Wafer distribution method, device, apparatus, medium, and program product

Abstract

The present disclosure provides a wafer distribution method, device, equipment, medium and program product, which can be applied to the field of cloud computing. The method comprises the following steps: determining a constraint condition for distributing wafers in a wafer storage container to a wafer processing area according to a distribution relationship between the wafer storage container and the wafer processing area in a distribution task; defining a distribution state of the wafers in the wafer storage container to construct a target function for representing a gap between an actual distribution result and an expected distribution result according to a definition result; solving the target function based on storage information of the wafer storage container and a number of the wafer processing areas in the distribution task under the constraint condition to obtain a solution result; and determining a wafer distribution scheme according to the solution result in a case where it is determined that the solution result meets a preset condition, wherein the preset condition is that the gap between the actual distribution result and the expected distribution result reaches a minimum.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of cloud computing, and more particularly, to a wafer distribution method, device, equipment, medium and program product. BACKGROUND

[0002] Wafer is a key material for semiconductor manufacturing. In the process of wafer processing, wafers are taken out from storage containers and distributed to processing areas of machines for centralized processing. At present, the wafer distribution technology mainly adopts a brute force search method, that is, the best wafer distribution strategy is determined by trying all possible distribution schemes.

[0003] In the process of implementing the present concept, the inventors have found that at least the following problem exists in the related art. When facing large-scale data processing, the brute force search method is used to traverse the wafer distribution scheme, which takes a long time and results in low wafer distribution efficiency. SUMMARY

[0004] Therefore, the present disclosure provides a wafer distribution method, device, equipment, medium and program product.

[0005] One aspect of the present disclosure provides a wafer distribution method, comprising: determining a constraint condition for distributing wafers in a wafer storage container to a wafer processing area according to a distribution relationship between the wafer storage container and the wafer processing area in a distribution task; defining a distribution state of the wafers in the wafer storage container to construct a target function for representing a gap between an actual distribution result and an expected distribution result according to a definition result, wherein the expected distribution result is an average distribution of wafers in a plurality of wafer storage containers to a plurality of wafer processing areas; solving the target function based on storage information of the wafer storage container and a number of the wafer processing areas in the distribution task under the constraint condition to obtain a solution result; and determining a wafer distribution scheme according to the solution result in a case where the solution result satisfies a preset condition, wherein the preset condition is that the gap between the actual distribution result and the expected distribution result reaches a minimum.

[0006] According to the embodiments of the present disclosure, the definition of the distribution state of the wafers in the wafer storage container comprises: defining the distribution state of the wafers in the wafer storage container as a value representing a positive direction in a binary decision variable in a case where all wafers in the wafer storage container are distributed to the same wafer processing area; and defining the distribution state of the wafers in the wafer storage container as a value representing a negative direction in a binary decision variable in a case where all wafers in the wafer storage container are not distributed to the same wafer processing area.

[0007] According to an embodiment of the present disclosure, the constructing the objective function for characterizing the gap between the actual allocation result and the expected allocation result according to the definition result comprises: constructing a factor for calculating the actual allocation result according to the definition result and a variable for characterizing the number of wafers in the wafer storage container; constructing a factor for calculating the expected allocation result according to the number of wafers in each wafer storage container and the number of wafer processing areas; and subtracting the factor corresponding to the actual allocation result from the factor corresponding to the expected allocation result to construct the objective function.

[0008] According to an embodiment of the present disclosure, the constraint condition comprises an allocation constraint condition and a capacity constraint condition, and the determining the constraint condition for allocating the wafers in the wafer storage container to the wafer processing area according to the allocation relationship between the wafer storage container and the wafer processing area in the allocation task comprises: determining a target processing area capable of wafer allocation corresponding to each wafer storage container from the plurality of wafer processing areas; generating the allocation constraint condition according to the allocation relationship between the target processing area and the wafer storage container; and generating the capacity constraint condition based on the maximum capacity of each wafer processing area for wafers.

[0009] According to an embodiment of the present disclosure, the solving the objective function based on the storage information of the wafer storage container and the number of wafer processing areas in the allocation task under the constraint condition to obtain a solution result comprises: generating a constraint expression corresponding to the binary decision variable according to the constraint condition; inputting the number of wafers stored in each wafer storage container in the storage information and the number of wafer processing areas into the objective function to solve the objective function under the constraint expression, and outputting the solution result.

[0010] According to an embodiment of the present disclosure, the method further comprises: comparing a plurality of solution results output by the objective function to determine a minimum value from the plurality of solution results, wherein the minimum value is a solution result satisfying the preset condition.

[0011] According to an embodiment of the present disclosure, the above determining the wafer distribution scheme according to the solving result comprises: determining values of a plurality of binary decision variables corresponding to the solving result; determining, from the values of the plurality of binary decision variables, a variable set corresponding to each of the wafer processing areas, wherein the values in the variable set correspond to the plurality of wafer storage containers respectively; for each of the wafer processing areas, extracting values in the variable set representing a positive direction to determine wafer storage containers to which wafers are distributed to the wafer processing area, to obtain a sub-distribution scheme corresponding to the wafer processing area; and combining the sub-distribution schemes of the plurality of wafer processing areas to obtain the wafer distribution scheme corresponding to the distribution task.

