Manufacturing Tool Calibration

Abstract

A method for calibrating a manufacturing system includes selecting a calibration recipe from a plurality of recipes, the calibration recipe including first process parameters for performing a manufacturing process on a substrate, and receiving, for each recipe and for two or more substrates, characteristic data representative of the manufacturing process performed on the two or more substrates using the recipe. A second process parameter is determined from first and second states of the substrate, and a process relationship between the first and second process parameters is determined for the recipe. The calibration recipe is selected from the plurality of recipes based on each process relationship, and a threshold variation of the process relationship is determined between the first and second process parameters, and the calibration recipe and the threshold variation are provided to calibrate the manufacturing system.

Description

[Technical Field]

[0001] This specification relates to semiconductor systems, processes, and devices.

[0002] Plasma etching is used in semiconductor processing to fabricate integrated circuits. Integrated circuits are formed from multiple (e.g., two or more) layer structures. Different etching gas chemistries (e.g., different gas mixtures) can be used to generate plasma in the processing environment, which allows for improved precision and selectivity to the layer structures being etched for a particular etching gas chemistries. As integrated circuits become smaller and the finer features and aspect ratios increase, the demand for precision etching of the layer structures increases. Overview

[0003] Described herein are techniques for calibrating manufacturing tools.

[0004] These techniques generally involve methods for reducing variations between different manufacturing tools and / or between different processing chambers within the same manufacturing tool. The variations are reduced by determining the chamber variations of the manufacturing process performed by the manufacturing tool using optimized, well-characterized, process parameter-sensitive recipes. The determined chamber variations are used to generate offset parameters for matching the manufacturing tool to a standardized manufacturing tool.

[0005] In general, one innovative aspect of the subject matter described herein can be embodied in a method for temperature calibration of a semiconductor processing manufacturing tool, including: selecting, by a system, a calibration recipe from a plurality of recipes, the calibration recipe including a first process parameter for performing a manufacturing process on a substrate. The selection includes, for each recipe of the plurality of recipes, receiving, by the system, characteristic data for two or more substrates, representing the manufacturing process performed on the two or more substrates using the recipe, wherein the manufacturing process for each of the two or more substrates includes a different value of the first process parameter, and the characteristic data representing the manufacturing process on each of the two or more substrates includes a first state of the substrate before the manufacturing process and a second state of the substrate after the manufacturing process. The system determines a second process parameter from the first state and the second state of the substrate, and determines a process relationship between the first process parameter and the second process parameter of the recipe for the manufacturing process performed on the two or more substrates using the recipe. The system selects the calibration recipe from the plurality of recipes based on the process relationship for each of the plurality of recipes. The system determines a threshold variation of a process relationship between the first process parameter and the second process parameter for a calibration recipe and provides the calibration recipe and the threshold variation for calibrating the manufacturing system.

[0006] Other embodiments of this aspect include corresponding systems, computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the method.

[0007] As used herein, "substrate" refers to a wafer or other carrier structure (e.g., a glass plate). The wafer may comprise a semiconductor material (e.g., silicon, GaAs, InP), or other semiconductor-based wafer material. In some cases, the wafer may comprise an insulating material (e.g., silicon-on-insulator (SOI), diamond, etc.). In some cases, the substrate includes a film formed on the surface of the wafer / carrier structure. The film may be, for example, a dielectric, a conductor, or an insulating film. The film may be formed on the surface of the wafer using various deposition techniques, such as spin coating, atomic layer deposition (ALD), chemical vapor deposition (CVD), metalorganic chemical vapor deposition (MOCVD), molecular beam epitaxy (MBE), or other similar techniques for forming thin film layers on wafers or other carrier structures. In some embodiments, the manufacturing tools described herein are plasma-based etching tools and are capable of performing etching processes on the surface of the wafer / carrier structure and / or on layers formed on the wafer.

