Substrate processing apparatus and substrate processing method

Abstract

Provided is, for example, a substrate processing apparatus that makes it possible to optimize the operations of processing units with high accuracy. The substrate processing apparatus comprises: a plurality of unit controllers that each optimize the operation of the corresponding processing unit; a main controller that, in accordance with an instruction from the substrate processing apparatus, provides each of the unit controllers with an instruction for the operation of the corresponding processing unit; and a storage unit. The main controller acquires a set of optimization results from each of the unit controllers, and derives an evaluation value and a set of time-series control parameters that corresponds to that unit controller, on the basis of the optimization results. The main controller stores a data set that includes the derived evaluation value and set of time-series control parameters in association with the instruction or a timing in the instruction. The main controller performs the above process with respect to instructions or timings in an instruction, and store a plurality of data sets that are associated with each of the instructions or each of the timings.

Description

Substrate Processing Apparatus and Substrate Processing Method

[0001] The present disclosure relates to a substrate processing apparatus and a substrate processing method.

[0002] Patent Document 1 discloses a technique in which an adjustment and control unit that controls the operation of a valve adjusts the value of the position of the valve closure body in order to bring the internal pressure of a vacuum chamber close to a target pressure. Patent Document 2 discloses a technique in which a control system sends a command to a local control system that controls an RF source, and the local control system controls the operation of the RF source according to the command.

[0003] Japanese Unexamined Patent Application Publication No. 2018-189230, Japanese Patent Publication No. 2023-530567

[0004] The present disclosure provides a substrate processing apparatus and the like that can optimize the operations of each processing unit with high precision.

[0005] A substrate processing apparatus according to one embodiment comprises a plurality of unit controllers corresponding to each of a plurality of processing units of the substrate processing apparatus, each unit controller being configured to optimize the operation of the corresponding processing unit, a main controller configured to instruct each of the plurality of unit controllers to operate the corresponding processing unit according to an instruction of the substrate processing apparatus, and a storage unit, wherein the main controller performs the following steps: (a) a step of acquiring a group of a plurality of optimization results corresponding to each of the plurality of unit controllers, each optimization result being obtained by optimization by the corresponding unit controller; (b) a step of deriving an evaluation value and a group of a plurality of time-series control parameters based on the plurality of optimization results acquired from the plurality of unit controllers, the plurality of time-series control parameters corresponding to each of the plurality of unit controllers; and (c) a step of storing a dataset including the derived evaluation value and the group of a plurality of time-series control parameters in the storage unit in association with the instruction or a timing in the instruction. (d) The system is configured to perform the steps (a) to (c) for each of the multiple instructions, or for each of the multiple timings in a single instruction, thereby storing a plurality of datasets associated with each of the multiple instructions or the multiple timings in the storage unit.

[0006] According to this disclosure, it becomes possible to optimize the operation of each processing unit with high precision.

[0007] This is a diagram illustrating an example configuration of a capacitively coupled plasma processing apparatus. This is a diagram illustrating an example of the functional configuration of a plasma processing apparatus. This is a diagram illustrating an example configuration of a higher-level controller and a lower-level controller. This is a flowchart illustrating an example of a processing procedure for identifying a set of optimal values ​​for control parameters for a controlled device. This is an explanatory diagram showing an example of a table generated by the higher-level controller during processing. This is a diagram illustrating an example of a timing chart showing data exchange between the higher-level controller and the lower-level controller. This is a flowchart illustrating an example of a processing procedure for determining whether the operation of the controlled device is appropriate.

[0008] The substrate processing apparatus and substrate processing method of this disclosure will be described in detail with reference to the drawings illustrating embodiments thereof. Hereinafter, an embodiment applied to a plasma processing apparatus will be described as an example of a substrate processing apparatus. However, this disclosure is not limited to the following examples, and is intended to include all modifications within the meaning and scope of the claims, as indicated by the claims.

[0009] The following describes an example of a plasma processing system configuration. Figure 1 is a diagram illustrating an example of a capacitively coupled plasma processing system configuration.

[0010] The plasma processing system includes a capacitively coupled plasma processing apparatus 1 and a control unit 2. The capacitively coupled plasma processing apparatus 1 includes a plasma processing chamber 10, a gas supply unit 20, a power supply 30, and an exhaust system 40. The plasma processing apparatus 1 also includes a substrate support unit 11 and a gas introduction unit. The gas introduction unit is configured to introduce at least one processing gas into the plasma processing chamber 10. The gas introduction unit includes a shower head 13. The substrate support unit 11 is located inside the plasma processing chamber 10. The shower head 13 is located above the substrate support unit 11. In one embodiment, the shower head 13 constitutes at least a portion of the ceiling of the plasma processing chamber 10. The plasma processing chamber 10 has a plasma processing space 10s defined by the shower head 13, the side walls 10a of the plasma processing chamber 10, and the substrate support unit 11. The plasma processing chamber 10 has at least one gas supply port for supplying at least one processing gas to the plasma processing space 10s, and at least one gas outlet for discharging gas from the plasma processing space. The plasma processing chamber 10 is grounded. The shower head 13 and the substrate support part 11 are electrically insulated from the housing of the plasma processing chamber 10.

[0011] The substrate support portion 11 includes a main body portion 111 and a ring assembly 112. The main body portion 111 has a central region 111a for supporting the substrate W and an annular region 111b for supporting the ring assembly 112. A wafer is an example of a substrate W. The annular region 111b of the main body portion 111 surrounds the central region 111a of the main body portion 111 in a plan view. The substrate W is placed on the central region 111a of the main body portion 111, and the ring assembly 112 is placed on the annular region 111b of the main body portion 111 so as to surround the substrate W on the central region 111a of the main body portion 111. Therefore, the central region 111a is also called the substrate support surface for supporting the substrate W, and the annular region 111b is also called the ring support surface for supporting the ring assembly 112.

[0012] In one embodiment, the main body 111 includes a base 1110 and an electrostatic chuck 1111. The base 1110 includes a conductive member. The conductive member of the base 1110 can function as a lower electrode. The electrostatic chuck 1111 is placed on the base 1110. The electrostatic chuck 1111 includes a ceramic member 1111a and an electrostatic electrode 1111b placed within the ceramic member 1111a. The ceramic member 1111a has a central region 111a. In one embodiment, the ceramic member 1111a also has an annular region 111b. Other members surrounding the electrostatic chuck 1111, such as an annular electrostatic chuck or an annular insulating member, may also have an annular region 111b. In this case, the ring assembly 112 may be placed on the annular electrostatic chuck or the annular insulating member, or on both the electrostatic chuck 1111 and the annular insulating member. Furthermore, at least one RF / DC electrode, which is coupled to the RF (Radio Frequency) power supply 31 and / or DC (Direct Current) power supply 32 described later, may be arranged within the ceramic member 1111a. In this case, at least one RF / DC electrode functions as a lower electrode. When a bias RF signal and / or DC signal, described later, is supplied to at least one RF / DC electrode, the RF / DC electrode is also called a bias electrode. Note that the conductive member of the base 1110 and at least one RF / DC electrode may function as multiple lower electrodes. Also, the electrostatic electrode 1111b may function as a lower electrode. Therefore, the substrate support portion 11 includes at least one lower electrode.

[0013] The ring assembly 112 includes one or more annular members. In one embodiment, the one or more annular members include one or more edge rings and at least one covering ring. The edge rings are formed of a conductive or insulating material, and the covering rings are formed of an insulating material.