[0012] Another aspect of the present disclosure provides a wafer distribution device, comprising: a constraint determination module configured to determine a constraint condition for distributing wafers in wafer storage containers to wafer processing areas according to a distribution relationship between the wafer storage containers and the wafer processing areas in a distribution task; a function construction module configured to define a distribution state of the wafers in the wafer storage containers, and to construct a target function for representing a gap between an actual distribution result and an expected distribution result according to a definition result, wherein the expected distribution result is an average distribution of the wafers in the plurality of wafer storage containers to the plurality of wafer processing areas; a function solving module configured to solve the target function based on storage information of the wafer storage containers and a number of the wafer processing areas in the distribution task under the constraint condition, to obtain a solving result; and a scheme determination module configured to determine a wafer distribution scheme according to the solving result when the solving result satisfies a preset condition, wherein the preset condition is that the gap between the actual distribution result and the expected distribution result is minimized.

[0013] Another aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method as described above.

[0014] Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions that, when executed, implement the method as described above.

[0015] Another aspect of the present disclosure provides a computer program product comprising computer-executable instructions that, when executed, implement the method as described above.

[0016] According to the embodiments of the present disclosure, constraint conditions are established according to the distribution relationship between the wafer storage container and the wafer processing area, and the distribution state of the wafers in the wafer storage container is defined, a target function is constructed for characterizing the gap between the actual distribution result and the expected distribution result, so that in the process of distributing the wafers, a better wafer distribution scheme can be quickly obtained under the condition of meeting multiple constraint conditions, thereby effectively improving the wafer distribution efficiency and reducing the time consumed. BRIEF DESCRIPTION OF DRAWINGS

[0017] The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure taken in conjunction with the accompanying drawings, in which:

[0018] Figure 1 An exemplary system architecture to which the wafer distribution method and device of the present disclosure can be applied is schematically shown;

[0019] Figure 2 A flowchart of the wafer distribution method according to the embodiments of the present disclosure is schematically shown;

[0020] Figure 3 A schematic diagram of wafer distribution in the wafer distribution method according to the embodiments of the present disclosure is schematically shown;

[0021] Figure 4 A schematic diagram of wafer distribution scheme determination in the wafer distribution method according to the embodiments of the present disclosure is schematically shown;

[0022] Figure 5 A block diagram of the wafer distribution device according to the embodiments of the present disclosure is schematically shown;

[0023] Figure 6 A block diagram of an electronic device suitable for implementing the wafer distribution method according to the embodiments of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0024] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it is to be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. However, it will be apparent to one skilled in the art that one or more embodiments can be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques have been omitted to avoid unnecessarily obscuring the concept of the present disclosure.

[0025] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the terms "comprises", "comprising", "includes", "including" and the like are specifically intended to be open-ended and to mean that other features, steps, operations, and / or components can be added.

[0026] All terms used herein, including technical and scientific terms, have the meanings commonly understood by one of ordinary skill in the art unless otherwise defined. It should be noted that the terms used herein are to be interpreted as having a meaning that is consistent with the context of the specification, and should not be interpreted in an idealized or overly formal way.

[0027] In situations where similar terminology is used, such as "at least one of A, B, and C is used in the context of expressing a set of possibilities the ordinary skill in the art will understand that such formal language is simply exemplary and that the term is intended to encompass numerous subsets of possibilities as well. For example, the term "a system having at least one of A, B, and C" shall be read to mean a system having A by itself, a system having B by itself, an A and B system, a B and C system, a system having only A and B, a system having only B and C, a system having only A and C, a system having A, B, and C, and / or a system having none of A, B, and C.

[0028] In embodiments of the present disclosure, the collection, updating, analysis, processing, use, transmission, provision, disclosure, storage, etc. of the data involved (for example, including but not limited to user personal information) comply with relevant laws and regulations, are used for legal purposes, and do not violate public order and good customs. In particular, necessary measures have been taken to prevent illegal access to user personal information data and to maintain user personal information security and network security.

[0029] In embodiments of the present disclosure, the authorization or consent of the user is obtained before the user's personal information is acquired or collected.

[0030] Embodiments of the present disclosure provide a wafer distribution method, device, equipment, medium and program product. The method comprises: determining a constraint condition for distributing wafers in a wafer storage container to a wafer processing area according to a distribution relationship between the wafer storage container and the wafer processing area in a distribution task; defining a distribution state of the wafers in the wafer storage container to construct a target function for representing a gap between an actual distribution result and an expected distribution result according to a definition result, wherein the expected distribution result is an average distribution of the wafers in the plurality of wafer storage containers to the plurality of wafer processing areas; solving the target function based on storage information of the wafer storage container and a number of the wafer processing areas in the distribution task under the constraint condition to obtain a solution result; and determining a wafer distribution scheme according to the solution result in a case where it is determined that the solution result meets a preset condition, wherein the preset condition is that the gap between the actual distribution result and the expected distribution result reaches a minimum.

[0031] Figure 1An exemplary system architecture to which the wafer distribution method and apparatus of the present disclosure can be applied is schematically shown. It should be noted that Figure 1 The shown is only an example of the system architecture to which the embodiments of the present disclosure can be applied, to help the skilled in the art understand the technical content of the present disclosure, but does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0032] As Figure 1 The system architecture 100 according to the embodiment can include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104 and a server 105, as shown. The network 104 is a medium to provide communication links between the first terminal device 101, the second terminal device 102, the third terminal device 103 and the server 105. The network 104 can include various connection types, such as wired and / or wireless communication links, etc.