[0008] The subject matter described herein may be implemented in these and other embodiments to achieve one or more of the following advantages: By implementing a calibration process to reduce chamber-to-chamber variations between manufacturing tools, the yield and fidelity of devices manufactured using the same manufacturing process between two or more manufacturing tools can be improved. Using the calibration methods described herein, the variation in critical dimensions (CDs) (e.g., specific dimensions used by end users to benchmark the fidelity and / or yield of etch processes) between manufacturing structures etched by different manufacturing tools can be reduced. Using the calibration methods described herein, the variation in etch rates under nominally identical conditions between different manufacturing tools can be reduced. Reducing variations, e.g., temperature variations, between different manufacturing tools can improve consistency between different manufacturing tools running the same manufacturing process (e.g., using the same recipe).

[0009] In particular, the calibration method can be used to measure and calibrate low-temperature etch processes performed on plasma-based etch tools. In this case, the substrate temperature during the manufacturing process is maintained at approximately −150 to −20°C, e.g., approximately −90 to −20°C, e.g., approximately −150 to −90°C. The limitations of conventional temperature sensors, which operate and / or have accuracy in the low-temperature range, can limit their ability to perform temperature control during the low-temperature etch process. Furthermore, the etch process can become more sensitive to temperature fluctuations in the low-temperature range, resulting in greater etch rate variation and reduced fidelity of the resulting manufacturing process. The calibration process can determine the offset of the manufacturing tool from a set standardized tool and provide a global (or local) offset for the manufacturing tool's feedback control to match the manufacturing tool's performance to the set standardized tool. In this way, variability between manufacturing tools performing low-temperature manufacturing processes (e.g., low-temperature etch processes) can be reduced to less than approximately 1.5°C. Reducing variability between manufacturing tools can reduce variability and improve utilization of systems in the field, as well as improve yield and fidelity of processes performed by different manufacturing tools. While the following disclosure identifies a specific calibration process for an etch-based manufacturing tool using the disclosed techniques, it will be readily understood that the systems and methods are equally applicable to a variety of other manufacturing tools and chambers. Thus, the present technology should not be construed as being limited solely to the described etch manufacturing tools. Before describing the operation of systems and methods, or exemplary process sequences, according to some embodiments of the present technology, the present disclosure will describe one system and chamber usable with the present technology. It should be understood that the present technology is not limited to the described apparatus, and the described processes can be performed with any number of processing chambers and systems. [Brief explanation of the drawings]

[0010] [Figure 1] 1 shows a schematic cross-sectional view of an example plasma processing chamber. [Figure 2] 1 illustrates a block diagram of an example operating environment for a process variable calibration system. [Figure 3] 1 illustrates a process flow diagram of an example process variable calibration system. [Figure 4] 10 illustrates a process flow diagram for another example process variable calibration system. [Figure 5] 1 shows an example of a process relationship graph. [Figure 6] 1 shows a typical computer system.

[0011] Like reference numbers and designations in the various drawings indicate like elements.

[0012] The present specification provides improved methods and assemblies for calibration of manufacturing tools. Embodiments of the present disclosure include methods for reducing variability between different manufacturing tools and / or different processing chambers within the same manufacturing tool. Variability is reduced by determining chamber variability for a manufacturing process performed by the manufacturing tool using an optimized, well-characterized, process-parameter-sensitive recipe. The determined chamber variability is used to generate offset parameters for aligning the manufacturing tool to a standardized manufacturing tool.

[0013] FIG. 1 shows a schematic cross-sectional view of an example of a processing chamber 100 (e.g., a plasma processing chamber) suitable for etching one or more material layers disposed on a substrate 103 (e.g., also referred to as a "wafer"). The processing chamber 100 includes a chamber body 105 defining a chamber volume 101 in which a substrate can be processed. The chamber body 105 has sidewalls 112 and a bottom 118 that is grounded to ground 126. The sidewalls 112 may include a liner 115 to protect the sidewalls 112 and extend the time between maintenance cycles of the plasma processing chamber 100. The chamber body 105 supports a chamber lid assembly 110 that encloses the chamber volume 101. The chamber body 105 may be fabricated from, for example, aluminum or other suitable material. A substrate access port 113 is formed through the sidewall 112 of the chamber body 105, allowing the substrate 103 to be easily moved in and out of the plasma processing chamber 100. The access port 113 can be coupled to a transfer chamber and / or other chambers (not shown) of a substrate processing system, for example, to perform other processes on the substrate. A pumping port 145 is formed through the bottom 118 of the chamber body 105 and is connected to the chamber volume 101. A pumping system can be coupled to the chamber volume 101 through the pumping port 145 to provide evacuation and pressure control within the processing volume. The pumping system can include one or more pumps and a throttle valve.

