Scheduling method and device of thin film deposition equipment, equipment and storage medium

Abstract

The invention relates to the technical field of semiconductors, in particular to a scheduling method and device for thin film deposition equipment, the equipment and a storage medium, and the method comprises the steps: obtaining the cleaning time information of each process module based on equipment information and assumed virtual conditions; obtaining the idling time of each process module based on the processing information and each piece of cleaning time information; constructing an ROPN model based on the equipment information and the processing information, and optimizing the ROPN model based on the idle time of each process module; guiding the scheduling of thin film deposition equipment based on the optimized ROPN model; according to the method disclosed by the invention, the ROPN model is optimized by calculating the idling time of each process module, so that peak shifting arrangement of the cleaning time of each process module is realized, the phenomenon of unbalanced load of a manipulator at a vacuum end is effectively avoided, and the production efficiency of thin film deposition equipment is remarkably improved; and on the basis of a periodic scheduling strategy of the ROPN model, the continuous peak shifting of the cleaning time of each process module can be ensured.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor technology, and in particular, to a scheduling method, device, equipment and storage medium for a thin film deposition device. Background Art

[0002] Semiconductor manufacturing is the core foundation of consumer electronics and high-end technology. Among them, wafer manufacturing is the most automated and complex process, covering key processes such as thin film deposition, photoresist coating, exposure, and etching. Among them, the thin film deposition process deposits thin films such as silicon dioxide on the wafer surface through physical vapor deposition, chemical vapor deposition, atomic layer deposition and other technologies, which is one of the core steps of wafer manufacturing. The production capacity utilization rate of the thin film deposition equipment directly restricts the output of semiconductor chips. Therefore, its efficient scheduling has become a key issue in the industry.

[0003] The thin film deposition equipment mainly consists of an atmospheric end, a vacuum lock and a vacuum end. After processing the wafer, the process module located at the vacuum end will leave residues of particles or chemical substances. Therefore, after processing n wafers, the process module needs to be cleaned and maintained once to ensure the wafer quality.

[0004] Currently, the scheduling of thin film deposition equipment mainly uses mathematical programming methods to construct a mixed integer programming model to generate action sequences, but there are the following significant problems: 1. The scale of the model increases exponentially with the increase of discrete variables. In actual production, it is difficult to solve the scheduling scheme within an effective time, delaying the production process; 2. To shorten the solution time, it is often necessary to reduce the number of wafers, relax the constraints or add assumptions. This approach is likely to result in a non-optimal solution or even an infeasible solution; 3. The centralized cleaning strategy causes the manipulator at the vacuum end to bear an excessive load during the non-cleaning stage of the process module, while being idle during the cleaning stage, thus causing the problem of uneven equipment load, and further leading to a reduction in the equipment production capacity utilization rate.

[0005] It can be seen that the existing technology still needs to be improved. Summary of the Invention

[0006] In order to overcome the deficiencies of the existing technology, the purpose of the present invention is to provide a scheduling method for a thin film deposition device, which optimizes the ROPN model based on the idle time, realizes continuous peak shifting arrangement of the cleaning time of the process module, improves the stability and reliability of the equipment operation, and avoids the phenomenon of uneven manipulator load.

[0007] The first aspect of the present invention provides a scheduling method for a thin film deposition device, including: obtaining device information, and based on the device information and preset assumed virtual conditions, obtaining the cleaning time information of each process module through theoretical derivation; obtaining processing information, and based on the processing information and the cleaning time information of each process module, obtaining the idle time of each process module through theoretical derivation; constructing a ROPN model based on the device information and the processing information, and optimizing the ROPN model based on the idle time of each process module to obtain an optimized ROPN model; guiding the scheduling of the thin film deposition device based on the optimized ROPN model.