[0033] The user can use the first terminal device 101, the second terminal device 102, the third terminal device 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients and / or social platform software, etc. (only as examples).

[0034] The first terminal device 101, the second terminal device 102, the third terminal device 103 can be various electronic devices with display screens and supporting web browsing, including but not limited to smartphones, tablet computers, laptop computers and desktop computers, etc.

[0035] The server 105 can be a server providing various services, such as a background management server supporting the website browsed by the user using the first terminal device 101, the second terminal device 102, the third terminal device 103 (only as an example). The background management server can analyze and process the received user requests and other data, and feed back the processing results (such as web pages, information or data obtained or generated according to user requests, etc.) to the terminal device.

[0036] It should be noted that the wafer distribution method provided by the embodiments of the present disclosure can be generally executed by the server 105. Accordingly, the wafer distribution apparatus provided by the embodiments of the present disclosure can be generally arranged in the server 105. The wafer distribution method provided by the embodiments of the present disclosure can also be executed by a server or a server cluster different from the server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Accordingly, the wafer distribution apparatus provided by the embodiments of the present disclosure can also be arranged in a server or a server cluster different from the server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Alternatively, the wafer distribution method provided by the embodiments of the present disclosure can also be executed by the first terminal device 101, the second terminal device 102 or the third terminal device 103, or by other terminal devices different from the first terminal device 101, the second terminal device 102 or the third terminal device 103. Accordingly, the wafer distribution apparatus provided by the embodiments of the present disclosure can also be arranged in the first terminal device 101, the second terminal device 102 or the third terminal device 103, or in other terminal devices different from the first terminal device 101, the second terminal device 102 or the third terminal device 103.

[0037] It should be understood that Figure 1 The number of terminal devices, networks and servers in the system is only illustrative. Any number of terminal devices, networks and servers can be provided according to the implementation needs.

[0038] Figure 2 A flowchart of a wafer distribution method according to an embodiment of the present disclosure is schematically shown.

[0039] As Figure 2 shown, the method comprises operations S210-S240.

[0040] At operation S210, a constraint condition for distributing wafers in wafer storage containers to wafer processing areas is determined according to a distribution relationship between the wafer storage containers and the wafer processing areas in a distribution task.

[0041] At operation S220, a distribution state of wafers in the wafer storage containers is defined to construct a target function for characterizing a gap between an actual distribution result and an expected distribution result according to a definition result, wherein the expected distribution result is an average distribution of wafers in multiple wafer storage containers to multiple wafer processing areas.

[0042] At operation S230, the target function is solved based on storage information of the wafer storage containers and a number of the wafer processing areas in the distribution task under the constraint condition, and a solution result is obtained.

[0043] In operation S240, in a case where it is determined that the solving result satisfies the preset condition, a wafer distribution scheme is determined according to the solving result, wherein the preset condition is that a difference between an actual distribution result and an expected distribution result reaches a minimum.

[0044] According to an embodiment of the present disclosure, a wafer is a basic material in semiconductor manufacturing, which is a circular silicon wafer after highly precise processing and is used for manufacturing integrated circuits and various semiconductor devices. In a semiconductor production scene, a wafer storage container is used for protecting, transporting and storing wafers. When processing wafers, the wafer storage container needs to be distributed to the wafer processing area of a machine table so that the machine table can process the wafers according to a certain order and steps.

[0045] According to an embodiment of the present disclosure, the wafer distribution process is abstracted as a mathematical calculation, which can quickly determine the optimal wafer distribution scheme. After obtaining the distribution task, the distribution relationship between the wafer storage container and the wafer processing area is determined, and a plurality of constraint conditions used in mathematical calculation are determined according to the distribution relationship. There can be a unique distribution relationship between the wafer storage container and the wafer processing area, or a one-to-many distribution relationship, for example: the wafers in the wafer storage container A can only be distributed to one of the wafer processing area A and the wafer processing area B.

[0046] According to an embodiment of the present disclosure, after determining the constraint condition, the decision variable used in the mathematical calculation is defined. The decision variable is the distribution state of the wafers in the wafer storage container, and the distribution state is used to represent whether all the wafers in the wafer storage container are distributed to one wafer processing area. In the process of defining the decision variable, different identifiers can be defined for the decision variable according to different distribution states, so as to facilitate mathematical calculation.

[0047] According to an embodiment of the present disclosure, based on the definition result of the decision variable, a target function is constructed to represent the difference between the actual distribution result and the expected distribution result. The expected distribution result is to distribute the wafers in the plurality of wafer storage containers to the wafer processing areas evenly, for example: there are two wafer storage containers, A container and B container, the number of wafers in A container is 4, the number of wafers in B container is 8, and there are three wafer processing areas, then the expected distribution result is to distribute three wafers in each wafer processing area.

[0048] According to an embodiment of the present disclosure, under the constraint condition, the objective function is solved based on the storage information of the wafer storage container in the allocation task and the number of wafer processing areas, and the solving process can be calculated by using a heuristic algorithm. One of the multiple solving results with the smallest difference from the expected allocation result is selected to generate a corresponding wafer allocation scheme according to the result.

[0049] According to an embodiment of the present disclosure, the constraint condition is established according to the allocation relationship between the wafer storage container and the wafer processing area, and the allocation state of the wafer in the wafer storage container is defined, and the objective function for representing the difference between the actual allocation result and the expected allocation result is constructed. In the process of allocating the wafer, a better wafer allocation scheme can be quickly obtained under the condition of meeting multiple constraint conditions, which effectively improves the wafer allocation efficiency and reduces the time consumed.

