Mass production process method, device and equipment of photoetching machine and medium

Abstract

The invention discloses a mass production process method, device and equipment of a photoetching machine and a medium, which refine a process abstract instruction in a mass production standard of the photoetching machine into specific character representations and instruction levels, and clarify a dependency relationship and a topological relationship between the character representations and the instruction levels. And defining an operation sequence and an output result of the mass production instruction set according to the dependency relationship and / or the topological relationship. The production efficiency, the stability and the reliability of the photoetching machine can be remarkably improved, the development and maintenance cost is reduced, and efficient, controllable and intelligent management of the mass production process of the photoetching machine is realized.

Description

Technical Field

[0001] The present invention belongs to the field of semiconductor manufacturing equipment, and in particular relates to a mass production process method, device, equipment and medium of a photolithography machine. Background Art

[0002] In the existing mass production process of lithography machines, instruction sets based on the SEMI 40 standard are usually used for control and operation. However, these instruction sets have many shortcomings in practical applications, such as difficult to understand abstract expressions, difficult software implementation, poor readability of engineering codes, poor robustness, and difficulty in testing. Therefore, a new method for mass production of lithography machines is urgently needed to overcome the defects of existing technologies. Summary of the invention

[0003] Based on this, it is necessary to provide a mass production process method, device, computer equipment, computer-readable storage medium and computer program product for lithography machines in response to the above-mentioned technical problems.

[0004] In a first aspect, the present application provides a mass production process method of a lithography machine, the method comprising: The process abstract instructions in the mass production standard of the lithography machine are refined into specific character representations and instruction levels, and the dependencies and topological relationships between the character representations and instruction levels are clarified, and the operation sequence and output results of the mass production instruction set are defined based on the dependencies and / or topological relationships.

[0005] In one of the embodiments, a function P is defined by a mathematical model to describe the selection and dependency relationship between the character representation and the instruction level.

[0006] In one of the embodiments, the input-output function F(X)=Y is set according to the mathematical model and applied in the mass production process for actual testing and verification.

[0007] In one embodiment, the instruction levels include: the highest level is the abandon mass production instruction, the high level is the stop mass production instruction, the middle level is the suspend mass production instruction and the resume mass production instruction, and the general level is the start mass production instruction, wherein the high level instruction can interrupt the current lower level instruction at any time.

[0008] In one embodiment, the character representation includes: the mass production start instruction is represented by A, the pause instruction is represented by B, the resume instruction is represented by C, the stop instruction is represented by D, and the abandon instruction is represented by E.

[0009] In one of the embodiments, the dependency and topological relationship between the instructions are specifically as follows: the mass production startup process can be directly interrupted by a pause instruction, a stop instruction or an abandon instruction; the pause process can be interrupted by a resume instruction, a stop instruction or an abandon instruction; the stop process can be interrupted by an abandon instruction.

[0010] In one embodiment, the function P is P({X1, X2, ..., Xn}|{Y1, Y2, ..., Yn}), which is used to describe the subsequently executable character instruction set {Y1, Y2, ..., Yn} given the executed character instruction set {X1, X2, ..., Xn}, where X represents the executed character instruction and Y represents the subsequently executable character instruction.

[0011] In one embodiment, in the input-output function F(X)=Y, a set of input X values ​​corresponds to a set of output Y values.

[0012] In a second aspect, the present application further provides a mass production process device for a lithography machine, the device comprising: an abstract instruction optimization module, an instruction set topology relationship establishment module, a mass production instruction set operation sequence determination module, a mathematical model definition module and a model application module, wherein: The abstract instruction optimization module is used to further refine the abstract instruction set of the mass production standard of the lithography machine into specific character representations, and to clarify the instruction level and process function; The instruction set topology relationship establishment module is used to establish the instruction set topology relationship and clarify the dependency relationship between the instructions represented by each character; The mass production instruction set operation sequence determination module is used to determine the mass production instruction set operation sequence and to define in detail the operation sequence and output results under various instruction combinations; The mathematical model definition module is used to define a mathematical model by defining a function P for describing the selection and dependency relationship between instructions, and the output represents all possible subsequent instruction combinations under a given executed instruction set; The model application module is used to apply the constructed mathematical model to the mass production process of the lithography machine to perform actual testing and verification.