[0014] The chamber volume 101 includes a processing region 107, e.g., a station for processing a substrate. The processing region 107 of the chamber volume 101 may include a substrate support 135 for supporting the substrate 103 during processing. The substrate support 135 may include an electrostatic chuck 122 for holding the substrate 103 during processing. The electrostatic chuck (ESC) 122 may hold the substrate 103 to the substrate support 135 using electrostatic attraction. The ESC 122 may be powered by an RF power supply 125 integrated with a matching network 124. The ESC 122 may include an electrode 121 embedded in a dielectric. The electrode 121 may be connected to the RF power supply 125 to provide a bias that attracts plasma ions generated from the process gas in the chamber volume 101 to the ESC 122 and the substrate 103 placed on a pedestal. The RF power supply 125 may be turned on and off, i.e., pulsed, during processing of the substrate 103. The ESC 122 can have an insulator 128 to make the sidewalls of the ESC 122 less susceptible to plasma adsorption and extend the maintenance life of the ESC 122. Additionally, the substrate support 135 can have a cathode liner 136 to protect the sidewalls of the substrate support 135 from plasma gases and extend the maintenance intervals of the plasma processing chamber 100. Alternatively, in some embodiments, the ESC 122 can be powered by a pulsed DC voltage applied to the substrate rather than by the RF power source 125.

[0015] The electrode 121 can be coupled to a DC power supply 150. The power supply 150 can supply a chucking voltage of approximately 200 volts to approximately 2000 volts to the electrode 121. The power supply 150 can also include a system controller that controls the operation of the electrode 121 by passing a DC current through the electrode 121 to chuck and dechuck the substrate 103. The ESC 122 can include an internal heater connected to a power supply for heating the substrate. Meanwhile, the cooling base 129 supporting the ESC 122 can include a conduit for circulating a heat transfer fluid to maintain the temperature of the ESC 122 and the substrate 103 disposed thereon. The ESC 122 can be configured to operate within a temperature range required by the thermal budget of a device fabricated on the substrate 103. For example, the ESC 122 can be configured to maintain the substrate 103 at a temperature of approximately −150° C. or lower to approximately 500° C. or higher, depending on the process being performed. A cover ring 130 can be disposed on the ESC 122 and along the periphery of the substrate support 135. The cover ring 130 may be configured to confine the etching gas to a desired portion of the exposed top surface of the substrate 103 while shielding the top surface of the substrate support 135 from the plasma environment within the plasma processing chamber 100 .

[0016] A gas panel 160 (e.g., also referred to as a "gas distribution manifold") may be connected to the chamber body 105 through the chamber lid assembly 110 by gas lines 167 to supply process gases into the chamber volume 101. The gas panel 160 may include one or more process gas sources 161, 162, 163, 164 and may further include inert, non-reactive, and reactive gases that may be used in any number of suitable processes. Examples of process gases that may be supplied by the gas panel 160 include, but are not limited to, hydrocarbon-containing gases including methane, sulfur hexafluoride, silicon chloride, silicon tetrachloride, carbon tetrafluoride, hydrogen bromide, and the like. Process gases that may be supplied by the gas panel include, but are not limited to, argon gas, chlorine gas, nitrogen, helium, or oxygen gas, sulfur dioxide, and any number of additional substances. Additionally, the process gas may include nitrogen-, chlorine-, fluorine-, oxygen-, or hydrogen-containing gases (e.g., BCl, C2F4, C4F8, C4F6, CHF3, CH2F2, CH3F, NF3, NH3, CO2, SO2, CO, N2, NO2, NO, H2, etc.), as well as any number of suitable precursors. Process gases from process gas sources (e.g., process gas sources 161, 162, 163, 164) may be combined to form one or more etch gas mixtures. For example, gas panel 160 may include one or more process gas sources specific to oxide-based etch chemistries. In another example, gas panel 160 may include one or more process gas sources specific to nitride-based etch chemistries.