[0050] According to an embodiment of the present disclosure, the allocation state of the wafer in the wafer storage container is defined, including: in the case where all wafers in the wafer storage container are allocated to the same wafer processing area, the allocation state of the wafer in the wafer storage container is defined as a value representing a positive direction in a binary decision variable; in the case where all wafers in the wafer storage container are not allocated to the same wafer processing area, the allocation state of the wafer in the wafer storage container is defined as a value representing a negative direction in a binary decision variable.

[0051] According to an embodiment of the present disclosure, the allocation state of the wafer in the wafer storage container is defined as a binary decision variable x ij , i represents the i th wafer storage area, and j represents the j th wafer processing area. If all wafers in the i th wafer storage area are allocated to the j th wafer processing area, x ij =1. Otherwise, if all wafers in the i th wafer storage area are not allocated to the j th wafer processing area, x ij =0. The specific expression is as follows:

[0052]

[0053] According to an embodiment of the present disclosure, since the wafers in one storage wafer storage container are one batch, multiple wafers cannot be allocated to different wafer processing areas. Through the definition of the allocation state, the allocation mode of the wafer is further limited, and the scheme without uniform allocation of all wafers is rejected.

[0054] According to an embodiment of the present disclosure, a target function for characterizing the gap between the actual allocation result and the expected allocation result is constructed according to the definition result, including: constructing a factor for calculating the actual allocation result according to the definition result and a variable for characterizing the number of wafers in the wafer storage container; constructing a factor for calculating the expected allocation result according to the number of wafers in each wafer storage container and the number of wafer processing areas; and subtracting the factor corresponding to the actual allocation result from the factor corresponding to the expected allocation result to construct the target function.

[0055] According to an embodiment of the present disclosure, a factor for calculating the actual allocation result of the wafer processing area is constructed according to the definition result of the decision variable and a variable for characterizing the number of wafers in the wafer storage container. The specific factor is as follows:

[0056]

[0057] total j represents the number of wafers allocated to the jth wafer processing area, W i represents the number of wafers in the wafer storage container.

[0058] According to an embodiment of the present disclosure, a factor for calculating the expected allocation result is constructed according to the number of wafers in each wafer storage container and the number of wafer processing areas. The specific factor is as follows:

[0059]

[0060] total represents the number of wafers in each wafer processing area after the wafers in the plurality of wafer storage containers are evenly allocated to the plurality of wafer processing areas, and Z represents the number of wafer processing areas.

[0061] According to an embodiment of the present disclosure, the factor corresponding to the actual allocation result is subtracted from the factor corresponding to the expected allocation result to construct the target function. The target function is used to solve the minimum difference between the actual allocation result and the expected allocation result. The specific factor is as follows:

[0062]

[0063] total z represents the number of wafers in the Zth wafer processing area, Z≥j, and the value range of Z changes with the change of the machine model.

[0064] According to an embodiment of the present disclosure, by constructing a target function for characterizing the gap between the actual allocation result and the expected allocation result, balanced allocation can be achieved when allocating wafers. Balanced allocation can prolong the service life of the machine and reduce the overuse of a single machine.

[0065] According to an embodiment of the present disclosure, the constraint conditions include an allocation constraint condition and a capacity constraint condition. The constraint condition for allocating wafers in the wafer storage container to the wafer processing area is determined according to the allocation relationship between the wafer storage container and the wafer processing area in the allocation task, including: determining, from the plurality of wafer processing areas, a target processing area corresponding to each wafer storage container that can perform wafer allocation; generating an allocation constraint condition according to the allocation relationship between the target processing area and the wafer storage container; and generating a capacity constraint condition based on the maximum capacity of each wafer processing area for wafers.

[0066] According to an embodiment of the present disclosure, since the plurality of wafers in each wafer storage container is of the same batch, and each batch can only be allocated to one wafer processing area. Therefore, it is necessary to limit the constraint condition in the allocation process. Specifically, a target processing area corresponding to each wafer storage container that can perform wafer allocation is determined from the plurality of wafer processing areas. The target processing area can be one or more. In the process of wafer allocation, the wafers of one batch can only be allocated to one of the plurality of target processing areas, thereby establishing the corresponding allocation constraint condition.

[0067] According to an embodiment of the present disclosure, each wafer processing area has a maximum capacity for wafers, so the number of wafers allocated to the wafer processing area needs to be less than or equal to the maximum capacity. The maximum capacity of the machine is usually 25 wafers. By setting the constraint condition, the generated wafer allocation scheme is feasible in the process of allocating wafers, and can meet the feasible configuration of the allocation process, so that the allocation result is more in line with the user's demand.

[0068] According to an embodiment of the present disclosure, under the constraint condition, the objective function is solved based on the storage information of the wafer storage container and the number of regions of the wafer processing area in the allocation task, to obtain a solution result, including: generating a constraint expression corresponding to the binary decision variable according to the constraint condition; and inputting the number of wafers stored in each wafer storage container in the storage information and the number of regions into the objective function to solve the objective function under the limitation of the constraint expression, and output the solution result.