[0013] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method in any one of the above embodiments when executing the computer program.

[0014] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method in any one of the above embodiments are implemented.

[0015] In a fifth aspect, the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the method in any one of the above embodiments.

[0016] The mass production process method, control method, device, computer equipment, storage medium and computer program product of the above-mentioned lithography machine have designed a set of intuitive and easy-to-understand instruction sets, defined detailed instruction set operation sequences and logic, and introduced mathematical models to simplify control logic and improve code readability. In practical applications, this method can significantly improve the production efficiency, stability and reliability of lithography machines, reduce development and maintenance costs, and realize efficient, controllable and intelligent management of the mass production process of lithography machines. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0018] Figure 1 is a flow chart of a mass production process method in one embodiment; Figure 2 A schematic diagram of a topological relationship structure of a mass production process method in an embodiment; Figure 3 A schematic diagram of a model comparison of a mass production process method in an embodiment; Figure 4 is an application schematic diagram of a mass production process method in an embodiment; Figure 5 is an application schematic diagram of a mass production process method in yet another embodiment; Figure 6 It is a structural block diagram of a mass production process device of a photolithography machine in one embodiment; Figure 7 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] The mass production process method of the lithography machine provided in the embodiment of the present application is as follows: Figure 1 As shown, the process includes the following steps 101 to 105. Among them: Step 101: Optimize the abstract instruction set, further refine the abstract instruction set of the SEMI 40 standard into specific character representations, and clarify the instruction level and process function. For example, the character representing the instruction sequence of start is represented by A, the corresponding instruction level is 0 (low), and the corresponding lithography machine mass production process is to start mass production. The details are shown in the table:

[0021] Among them, the instruction level increases from 0 to 3, and 3 is the highest instruction level.

[0022] Step 102: Establish the instruction set topology relationship and clarify the dependency relationship between the instructions. For example, if the low-level instructions work as a prerequisite, they can be used across levels. The specific topology relationship is as follows: Figure 2 shown.

[0023] In this embodiment, the start instruction in the topology diagram is the starting point of the mass production process; the pause instruction can interrupt the currently ongoing mass production process, but will not directly end or abandon the entire mass production batch; the resume instruction depends on the pause instruction, that is, the resume instruction can only be executed after the pause instruction is executed; the stop instruction can interrupt the currently ongoing mass production process and prepare to end the entire mass production batch; the abandon instruction is the highest level instruction and can interrupt any low-level instruction, including start, pause, resume and stop.

[0024] Furthermore, the execution and dependency relationships between the following instructions are: Mass production-stop: It means that the stop instruction can be executed at any time during the mass production process.

[0025] Mass production-abandon: Indicates that during the mass production process, the abandon instruction can be directly executed to interrupt and abandon the entire mass production batch.

[0026] Pause-Abandon: means that after pausing the mass production process, you can directly execute the abandon command.

[0027] Stop-Abandon: It means that after stopping the mass production process, the abandonment instruction can be continued (although in actual practice, the abandonment action is often close to or completed after stopping, but this relationship still holds logically).

[0028] Step 103: Determine the mass production instruction set operation sequence, and define in detail the operation sequence and output results under various instruction combinations so that developers and testers can accurately understand and execute them. The details are shown in the table (part):

[0029]

[0030] Step 104: Define a mathematical model, by defining a function P to describe the selection and dependency between instructions, and the output represents all possible subsequent instruction combinations under a given executed instruction set. This function can be used to deduce possible results under different instruction combinations, thereby improving the readability and robustness of the code.