[0017] The gas panel 160 includes various valves, pressure regulators (not shown), and mass flow controllers (not shown) arranged relative to the gas sources 161, 162, 163, and 164 to control the flow of process gas from the gas sources. A valve 166 can control the flow of process gas from the gas panel 160 and from the gas sources 161, 162, 163, and 164. The operation of the valves, pressure regulators, and / or mass flow controllers can be controlled by a controller 165. The controller 165 can be operatively coupled to an electric valve (EV) manifold (not shown) and can control the operation of one or more of these valves, pressure regulators, and / or mass flow controllers. The lid assembly 110 can include a gas delivery nozzle 114. The gas delivery nozzle 114 can include one or more openings for introducing process gas from the sources 161, 162, 163, and 164 of the gas panel 160 into the chamber volume 101. After the process gas is introduced into the plasma processing chamber 100, the gas can be excited to form a plasma. An antenna 148, such as one or more inductor coils, may be provided adjacent to the plasma processing chamber 100. An antenna power supply 142 supplies power to the antenna 148 through a matching network 141 to inductively couple energy, such as RF energy, to the process gas to maintain a plasma formed from the process gas within the chamber volume 101 of the plasma processing chamber 100. Instead of or in addition to the antenna power supply 142, process electrodes below and / or above the substrate 103 may be used to capacitively couple RF power to the process gas to maintain a plasma within the chamber volume 101. The operation of the power supply 142 may be controlled by a controller, such as controller 165, which also controls the operation of other components within the plasma processing chamber 100.

[0018] The controller 165 can be used to control process sequences, adjust gas flow rates from the gas panel 160 to the plasma processing chamber 100, and adjust other process parameters. The software routines, when executed by a computing device having one or more processors (e.g., central processing units (CPUs)) in data communication with one or more memory storage devices, can transform the computing device into a special-purpose computer, such as a controller, that controls the plasma processing chamber 100 to perform processes in accordance with the present disclosure. The software routines can also be stored and / or executed by one or more other controllers that can be associated with the plasma processing chamber 100.

[0019] In some embodiments, the controller 165 is in data communication with the characterization device 172. The characterization device 172 can include one or more sensors (e.g., image sensors) operable to collect process data related to the process chamber 100. For example, the characterization device 172 can include an optical emission spectroscopy device configured to monitor a signal, e.g., plasma emission, within the processing region of the processing chamber 100. For example, the signal can be the dominant wavelength, i.e., the wavelength with the highest intensity, of the emitted light. The characteristics (e.g., wavelength and intensity) of the emitted light from the plasma within the processing region can depend, in part, on the etching gas mixture used to generate the plasma and the layer composition of the layer being etched. For example, each etching gas mixture and the corresponding layer composition can have a different signal signature. By monitoring emission wavelengths unique or characteristic of each etching gas mixture and corresponding layer composition, the etching status of the layer being etched can be monitored, such as the remaining thickness of the layer being etched. The characteristics of the light emitted from the plasma can change based on, for example, the etching process. For example, the intensity of the monitored signal can change as material is removed from the layer being processed. The characterization device 172 can be configured to collect process data including signals corresponding to the etching gas mixture utilized in substrate processing and signals corresponding to corresponding layer compositions of the structure being processed in the process chamber 100. The controller 165 can receive the process data from the characterization device 172 and determine one or more actions to perform based on the process data.

[0020] In some embodiments, upon completion of etching processing of the substrate, an automated or semi-automated robotic manipulator (not shown) may be used to transfer the substrate from the substrate support out of the processing chamber, for example, via the substrate access port 113. For example, the robotic manipulator may transfer the substrate to another chamber (or other location) to perform other steps in the fabrication process.

[0021] In some embodiments, the substrate can be transferred to a metrology chamber, such as another chamber containing one or more metrology tools. For example, the metrology chamber can be coupled to the processing chamber via the substrate access port 113. The metrology chamber can be an external metrology chamber, where the substrate is removed from the processing chamber and provided to the external metrology chamber. The metrology chamber can be configured to evaluate properties of the substrate before, during, and / or after a fabrication process performed in the processing chamber. In some cases, the metrology chamber can be configured to evaluate properties of the substrate between fabrication processes. As described in more detail with reference to FIG. 2 , the metrology chamber can be configured to characterize an etching process performed on the substrate, for example, by evaluating properties of a thin film formed on the surface of the substrate before and after the etching process in the processing chamber.