[0008] Optionally, in the first implementation manner of the first aspect of the present invention, the obtaining device information, and based on the device information and preset assumed virtual conditions, obtaining the cleaning time information of each process module through theoretical derivation includes: obtaining device information, where the device information includes the cleaning cycle of the process module; obtaining preset assumed virtual conditions, where the preset assumed virtual conditions are that all process modules enter the processing cycle synchronously; based on the cleaning cycle of the process module and the preset assumed virtual conditions, simulating the processing and cleaning processes of each process module through theoretical derivation to obtain the cleaning time information of each process module, where the cleaning time information includes the start time, end time, and cleaning duration of the first cleaning.

[0009] Optionally, in the second implementation manner of the first aspect of the present invention, the based on the cleaning cycle of the process module and the preset assumed virtual conditions, simulating the processing and cleaning processes of each process module through theoretical derivation to obtain the cleaning time information of each process module includes: constructing a simulation mathematical model based on the cleaning cycle of the process module and the preset assumed virtual conditions; running the constructed simulation mathematical model to obtain the cleaning time information of each process module.

[0010] Optionally, in the third implementation manner of the first aspect of the present invention, the obtaining processing information, and based on the processing information and the cleaning time information of each process module, obtaining the idle time of each process module through theoretical derivation includes: obtaining processing information, where the processing information includes the processing cycle of the process module; selecting a process module as a reference module, and obtaining the idle time of the reference module based on the start time and cleaning duration of the first cleaning of the reference module; based on the interval principle determined by the processing cycle, and through reverse calculation based on the interval principle, obtaining the idle time of other process modules.

[0011] Optionally, in the fourth implementation manner of the first aspect of the present invention, the method of selecting a process module as a reference module and obtaining the idle time of the reference module based on the first cleaning start time and cleaning duration of the reference module includes: selecting a process module as a reference module, and obtaining the first cleaning start time and cleaning duration corresponding to the reference module; calculating the actual start time corresponding to the reference module based on the first cleaning start time and cleaning duration; and deriving the idle time of the reference module based on the actual start time, in combination with the processing cycle and cleaning duration, using algebraic operations.

[0012] Optionally, in the fifth implementation manner of the first aspect of the present invention, the method of determining the interval principle based on the processing cycle and obtaining the idle time of other process modules based on the interval principle through theoretical derivation includes: setting that there is at least an interval of one processing cycle between the first cleaning end time of each process module and the first cleaning end time of the adjacent process module as the interval principle; and obtaining the idle time of other process modules based on the interval principle through the law of the sequence.

[0013] Optionally, in the sixth implementation manner of the first aspect of the present invention, the method of constructing an ROPN model based on device information and processing information and optimizing the ROPN model based on the idle time of each process module to obtain an optimized ROPN model includes: constructing an ROPN model based on device information and processing information, where the device information further includes the device composition and the load condition of the vacuum end robot, and the processing information further includes the process path and the number of wafer flows; and using the idle time of each process module as the initial state of the ROPN model to optimize the ROPN model to obtain an optimized ROPN model.

[0014] The second aspect of the present invention provides a scheduling device for a thin film deposition device, including: a first derivation module, configured to obtain device information and obtain the cleaning time information of each process module through theoretical derivation based on the device information and preset assumed virtual conditions; a second derivation module, configured to obtain processing information and obtain the idle time of each process module through theoretical derivation based on the processing information and the cleaning time information of each process module; an optimization module, configured to construct an ROPN model based on the device information and processing information and optimize the ROPN model based on the idle time of each process module to obtain an optimized ROPN model; and a guidance module, configured to guide the scheduling of the thin film deposition device based on the optimized ROPN model.

[0015] The third aspect of the present invention provides a scheduling device for a thin film deposition device, where the scheduling device for the thin film deposition device includes: a memory and at least one processor, and instructions are stored in the memory; at least one of the processors invokes the instructions in the memory so that the scheduling device for the thin film deposition device executes each step of the scheduling method for the thin film deposition device described in any one of the above.