[0031] Specifically, the function P({X1,X2,...,Xn}|{Y1,Y2,...,Yn}) is used to describe the subsequent executable instruction set {Y1,Y2,...,Yn} given the executed instruction set {X1,X2,...,Xn}, where X represents the selected element (i.e. the executed instruction) and Y represents the element that can be selected later (i.e. the subsequent executable instruction). For example, P({A}|{B,C,D,E}) represents all possible subsequent instruction combinations when the start instruction A has been executed. The function is as follows, P({A}|{B,C,D,E})={{A,B},{A,C},{A,D},{A,E},{A,B,C},{A,B,D},{A,B,E},{A,C,B},{A ,C,D},{A,C,E},{A,D,E},{A,B,C,D},{A,B,C,E},{A,B,D,E},{A,B,C,D,E},{A,C,B,D,E}} P({A,B}|{C,D,E}) represents all possible combinations of subsequent instructions when the start instruction A+B has been executed. The function is as follows, P({A,B}|{C,D,E})={{A,B,C},{A,B,D},{A,B,E},{A,B,C,D},{A,B,C,E},{A,B,D,E},{A,B,C,D,E},{A,C,B,D,E}} P({A,B,C}|{D,E}) represents all possible combinations of subsequent instructions when the start instruction A+B+C has been executed. The function is as follows, P({A,B,C}|{D,E})={{A,B,C},{A,B,C,D},{A,B,C,E},{A,B,C,D,E}} Through the function P, the possibilities and relationships between different instruction combinations can be derived. It should be noted that those skilled in the art can understand that the above embodiments are only part of the possible functions.

[0032] Furthermore, in order to more intuitively represent the relationship of the function P, a matrix relationship representation method is introduced.

[0033] That is, P({X1,X2,…Xn}|{Y1,Y2,…Yn})=

[0034] Among them, P(1,1) is a rectangular representation, the subscript (1,1) represents the value of x1, y1, the (2,2) in P(2,2) represents the value of x2, y2, and so on; Since the main diagonal is 1 and the rank is 1, in order to effectively distinguish, the matrix relationship is further evolved into a specific formula form, as follows: P({A}|{B,C,D,E})=

[0035] Among them, since the "resume instruction" depends on the "pause instruction", the above formula is simplified to P({A}|{B,C,D,E})=

[0036] Similarly, P({A,B}|{C,D,E})=; P({A,B,C}|{D,E})=; P({A,B,C,D}|{E})= Through this function, the dependencies and executable paths between instructions can be clearly expressed, providing a solid theoretical foundation for the mass production process.

[0037] Among them, E represents a single operation, E2, E3, E4 represent the 2nd, 3rd, 3rd operations, etc.

[0038] Step 105: Apply the mathematical model and apply the above mathematical model to the mass production process of the lithography machine for actual testing and verification. According to the mathematical model constructed in step 104, the input-output function F(X)=Y is set so that a set of input X values ​​corresponds to a set of output Y values, such as F(A)= , F(A,B)= , F(A,B,C)= , F(A,B,C,D)= , etc. Figure 3 As shown, compared with the traditional method, the method proposed in this application not only simplifies the instruction processing logic in the mass production process, but also significantly improves the readability and robustness of the code. Figure 4-5 As shown, white represents input; gray represents output; Figure 4 For example, let F(A)={B,C,D,E} be a function. Figure 5 is an example of the function F(A,B,C,D)={E}. By applying these formulas, the lithography machine can perform mass production tasks more efficiently while reducing the error rate.

[0039] In an exemplary embodiment, as shown in the figure, a mass production process device of a lithography machine is provided, including: an abstract instruction optimization module 601, an instruction set topology relationship establishment module 602, a mass production instruction set operation sequence determination module 603, a mathematical model definition module 604 and a model application module 605, wherein: Abstract instruction optimization module 601, used to further refine the abstract instruction set of SEMI 40 standard into specific character representation, and clarify the instruction level and process function; The instruction set topology relationship establishment module 602 is used to establish the instruction set topology relationship and clarify the dependency relationship between the instructions; The mass production instruction set operation sequence determination module 603 determines the mass production instruction set operation sequence and defines the operation sequence and output results under various instruction combinations in detail so that developers and testers can accurately understand and execute them; Mathematical model definition module 604, used to define a mathematical model, by defining a function P, used to describe the selection and dependency relationship between instructions, the output represents all possible subsequent instruction combinations under a given executed instruction set; The model application module 605 is used to apply the constructed mathematical model to the mass production process of the lithography machine to perform actual testing and verification.