[0022] As used herein, processing chamber 100 is a component of a manufacturing tool, such as, for example, a plasma etcher. In some cases, a manufacturing tool may include two or more processing chambers 100 configured as described with reference to FIG. 1. A manufacturing tool may include one or more additional auxiliary chambers, such as a load lock, a metrology chamber, a substrate cleaning / preparation chamber, a transfer chamber, etc. When described herein as a manufacturing process being performed by a manufacturing tool, it should be understood that the manufacturing process can be performed in a processing chamber, such as, for example, processing chamber 100 of FIG. 1.

[0023] In some cases, a manufacturing process performed using a recipe on one manufacturing tool may produce different results when the same recipe is used on a different manufacturing tool. For example, variations in installed hardware, hardware aging and wear, variations in sensor calibration / offset, variations in manufacturing tool calibration / offset, or other variations between manufacturing tools can all contribute to chamber-to-chamber variations when performing a manufacturing process using the same recipe. Furthermore, certain operating modes may result in greater variability in recipe results between chambers due to greater sensitivity to one or more process parameters in the recipe. To reduce chamber-to-chamber variations, a calibration procedure can be developed using a standardized (e.g., "gold standard") manufacturing tool, and the procedure can be used to reduce variations relative to the standardized tool or between other manufacturing tools.

[0024] FIG. 2 illustrates an example operating environment 200 for a process variable calibration system 202. The process variable calibration system 202 includes a recipe selection module 204 and an offset generation module 206. The process variable calibration system 202 can receive multiple recipes 208, each containing process parameters 210, for performing a manufacturing process on a manufacturing tool 212. The manufacturing tool 212 can be a standardized system, such as a "gold standard" system (or an average set of standardized systems), based on which other manufacturing tools 212 of the same model or model family can be calibrated. Different standardized systems can be used for different hardware configurations, e.g., different hardware subsystems. For example, a dielectric etch system can have a different standardized system than a conductor etch system.

[0025] The process variable calibration system 202 is in data communication with the manufacturing tools 212 via a network 214 (e.g., a local area network (LAN) or a wide area network (WAN), e.g., the Internet). One or more operations described with respect to the process variable calibration system 202 may be performed by one or more servers (e.g., a local server and / or a cloud-based server). For example, the entire process variable calibration system may be hosted on a cloud-based server.

[0026] The process variable calibration system 202 is in data communication with one or more metrology tools 216 via a network 214. The metrology tools 216 are used to characterize substrates processed by the manufacturing tool 212 before, during, and / or after performing a manufacturing process on the substrate using the recipe 208. The metrology tools may optionally be subsystems of the manufacturing tool 212, such as a metrology chamber of the manufacturing tool 212. The metrology tools may be located outside (in situ) of a processing chamber (e.g., processing chamber 100) of the manufacturing tool and may include, for example, interferometry-based metrology tools or other thin film metrology tools. The metrology tools may include internal (in situ) metrology tools. In some embodiments, the in situ metrology tools may be located in a metrology chamber (e.g., an auxiliary chamber) connected to a processing chamber by, for example, a transfer chamber or a load lock. In some embodiments, the in situ metrology tools may be, for example, a temperature sensor (e.g., a thermocouple, an optical temperature sensor, a resistive temperature sensor, an etalon interferometer, etc.) located within the processing chamber of the manufacturing tool. In some embodiments, the metrology tool may be a separate system from, and may be located external to, the fabrication tool 212. The metrology tool 216 may operate to generate property data 218 for one or more substrates.

[0027] In some embodiments, characteristic data 218 includes measurements of dimensions of the substrate, such as the thickness of one or more thin films formed on the wafer and / or the thickness of the wafer. Characteristic data 218 can include measurements of dimensions of the substrate before and after a manufacturing process performed on the substrate by a manufacturing tool using a recipe. For example, measurements of the thickness of a substrate (e.g., including one or more layers) before and after an etching process. In some cases, characteristic data 218 can include a wafer map including multiple measurement points across the substrate, as shown in FIG. 5, for example. Characteristic data 218 can include a central tendency (e.g., mean, median, etc.) of multiple measurements of dimensions of the substrate. Characteristic data 218 can include a measurement of a dimension of the substrate at a center point of the substrate (e.g., a point aligned with a central axis perpendicular to the surface of the substrate).