[0016] The fourth aspect of the present invention provides a computer-readable storage medium, on which instructions are stored, and when the instructions are executed by a processor, each step of the scheduling method of the thin film deposition equipment described in any one of the above is implemented.

[0017] In the technical solution of the present invention, by calculating the idle time of each process module to optimize the ROPN model, the peak-shifting arrangement of the cleaning time of the process module is realized, effectively avoiding the unbalanced phenomenon of the load of the vacuum end manipulator, which not only helps to ensure the quality of the wafer product, but also significantly improves the production efficiency of the thin film deposition equipment; based on the periodic scheduling strategy of the ROPN model, the continuous peak-shifting of the cleaning time of each process module is ensured, thereby improving the stability and reliability of the operation of the thin film deposition equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic structural diagram of the thin film deposition equipment provided by the embodiment of the present invention; Figure 2 It is a logical flow chart of the scheduling method of the thin film deposition equipment provided by the embodiment of the present invention; Figure 3 It is a schematic structural diagram of the scheduling device of the thin film deposition equipment provided by the embodiment of the present invention; Figure 4 It is a schematic structural diagram of the scheduling equipment of the thin film deposition equipment provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] The present invention provides a scheduling method, device, equipment and storage medium for a thin film deposition equipment. In the present invention, the terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments described herein can be implemented in an order different from that shown or described herein. In addition, the terms "comprising" or "having" and any variation thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or equipment that includes a series of steps or units does not have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or equipment.

[0020] For ease of understanding, the thin film deposition equipment applicable to the embodiments of the present invention is described below. Please refer to Figure 1, The thin film deposition equipment mainly consists of three regions: the atmospheric end region, the vacuum lock region, and the vacuum end region. In the atmospheric end region, the LoadPort (wafer loader / unloader) serves as the interaction interface between the thin film deposition equipment and the outside, and is used to place wafers to be processed or already processed. The capacity of each LoadPort can be 25; the CoolingBuffer is a wafer cooling module, and the processed wafers need to be cooled here before being placed into the LoadPort; the ATR (atmospheric end robot) is responsible for transporting wafers between the LoadPort, the CoolingBuffer, and the LoadLock; the Aligner is a wafer calibration module, and the wafers taken out from the LoadPort need to be calibrated here first before entering the vacuum lock region; the vacuum lock region (LoadLock) serves as a connection between the atmospheric end and the vacuum end, and transports the unprocessed wafers at the atmospheric end to the vacuum end through the pump (vacuum pumping) operation, and transports the processed wafers at the vacuum end to the atmospheric end through the vent (filling with air) operation; the vacuum end region includes the PM (process module), and the process module is used for the thin film deposition processing of wafers. After processing a certain number of wafers, the process module needs to perform a cleaning (wac) operation; the VTR (vacuum end robot) transports wafers between various PMs and between the PM and the LoadLock.

[0021] The processing flow of the semiconductor combination equipment disclosed in this embodiment is as follows: The atmospheric end robot is responsible for transporting the wafers to be processed from the storage unit to the calibration table for calibration, and then transporting them to the vacuum lock; after receiving the wafers in the atmosphere, the vacuum lock performs a vacuum pumping operation. After the vacuum pumping is completed, the vacuum end robot takes out the unprocessed wafers from the vacuum lock and places them into the process module for processing; if the wafer path recipe specifies that the processing chamber needs to be cleaned before processing, the cleaning wafer must be cleaned first, and then the wafer can enter the processing chamber of the process module; after the wafer is processed according to the recipe path, the vacuum end robot takes it out of the processing chamber and puts it back into the vacuum lock; after the vacuum lock receives the wafer, it performs a venting operation; finally, the atmospheric end robot places the processed wafers into the cooling table for cooling and finally into the wafer loader / unloader. If there are unprocessed wafers for this task in the wafer loader / unloader, the wafers need to be placed into the storage unit for caching first, and then transported to the wafer loading / unloading when there are no unprocessed wafers in the wafer loader / unloader.