[0069] According to an embodiment of the present disclosure, the constraint expression corresponding to the binary decision variable is generated according to the constraint condition, wherein the constraint expression of the allocation constraint condition is as follows:

[0070]

[0071] possible_Zone iindicates the target processing area corresponding to the wafer storage area which can perform wafer distribution. When all the wafers in the wafer storage area are distributed to the corresponding target processing area, the decision variable is a positive value 1.

[0072] According to an embodiment of the present disclosure, the constraint expression containing the constraint condition is as follows:

[0073]

[0074] wherein M j indicates the maximum capacity of the wafer processing area to the wafer.

[0075] Figure 3 A schematic diagram of wafer distribution in a wafer distribution method according to an embodiment of the present disclosure is schematically shown.

[0076] According to an embodiment of the present disclosure, the number of wafers stored in each wafer storage container in the storage information and the number of regions are input into the objective function, so as to solve the objective function under the limitation of the constraint expression, and output the solution result.

[0077] As Figure 3 shown, there are 9 wafer storage containers 310 and 5 wafer processing areas 320. The numbers in each wafer storage container represent the number of wafers stored therein. It can be seen that the number of wafers in each wafer processing area in the expected distribution result can be calculated as (5+24+5+13+9+18+16+2+11) / 5≈20.

[0078] When the wafers are distributed to the wafer processing area for production, the wafers in the wafer storage container need to be combined and placed in a new wafer storage container and then loaded into the wafer processing area of the machine for production. In the distribution process, the objective function and the constraint condition are used to solve an actual distribution result which has the smallest difference from the expected distribution result. That is, the number of wafers in each wafer distribution area is as close to 20 as possible.

[0079] According to an embodiment of the present disclosure, by using the objective function to solve the wafer distribution scheme, the wafer distribution scheme can be quickly optimized under the condition of meeting multiple constraint conditions in the wafer distribution process, thereby effectively improving the wafer distribution efficiency and improving the utilization rate of the machine.

[0080] According to an embodiment of the present disclosure, the wafer distribution method further comprises: comparing a plurality of solution results output by the objective function to determine a minimum value from the plurality of solution results, wherein the minimum value is a solution result meeting a preset condition.

[0081] According to embodiments of this disclosure, in the process of determining a solution that satisfies preset conditions, a heuristic algorithm can be used to analyze and compare multiple solution results to determine the minimum value among them. Since the objective function is a nonlinear function, gradient descent can also be used to compare and analyze multiple solution results. By determining the minimum value as the solution that satisfies the preset conditions, the wafer allocation scheme that is closest to the desired allocation result is obtained.

[0082] Figure 4 The diagram illustrates a wafer allocation scheme determination in a wafer allocation method according to an embodiment of the present disclosure.

[0083] According to embodiments of this disclosure, determining a wafer allocation scheme based on the solution results includes: determining the values ​​of multiple binary decision variables corresponding to the solution results; determining a set of variables corresponding to each wafer processing region from the values ​​of the multiple binary decision variables, wherein multiple values ​​in the variable set correspond to multiple wafer storage containers respectively; for each wafer processing region, extracting positive values ​​from the variable set to determine multiple wafer storage containers to allocate the wafer to the wafer processing region, thereby obtaining an allocation sub-scheme corresponding to the wafer processing region; and combining the allocation sub-schemes of multiple wafer processing regions to obtain a wafer allocation scheme corresponding to the allocation task.

[0084] According to embodiments of this disclosure, since the allocation of wafers in each wafer storage container is defined using binary decision variables, the allocation state of each wafer storage container can be directly determined based on the values ​​of multiple binary decision variables corresponding to the solution results. Specifically, a set of variables corresponding to each wafer processing area is determined from the values ​​of multiple binary decision variables. The set of variables can be in the form of a matrix, and multiple values ​​in the set of variables correspond to multiple wafer storage containers respectively.

[0085] According to embodiments of this disclosure, for each wafer processing region, positive values ​​are extracted from a set of variables to determine multiple wafer storage containers to allocate wafers to the wafer processing region, thus obtaining an allocation sub-scheme corresponding to the wafer processing region.

[0086] like Figure 4 As shown, the set of variables corresponding to wafer processing area A in machine 410 is: Then it can be determined that the wafers of wafer storage container a and wafer storage container b will be allocated to wafer processing area A.

[0087] According to embodiments of this disclosure, multiple allocation schemes for wafer processing regions are combined to obtain a wafer allocation scheme corresponding to the allocation task. By analyzing the set of variables to determine the wafer allocation scheme, the process of determining the wafer allocation scheme becomes more intuitive and efficient.

[0088] Figure 5 A block diagram of a wafer distribution device is shown.

[0089] As shown in Figure 5 The wafer distribution device 500 includes a constraint determining module 510, a function constructing module 520, a function solving module 530, and a scheme determining module 540.

[0090] The constraint determining module 510 is configured to determine a constraint condition for distributing wafers in wafer storage containers to wafer processing regions according to a distribution relationship between the wafer storage containers and the wafer processing regions in a distribution task.

[0091] The function constructing module 520 is configured to define a distribution state of the wafers in the wafer storage containers, and construct a target function for representing a gap between an actual distribution result and an expected distribution result according to a definition result, where the expected distribution result is an average distribution of the wafers in the wafer storage containers to the wafer processing regions.

[0092] The function solving module 530 is configured to solve the target function based on storage information of the wafer storage containers and a number of the wafer processing regions in the distribution task under the constraint condition, and obtain a solving result.