[0014] The substrate support section 11 may also include a temperature control module configured to adjust at least one of the electrostatic chuck 1111, the ring assembly 112, and the substrate to a target temperature. The temperature control module may include a heater, a heat transfer medium, a flow path 1110a, or a combination thereof. A heat transfer fluid such as brine or gas flows through the flow path 1110a. In one embodiment, the flow path 1110a is formed within the base 1110, and one or more heaters are arranged within the ceramic member 1111a of the electrostatic chuck 1111. The substrate support section 11 may also include a heat transfer gas supply section configured to supply heat transfer gas to the gap between the back surface of the substrate W and the central region 111a.

[0015] The showerhead 13 is configured to introduce at least one processing gas from the gas supply unit 20 into the plasma processing space 10s. The showerhead 13 has at least one gas supply port 13a, at least one gas diffusion chamber 13b, and a plurality of gas inlet ports 13c. The processing gas supplied to the gas supply port 13a passes through the gas diffusion chamber 13b and is introduced into the plasma processing space 10s through the plurality of gas inlet ports 13c. The showerhead 13 also includes at least one upper electrode. In addition to the showerhead 13, the gas introduction unit may also include one or more side gas injectors (SGIs) attached to one or more openings formed in the side wall 10a.

[0016] The gas supply unit 20 may include at least one gas source 21 and at least one flow controller 22. In one embodiment, the gas supply unit 20 is configured to supply at least one processing gas to the shower head 13 from a corresponding gas source 21 via a corresponding flow controller 22. Each flow controller 22 may include, for example, a mass flow controller or a pressure-controlled flow controller. Furthermore, the gas supply unit 20 may include one or more flow modulation devices that modulate or pulse the flow rate of at least one processing gas.

[0017] The power supply 30 includes an RF power supply 31 coupled to the plasma processing chamber 10 via at least one impedance matching circuit. The RF power supply 31 is configured to supply at least one RF signal (RF power) to at least one lower electrode and / or at least one upper electrode. This causes plasma to be formed from at least one processing gas supplied to the plasma processing space 10s. Thus, the RF power supply 31 can function as at least part of a plasma generation unit configured to generate plasma from one or more processing gases in the plasma processing chamber 10. Furthermore, by supplying a bias RF signal to at least one lower electrode, a bias potential is generated on the substrate W, and ionic components in the formed plasma can be drawn into the substrate W.

[0018] In one embodiment, the RF power supply 31 includes a first RF generation unit 31a and a second RF generation unit 31b. The first RF generation unit 31a is coupled to at least one lower electrode and / or at least one upper electrode via at least one impedance matching circuit and is configured to generate a source RF signal (source RF power) for plasma generation. In one embodiment, the source RF signal has a frequency in the range of 10 MHz to 150 MHz. In one embodiment, the first RF generation unit 31a may be configured to generate a plurality of source RF signals having different frequencies. One or more generated source RF signals are supplied to at least one lower electrode and / or at least one upper electrode.

[0019] The second RF generation unit 31b is coupled to at least one lower electrode via at least one impedance matching circuit and is configured to generate a bias RF signal (bias RF power). The frequency of the bias RF signal may be the same as or different from the frequency of the source RF signal. In one embodiment, the bias RF signal has a frequency lower than the frequency of the source RF signal. In one embodiment, the bias RF signal has a frequency in the range of 100 kHz to 60 MHz. In one embodiment, the second RF generation unit 31b may be configured to generate a plurality of bias RF signals having different frequencies. One or more generated bias RF signals are supplied to at least one lower electrode. In various embodiments, at least one of the source RF signal and the bias RF signal may be pulsed.

[0020] The power supply 30 may also include a DC power supply 32 coupled to the plasma processing chamber 10. The DC power supply 32 includes a first DC generation unit 32a and a second DC generation unit 32b. In one embodiment, the first DC generation unit 32a is connected to at least one lower electrode and configured to generate a first DC signal. The generated first bias DC signal is applied to at least one lower electrode. In one embodiment, the second DC generation unit 32b is connected to at least one upper electrode and configured to generate a second DC signal. The generated second DC signal is applied to at least one upper electrode.

[0021] In various embodiments, at least one of the first and second DC signals may be pulsed. In this case, a sequence of voltage pulses is applied to at least one lower electrode and / or at least one upper electrode. The voltage pulses may have a rectangular, trapezoidal, triangular, or combination thereof pulse waveform. In one embodiment, a waveform generation unit for generating a sequence of voltage pulses from a DC signal is connected between the first DC generation unit 32a and at least one lower electrode. Thus, the first DC generation unit 32a and the waveform generation unit constitute a voltage pulse generation unit. When the second DC generation unit 32b and the waveform generation unit constitute a voltage pulse generation unit, the voltage pulse generation unit is connected to at least one upper electrode. The voltage pulses may have positive or negative polarity. Furthermore, the sequence of voltage pulses may include one or more positive voltage pulses and one or more negative voltage pulses within one period. The first and second DC generation units 32a and 32b may be provided in addition to the RF power supply 31, and the first DC generation unit 32a may be provided in place of the second RF generation unit 31b.

[0022] The exhaust system 40 may be connected to, for example, a gas outlet 10e located at the bottom of the plasma processing chamber 10. The exhaust system 40 may include a pressure regulating valve 41 and a vacuum pump 42. The pressure regulating valve 41 regulates the pressure in the plasma processing space 10s. The vacuum pump 42 may include a turbomolecular pump, a dry pump, or a combination thereof.

[0023] The control unit 2 processes computer-executable instructions that cause the plasma processing apparatus 1 to perform various processes described herein. The control unit 2 may be configured to control each element of the plasma processing apparatus 1 to perform the various processes described herein. In one embodiment, part or all of the control unit 2 may be included in the plasma processing apparatus 1. The control unit 2 may include a processing unit 2a1, a storage unit 2a2, and a communication interface 2a3. The control unit 2 is implemented, for example, by a computer 2a. The processing unit 2a1 may be configured to perform various control operations by reading a program from the storage unit 2a2 and executing the read program. This program may be stored in the storage unit 2a2 in advance, or it may be obtained via a medium when needed. The obtained program is stored in the storage unit 2a2 and read from the storage unit 2a2 and executed by the processing unit 2a1. The medium may be various storage media readable by the computer 2a, or it may be a communication line connected to the communication interface 2a3. The processing unit 2a1 may be a CPU (Central Processing Unit). The storage unit 2a2 may include RAM (Random Access Memory), ROM (Read Only Memory), HDD (Hard Disk Drive), SSD (Solid State Drive), or a combination thereof. The communication interface 2a3 may communicate with the plasma processing device 1 via a communication line such as a LAN (Local Area Network).

[0024] Figure 2 is a diagram illustrating an example of the functional configuration of the plasma processing apparatus 1. In the plasma processing system, the control unit 2 is the higher-level controller (main controller), and the plasma processing apparatus 1 is provided with a plurality of lower-level controllers 5 (unit controllers) that control the operation of hardware resources (processing apparatus, processing unit) responsible for each function of the plasma processing apparatus 1 according to the control from the control unit 2. The lower-level controllers 5 may be implemented by a computer, for example, and may include a processing unit, a memory unit, and a communication interface. Each lower-level controller 5 is connected to the control unit 2 so as to be able to communicate, and controls the operation of the processing apparatus to be controlled according to the control parameters provided by the control unit 2.