[0028] The recipe selection module 204 of the process variable calibration system 202 can access characteristic data 218 generated for substrates processed by the manufacturing tool 212 according to the recipe 208 using the process parameters 210 and generate a calibration procedure that includes selecting a calibration recipe from the recipe 208 for calibrating the manufacturing tool. Details regarding the selection of a calibration recipe are described with reference to FIG. 4. The process variable calibration system 202 can store the calibration procedure, including the calibration recipe, in a calibration database 220.

[0029] Process variable calibration system 202 can provide calibration procedures (including calibration recipes for performing the calibration procedures) from calibration database 220 via network 214 to one or more on-site manufacturing tools 224. As used herein, on-site manufacturing tool 224 refers to a manufacturing tool that is the same model or family as manufacturing tool 212 and that is being prepared for deployment or has been deployed in a production environment.

[0030] In some embodiments, the process variable calibration system 202 can receive on-site characteristic data 226, for example, via the network 214. The on-site characteristic data 226 includes characteristic data collected from substrates processed at an on-site manufacturing tool 224 using a calibration recipe from the calibration database 220. The on-site manufacturing tool 224 can use the calibration recipe to generate a set of substrates processed at different process parameter values ​​(e.g., different temperature values) for each calibration procedure. The set of substrates is characterized, for example, by the metrology tool 216, and the on-site characteristic data 226 is provided as an input to the offset generation module 206. The offset generation module 206 determines whether an offset is needed for the on-site manufacturing tool (e.g., provides an offset, if needed) in response to the on-site characteristic data 226, as will be described in further detail with reference to FIG. 5 .

[0031] Although described in FIG. 2 as operations performed by process variable calibration system 202, in some embodiments, some or all of the described on-site calibration methods may be performed by a local version of process variable calibration system 202 and / or by an offset generation program operating as part of a local controller (e.g., controller 165) on on-site manufacturing tool 224.

[0032] In some embodiments, the system can generate a calibration procedure that includes selecting a calibration recipe from a plurality of available recipes, where a second process parameter (e.g., etch rate) exhibits a higher sensitivity (e.g., 2-3 times, 5-10 times, or more) to a first process parameter (e.g., temperature) than to one or more other process parameters in a manufacturing process performed using the recipe. For example, a calibration recipe for a low-temperature process can include selecting a calibration recipe that exhibits a higher sensitivity of the etch process to process temperature than to other process parameters (e.g., plasma power, backside gas cooling pressure, chamber pressure, etc.).

[0033] 3 is a flow diagram of an example process 300 for calibrating a manufacturing tool. For convenience, process 300 will be described as being performed by a system comprising one or more computers located at one or more locations and suitably programmed in accordance with this specification. For example, a suitably programmed process variable calibration system, such as process variable calibration system 202 of FIG. 2, may perform process 300.

[0034] The process variable calibration system selects a calibration recipe from a plurality of recipes including first process parameters for performing a manufacturing process on a substrate (302). The plurality of recipes (e.g., recipe 208) may be for different types of manufacturing processes, such as a dielectric etch process, a conductor etch process, etc., and the manufacturing process may be specific to the material of the substrate. Each recipe may include a set of process parameters, such as process parameters 210. The process parameters may include, for example, a process temperature, a backside gas pressure, a plasma bias power, an ion density, a pressure in the process chamber, a source power, etc. The process parameters may be adjustable (e.g., selectable within a certain range) depending on the recipe. In some cases, one of the process parameters may be selectable, allowing multiple manufacturing processes to be performed using the recipe on multiple substrates, each processed using a different value of the process parameter. For example, the process temperature may be selected from a range of process temperatures (e.g., −90 to −20° C., e.g., −150 to −90° C.), each processed using a different process temperature.

[0035] In some embodiments, a recipe may have multiple selectable ranges for a process parameter. For example, the process temperature of a recipe may be selectable from two or more process temperature ranges, such as -90 to -50°C and 60 to -20°C, or -150 to -90°C and 90 to -20°C. Here, each substrate may be processed using a different process temperature within each range. In some cases, the etch rate of a substrate in a recipe may be more sensitive to process temperature in a first process temperature range compared to a second process temperature range in the same recipe. As described in more detail below, selecting a temperature range with a higher etch rate sensitivity may be advantageous for a calibration procedure to calibrate the process temperature.