[0022] Furthermore, for ease of understanding, the specific process of the embodiment of the present invention will be described below. Please refer to Figure 2 , An embodiment of the scheduling method for the thin film deposition equipment in the embodiment of the present invention includes: 101. Obtain equipment information, and based on the equipment information and preset assumed virtual conditions, obtain the cleaning time information of each process module through theoretical derivation; In this embodiment, by introducing a preset hypothetical virtual condition, the computational complexity of the cleaning time information can be simplified, facilitating the rapid establishment of the theoretical benchmark for the cleaning time of each process module and providing basic data support for subsequent peak-shifting scheduling.

[0023] 102. Obtain processing information, and based on the processing information and the cleaning time information of each process module, obtain the idle time of each process module through theoretical derivation; 103. Construct an ROPN model based on the equipment information and the processing information, and optimize the ROPN model based on the idle time of each process module to obtain an optimized ROPN model; 104. Guide the scheduling of the thin film deposition equipment based on the optimized ROPN model; In this embodiment, a scheduling sequence is generated based on the optimized ROPN model to guide the scheduling process of the thin film deposition equipment; the ROPN model is a graphical mathematical model composed of places (representing system states), transitions (representing system changes or events), and Tokens (tokens that flow between places and transitions); the ROPN model has the advantages of small scale and strong versatility and is suitable for industrial field modeling; using the ROPN model to generate a scheduling sequence for guiding the thin film deposition equipment requires only extremely low computing resources, can complete the scheduling plan within 1 second, and effectively reduces equipment energy consumption.

[0024] The scheduling method of the thin film deposition equipment disclosed in this application optimizes the ROPN model by calculating the idle time of each process module, realizes the peak-shifting arrangement of the cleaning time of the process module, effectively avoids the uneven load of the vacuum end manipulator, not only helps to ensure the quality of the wafer product, but also significantly improves the production efficiency of the thin film deposition equipment; based on the periodic scheduling strategy of the ROPN model, it ensures the continuous peak-shifting of the cleaning time of each process module, thereby improving the stability and reliability of the operation of the thin film deposition equipment.

[0025] In this embodiment, the obtaining of the equipment information, and based on the equipment information and the preset hypothetical virtual condition, obtaining the cleaning time information of each process module through theoretical derivation includes: 201. Obtain equipment information, where the equipment information includes the cleaning cycle of the process module; In this embodiment, the cleaning cycle is the threshold of the number of wafer processes that the process module needs to clean, such as cleaning the process module once every n processed wafers; the cleaning cycle can be preset by the designer according to the actual processing situation and equipment parameters to ensure that the cleaning operation matches the actual processing load and avoid waste of equipment utilization rate caused by premature cleaning or the risk of wafer contamination caused by too late cleaning.

[0026] 202. Obtain the preset hypothetical virtual condition, and the preset hypothetical virtual condition is to assume that all process modules enter the processing cycle synchronously; In this embodiment, by assuming that all process modules enter the processing cycle synchronously, the complex scenario of asynchronous startup of multiple modules can be simplified into a synchronous model with a unified starting point, eliminating the interference of the initial time difference, facilitating subsequent unified derivation of cleaning time information through mathematical methods, reducing the problem complexity, and improving the calculation efficiency.

[0027] 203. Based on the cleaning cycle of the process module and the preset assumed virtual conditions, simulate the processing and cleaning processes of each process module through theoretical derivation to obtain the cleaning time information of each process module. The cleaning time information includes the start time, end time, and cleaning duration of the first cleaning. In this implementation, by simulating the actual processing and cleaning process through theoretical derivation, the precise time points of the first cleaning of each process module can be systematically calculated, providing a quantifiable initial benchmark for subsequent staggered scheduling, ensuring that the cleaning operation is executed as planned, and avoiding equipment conflicts or quality hazards caused by time chaos.