[0025] The lower-level controller 5 is equipped with a processing unit to be controlled (hereinafter referred to as the controlled device 7), or the controlled device 7 is connected to it via signal lines, etc. The controlled device 7 (processing unit) is, for example, equipment provided in the plasma processing device 1, such as an actuator. The lower-level controller 5 is also equipped with a sensor 6 that measures various information related to the operation of the controlled device 7, or the sensor 6 is connected to it via signal lines, etc. The sensor 6 measures various values ​​such as temperature or pressure related to substrate processing, and the lower-level controller 5 acquires the values ​​measured by the sensor 6 (sensor values). In addition to temperature and pressure sensors, the sensor 6 may also include various other sensors such as sensors that measure humidity, type and concentration of gas, fluid flow rate, voltage, current, charge amount, and light including spectral data. The lower-level controller 5 is a controller that controls the connected controlled device 7 based on the sensor values ​​acquired from the connected sensor 6. In addition, the plasma processing device 1 may include multiple lower-level controllers 5, such as controllers that acquire sensor values ​​from the sensor 6 but do not control the controlled device 7, or controllers that control the controlled device 7 without acquiring sensor values ​​from the sensor 6.

[0026] The lower-level controller 5 includes, for example, a pressure control controller 5a, a power supply control controller 5b, a gas flow rate control controller 5c, and an ESC (Electric Static Chuck) temperature control controller 5d. A pressure regulating valve 41 is connected to the pressure control controller 5a as a controlled device 7, and a pressure sensor provided at an appropriate location in the plasma processing chamber 10 is connected as a sensor 6. The pressure control controller 5a controls the operation of the pressure regulating valve 41 to adjust the pressure in the plasma processing space 10s. An RF power supply 31 is connected to the power supply control controller 5b as a controlled device 7, and the power supply control controller 5b controls the operation of the RF power supply 31 in the power supply 30. A flow rate controller 22 is connected to the gas flow rate controller 5c as a controlled device 7, and a flow rate sensor provided at the gas supply port 13a is connected as a sensor 6. The gas flow rate control controller 5c controls the operation of the flow rate controller 22 to control the amount of gas supplied by the gas supply unit 20 to the shower head 13 (or plasma processing chamber 10). The gas flow control controller 5c may also control the operation of the exhaust system 40, which controls the amount of gas discharged from the plasma processing space 10s. The ESC temperature control controller 5d is connected to a temperature control module provided on the substrate support section 11 as a controlled device 7, and a temperature sensor provided at an appropriate location on the substrate support section 11 is connected as a sensor 6. The ESC temperature control controller 5d controls the operation of the temperature control module to control the temperature of, for example, the electrostatic chuck 1111.

[0027] The lower-level controller 5 shown in Figure 2 is just one example and is not limited to it. If various processing devices other than those shown are provided in the plasma processing device 1, the lower-level controller may include controllers that control various processing devices. Furthermore, the lower-level controller 5 provided in the plasma processing device 1 is not limited to controllers for different functions as shown in Figure 2, but may include multiple controllers that realize the same function. In this embodiment, the plasma processing system has a two-tiered configuration of a control unit 2 (upper-level controller) and lower-level controllers 5, but is not limited to this. For example, it may have a three-tiered configuration of an upper-level controller, an intermediate-level controller and lower-level controllers, or a configuration of four or more tiers. Hereafter, the control unit 2 will be referred to as the upper-level controller 2, and the pressure control controller 5a, power supply control controller 5b, gas flow rate control controller 5c, and ESC temperature control controller 5d will be collectively referred to as the lower-level controller 5. Note that in this embodiment, the plasma processing device 1 may have a configuration in which multiple lower-level controllers 5 are connected to one upper-level controller 2, or a configuration in which only one lower-level controller 5 is connected.

[0028] The higher-level controller 2 stores a recipe DB (database) in its storage unit 2a2, which contains instruction information (recipe) such as the procedure and conditions for substrate processing (process) created in advance by the user. Alternatively, the lower-level controller 5 may download the recipe DB or instruction information from the storage unit 2a2 of the higher-level controller 2 and store it in its own storage unit (not shown). A recipe is prepared for each process performed by the plasma processing apparatus 1, and stores the target values ​​(recipe data) of the control parameters for each controlled device 7 for each processing step included in the process. A recipe is an example of instruction information. The instruction information may also include input / output parameters of a model such as a Bayesian model (statistical model), control parameters for each lower-level controller 5, and specifications of the control algorithm applied to each lower-level controller 5. The target values ​​for each processing step are information that shows time-series changes, and may be referred to as time-series control parameters below. In one embodiment, the time-series control parameters include data in which multiple target values ​​are arranged in time-series order, and data in which output values ​​resulting from control to converge to multiple target values ​​are arranged in time-series order. Each target value included in the trajectory may be the difference value from the target value at the previous point in time. The upper controller 2 is configured to provide each lower controller 5 with time-series control parameters for each controlled device 7 based on recipe data stored in the recipe DB for each processing step, and to instruct the lower controller 5 to operate the corresponding controlled device 7 (processing unit). Each controlled device 7 controlled by each lower controller 5 has a different control response time to reach the target value in response to control from the lower controller 5. Therefore, the upper controller 2 may provide each lower controller 5 with time-series control parameters for each controlled device 7 at a timing that takes into account the control response time of each controlled device 7.

[0029] The lower-level controller 5 controls the operation of the controlled device 7 based on time-series control parameters provided by the upper-level controller 2. For example, the pressure control controller 5a receives time-series control parameters for the pressure in the plasma processing space 10s provided by the upper-level controller 2 and controls the pressure regulating valve 41 so that the pressure in the plasma processing space 10s approaches the time-series control parameters. Specifically, the pressure control controller 5a generates a control signal corresponding to the time-series difference between the time-series control parameters for pressure from the upper-level controller 2 and the time-series pressure in the plasma processing space 10s measured by the pressure sensor, or the average of these values, and outputs it to the pressure regulating valve 41.

[0030] In the plasma processing system with the above configuration, the lower-level controller 5 stores a control specification DB (database) in its memory unit, which contains information such as a model that reproduces the operating characteristics of the controlled device 7 or a function that shows the response characteristics. Based on the operating characteristics or response characteristics of the controlled device determined by the model or function stored in the control specification DB, the lower-level controller 5 determines the appropriate input trajectory (optimization result) of the control parameters to be input to the controlled device 7 in order to realize the time-series control parameters given by the higher-level controller 2 (optimizing the operation of the controlled device 7). The optimization process can be performed, for example, by a mathematical optimization method that uses a pre-trained model that has been trained in advance to output the trajectory of the optimal value of the control parameters when time-series control parameters are input. The pre-trained model is trained in advance for time-series control parameters using the optimal value trajectory derived from experimental results or simulation results using the plasma processing device 1. Furthermore, the optimization process can be carried out using a statistical method that records the trajectory of the optimal value derived from experimental or simulation results using the plasma processing apparatus 1 in relation to the time-series control parameters, and reads out the trajectory of the optimal value corresponding to the time-series control parameters from the table and outputs it, or a physical model that identifies the trajectory of the optimal value corresponding to the time-series control parameters based on physical principles (calculation formulas). The above-described process is just one example, and the lower-level controller 5 may optimize the control parameters of the controlled device 7 using existing technology. The lower-level controller 5 controls the operation of the controlled device 7 based on the trajectory (optimal value) of the determined input value (optimal value) of the control parameters (optimal result).

