, the EAP terminal can calculate the predicted gas flow rate for each Load Port based on a mathematical model and assign it to the machine. Specifically, after receiving the standardized flow parameters, the EAP terminal can configure the machine's configuration parameters. Once the configuration is complete, it can generate flow control commands for the machine's loading ports based on the configuration parameters. For example, the flow control command could be an S2F15 command. The EAP terminal then sends the flow control command to the machine (Tool).

[0116] Because the flow control command includes the predicted target flow rate at the target loading port, the machine can be controlled to purge gas onto the product to be processed at the target loading port based on the predicted target flow rate. After the FOUP is removed, the gas purging can be stopped, and the actual purging flow rate value can be automatically recorded for subsequent comparison of inventory and material consistency.

[0117] In one exemplary embodiment of this disclosure, the actual purging flow rate value of the machine purging the target loading port is obtained; the actual purging flow rate value is compared with the target flow rate prediction value to obtain the flow rate comparison result; if the flow rate comparison result is inconsistent, the gas purging fault is located.

[0118] The flow rate comparison result is obtained by comparing the actual purging flow rate with the predicted target flow rate. Gas purging failures can cause inconsistencies in the flow rate comparison results.

[0119] Since the actual purging flow rate was recorded during the gas purging process at the loading port, this flow rate can be retrieved during subsequent verification and compared with the predicted target flow rate. If they match, the gas purging process is considered normal. If they don't match, a malfunction is considered to have occurred, requiring the identification of the specific gas purging fault. For example, a gas purging fault might include a leak in the gas purging equipment or a deviation in the calculated predicted value. By identifying the gas purging fault, problems in the gas purging process can be corrected promptly, ensuring the effectiveness of the gas purging process and further improving product yield.

[0120] In summary, the gas flow control method disclosed herein includes: responding to a product arrival event where a product to be processed arrives at a target loading port, determining the production batch corresponding to the product to be processed; acquiring machine configuration parameters; the machine configuration parameters including a predicted gas flow rate value corresponding to at least one production batch at the machine loading port; determining a predicted target flow rate value corresponding to the production batch to be processed arriving at the target loading port from the machine configuration parameters; and controlling the machine to purge gas onto the product to be processed arriving at the target loading port based on the predicted target flow rate value. During machine operation, testing, or maintenance, on the one hand, by automatically calculating the predicted gas flow rate value for each loading port, manual setting of gas purging parameters is unnecessary, which can shorten process time, increase machine utilization, and save labor costs. On the other hand, automatically controlling the machine to purge gas onto the loading port when the product to be processed arrives can effectively improve processing efficiency and product yield. Furthermore, sequentially determining the predicted gas flow rate values ​​and performing gas purging based on the determined predicted gas flow rate values ​​can effectively control the gas purging flow rate and avoid gas waste. On the other hand, during gas purging, the actual gas purging volume is automatically recorded, which facilitates subsequent verification of gas usage and product consistency.

[0121] It should be noted that although the steps of the method in this invention are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0122] Furthermore, in this example embodiment, a gas flow control device is also provided. (See reference...) Figure 7 The gas flow control device 700 may include: an event response module 710, a parameter acquisition module 720, a target prediction value acquisition module 730, and a control module 740.

[0123] Specifically, the event response module 710 is used to respond to a product arrival event when the product to be processed arrives at the target loading port and determine the production batch corresponding to the product to be processed; the parameter acquisition module 720 is used to acquire machine configuration parameters, including the gas flow prediction value corresponding to at least one production batch at the machine loading port; the target prediction value determination module 730 is used to determine the target flow prediction value corresponding to the production batch to be processed arriving at the target loading port from the machine configuration parameters; and the control module 740 is used to control the machine to purge gas onto the product to be processed arriving at the target loading port according to the target flow prediction value.

[0124] In one exemplary embodiment of this disclosure, the gas flow control device 700 further includes a flow prediction value determination module, which is used to acquire at least one loading port included in the machine; determine all production batches corresponding to the products to be processed that are about to arrive at each loading port; acquire the production batch number corresponding to each production batch; and determine the gas flow prediction value corresponding to each production batch in sequence according to the production batch number.