[0028] In this embodiment, based on the cleaning cycle of the process module and the preset assumed virtual conditions, simulating the processing and cleaning processes of each process module through theoretical derivation to obtain the cleaning time information of each process module includes: 301. Construct a simulation mathematical model based on the cleaning cycle of the process module and the preset assumed virtual conditions. In this embodiment, the mathematical model abstracts physical problems into computable expressions, that is, converts the cleaning cycle of the process module and the preset assumed virtual conditions into mathematical formulas, ensuring the rigor and reproducibility of theoretical derivation.

[0029] 302. Run the constructed simulation mathematical model to obtain the cleaning time information of each process module. In this embodiment, by running the constructed simulation mathematical model to automatically calculate the cleaning time information of each process module, not only can human errors be avoided, but also accurate cleaning time information can be quickly generated.

[0030] In this embodiment, the obtaining of processing information, and based on the processing information and the cleaning time information of each process module, obtaining the idle time of each process module through theoretical derivation includes: 401. Obtain processing information, where the processing information includes the processing cycle of the process module. In this embodiment, the processing cycle is the processing time of a single wafer, which is a key indicator for measuring the equipment production capacity and also the basis for calculating the idle time. Combining the processing cycle and the cleaning time information can accurately evaluate the idle duration of the module outside of processing and cleaning, providing data support for load balancing.

[0031] 402. Select a process module as the reference module, and obtain the idle time of the reference module based on the first cleaning start time and cleaning duration of the reference module; In this embodiment, the reference module is selected as the time reference point. The reference module is the first module to start processing in the actual scheduling process. The idle time is deduced through its cleaning time to establish a unified reference for the multi-module time coordination; it avoids time chaos caused by multi-start point calculations and ensures the comparability of the time parameters of each process module.

[0032] 403. Based on the processing cycle, confirm the interval principle, and based on the interval principle, obtain the idle times of other process modules through reverse calculation; In this embodiment, the reverse calculation starts from the target state, that is, the peak-shifted cleaning, to deduce the initial idle time, ensuring that the cleaning times of all process modules are distributed at a preset interval; compared with the forward calculation, the reverse deduction is more efficient and targeted, can quickly meet the load balancing requirements, and reduce calculation redundancy.

[0033] In this embodiment, the step of selecting a process module as the reference module and obtaining the idle time of the reference module based on the first cleaning start time and cleaning duration of the reference module includes: 501. Select a process module as the reference module, and obtain the first cleaning start time and cleaning duration corresponding to the reference module; 502. Calculate the actual start time corresponding to the reference module based on the first cleaning start time and cleaning duration; In this embodiment, it is set that the time difference between the actual start time and the first cleaning start time is the cleaning duration. The actual start time reflects the starting point of the actual input of the process module for processing; by stripping the cleaning time, the time distribution in the processing stage can be analyzed separately, providing a clear boundary for the calculation of the idle time.

[0034] 503. Based on the actual start time, combined with the processing cycle and cleaning duration, deduce the idle time of the reference module through algebraic operations; In this embodiment, the idle duration from the start of the module to the actual processing is quantified through an algebraic formula; algebraic operations have certainty and verifiability, ensuring that the calculation result of the idle time is unique and accurate, providing a reliable input for subsequent model optimization.

[0035] In this embodiment, the step of based on the processing cycle, confirm the interval principle, and based on the interval principle, obtain the idle times of other process modules through theoretical deduction includes: 601. Set that there is at least an interval of one processing cycle between the first cleaning end time of each process module and the first cleaning end time of the adjacent process module as the interval principle; In this embodiment, the interval principle avoids multiple process modules finishing cleaning simultaneously at the physical level, preventing the vacuum end robot from concentrating on restart tasks of multiple process modules in a short period of time, thereby balancing the load of the vacuum end robot and avoiding equipment jams or failures caused by instantaneous overload of the vacuum end robot.