[0093] The scheme determining module 540 is configured to determine a wafer distribution scheme according to the solving result in a case where the solving result satisfies a preset condition, where the preset condition is that the gap between the actual distribution result and the expected distribution result is minimized.

[0094] According to an embodiment of the present disclosure, the function constructing module 520 includes a first definition sub-module and a second definition sub-module.

[0095] The first definition sub-module is configured to define the distribution state of the wafers in the wafer storage containers as a value representing a positive direction in a binary decision variable in a case where all the wafers in the wafer storage containers are distributed to a same wafer processing region.

[0096] The second definition sub-module is configured to define the distribution state of the wafers in the wafer storage containers as a value representing a negative direction in a binary decision variable in a case where all the wafers in the wafer storage containers are not distributed to the same wafer processing region.

[0097] According to an embodiment of the present disclosure, the function constructing module 520 further includes an actual constructing sub-module, an expected constructing sub-module, and a function constructing sub-module.

[0098] The actual constructing sub-module is configured to construct a factor for calculating the actual distribution result according to the definition result and a variable representing a number of the wafers in the wafer storage containers.

[0099] The expectation constructing submodule is configured to construct a factor for calculating an expected allocation result according to the number of wafers in each wafer storage container and the number of wafer processing areas.

[0100] The function constructing submodule is configured to subtract the factor corresponding to the actual allocation result from the factor corresponding to the expected allocation result to construct a target function.

[0101] According to an embodiment of the present disclosure, the constraint determining module 510 includes an area determining submodule, an allocation determining submodule, and a capacity determining submodule.

[0102] The area determining submodule is configured to determine, from the plurality of wafer processing areas, a target processing area corresponding to each wafer storage container and capable of wafer allocation.

[0103] The allocation determining submodule is configured to generate an allocation constraint condition according to an allocation relationship between the target processing area and the wafer storage container.

[0104] The capacity determining submodule is configured to generate a capacity constraint condition based on a maximum capacity of each wafer processing area for wafers.

[0105] According to an embodiment of the present disclosure, the function solving module 530 includes a constraint generating submodule and a function solving submodule.

[0106] The constraint generating submodule is configured to generate a constraint expression corresponding to a binary decision variable according to the constraint condition.

[0107] The function solving submodule is configured to input the number of wafers stored in each wafer storage container in the storage information and the number of areas into the target function to solve the target function under the constraint expression, and output a solution result.

[0108] According to an embodiment of the present disclosure, the wafer allocation device 500 further includes a result comparing module.

[0109] The result comparing module is configured to compare a plurality of solution results output by the target function to determine a minimum value from the plurality of solution results, wherein the minimum value is a solution result satisfying a preset condition.

[0110] According to an embodiment of the present disclosure, the scheme determining module 540 includes a variable value determining submodule, a set determining submodule, a sub-scheme determining submodule, and a scheme combining submodule.

[0111] The variable value determining submodule is configured to determine values of a plurality of binary decision variables corresponding to the solution result.

[0112] The set determining submodule is configured to determine, from the values of the plurality of binary decision variables, a variable set corresponding to each wafer processing area, wherein the plurality of values in the variable set correspond to the plurality of wafer storage containers respectively.

[0113] The sub-scheme determining submodule is configured to, for each wafer processing area, extract a value representing a positive direction in the variable set to determine the plurality of wafer storage containers to which the wafer is allocated in the wafer processing area, to obtain an allocation sub-scheme corresponding to the wafer processing area.

[0114] The scheme combining submodule is configured to combine the allocation sub-schemes of the plurality of wafer processing areas to obtain a wafer allocation scheme corresponding to the allocation task.

[0115] Any one or more of the modules, sub-modules, units, sub-units according to the embodiments of the present disclosure, or at least part of the functions of any one or more of the modules, sub-modules, units, sub-units, can be implemented in one module. Any one or more of the modules, sub-modules, units, sub-units according to the embodiments of the present disclosure can be split into a plurality of modules for implementation. Any one or more of the modules, sub-modules, units, sub-units according to the embodiments of the present disclosure can be implemented at least in part as a hardware circuit, for example, a field programmable gate array (FPGA), a programmable logic array (PLA), a system on chip, a system on substrate, a system on package, an application specific integrated circuit (ASIC), or any other reasonable manner of hardware or firmware through integration or packaging of a circuit, or in any one of software, hardware and firmware or in an appropriate combination of any of the foregoing. Alternatively, one or more of the modules, sub-modules, units, sub-units according to the embodiments of the present disclosure can be implemented at least in part as computer program modules, which, when executed, can perform corresponding functions.

[0116] For example, any plurality of the constraint determination module 510, function construction module 520, function solving module 530, and scheme determination module 540 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functionality of one or more of these modules / units / subunits can be combined with at least part of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of the present disclosure, at least one of the constraint determination module 510, function construction module 520, function solving module 530, and scheme determination module 540 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the constraint determination module 510, function construction module 520, function solving module 530, and scheme determination module 540 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0117] It should be noted that the wafer allocation device part in the embodiments of this disclosure corresponds to the wafer allocation method part in the embodiments of this disclosure. The description of the wafer allocation device part is specifically referred to in the wafer allocation method part, and will not be repeated here.

[0118] Figure 6 A block diagram of an electronic device suitable for implementing a wafer assignment method according to an embodiment of the present disclosure is shown schematically. Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0119] like Figure 6 As shown, an electronic device 600 according to an embodiment of this disclosure includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage portion 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this disclosure.