[0031] When the lower-level controller 5 optimizes the time-series control parameters of the controlled device 7, it calculates information (likelihood, degree of optimization) indicating how well the control result of the controlled device 7, based on the optimized control parameters (optimization result), was optimized for the time-series control parameters. The likelihood is expressed as a numerical value that indicates how well the control result is optimized (fits) to the trajectory of the target value, such as the slope (amount reached per unit time) until the control result reaches the target value, the speed (time), and the offset amount from the target value when reaching the target value. For example, in the case of a pressure control controller 5a, the likelihood for the optimized control parameters is calculated based on the time until the pressure change in the plasma processing space 10s begins, the time until the pressure in the plasma processing space 10s reaches the target value, the time until the pressure in the plasma processing space 10s stabilizes near the target value, the amount of upward deviation exceeding the target value before the pressure in the plasma processing space 10s stabilizes near the target value, and the amount of downward deviation after exceeding the target value. In addition to the degree of optimization with respect to the trajectory of the target value, the likelihood may also be information indicating the degree of fit, such as high, medium, or low. The lower-level controller 5 transmits the optimal value of the control parameter obtained through optimization (optimization result) and the likelihood of that optimal value to the higher-level controller 2.

[0032] The higher-level controller 2 acquires the operation log (optimization result) and likelihood of each controlled device 7 from each lower-level controller 5 and stores them in the storage unit 2a2. In one embodiment, the likelihood is acquired using a Bayesian model (statistical model) obtained from the operation log. The higher-level controller 2 acquires the operation log (optimization result) and likelihood of each controlled device 7 for each process (each recipe) or at specific timings within a single process (recipe). The higher-level controller 2 generates a group of multiple time-series control parameters for the recipe from which the operation log has been acquired. The multiple time-series control parameters correspond to each of the multiple lower-level controllers 5. The lower-level controller 5 controls the operation of the controlled device 7 in a first time interval (e.g., in msec, microsec, or nsec units), and accordingly, repeatedly performs optimization processing in the first or second time interval (e.g., in msec, microsec, or nsec units). The second time interval is different from the first time interval. In one embodiment, the second time interval is larger than the first time interval. In one embodiment, the second time interval is smaller than the first time interval. That is, the lower-level controller 5 controls the controlled device 7 based on time-series control parameters acquired from the upper-level controller 2 at each first time interval, and repeatedly optimizes the control parameters at each first or second time interval until an optimization result is obtained. The upper-level controller 2 then acquires the optimized results (a group of optimization results) from each of the multiple lower-level controllers 5.

[0033] Furthermore, the higher-level controller 2 evaluates whether each operation log (optimization result) is appropriate based on the likelihood of each operation log acquired along with the operation log (optimization result) of each controlled device 7 for a single recipe. For example, the higher-level controller 2 calculates the average value of the likelihood of each operation log, and uses the calculated average value of the likelihood and the likelihood of each operation log as the evaluation value for the optimization result. Alternatively, the higher-level controller 2 may calculate the evaluation value for the optimization result based on the average value of the likelihood and the likelihood of each operation log. The higher-level controller 2 calculates the evaluation value for the optimization result for each recipe or each specific timing in a single recipe. For each recipe or each timing in a single recipe, the higher-level controller 2 identifies the group of operation logs (optimization results) of each controlled device 7 that obtained the highest evaluation value, and determines the time-series control parameters for each controlled device 7 to be adopted. At this time, the higher-level controller 2 may determine a group of operation logs that yielded the highest evaluation value as the time-series control parameter for each controlled device 7 if the likelihood for that group and the likelihood for each operation log are equal to or greater than their respective thresholds. When the higher-level controller 2 has determined the time-series control parameter for each controlled device 7, it stores the determined time-series control parameter for each controlled device 7 in a recipe database, for example, by associating it with a recipe or information indicating a specific timing (e.g., a recipe ID). The higher-level controller 2 may also rewrite the recipe based on the determined time-series control parameter for each controlled device 7.

[0034] Through the process described above, for each process based on a recipe, a group of operation logs (optimization results) for each controlled device 7 obtained through optimization processing performed by each lower-level controller 5 are collected by the upper-level controller 2. The upper-level controller 2 then evaluates each group of operation logs for each controlled device 7, and stores the evaluation value for each group. Furthermore, for each recipe or at specific timings within a recipe, the group of operation logs for each controlled device 7 that received a high evaluation is determined to be the time-series control parameter for each controlled device 7 to be adopted in subsequent board processing. Note that the evaluation of the operation log group is performed considering not only the evaluation (likelihood) of each operation log for each controlled device 7 obtained by optimization by each lower-level controller 5, but also the average likelihood of each operation log. Therefore, the time-series control parameter for each controlled device 7 is appropriately determined based on the results of a comprehensive evaluation of the operation of multiple controlled devices 7, not just the operation of each controlled device 7 individually.

[0035] Figure 3 is a diagram illustrating one example configuration of a higher-level controller 2 and a lower-level controller 5. Although the plasma processing apparatus 1 of this embodiment is equipped with multiple lower-level controllers 5, Figure 3 shows a simplified configuration illustrating only one lower-level controller 5. The plasma processing apparatus 1 of this embodiment may also be equipped with multiple higher-level controllers 2 (control units 2).

[0036] As described above, the storage unit 2a2 of the upper-level controller 2 stores the program 2a2a (program product, computer program) executed by the processing unit 2a1. The program 2a2a may be read from a storage medium 2s such as a memory card or optical disc and stored in the storage unit 2a2. The program 2a2a may also be written to the storage unit 2a2 during the manufacturing or installation stage of the plasma processing apparatus 1 or the upper-level controller 2. Alternatively, the program 2a2a may be downloaded by the processing unit 2a1 from a remote server device or the like and stored in the storage unit 2a2.

[0037] The memory unit 2a2 also stores a recipe DB 2a2b for controlling each part of the plasma processing apparatus 1, and a control response time DB 2a2c in which the control response times of each lower-level controller 5 and each controlled device 7 are registered. The recipe DB 2a2b is prepared for each process and stores the time-series control parameters of each controlled device 7 for each processing step in each process. The control response time DB 2a2c stores the control response times of each lower-level controller 5 and each controlled device 7, associating them with the identification information of the lower-level controller 5 or the controlled device 7. The control response time includes, for example, the time required for each lower-level controller 5 to send a control signal to the controlled device 7 after receiving an instruction from the upper-level controller 2, the time required for each controlled device 7 to start operation after receiving a control signal from each lower-level controller 5, and the time required for each controlled device 7 to reach a target value after starting operation.

[0038] The communication interface 2a3 of the upper-level controller 2 is connected to the lower-level controller 5 via a communication line or control signal line, and transmits and receives various data with the lower-level controller 5. The upper-level controller 2 and the lower-level controller 5 may communicate one-to-one, or the upper-level controller 2 and multiple lower-level controllers 5 may be connected in a network configuration such as a bus, star, or ring. The communication interface 2a3 transmits time-series control parameter data generated by the processing unit 2a1 to the lower-level controller 5, and receives sensor values ​​from the sensor 6 transmitted by the lower-level controller 5 as a response to the control, and provides them to the processing unit 2a1. In this embodiment, the communication interface 2a3 receives optimization results and likelihood data obtained by the optimization process in the lower-level controller 5 and provides them to the processing unit 2a1.

[0039] The processing unit 2a1 of the upper-level controller 2 reads and executes the program 2a2a stored in the memory unit 2a2, thereby realizing software-based functional units such as the control processing unit 2a1a and the optimization processing unit 2a1b. In Figure 3, the functional units of the processing unit 2a1 are shown as the control processing unit 2a1a, which controls the lower-level controller 5, and the optimization processing unit 2a1b, which optimizes the control parameters for each lower-level controller 5, and the illustration of functional units related to other processing is omitted. The control processing unit 2a1a realizes board processing according to the recipe by controlling the operation of each lower-level controller 5 according to the contents of the recipe. For example, the control processing unit 2a1a determines the time-series control parameters to be output to each lower-level controller 5 based on the recipe data of each processing step described in the recipe created by the user, and transmits the determined time-series control parameters to the lower-level controller 5. Furthermore, the control processing unit 2a1a receives, as a response to the time-series control parameters transmitted to the lower controller 5, sensor values ​​acquired by the lower controller 5 from the sensor 6, operation logs (optimization results) and likelihood data for each controlled device 7 obtained through optimization processing in the lower controller 5.