[0036] 602. Based on the interval principle, obtain the idle time of other process modules through sequence rules; In this embodiment, by using an arithmetic sequence or an equal-interval sequence model, the idle time of each process module can be quickly deduced; the sequence rules simplify the complex time coordination process, making the multi-module peak-shifting scheduling have mathematical regularity, which is convenient for program implementation and dynamic adjustment.

[0037] To further illustrate the reverse calculation process of the idle time of each process module, take a thin film deposition device with a cleaning cycle n = 3, a processing cycle of T, and a cleaning duration of WacTime as an example; in the virtual stage, that is, during the execution of step 203, assume that all process modules start synchronously from the 0 moment and no idle time is inserted. At this time, the first cleaning end time of PM3 and PM2 is both 3T + WacTime, and that of PM1 is 6T + WacTime, resulting in the problem of the robot being idle due to concentrated cleaning; to solve this problem, set the actual start time as the virtual start time + WacTime. Taking PM3 as the benchmark, its idle time is 0 and it can be directly started, that is, directly enter the processing cycle; determine the idle time of other process modules through reverse deduction: PM2 needs to wait for T time to start after the actual start time, so that its first processing start time is T later than that of PM3, and the first cleaning end time is 4T + 2WacTime, with an interval of T from PM3; PM1 needs to wait for 2T time to start, and the first cleaning end time is 8T + 2WacTime; although the initial cleaning intervals are T and 4T, based on the periodicity of the ROPN model scheduling, after the system enters the steady state, the cleaning time intervals of each PM will be fixed at T, avoiding concentrated cleaning, balancing the load of the vacuum end robot, and improving equipment efficiency.

[0038] In this embodiment, constructing an ROPN model based on device information and processing information, and optimizing the ROPN model based on the idle time of each process module to obtain an optimized ROPN model, includes: 701. Construct an ROPN model based on device information and processing information, where the device information further includes the device composition and the load condition of the vacuum end robot, and the processing information further includes the process path and the number of wafer flows; In this embodiment, parameters such as device composition, robot load condition, and process path are incorporated into the construction of the ROPN model, so that the constructed ROPN model truly reflects the physical constraints and production logic of the thin film deposition device, and avoids the infeasibility of the scheduling scheme caused by ignoring the constraints.

[0039] In this embodiment, taking the wafer flow as m1 = (3), the cleaning cycle n = 3, and the robot pick - and - place as the swap strategy as an example, a Petri net (ROPN) model based on resource optimization is constructed to manage its cleaning cycle. In the constructed ROPN model, taking three parallel production modules (PM1, PM2, PM3) as an example, the place P3 is represented by three Tokens indicating the availability of the three PMs, and each Token represents one PM being idle. The transition t1 represents the wafer being taken out from the LoadLock, and the place P1 represents the VTR moving a wafer from the vacuum lock to the PM. The transition t2 represents putting the wafer into the PM for processing, which consumes one Token in P3, meaning one PM is occupied. The transition t3 represents taking out a wafer from the PM, and the Token in P3 is not restored temporarily because each PM module needs to perform a cleaning operation after processing three wafers. The transition t4 represents the VTR placing the wafer in the vacuum lock, and the place P4 represents the VTR moving a wafer from the PM to the vacuum lock. The place P5 represents the resource availability of the VTR, and the place P6 represents the PM performing the cleaning operation. When a PM has processed three wafers, the transition t6 is triggered, indicating that a cleaning operation is required, and at this time, this process module is unavailable, and the Token in the place P3 is not restored. In this way, the ROPN model ensures that each PM will be cleaned after processing three wafers, thus maintaining production efficiency and product quality.