[0036] In some embodiments, design of experiments (DOE) or other experiment- or simulation-based design schemes can be used to determine a given recipe from a set of recipes in which a second process parameter exhibits a threshold dependency (e.g., sensitivity) to a first process parameter relative to one or more other process parameters. For example, simulations can be used to screen sensitive process parameters (e.g., plasma parameters) and generate a DOE. Furthermore, the DOE can be used to determine, for a given recipe, a range of values ​​for a first process parameter in which a second process parameter exhibits a threshold-level sensitivity to the first process parameter relative to one or more other process parameters. For example, a set of recipes and process temperature values ​​can be determined in which the substrate etch rate exhibits a threshold-level sensitivity to temperature, and in which the sensitivity of each of the etch rate to other process parameters (e.g., plasma power, backside gas pressure, ion density, etc.) is less than the threshold level (e.g., an order of magnitude less). That is, the DOE can be used to select a recipe and a range of values ​​for a first process parameter (e.g., temperature) in which the sensitivity of a second process parameter (e.g., etch rate) to variations in the other process parameters is reduced.

[0037] The manufacturing process can be performed for each of a plurality of recipes, for example, using a standardized manufacturing tool. The manufacturing process can be performed on a plurality of substrates, for example, two or more substrates, where each substrate is processed using the recipe with different values ​​for certain process parameters, while other process parameters are fixed as nominal values. For example, a set of two or more substrates (e.g., three or more, four or more) can be etched in a plasma etching tool (e.g., as shown in FIG. 1) using the recipe at different substrate processing temperatures.

[0038] The system receives, for each recipe of the plurality of recipes, characteristic data representative of a manufacturing process performed on two or more substrates using the recipe (304). The manufacturing process for each substrate or two or more substrates includes a different value of a first process parameter, and the characteristic data representative of the manufacturing process for each of the two or more substrates includes a first state of the substrate before the manufacturing process and a second state of the substrate after the manufacturing process. For example, the manufacturing process may be an etching process. The characteristic data may include, for example, measurements of a dimension (e.g., thickness) of the substrate. For example, the characteristic data may include measurements of a thickness of a thin film formed on the substrate. The characteristic data may include measurements of the dimension before and after the manufacturing process, for example, before and after an etching process is performed on the substrate.

[0039] In some embodiments, the characteristic data includes a central tendency (e.g., mean, median, mode, etc.) of a measured dimension at multiple points on the substrate. For example, multiple measurements of a dimension of the substrate can be collected using the metrology tool 216 before an etching process and after an etching process using the recipe. In some embodiments, the characteristic data includes a measurement of a center point of the substrate. For example, a dimension of a center point of the substrate (e.g., a point aligned along a central axis) can be collected using the metrology tool 216 before and after a fabrication process.

[0040] The system determines (306) a second process parameter from the first and second states of the substrate for each of the plurality of recipes. For example, the difference in measured dimensions between the first and second states (e.g., before and after the etching process) can be used to calculate the amount of etching of the substrate. The second process parameter (e.g., etch rate) can be extracted using the amount of etching of the substrate and the etching process time (e.g., from the recipe used to perform the manufacturing process). For example, the etch rate can be determined as follows: Etching rate = (D2 - D1) / time (1) Here, D1 and D2 are the measured dimensions before and after the etching process, respectively.

[0041] The system determines (308) a process relationship between a first process parameter and a second process parameter of the recipe for each of the plurality of recipes and for a manufacturing process performed on two or more substrates using the recipe. To determine the process relationship between the first process parameter and the second process parameter, the system can generate plots of each of the first process parameter and the second process parameter at different values ​​of the first process parameter for two or more substrates processed using the recipe. As shown in FIG. 5, calibration data is collected for each of the two or more substrates processed using the recipe and for multiple values ​​of the first process parameter. The etch rate for each substrate is calculated using Equation (1). Here, the etch rate range corresponding to the etch rate non-uniformity across the substrate surface is represented in FIG. 5 as the deviation from the central tendency of the etch rate (e.g., the average etch rate). The system can determine a process relationship, such as a linear approximation, from the plot corresponding to the average etch rate versus process temperature. The slope of the linear fit of the data can be used to determine the sensitivity of the second process parameter (e.g., etch rate) to the first process parameter (e.g., temperature). For example, a shallow slope indicates a less sensitive relationship between the second process parameter (e.g., etch rate) and the first process parameter (e.g., process temperature), while a steeper slope indicates a more sensitive relationship between the second process parameter (e.g., etch rate) and the first process parameter (e.g., process temperature).