[0040] In one embodiment, the optimization processing unit 2a1b calculates an evaluation value for a group of operation logs based on the operation logs (optimization results) of each controlled device 7 acquired from each lower-level controller 5 and the likelihood of each operation log. In another embodiment, the optimization processing unit 2a1b calculates an evaluation value for a group of operation logs based on the operation logs (optimization results) of each controlled device 7 acquired from each lower-level controller 5, a statistical model (Bayesian model) obtained from the operation logs, and the likelihood obtained from the statistical model. The optimization processing unit 2a1b acquires a group of operation logs for each controlled device 7 and the likelihood of each operation log for each recipe or for each processing step included in the recipe, and calculates evaluation values ​​for multiple groups. For each recipe or for each processing step included in the recipe, the optimization processing unit 2a1b identifies a group from which a desired evaluation value has been obtained, and identifies the operation logs of each controlled device 7 included in the identified group as time-series control parameters of each controlled device 7. The desired evaluation value may be the highest evaluation value, or it may be a group of multiple high evaluation values. The optimization processing unit 2a1b stores the operation log of each controlled device 7, which is specified for the time-series control parameters of each controlled device 7, in the recipe DB 2a2b, associating it with the recipe identification information, and uses it in subsequent processes.

[0041] The lower-level controller 5 may include a processing unit 51, a storage unit 52, a communication interface 53, an input unit 54, and an output unit 55. The processing unit 51, storage unit 52, and communication interface 53 have the same configuration as the processing unit 2a1, storage unit 2a2, and communication interface 2a3 of the upper-level controller 2. The storage unit 52 stores various programs and data, including a program 52a executed by the processing unit 51. The program 52a (computer program, program product) may be read from a storage medium 5s such as a memory card or optical disc and stored in the storage unit 52. The program 52a may be written to the storage unit 52 during the manufacturing or installation stage of the plasma processing apparatus 1 or the lower-level controller 5. Alternatively, the program 52a may be downloaded by the processing unit 51 from a remote server device or the like and stored in the storage unit 52. The storage unit 52 stores a control specification DB 52b in which information such as a model that reproduces the operating characteristics of the controlled device 7 or a function that shows the response characteristics is registered.

[0042] The communication interface 53 may communicate with the higher-level controller 2 via a communication line such as a LAN. The communication interface 53 receives time-series control parameters of the controlled device 7 transmitted from the higher-level controller 2 and provides the received time-series control parameters to the processing unit 51. The communication interface 53 also transmits sensor values ​​from the sensor 6 provided by the processing unit 51, operation logs (optimization results) of the controlled device 7 obtained by the optimization processing by the processing unit 51, and likelihood data to the higher-level controller 2.

[0043] The input unit 54 is connected to the sensor 6 via a signal line or the like. The input unit 54 samples and acquires the signal output by the sensor 6 (measurement result by the sensor 6) at a predetermined sampling period, and gives the acquired sensor value to the processing unit 51. Note that a plurality of sensors 6 may be connected to the input unit 54, and the input unit 54 may acquire sensor values from the plurality of sensors 6 at individual sampling periods. The output unit 55 is connected to the controlled device 7 via a signal line or the like. The output unit 55 outputs the control signal given from the processing unit 51 to the controlled device 7 to operate the controlled device 7. Note that a plurality of controlled devices 7 may be connected to the output unit 55, and the output unit 55 may output individual control signals to the plurality of controlled devices 7 respectively to individually control the operations of the plurality of controlled devices 7.

[0044] The processing unit 51 realizes software functional units such as the control processing unit 51a and the optimization processing unit 51b by reading and executing the program 52a stored in the storage unit 52. In FIG. 3, as functional units of the processing unit 51, a control processing unit 51a that performs communication with the upper controller 2 and controls the controlled device 7, and an optimization processing unit 51b that optimizes control parameters for controlling the controlled device 7 are illustrated, and illustration of functional units related to other processes is omitted. The control processing unit 51a communicates with the upper controller 2 via the communication interface 53, and performs a process of controlling the operation of the controlled device 7 connected to the output unit 55 according to a control instruction transmitted from the upper controller 2. The control processing unit 51a performs a process of transmitting the sensor value from the sensor 6 acquired by the input unit 54 during the control of the controlled device 7 from the communication interface 53 to the upper controller 2 at a predetermined transmission period. The control processing unit 51a determines the state of the controlled device 7 based on the sensor value of the sensor 6, and based on the time-series control parameter given as a control instruction from the upper controller 2 and the current state of the controlled device 7, calculates a control value of the controlled device 7, and may control the operation of the controlled device 7 based on the control signal of the calculated control value.

[0045] The optimization processing unit 51b performs optimization processing to determine the optimal trajectory of the control parameters to be input to the controlled device 7 in order to realize the time-series control parameters given by the higher-level controller 2, based on the control specification DB 52b. The control processing unit 51a performs processing to control the operation of the controlled device 7 based on the optimal trajectory identified by the optimization processing unit 51b from the time-series control parameters obtained from the higher-level controller 2. The optimization processing unit 51b performs processing to calculate the likelihood of the optimal value of the control parameters obtained by the optimization processing, and the control processing unit 51a performs processing to transmit the time-series control parameters and their likelihood to the higher-level controller 2 via the communication interface 53.

[0046] Figure 4 is a flowchart showing an example of a processing procedure for identifying a group of optimal values ​​for control parameters for a controlled device 7, and Figure 5 is an explanatory diagram showing an example of a table generated by the higher-level controller 2 during processing. In Figure 4, the processing performed by the higher-level controller 2 is shown on the left, and the processing performed by the lower-level controller 5 is shown on the right. In the table in Figure 5, the initial instruction information in the recipe data for each processing step is stored, associated with the recipe ID assigned to each recipe and the processing step ID assigned to the processing steps included in the recipe. The table in Figure 5 also stores the initial values ​​of the control values ​​that the higher-level controller 2 gives to each lower-level controller 5, the operation logs (optimization results) of the controlled device 7 obtained by the higher-level controller 2 from each lower-level controller 5, and their likelihoods, associated with information for identifying the lower-level controller 5 (e.g., lower-level controller ID). Furthermore, evaluation values ​​calculated from each operation log and its likelihood, and time-series control parameters identified based on the recipe data and each operation log are stored. In the example in Figure 5, the initial instruction information (recipe data) is stored in the table, but the recipe data does not necessarily have to be stored.

[0047] The processing unit 2a1 of the upper-level controller 2 performs the following processing for each processing step included in the process performed by the plasma processing apparatus 1. The processing unit 2a1 obtains recipe data for the processing steps to be executed by the plasma processing apparatus 1 from the recipe DB 2a2b (S11). The processing unit 2a1 generates a group of multiple time-series control parameters based on the recipe data or the stored dataset (S12). The multiple time-series control parameters correspond to each of the multiple unit controllers. The processing unit 2a1 outputs the generated multiple time-series control parameters to the corresponding lower-level controllers 5 (S13). At this time, the processing unit 2a1 may identify the timing at which the time-series control parameters should be sent to each lower-level controller 5 according to the control response time of each lower-level controller 5 and each controlled device 7, based on the contents stored in the control response time DB 2a2c, and output the time-series control parameters at the identified timing. Alternatively, the processing unit 2a1 may use existing technology to calculate the optimal value of the time-series control parameters from the time-series control parameters of the controlled device 7 generated from the recipe data, etc., and output it to each lower-level controller 5.