[0040] 702. Take the idle time of each process module as the initial state of the ROPN model to optimize the ROPN model and obtain an optimized ROPN model. In this embodiment, by adjusting the initial state of the ROPN model, specifically, adjusting the Token distribution corresponding to the space - time of the PM, the optimization of the ROPN model is realized. Taking the theoretically deduced idle time as the initial state of the ROPN model can directly guide the ROPN model to generate a scheduling scheme that meets the peak - shifting requirements, reducing the time cost of the model searching for feasible solutions. At the same time, the rationality of the initial state ensures that the optimized ROPN model outputs a periodic stable solution, realizing continuous peak - shifting of the cleaning time.

[0041] The scheduling method of the thin - film deposition equipment in the embodiment of the present invention has been described above. Next, the scheduling device of the thin - film deposition equipment in the embodiment of the present invention will be described. Please refer to Figure 3 One embodiment of the scheduling device of the thin - film deposition equipment in the embodiment of the present invention includes: A first derivation module 801, configured to obtain device information, and based on the device information and preset assumed virtual conditions, obtain the cleaning time information of each process module by means of theoretical derivation. The second derivation module 802 is configured to obtain processing information, and based on the processing information and the cleaning time information of each process module, obtain the idle time of each process module through theoretical derivation; The optimization module 803 is configured to construct a ROPN model based on the device information and the processing information, and optimize the ROPN model based on the idle time of each process module to obtain an optimized ROPN model; The guidance module 804 is configured to guide the scheduling of the thin film deposition equipment based on the optimized ROPN model.

[0042] Based on the same idea as the method in the above embodiment, the device provided in this application can implement the method in the above embodiment.

[0043] Above Figure 3 The scheduling device of the thin film deposition equipment in the embodiment of the present invention is described in detail from the perspective of modular functional entities. Below, the scheduling device of the thin film deposition equipment in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0044] Figure 4 FIG. is a schematic structural diagram of a scheduling device of a thin film deposition equipment provided by an embodiment of the present invention. The scheduling device 900 of the thin film deposition equipment may vary greatly due to configuration or performance, and may include one or more processors (central processing units, CPU) 910 (for example, one or more processors) and a memory 920, and one or more storage media 930 (for example, one or more mass storage devices) for storing application programs 933 or data 932. Among them, the memory 920 and the storage media 930 may be transient storage or persistent storage. The program stored in the storage media 930 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the scheduling device 900 of the thin film deposition equipment. Further, the processor 910 may be configured to communicate with the storage media 930 and execute a series of instruction operations in the storage media 930 on the scheduling device 900 of the thin film deposition equipment to implement the steps of the scheduling method of the thin film deposition equipment provided in the above method embodiments.

[0045] The scheduling device 900 of the thin film deposition equipment may further include one or more power supplies 940, one or more wired or wireless network interfaces 950, one or more input / output interfaces 960, and / or one or more operating systems 931, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art can understand, Figure 4The scheduling device structure of the illustrated thin film deposition device does not limit the scheduling device of the thin film deposition device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0046] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are run on a computer, the computer is caused to execute the steps of the scheduling method of the thin film deposition device.

[0047] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described system or device and unit can refer to the corresponding processes in the foregoing method embodiments and will not be described herein again.

[0048] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0049] Finally, it should be noted that the above are only preferred examples of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A scheduling method for a thin film deposition device, characterized in that Including: Obtain device information, and based on the device information and preset assumed virtual conditions, obtain the cleaning time information of each process module through theoretical derivation; Obtain processing information, and based on the processing information and the cleaning time information of each process module, obtain the idle time of each process module through theoretical derivation; Construct an ROPN model based on the device information and the processing information, and optimize the ROPN model based on the idle time of each process module to obtain an optimized ROPN model; Guide the scheduling of the thin film deposition equipment based on the optimized ROPN model.

2. The scheduling method of the thin film deposition equipment according to claim 1, characterized in that, The obtaining of the device information, and based on the device information and preset assumed virtual conditions, obtaining the cleaning time information of each process module through theoretical derivation, includes: Obtain device information, where the device information includes the cleaning cycle of the process module; Obtain the preset assumed virtual conditions, where the preset assumed virtual conditions are that all process modules are assumed to enter the processing cycle synchronously; Based on the cleaning cycle of the process module and the preset assumed virtual conditions, simulate the processing and cleaning processes of each process module through theoretical derivation to obtain the cleaning time information of each process module, where the cleaning time information includes the start time, end time, and cleaning duration of the first cleaning.