[0125] In one exemplary embodiment of this disclosure, the flow prediction value determination module includes a flow prediction unit, configured to determine the production batch to be predicted based on the production batch number; obtain a pre-configured number of reference production batches; determine a set of production batches corresponding to the production batch to be predicted based on the number of reference production batches; the set of production batches includes at least one reference production batch; obtain the actual gas flow value corresponding to each reference production batch; and determine the gas flow prediction value corresponding to the production batch to be predicted based on the obtained actual gas flow value.

[0126] In one exemplary embodiment of this disclosure, the number of reference production batches is multiple, and the flow prediction unit includes a batch set determination subunit, which is used to obtain the batch end number of multiple reference production batches; determine the corresponding batch start number according to the number of reference production batches and the batch end number; and take the reference production batches between the batch start number and the batch end number as the production batch set.

[0127] In one exemplary embodiment of this disclosure, there are multiple actual gas flow rates, and the flow prediction unit further includes a flow prediction subunit for calculating the average of the multiple actual gas flow rates to obtain a predicted gas flow rate value; the predicted gas flow rate value Among them, MA LPi (i = 1, 2, ..., n) represents the predicted gas flow rate for each loading port, where n can represent the number of loading ports on the machine; N represents the number of reference production batches; Xt represents the actual gas flow rate of the reference production batch corresponding to the batch end number; t represents the batch end number; and t-N+1 represents the batch start number.

[0128] In one exemplary embodiment of this disclosure, the flow prediction value determination module further includes a flow range determination unit, used to determine the standard deviation of the gas flow rate for each loading port based on the reference production batch quantity corresponding to each loading port, multiple actual gas flow rates, and multiple predicted gas flow rates; and to determine the corresponding gas flow rate range based on the predicted gas flow rate and the standard deviation of the gas flow rate for each loading port. in, Indicates the standard deviation of gas flow rate corresponding to the loading port; N represents the reference production batch quantity; MA LPi (i = 1, 2, ..., n) represents the predicted gas flow rate for each loading port, and n can represent the number of loading ports included on the machine. This represents the initial gas flow rate for each loading port; t represents the batch end number.

[0129] In one exemplary embodiment of this disclosure, the gas flow rate range includes a maximum predicted value and a minimum predicted value. The flow rate prediction value determination module further includes a prediction value adjustment unit, which is used to obtain the gas flow rate prediction value corresponding to the production batch to be predicted. If the gas flow rate prediction value is less than the minimum predicted value, the minimum predicted value is used as the gas flow rate prediction value. If the gas flow rate prediction value is greater than the maximum predicted value, the maximum predicted value is used as the gas flow rate prediction value.

[0130] In one exemplary embodiment of this disclosure, the flow prediction value determination module further includes a machine parameter configuration unit, which is used to obtain a pre-built flow parameter configuration template; based on the flow parameter configuration template, the gas flow parameters of each loading port of the machine are assigned parameters to obtain the machine configuration parameters.

[0131] In one exemplary embodiment of this disclosure, the machine parameter configuration unit includes a machine parameter configuration subunit, used to perform parameter assignment processing on the gas flow parameters of each loading port of the machine based on the flow parameter configuration template to obtain machine configuration parameters. This includes: determining the machine characteristic value corresponding to the machine characteristic in the flow parameter configuration template; if the machine characteristic value is a recipe-controlled machine, then using the default gas flow parameter value to perform parameter assignment processing on the gas flow parameter to obtain the machine configuration parameters; if the machine characteristic value is a parameter-controlled machine, then using the calculated gas flow parameter value to perform parameter assignment processing on the gas flow parameter to obtain the machine configuration parameters.

[0132] In one exemplary embodiment of this disclosure, the control module 440 includes a control unit, configured to generate a flow control command for a target loading port based on a target flow prediction value; send the flow control command to the machine tool; control the machine tool to purge gas onto the product to be processed arriving at the target loading port based on the target flow prediction value, and record the actual purging flow value.

[0133] In one exemplary embodiment of this disclosure, the gas flow control device 400 further includes a fault location module, which is used to obtain the actual purging flow value of the machine purging the target loading port; compare the actual purging flow value with the target flow prediction value to obtain the flow comparison result; if the flow comparison result is inconsistent, then locate the gas purging fault.

[0134] The specific details of the virtual modules of each gas flow control device mentioned above have been described in detail in the corresponding gas flow control methods, so they will not be repeated here.

[0135] It should be noted that although several modules or units of the gas flow control device have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0136] Furthermore, in an exemplary embodiment of this disclosure, an electronic device capable of implementing the above-described method is also provided.