[0048] The processing unit 51 of the lower controller 5 acquires the time-series control parameters from the upper controller 2 (S14), and controls the operation of the controlled device 7 based on the acquired time-series control parameters (S15). The processing unit 51 acquires the sensor values measured by the sensor 6 during the operation of the controlled device 7 (S16), and determines whether an optimization result has been obtained based on the sensor values (S17). When the processing unit 51 determines that no optimization result has been obtained (S17: NO), it performs optimization processing based on the acquired sensor values (S18). The processing unit 51 returns to step S15 and controls the operation of the controlled device 7 based on the optimized control parameters (S15). The optimization processing is repeatedly performed until an optimization result is obtained. When the processing unit 51 determines that an optimization result has been obtained (S17: YES), it calculates the likelihood (optimization degree) for the optimization result (S19). For example, the processing unit 51 calculates the optimization degree indicating how optimal the operation of the controlled device 7 indicated by the sensor value is with respect to the time-series control parameters acquired from the upper controller 2. For example, when the lower controller 5 is a pressure control controller 5a, it calculates the degree of coincidence between the change in pressure within the plasma processing space 10s indicated by the sensor value and the change in pressure indicated by the time-series control parameters. The processing unit 51 outputs the optimization result and the likelihood for the optimization result calculated in step S19 to the upper controller 2 (S20). The optimization result includes the operation log of the controlled device 7. Here, the processing unit 51 may determine which of a plurality of levels, such as high, medium, and low, the calculated likelihood is based on a preset threshold value, and output the determination result to the upper controller 2.

[0049] In each lower-level controller 5, the processing unit 51 executes the processes of steps S14 to S20, and the processing unit 2a1 of the upper-level controller 2 acquires the optimization results and their likelihoods output from each lower-level controller 5 (S21). The processing unit 2a1 acquires the optimization results and likelihoods from at least one lower-level controller 5. The processing unit 2a1 stores the dataset containing the acquired optimization results and likelihoods in the storage unit 2a2, associating it with the recipe ID and processing step ID (S22). Specifically, the processing unit 2a1 stores the optimization results and their likelihoods of the time-series control parameters of each controlled device 7 acquired from each lower-level controller 5 in the table shown in Figure 5, which is prepared in the storage unit 2a2, associating them with the recipe ID, processing step ID, and information for identifying each lower-level controller 5.

[0050] The processing unit 2a1 calculates an evaluation value for the group of optimization results stored in the table and stores it in the table in Figure 5, associating it with the recipe ID and processing step ID (S23). For example, the processing unit 2a1 calculates the degree of optimality for the operation of the entire plasma processing apparatus 1 based on the degree of optimality for the operation of each controlled device 7 indicated by the likelihood of the optimization result. The degree of optimality for the operation of the entire plasma processing apparatus 1 may be, for example, the average value of the degree of optimality for the operation of each controlled device 7, or a weighted average value based on weight coefficients set for each controlled device 7. The processing unit 2a1 uses the likelihood of each optimization result (the degree of optimality for the operation of each controlled device 7) and the degree of optimality for the operation of the entire plasma processing apparatus 1 as the evaluation value for the group of optimization results. The processing unit 2a1 may also calculate the evaluation value for the group of optimization results based on the likelihood of each optimization result and the degree of optimality for the operation of the entire plasma processing apparatus 1. By using such evaluation values, it becomes possible to comprehensively evaluate the optimization results of the control parameters of each controlled device 7.

[0051] The processing unit 2a1 determines whether to terminate the process (S24), and if it determines not to terminate (S24: NO), it returns to step S12. The processing unit 2a1 performs the above-described process for each recipe, or for each timing (each processing step) in a single recipe, and stores a dataset including the optimization result and likelihood by the lower-level controller 5, and an evaluation value for the optimization result, associated with the recipe ID or processing step ID. If the processing unit 2a1 determines to terminate the process (S24: YES), it terminates the process.

[0052] In the process shown in Figure 4, the upper controller 2 and the lower controller 5 may, after performing steps S11 to S22 on the recipe data for each processing step to be processed, perform step S23 on the group of optimization results corresponding to each processing step stored in the table shown in Figure 5.

[0053] The above-described process makes it possible to set optimal time-series control parameters for each controlled device 7 for each processing step of each recipe. When identifying the optimal time-series control parameters, each lower-level controller 5 performs optimization processing, and the upper-level controller 2 evaluates the operation of the plasma processing apparatus 1 based on the results of the optimization processing performed by each lower-level controller 5. The upper-level controller 2 evaluates the optimization results obtained by each lower-level controller 5 based on the degree of optimality for the operation of each controlled device 7 as well as the degree of optimality for the operation of the plasma processing apparatus 1. Then, the optimization results that receive a high evaluation are set as time-series control parameters, making it possible to set time-series control parameters that ensure appropriate operation of each controlled device 7 as well as appropriate operation of the plasma processing apparatus 1 as a whole. The time-series control parameters for each controlled device 7 set for each processing step of each recipe are stored in the recipe DB 2a2b or the table shown in Figure 5 and used in subsequent substrate processing.

[0054] In the plasma processing apparatus 1 of this embodiment, the accuracy of substrate processing can be improved by the lower-level controller 5 optimizing the time-series control parameters of the controlled devices 7. Furthermore, the lower-level controller 5 transmits the optimization results to the upper-level controller 2, and the upper-level controller 2 updates the time-series control parameters of each controlled device 7 based on the optimization results from each lower-level controller 5, thereby enabling coordinated control of each controlled device 7. In the plasma processing apparatus 1, the time-series control parameters of each controlled device 7 (processing unit) influence each other, so by coordinating the controlled devices 7 by the upper-level controller 2, it is possible to optimize the processing of the plasma processing apparatus 1 as a whole. In addition, in the plasma processing apparatus 1 of this embodiment, the roles of the lower-level controller 5, which controls each controlled device 7, and the upper-level controller 2, which controls each lower-level controller 5, can be separated, enabling advanced optimization with a minimal system configuration.

[0055] The following describes the process by which the upper controller 2 controls each lower controller 5 based on recipe DB2a2b (new instruction) to cause the plasma processing apparatus 1 to perform substrate processing. Figure 6 is a diagram showing an example of a timing chart that shows the exchange of data between the upper controller 2 and the lower controller 5. Figure 6 shows the timing of sending time-series control parameters to the lower controller 5. In Figure 6, the horizontal axis shows time, and the vertical axis shows the upper controller 2 and the lower controller 5, showing the processing status of the upper controller 2 and the lower controller 5. Note that in Figure 6, the processing status of three lower controllers A to C is shown as the lower controller 5, and lower controllers A to C may be any of the lower controllers 5a to 5d shown in Figure 2, or other lower controllers 5.

[0056] The processing unit 2a1 of the upper-level controller 2 acquires sensor values ​​from the sensor 6 transmitted from the lower-level controllers 5 (A to C) ("Collect Data" in Figure 6). Based on the acquired sensor values ​​and the time-series control parameters of each controlled device 7 stored in the recipe DB 2a2b, the processing unit 2a1 identifies the optimal value of the time-series control parameter to be input to the controlled device 7 in order to realize the time-series control parameter ("Model Calculation" in Figure 7). For example, the processing unit 2a1 may identify, for example, the time-series control parameter for the desired evaluation value (one dataset) from among the group of time-series control parameters (multiple datasets) stored in the table of Figure 5, associated with the recipe ID and processing step ID.