3. The scheduling method of the thin film deposition equipment according to claim 2, characterized in that, The based on the cleaning cycle of the process module and the preset assumed virtual conditions, simulating the processing and cleaning processes of each process module through theoretical derivation to obtain the cleaning time information of each process module, includes: Construct a simulation mathematical model based on the cleaning cycle of the process module and the preset assumed virtual conditions; Run the constructed simulation mathematical model to obtain the cleaning time information of each process module.

4. The scheduling method of the thin film deposition equipment according to claim 2, characterized in that, The obtaining of the processing information, and based on the processing information and the cleaning time information of each process module, obtaining the idle time of each process module through theoretical derivation, includes: Obtain processing information, where the processing information includes the processing cycle of the process module; Select a process module as the reference module, and obtain the idle time of the reference module based on the start time and cleaning duration of the first cleaning of the reference module; Based on the processing cycle, confirm the interval principle, and based on the interval principle, obtain the idle time of other process modules through reverse calculation.

5. The scheduling method of the thin film deposition equipment according to claim 4, characterized in that The selecting a process module as the reference module, and obtaining the idle time of the reference module based on the start time and cleaning duration of the first cleaning of the reference module, includes: Select a process module as the reference module, and obtain the start time and cleaning duration of the first cleaning corresponding to the reference module; Calculate the actual start time corresponding to the reference module based on the start time and cleaning duration of the first cleaning; Based on the actual start time, combined with the processing cycle and the cleaning duration, use algebraic operations to derive the idle time of the reference module.

6. The scheduling method of the thin film deposition equipment according to claim 4, characterized in that, The based on the processing cycle, confirm the interval principle, and based on the interval principle, obtaining the idle time of other process modules through theoretical derivation, includes: Set that there is at least an interval of one processing cycle between the end time of the first cleaning of each process module and the end time of the first cleaning of the adjacent process module, as the interval principle; Based on the interval principle, obtain the idle time of other process modules through the law of the sequence.

7. The scheduling method of the thin film deposition equipment according to claim 1, characterized in that, Construct an ROPN model based on device information and processing information, and optimize the ROPN model based on the idle time of each process module to obtain an optimized ROPN model, including: Construct an ROPN model based on device information and processing information, where the device information further includes the device composition and the load condition of the vacuum end manipulator, and the processing information further includes the process path and the number of wafer flows; Use the idle time of each process module as the initial state of the ROPN model to optimize the ROPN model and obtain an optimized ROPN model.

8. A scheduling device for a thin film deposition apparatus, characterized in that, Including: A first derivation module for obtaining device information and, based on the device information and preset assumed virtual conditions, obtaining the cleaning time information of each process module through theoretical derivation; A second derivation module for obtaining processing information and, based on the processing information and the cleaning time information of each process module, obtaining the idle time of each process module through theoretical derivation; An optimization module for constructing an ROPN model based on device information and processing information and optimizing the ROPN model based on the idle time of each process module to obtain an optimized ROPN model; A guidance module for guiding the scheduling of the thin film deposition equipment based on the optimized ROPN model.

9. A scheduling device for a thin film deposition apparatus, characterized in that, The scheduling device of the thin film deposition equipment includes: a memory and at least one processor, and instructions are stored in the memory; At least one of the processors calls the instructions in the memory so that the scheduling device of the thin film deposition equipment executes each step of the scheduling method of the thin film deposition equipment according to any one of claims 1-7.

10. A computer-readable storage medium, on which instructions are stored, characterized in that, When the instructions are executed by the processor, each step of the scheduling method of the thin film deposition equipment according to any one of claims 1-7 is implemented.

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