[0120] In the RAM 603, various programs and data required for the operation of the electronic device 600 are stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other via the bus 604. The processor 601 performs various operations of the method flow according to the embodiments of the present disclosure by executing the programs in the ROM 602 and / or the RAM 603. It is to be noted that the programs can also be stored in one or more memories other than the ROM 602 and the RAM 603. The processor 601 can also perform various operations of the method flow according to the embodiments of the present disclosure by executing the programs stored in the one or more memories.

[0121] According to an embodiment of the present disclosure, the electronic device 600 can further include an input / output (I / O) interface 605, which is also connected to the bus 604. The electronic device 600 can further include one or more of the following components connected to the input / output (I / O) interface 605: an input part 606 including a keyboard, a mouse, and the like; an output part 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), and the like, and a speaker, and the like; a storage part 608 including a hard disk, and the like; and a communication part 609 including a network interface card such as a LAN card, a modem, and the like. The communication part 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the input / output (I / O) interface 605 as necessary. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is mounted on the drive 610 as necessary, so that a computer program read therefrom is installed in the storage part 608 as necessary.

[0122] According to an embodiment of the present disclosure, the method flow according to the embodiments of the present disclosure can be implemented as a computer software program. For example, the embodiments of the present disclosure include a computer program product including a computer program carried on a computer-readable storage medium, the computer program containing program codes for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network by the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the above-described functions defined in the system of the embodiments of the present disclosure are performed. According to an embodiment of the present disclosure, the system, the device, the apparatus, the module, the unit, and the like described above can be implemented by computer program modules.

[0123] The present disclosure also provides a computer readable storage medium, which can be included in the device / apparatus / system described in the above embodiments, or exist independently without being assembled into the device / apparatus / system. The above computer readable storage medium carries one or more programs, which when executed, implement the method according to the embodiments of the present disclosure.

[0124] According to the embodiments of the present disclosure, the computer readable storage medium can be a non-volatile computer readable storage medium. For example, it can include, but is not limited to: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, the computer readable storage medium can be any tangible medium that contains or stores a program, which can be used by or in connection with an instruction execution system, apparatus, or device.

[0125] For example, according to the embodiments of the present disclosure, the computer readable storage medium can include one or more memories of the ROM 602 and / or the RAM 603 described above and / or other than the ROM 602 and the RAM 603.

[0126] The embodiments of the present disclosure also include a computer program product, which includes a computer program containing program codes for executing the method provided by the embodiments of the present disclosure, and when the computer program product is run on an electronic device, the program codes are used to make the electronic device implement the wafer distribution method provided by the embodiments of the present disclosure.

[0127] When the computer program is executed by the processor 601, the above functions defined in the system / apparatus of the embodiments of the present disclosure are performed. According to the embodiments of the present disclosure, the system, apparatus, module, unit, etc. described above can be implemented by computer program modules.

[0128] In one embodiment, the computer program can rely on tangible storage media such as optical storage media, magnetic storage media, etc. In another embodiment, the computer program can also be transmitted, distributed, downloaded and installed in the form of signals on a network medium, and be downloaded and installed through the communication part 609 and / or installed from the detachable medium 611. The program codes contained in the computer program can be transmitted by any appropriate network medium, including but not limited to wireless, wired, etc., or any suitable combination of the foregoing.

[0129] According to embodiments of the present disclosure, program code of the computer program for performing the methods provided by the embodiments of the present disclosure can be written in any combination of one or more programming languages, including a high-level procedural and / or object-oriented programming language, and / or an assembly / machine language. Programming languages include, but are not limited to, Java, C++, python, "C" language, or the like. The program code can execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on a remote computing device, or entirely on the remote computing device or server. In the latter scenario, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computing device, such as through the Internet using an Internet Service Provider.

[0130] The computer program product of the present disclosure can be a computer program product, which is a machine-readable medium (media) having exact sequences of instructions, program, code segments, routines, subroutines, programs, functions, objects, processing options / script modules, or any combination of the above, which, when executed by a processor in a computing device, cause the processor to carry out the steps of the methods described herein. The machine-readable medium can be a transitory or non-transitory computer-readable medium. The machine-readable medium can be a tangible computer-readable medium. The machine-readable medium can be a non-transitory computer-readable medium. The machine-readable medium can be a computer-readable storage medium. The machine-readable medium can be a non-transitory computer-readable storage medium. The machine-readable medium can be a computer-readable non-transitory storage medium. The machine-readable medium can be a computer-readable tangible storage medium. The machine-readable medium can be a computer-readable non-transitory tangible storage medium. The machine-readable medium can be a computer-readable non-transitory storage medium that is not a signal. The machine-readable medium can be a computer-readable non-transitory storage medium that is tangible.

[0131] The above-described embodiments of the present disclosure are merely descriptive and are not intended to limit or restrict the scope of the present disclosure. Although the above-described embodiments are described separately, this does not mean that the measures in each embodiment cannot be used advantageously in combination. Without departing from the scope of the present disclosure, those skilled in the art can make various substitutions and modifications, and these substitutions and modifications should fall within the scope of the present disclosure.