[0057] The processing unit 2a1, based on the contents of the control response time DB 2a2c, identifies the response time required for each lower-level controller A to C from the time the upper-level controller 2 transmits time-series control parameters to the lower-level controller 5 until the controlled device 7 starts operating. The response time includes the time from when each lower-level controller 5 receives time-series control parameters from the upper-level controller 2 until it transmits a control signal to the controlled device 7 (response speed by the lower-level controller 5), the time from when the controlled device 7 receives a control signal from the lower-level controller 5 until it starts operating in accordance with the control signal (response speed by the processing unit), etc. ("Operation Calculation" in Figure 7). The processing unit 2a1 also identifies the timing for transitioning the operating state of each controlled device 7 to the state of the next processing step. The timing for the controlled device 7 to transition to the state of the next processing step may be when the state of the controlled device 7 continues for a predetermined time or when predetermined conditions are met, when it follows the schedule described in the recipe, or when the user operating the upper-level controller 2 or the plasma processing apparatus 1 gives an instruction to forcibly transition.

[0058] The processing unit 2a1 identifies a timing that is a number of minutes prior to the response time required from when the upper-level controller 2 sends time-series control parameters to the lower-level controller 5 until the controlled device 7 starts operating, based on the timing of transitioning the operating state of each controlled device 7. The processing unit 2a1 then identifies this timing as the timing for sending control parameters to the lower-level controller 5 ("Deliver Parameters" in Figure 6). In the example in Figure 6, arrows A1a and A1b indicate the timing when the upper-level controller 2 sends time-series control parameters to the lower-level controller A, arrows A2a and A2b indicate the timing when the upper-level controller 2 sends time-series control parameters to the lower-level controller B, and arrows A3a and A3b indicate the timing when the upper-level controller 2 sends time-series control parameters to the lower-level controller C. Since the timing at which each of the lower-level controllers A to C sends control signals to the controlled device 7 (control cycle of the controlled device 7) is different, the processing unit 2a1 determines the timing for sending time-series control parameters to each of the lower-level controllers A to C in time for the timing at which each of the lower-level controllers A to C controls the controlled device 7. The processing unit 2a1 outputs time-series control parameters for each controlled device 7 to each lower-level controller 5 at a specified transmission timing.

[0059] Through the process described above, the time-series control parameters of each controlled device 7 are optimized by coordinating the controlled devices 7 as shown in Figure 4 and optimizing the overall processing of the plasma processing apparatus 1. Furthermore, when the higher-level controller 2 outputs the time-series control parameters for each controlled device 7 to each lower-level controller 5, it does so at a timing that takes into account the control response time of each lower-level controller 5 and each controlled device 7. Therefore, the operation of each controlled device 7 can be controlled with optimal time-series control parameters that take into account the control response time of each controlled device 7, enabling optimized control not only of the operation of each controlled device 7 but also of the operation of the entire plasma processing apparatus 1.

[0060] Optimization processing for each part of the plasma processing apparatus 1 can be performed by either a lower-level controller 5 that controls each part, or by a higher-level controller 2. When a lower-level controller 5 performs optimization processing, it collects various information from other lower-level controllers 5 and performs optimization processing for the controlled equipment 7 on its own. When a higher-level controller 2 performs optimization processing, it collects various information from each lower-level controller 5, performs optimization processing for each controlled equipment 7 in a single operation, and outputs control signals to each lower-level controller 5. Since each controlled equipment 7 has a different control cycle (time resolution) and response time to control from the lower-level controller 5, and uses different data for control, optimizing the plasma processing apparatus 1 as a whole is difficult when optimization is performed by a lower-level controller 5 alone or when optimization is performed collectively by the higher-level controller 2. In contrast, in this embodiment, each lower-level controller 5 optimizes the time-series control parameters of the controlled equipment 7, and the higher-level controller 2 optimizes the plasma processing apparatus 1 as a whole based on the optimization results from each lower-level controller 5. With this configuration, it is possible to optimize the time-series control parameters for controlled equipment 7 that have different control cycles (time resolution) and types of data used for control.

[0061] The higher-level controller 2 collects sensor values ​​measured by each sensor 6 during the operation of the plasma processing apparatus 1 when each controlled device 7 is controlled by each lower-level controller 5. Based on the sensor values ​​of each sensor 6 collected in this way, it is possible to determine whether each controlled device 7 behaved appropriately. The process for determining whether the operation of each controlled device 7 is appropriate based on the sensor values ​​of the sensors 6 measured during the operation of the plasma processing apparatus 1 is described below. Figure 7 is a flowchart showing an example of the procedure for determining whether the operation of the controlled device 7 is appropriate. In the process shown in Figure 7, it is determined whether the operation of each controlled device 7 is appropriate based on whether the operation of each controlled device 7 indicated by the sensor values ​​of each sensor 6 is within a preset tolerance range.

[0062] The processing unit 2a1 of the upper-level controller 2 reads the sensor values ​​measured by each sensor 6 from the storage unit 2a2 when the plasma processing device 1 is made to execute the operation of one processing step included in one recipe (S51). The sensor values ​​of each sensor 6 are stored in the storage unit 2a2 in association with the recipe identification information and the processing step information, and the processing unit 2a1 reads the sensor values ​​corresponding to the recipe identification information and the processing step information here.

[0063] The processing unit 2a1 performs a determination process based on the sensor values ​​read from each sensor 6 to determine whether the operation of the controlled device 7 measured by each sensor 6 is within an acceptable range (S52). For example, the acceptable ranges for the sensor values ​​of the sensors 6 that indicate the operation of each controlled device 7 are stored in advance in the storage unit 2a2 (for example, the recipe DB 2a2b), and the processing unit 2a1 obtains the acceptable ranges for each controlled device 7 from the storage unit 2a2 and determines whether the sensor values ​​of each sensor 6 read in step S51 are within their respective acceptable ranges. The processing unit 2a1 outputs the determination result to a display unit connected to the upper-level controller 2 or a display unit provided on the plasma processing device 1 (S53). This makes it possible to notify the user of the plasma processing device 1 whether the operation of each controlled device 7 is appropriate (whether it is within an acceptable range). If the processing unit 2a1 determines that the operation of each controlled device 7 is within an acceptable range, it may terminate the process without performing the process in step S53. Furthermore, if the processing unit 2a1 determines that the operation of any of the controlled devices 7 is outside the acceptable range, it may notify the processing unit that the operation of the controlled device 7 is inappropriate and may also accept a request for optimization of the time-series control parameters of each controlled device 7. If the processing unit 2a1 receives a request to execute the optimization process, it may, for example, execute the optimization process shown in Figure 4 again to optimize the time-series control parameters of each controlled device 7.

[0064] As a result of the process described above, when each controlled device 7 is controlled based on the time-series control parameters optimized by the process in Figure 4 and the plasma processing apparatus 1 executes the process, it is possible to determine whether the operation of each controlled device 7 is appropriate based on the sensor values ​​measured by each sensor 6 during the execution of the process. Therefore, it becomes possible to notify the result of the determination of whether the operation of each controlled device 7 based on the optimized time-series control parameters is appropriate or not, and if it is determined to be inappropriate, it becomes possible to decide whether or not to perform the optimization process again.

[0065] In the embodiment described above, the higher-level controller 2 was configured to control each component of a single plasma processing chamber 10, such as the gas supply unit 20, power supply 30, and exhaust system 40. With this configuration, it is possible to optimize the operation of each component and the overall operation of the plasma processing apparatus 1 across all components. Alternatively, the higher-level controller 2 may be configured to control each component of each of the multiple plasma processing chambers 10. In this case, the higher-level controller 2 may not only optimize each component for a single plasma processing chamber 10, but also optimize the operation of each component and the overall operation of the plasma processing apparatus 1 across multiple plasma processing chambers 10. For example, if multiple plasma processing chambers 10 share one gas supply unit 20 (gas source 21), the control parameters for the gas supply unit 20 (gas flow rate control controller 5c) may be optimized among the multiple plasma processing chambers 10 that share the gas supply unit 20. In this case, optimization may be performed in each gas flow control controller 5c, and based on the results, the higher-level controller 2 may determine the optimal values ​​for the control parameters for each gas flow control controller 5c (gas supply unit 20).