[0040] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for calculating the life of a surgical instrument and a method for controlling a surgical instrument are realized. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0041] Those skilled in the art will understand that Figure 7The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0042] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0043] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0044] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0045] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0046] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0047] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It is to be understood that the present invention is described by some embodiments, and it is known to those skilled in the art that various changes or equivalent substitutions may be made to these features and embodiments without departing from the spirit and scope of the present invention. In addition, under the teachings of the present invention, these features and embodiments may be modified to adapt to specific circumstances and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of the present application are within the scope protected by the present invention.

Claims

1. A mass production process method of a photolithography machine, characterized in that: The process abstract instructions in the mass production standard of the lithography machine are refined into specific character representations and instruction levels, and the dependencies and topological relationships between the character representations and instruction levels are clarified, and the operation sequence and output results of the mass production instruction set are defined based on the dependencies and / or topological relationships.

2. The mass production process method of the lithography machine according to claim 1, characterized in that: A function P is defined by a mathematical model to describe the selection and dependency relationship between the character representation and the instruction level.

3. The mass production process method of the lithography machine according to claim 2, characterized in that: The input-output function F(X)=Y is set according to the mathematical model and applied in mass production for actual testing and verification.

4. The mass production process method of the lithography machine according to claim 1, characterized in that: The instruction levels include: the highest level is the abandonment of mass production instruction, the high level is the stop mass production instruction, the middle level is the pause mass production instruction and the resume mass production instruction, and the general level is the start mass production instruction, wherein the high level instruction can interrupt the current lower level instruction at any time.

5. The mass production process method of a photolithography machine according to claim 1 or 4, characterized in that: The character representation includes: A for the mass production start instruction, B for the pause instruction, C for the resume instruction, D for the stop instruction, and E for the abandon instruction.

6. The mass production process method of a photolithography machine according to claim 1, characterized in that: The dependency and topological relationship between the instructions are specifically as follows: the mass production startup process can be directly interrupted by a pause instruction, a stop instruction or an abandon instruction; the pause process can be interrupted by a resume instruction, a stop instruction or an abandon instruction; the stop process can be interrupted by an abandon instruction.

7. According to the mass production process method of the lithography machine according to claim 2 or 3, the function P is P({X1, X2, ..., Xn}|{Y1, Y2, ..., Yn}), which is used to describe the subsequently executable character instruction set {Y1, Y2, ..., Yn} given the executed character instruction set {X1, X2, ..., Xn}, wherein X represents the executed character instruction and Y represents the subsequently executable character instruction. 8 . The mass production process method of a lithography machine according to claim 3 , wherein in the input-output function F(X)=Y, a set of input X values ​​corresponds to a set of output Y values.

9. A mass production process device for a photolithography machine, characterized in that: The device comprises: an abstract instruction optimization module, an instruction set topology relationship establishment module, a mass production instruction set operation sequence determination module, a mathematical model definition module and a model application module, wherein: The abstract instruction optimization module is used to further refine the abstract instruction set of the mass production standard of the lithography machine into specific character representations, and to clarify the instruction level and process function; The instruction set topology relationship establishment module is used to establish the instruction set topology relationship and clarify the dependency relationship between the instructions represented by each character; The mass production instruction set operation sequence determination module is used to determine the mass production instruction set operation sequence and to define in detail the operation sequence and output results under various instruction combinations; The mathematical model definition module is used to define a mathematical model by defining a function P for describing the selection and dependency relationship between instructions, and the output represents all possible subsequent instruction combinations under a given executed instruction set; The model application module is used to apply the constructed mathematical model to the mass production process of the lithography machine to perform actual testing and verification.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

12. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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