[0137] Those skilled in the art will understand that various aspects of the present invention can be implemented as systems, methods, or program products. Therefore, various aspects of the present invention can be specifically implemented as entirely hardware embodiments, entirely software embodiments (including firmware, microcode, etc.), or embodiments combining hardware and software aspects, collectively referred to herein as “circuit,” “module,” or “system.”

[0138] The following is for reference. Figure 8 To describe an electronic device 800 according to such an embodiment of the present disclosure. Figure 8 The electronic device 800 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0139] like Figure 8 As shown, the electronic device 800 is presented in the form of a general-purpose computing device. The components of the electronic device 800 may include, but are not limited to: at least one processing unit 810, at least one storage unit 820, a bus 830 connecting different system components (including storage unit 820 and processing unit 810), and a display unit 840.

[0140] The storage unit stores program code that can be executed by the processing unit 810, causing the processing unit 810 to perform the steps described in the "Exemplary Methods" section above, according to various exemplary embodiments of this disclosure.

[0141] Storage unit 820 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 821 and / or cache memory 822, and may further include a read-only memory (ROM) 823.

[0142] Storage unit 820 may include a program / utility 824 having a set (at least one) of program modules 825, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0143] Bus 830 can represent one or more of several bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0144] Electronic device 800 can also communicate with one or more external devices 870 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 800, and / or with any device that enables electronic device 800 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 850. Furthermore, electronic device 800 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 860. As shown, network adapter 860 communicates with other modules of electronic device 800 via bus 830. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0145] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0146] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of the invention may also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of the invention described in the "Exemplary Methods" section above.

[0147] refer to Figure 9 As shown, a program product 900 for implementing the above-described method according to an embodiment of the present invention is described. It may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0148] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0149] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0150] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0151] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0152] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0153] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

[0154] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A gas flow control method, characterized in that, include: In response to a product arrival event where the product to be processed arrives at the target loading port, the production batch corresponding to the product to be processed is determined; Obtain the machine configuration parameters; the machine configuration parameters include the predicted gas flow rate value corresponding to at least one production batch in the machine loading port; The target flow prediction value corresponding to the production batch to be processed that arrives at the target loading port is determined from the machine configuration parameters; Based on the predicted target flow rate, the machine is controlled to purge gas onto the product to be processed that has reached the target loading port; The predicted gas flow rate is obtained through the following steps: Obtain at least one loading port included in the machine; Identify all production batches corresponding to the products to be processed that are about to arrive at each of the loading ports; Obtain the production batch number corresponding to each of the aforementioned production batches; Based on the production batch number, the gas flow prediction value corresponding to each production batch is determined sequentially. This process includes: The production batch to be predicted is determined based on the production batch number; Obtain a pre-configured reference production batch quantity, and determine a set of production batches corresponding to the production batch to be predicted based on the reference production batch quantity; the set of production batches includes at least one reference production batch. Obtain the actual gas flow rate value corresponding to each of the reference production batches; Based on the obtained actual gas flow rate value, the predicted gas flow rate value corresponding to the production batch to be predicted is determined.

2. The method according to claim 1, characterized in that, The number of reference production batches is multiple, and the step of determining the set of production batches corresponding to the production batch to be predicted based on the number of reference production batches includes: Obtain the batch end numbers of multiple reference production batches; Based on the reference production batch quantity and the batch end number, determine the corresponding batch start number; The reference production batches between the start number and the end number of the batch are used as the production batch set.

3. The method according to claim 2, characterized in that, The number of actual gas flow rates is multiple. The step of determining the predicted gas flow rate value corresponding to the production batch to be predicted based on the obtained actual gas flow rates includes: The gas flow rate prediction value is obtained by averaging multiple actual gas flow rate values. The predicted gas flow rate ; Among them, MA LPi (i=1, 2, ..., n) represents the predicted gas flow rate for each loading port, n represents the number of loading ports on the machine, N represents the number of reference production batches, Xt represents the actual gas flow rate of the reference production batch corresponding to the batch end number, t represents the batch end number, and t-N+1 represents the batch start number.