[0066] The technology disclosed herein enables optimization processing that optimizes the operation of the entire plasma processing apparatus 1 while considering the optimization results of each processing unit (controlled equipment 7) that mutually influence each other during the operation of the plasma processing apparatus 1. The range of controlled equipment 7 that is optimized by coordinated control across the plasma processing apparatus 1 may be changed as appropriate.

[0067] While various exemplary embodiments have been described above, various additions, omissions, substitutions, and modifications are possible without limiting the embodiments described herein. The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The scope of this disclosure is indicated by the claims, not in the sense described above, and all modifications are intended to be in the sense and scope equivalent to the claims.

[0068] In this embodiment, an example of application to a capacitively coupled plasma processing apparatus 1 was described, but it is not limited to capacitive coupling and can be applied to any type of plasma processing apparatus, such as Inductively Coupled Plasma (ICP), Radial Line Slot Antenna (RLSA), Electron Cyclotron Resonance Plasma (ECR), Helicon Wave Plasma (HWP), Surface Wave Plasma (SWP), etc.

[0069] The independent and dependent claims described in the claims can be combined with each other in any combination, regardless of the form of reference. Furthermore, while the claims use a multi-claim format in which claims refer to two or more other claims (multi-claim format), this is not the only way to do so. A multi-claim format in which at least one multi-claim is referenced (multi-multi-claim format) may also be used.

[0070] 1 Plasma processing apparatus 2 Control unit (higher-level controller) 2a1 Processing unit 2a2 Memory unit 2a3 Communication interface 5 Lower-level controller 6 Sensor 7 Controlled equipment 10 Plasma processing chamber 20 Gas supply unit 30 Power supply 40 Exhaust system 51 Processing unit 52 Memory unit 53 Communication interface

Claims

1. A plurality of unit controllers corresponding to each of the plurality of processing units of a substrate processing apparatus, each unit controller configured to optimize the operation of the corresponding processing unit; a main controller configured to instruct each of the plurality of unit controllers to operate the corresponding processing unit according to the instructions of the substrate processing apparatus; and a storage unit, wherein the main controller comprises: (a) a step of acquiring a group of a plurality of optimization results corresponding to each of the plurality of unit controllers, each optimization result being obtained by optimization by the corresponding unit controller; (b) a step of deriving an evaluation value and a group of a plurality of time-series control parameters based on the plurality of optimization results acquired from the plurality of unit controllers, each of the plurality of time-series control parameters corresponding to each of the plurality of unit controllers; and (c) a step of storing a dataset including the derived evaluation value and the group of a plurality of time-series control parameters in the storage unit in association with the instruction or a timing in the instruction. (d) A substrate processing apparatus configured to perform the steps (a) to (c) above for each of the multiple instructions, or for each of the multiple timings in a single instruction, thereby storing a plurality of datasets associated with the plurality of instructions or the plurality of timings in the storage unit.

2. The substrate processing apparatus according to claim 1, wherein the main controller is configured to perform the steps of: (e) receiving a new instruction for the substrate processing apparatus; (f) identifying a single data set to be adopted for the received new instruction from the plurality of data sets stored in the storage unit; and (g) simultaneously or separately transmitting a plurality of time-series control parameters included in the identified single data set to the plurality of unit controllers.

3. The substrate processing apparatus according to claim 1 or 2, wherein the main controller obtains the optimization result and the degree of optimization of the optimization result from each of the plurality of unit controllers, calculates the degree of optimization for the group of optimization results obtained from the plurality of unit controllers based on the degree of optimization of the optimization result obtained from each of the plurality of unit controllers, and derives the evaluation value for the group of optimization results based on the degree of optimization of the optimization result obtained from each of the plurality of unit controllers and the degree of optimization for the group of optimization results.

4. The substrate processing apparatus according to claim 3, wherein the unit controller optimizes the operation of the corresponding processing unit and obtains the optimization result, controls the operation of the processing unit based on the obtained optimization result, derives the optimal degree of operation of the processing unit in accordance with the instructions of the substrate processing apparatus, and outputs the obtained optimization result and the derived optimal degree to the main controller.

5. The substrate processing apparatus according to claim 1 or 2, wherein the plurality of unit controllers include a pressure control controller for controlling the pressure within the substrate processing apparatus, a power control controller for controlling the power supply of the substrate processing apparatus, a gas flow control controller for controlling the gas flow rate within the substrate processing apparatus, or a temperature control controller for controlling the temperature at a predetermined location within the substrate processing apparatus.

6. The substrate processing apparatus according to claim 1 or 2, wherein the instructions for the substrate processing apparatus include a recipe that contains information on the process performed by the substrate processing apparatus.

7. The substrate processing apparatus according to claim 2, wherein the main controller outputs the time-series control parameters to the corresponding unit controller at a timing corresponding to the response speed of the unit controller and the response speed of the processing unit corresponding to the unit controller.

8. The substrate processing apparatus according to claim 2, wherein the unit controller optimizes the operation of the corresponding processing unit based on the time-series control parameters obtained from the main controller and obtains the optimization result, and controls the operation of the corresponding processing unit based on the obtained optimization result.

9. A substrate processing apparatus comprising: a plurality of unit controllers corresponding to each of a plurality of processing units of a substrate processing apparatus, each unit controller configured to optimize the operation of the corresponding processing unit; a main controller configured to instruct each of the plurality of unit controllers to operate the corresponding processing unit according to the instructions of the substrate processing apparatus; and a storage unit that stores a plurality of datasets associated with a plurality of instructions or a plurality of timings in a single instruction, each dataset including an evaluation value and a group of a plurality of time-series control parameters, the plurality of time-series control parameters corresponding to each of the plurality of unit controllers, wherein the main controller is configured to perform: (a) the step of receiving instructions from the substrate processing apparatus; (b) the step of identifying a dataset to be adopted for the received instruction from the plurality of datasets stored in the storage unit; and (c) the step of simultaneously or separately transmitting a plurality of time-series control parameters included in the identified dataset to the plurality of unit controllers.

10. A substrate processing method comprising: a main controller configured to instruct the operation of a corresponding processing unit to each of a plurality of unit controllers, each of which corresponds to a plurality of processing units of the substrate processing apparatus, according to instructions of the substrate processing apparatus, the main controller being configured to instruct the operation of a corresponding processing unit to each of the plurality of unit controllers configured to optimize the operation of the corresponding processing unit, the main controller being configured to perform: (a) a step of acquiring a group of a plurality of optimization results corresponding to each of the plurality of unit controllers, wherein each optimization result is obtained by optimization by the corresponding unit controller; (b) a step of deriving a group of evaluation values ​​and a plurality of time-series control parameters based on the plurality of optimization results acquired from the plurality of unit controllers, wherein the plurality of time-series control parameters correspond to each of the plurality of unit controllers; (c) a step of storing a dataset including the derived evaluation values ​​and the group of a plurality of time-series control parameters in a storage unit in association with the instruction or a single timing in the instruction; and (d) a step of storing a plurality of datasets associated with the plurality of instructions or the plurality of timings in a storage unit by performing steps (a) to (c) for each of the plurality of instructions or for each of the plurality of timings in a single instruction.

Images