Claims

1. A wafer assignment method, comprising: Based on the allocation relationship between the wafer storage container and the wafer processing area in the allocation task, determine the constraints for allocating the wafer in the wafer storage container to the wafer processing area; The allocation state of the wafers in the wafer storage container is defined, and an objective function is constructed based on the definition result to characterize the difference between the actual allocation result and the expected allocation result, wherein the expected allocation result is to evenly allocate the wafers in the multiple wafer storage containers to the multiple wafer processing areas. Under the constraints, the objective function is solved based on the storage information of the wafer storage container and the number of wafer processing areas in the allocation task, and the solution result is obtained. If the solution result satisfies a preset condition, a wafer allocation scheme is determined based on the solution result, wherein the preset condition is that the difference between the actual allocation result and the expected allocation result is minimized; The definition of the allocation state of wafers in the wafer storage container includes: If it is determined that all wafers in the wafer storage container are allocated to the same wafer processing area, the allocation state of the wafers in the wafer storage container is defined as a positive value in the binary decision variable; If it is determined that none of the wafers in the wafer storage container are assigned to the same wafer processing area, the allocation status of the wafers in the wafer storage container is defined as a negative value in the binary decision variable; The method further includes: Based on the defined results and the variable used to characterize the number of wafers in the wafer storage container, a factor is constructed to calculate the actual allocation result, as follows: Where i represents the i-th wafer storage region, j represents the j-th wafer processing region, and x ij This represents the allocation state of the j-th wafer in the i-th wafer storage container, total. j W represents the number of wafers allocated to the j-th wafer processing region. i This indicates the number of wafers in the wafer storage container.

2. The method according to claim 1, wherein, The construction of the objective function based on the defined result to characterize the difference between the actual allocation result and the expected allocation result includes: Based on the number of wafers in each of the wafer storage containers and the number of regions in the plurality of wafer processing areas, a factor is constructed to calculate the desired allocation result; The objective function is constructed by subtracting the factor corresponding to the actual allocation result from the factor corresponding to the expected allocation result.

3. The method according to claim 1, wherein, The constraints include allocation constraints and capacity constraints. The step of determining the constraints for allocating wafers from the wafer storage container to the wafer processing area based on the allocation relationship between the wafer storage container and the wafer processing area in the allocation task includes: From the plurality of said wafer processing areas, determine the target processing area for wafer allocation corresponding to each said wafer storage container; The allocation constraints are generated based on the allocation relationship between the target processing area and the wafer storage container; The capacity constraint is generated based on the maximum capacity of each wafer processing region for the wafer.

4. The method according to claim 1, wherein, Under the constraints, based on the storage information of the wafer storage container and the number of wafer processing areas in the allocation task, the objective function is solved to obtain the solution result, including: Generate constraint expressions corresponding to the binary decision variables based on the constraints; The number of wafers stored in each wafer storage container and the number of regions in the storage information are input into the objective function to solve the objective function under the constraints of the expression, and the solution result is output.

5. The method according to claim 1, further comprising: The multiple solution results output by the objective function are compared to determine the minimum value from the multiple solution results, wherein the minimum value is the solution result that satisfies the preset condition.

6. The method according to claim 1, wherein, The step of determining the wafer allocation scheme based on the solution results includes: Determine the values ​​of multiple binary decision variables corresponding to the solution result; A set of variables corresponding to each wafer processing region is determined from the values ​​of the plurality of binary decision variables, wherein the plurality of values ​​in the set of variables correspond to the plurality of wafer storage containers respectively; For each wafer processing region, positive values ​​are extracted from the variable set to determine multiple wafer storage containers to allocate wafers to the wafer processing region, thus obtaining an allocation sub-scheme corresponding to the wafer processing region; The multiple allocation schemes for the wafer processing areas are combined to obtain a wafer allocation scheme corresponding to the allocation task.

7. A wafer distribution apparatus, comprising: The constraint determination module is used to determine the constraint conditions for allocating the wafer in the wafer storage container to the wafer processing area based on the allocation relationship between the wafer storage container and the wafer processing area in the allocation task. A function construction module is used to define the allocation state of wafers in the wafer storage container, and to construct an objective function to characterize the difference between the actual allocation result and the expected allocation result based on the definition result, wherein the expected allocation result is to evenly allocate the wafers in the multiple wafer storage containers to the multiple wafer processing areas. The function solving module is used to solve the objective function under the constraints, based on the storage information of the wafer storage container and the number of wafer processing areas in the allocation task, and obtain the solution result. The scheme determination module is used to determine a wafer allocation scheme based on the solution results when the solution results meet preset conditions, wherein the preset conditions are that the difference between the actual allocation result and the expected allocation result is minimized; The first definition submodule is used to define the allocation state of the wafers in the wafer storage container as a positive value in the binary decision variable when it is determined that all wafers in the wafer storage container are allocated to the same wafer processing area. The second definition submodule is used to define the allocation state of the wafers in the wafer storage container as a negative value in the binary decision variable when it is determined that all wafers in the wafer storage container have not been allocated to the same wafer processing area. The actual construction submodule is used to construct factors for the actual allocation result based on the defined result and the variable representing the number of wafers in the wafer storage container. The specific factors are as follows: Where i represents the i-th wafer storage region, j represents the j-th wafer processing region, and x ij This represents the allocation state of the j-th wafer in the i-th wafer storage container, total. j W represents the number of wafers allocated to the j-th wafer processing region. i This indicates the number of wafers in the wafer storage container.

8. An electronic device, comprising: One or more processors; Memory, used to store one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the method of any one of claims 1 to 6.

9. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 6.

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