4. The method according to claim 1, characterized in that, The method further includes: Based on the reference production batch quantity corresponding to each loading port, the multiple actual gas flow rates and the multiple predicted gas flow rates, determine the standard deviation of the gas flow rate corresponding to each loading port. The corresponding gas flow rate range is determined based on the predicted gas flow rate value and the standard deviation of the gas flow rate for each loading port. The standard deviation of gas flow rate ; in, The standard deviation of the gas flow rate corresponding to the loading port is represented by N; N represents the reference production batch quantity; MA LPi (i=1, 2, ..., n) represents the predicted gas flow rate for each loading port, and n represents the number of loading ports included on the machine. (i=1, 2, ..., n) represents the initial gas flow rate corresponding to each loading port; t represents the batch end number.

5. The method according to claim 1, characterized in that, The gas flow rate range includes the maximum predicted value and the minimum predicted value, and the method further includes: Obtain the predicted gas flow rate value corresponding to the production batch to be predicted; If the predicted gas flow rate is less than the minimum predicted value, then the minimum predicted value is used as the predicted gas flow rate. If the predicted gas flow rate is greater than the maximum predicted value, then the maximum predicted value is used as the predicted gas flow rate.

6. The method according to claim 1, characterized in that, The machine configuration parameters are generated through the following steps: Obtain a pre-built traffic parameter configuration template; Based on the flow parameter configuration template, the gas flow parameters of each loading port of the machine are assigned values ​​to obtain the machine configuration parameters.

7. The method according to claim 6, characterized in that, The flow parameter configuration template includes a combination of any one or more parameters among machine characteristics, flow level, and gas flow purging value.

8. The method according to claim 7, characterized in that, Based on the flow parameter configuration template, the gas flow parameters at each loading port of the machine are assigned values ​​to obtain the machine configuration parameters, including: Determine the machine characteristic value corresponding to the machine characteristic in the flow parameter configuration template; If the machine characteristic value is a recipe control machine, then the default gas flow parameter value is used to assign a parameter value to the gas flow parameter to obtain the machine configuration parameters; If the machine characteristic value is a parameter-controlled machine, then the calculated gas flow rate parameter value is used to assign a parameter value to the gas flow rate parameter to obtain the machine configuration parameters.

9. The method according to claim 1, characterized in that, The step of controlling the machine to purge gas onto the product to be processed arriving at the target loading port based on the predicted target flow rate includes: Generate flow control instructions for the target loading port based on the target flow prediction value; Send the flow control command to the machine; The machine is controlled to purge gas onto the product to be processed that arrives at the target loading port based on the predicted target flow rate, and the actual purge flow rate is recorded.

10. The method according to claim 9, characterized in that, The method further includes: Obtain the actual purging flow rate value of the machine purging the target loading port; The actual purging flow rate value is compared with the target flow rate prediction value to obtain the flow rate comparison result; If the flow rate comparison results are inconsistent, then a gas purging fault is located.

11. A gas flow control device, characterized in that, include: The event response module is used to respond to the product arrival event of the product to be processed arriving at the target loading port and determine the production batch corresponding to the product to be processed; The parameter acquisition module is used to acquire machine configuration parameters; the machine configuration parameters include the predicted gas flow rate value corresponding to at least one production batch in the machine loading port; The target prediction value determination module is used to determine the target flow prediction value corresponding to the production batch to be processed that arrives at the target loading port from the machine configuration parameters; The control module is used to control the machine to blow purge gas onto the product to be processed that has arrived at the target loading port, based on the predicted target flow rate. The parameter acquisition module obtains the predicted gas flow rate value through the following steps: Obtain at least one loading port included in the machine; Identify all production batches corresponding to the products to be processed that are about to arrive at each of the loading ports; Obtain the production batch number corresponding to each of the aforementioned production batches; Based on the production batch number, the gas flow prediction value corresponding to each production batch is determined sequentially. This process includes: The production batch to be predicted is determined based on the production batch number; Obtain a pre-configured reference production batch quantity, and determine a set of production batches corresponding to the production batch to be predicted based on the reference production batch quantity; the set of production batches includes at least one reference production batch. Obtain the actual gas flow rate value corresponding to each of the reference production batches; Based on the obtained actual gas flow rate value, the predicted gas flow rate value corresponding to the production batch to be predicted is determined.

12. An electronic device, characterized in that, include: processor; as well as A memory storing computer-readable instructions that, when executed by the processor, implement the gas flow control method according to any one of claims 1 to 11.

13. A computer-readable storage medium having a computer program stored thereon, the computer program, when executed by a processor, implementing the gas flow control method according to any one of claims 1 to 11.

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