[0042] Referring to FIG. 3 , the system selects 310 a calibration recipe from a plurality of recipes based on the process relationship of each of the plurality of recipes. The system can generate a respective plot for each of the plurality of recipes to determine the process relationship between a second process parameter and a first process parameter in the recipe. By comparing the slope of each generated plot with that corresponding to each recipe, the system can select a calibration recipe from a plurality of recipes having a threshold dependency between the second process parameter and the first process parameter (e.g., for a given substrate material composition). As described above, the system can perform a DOE (design of experiments) for each recipe to establish a sensitivity regime, where the second process parameter has at least a threshold sensitivity to the first process parameter.

[0043] The system determines (312) a threshold variability of the process relationship between the first process parameter and the second process parameter for the calibration recipe. The system can determine the variability (e.g., root mean square (RMS)) of each variable sensitivity in a manufacturing process executed using the calibration recipe. The variable sensitivity includes expected variability of process parameters such as pressure control, plasma power, chamber gas pressure, ion density, etc., and expected wafer-to-wafer intrinsic variability (e.g., provided by the wafer manufacturer). For example, the threshold variability, which represents the overall chamber-to-chamber variability, is determined by combining (e.g., adding) all of the individual subsystem variabilities and wafer-to-wafer intrinsic variability. The individual subsystem variability can be determined through analysis of hardware performance (e.g., performance logs, self-tests, test procedures, etc.). The wafer-to-wafer variability can be determined through metrology measurements, such as in-line metrology including, for example, ellipsometry, CD-SEM, etc. The threshold variability can include, for example, a standard deviation from a nominal RMS variability. The threshold variability can include, for example, a percentage variation from a nominal RMS variability. In some embodiments, the determined threshold variability may be stored in the calibration database 220 along with the corresponding calibration recipe and calibration procedure.

[0044] The system provides a calibration recipe and threshold variability for calibrating the manufacturing system (314). In some embodiments, the manufacturing system is calibrated using the calibration recipe. Calibration of the manufacturing system can be performed, for example, during the initial installation and qualification process of the on-site manufacturing system. In some embodiments, the manufacturing system can be recalibrated using the calibration recipe. For example, the manufacturing system can be recalibrated in response to drift from expected results in the manufacturing process, such as etch rate non-uniformity between process chambers. In other examples, the manufacturing system can be recalibrated in response to changes in the configuration of the manufacturing system, such as component replacement or reconfiguration. In some embodiments, the manufacturing system can be recalibrated periodically, for example, for quality control purposes.

[0045] The process variable calibration system can provide an on-site manufacturing tool (e.g., on-site manufacturing tool 224) with a calibration procedure that includes a calibration recipe selected based on one or more process parameters of the manufacturing tool. For example, the calibration procedure that includes the calibration recipe can be selected based on an etch chemistry, a substrate composition, a process temperature, or other process parameters.

[0046] 4 is a flow diagram of another example process 400 for calibrating a manufacturing tool using a calibration procedure. For convenience, process 400 will be described as being executed by one or more computer systems located at one or more locations and suitably programmed in accordance with this specification.

[0047] The system provides a calibration recipe to the manufacturing tool and executes a series of manufacturing processes on each substrate using the calibration recipe. The manufacturing processes use different first process parameter values ​​from the set of first process parameter values ​​(402). The calibration recipe is provided by the system along with a calibration procedure, e.g., instructions for executing the calibration recipe to generate calibration data. For example, the process variable calibration system 202 can receive a request for a calibration procedure to calibrate the on-site manufacturing tool from the on-site manufacturing tool 224 (e.g., a tool technician or end operator). The process variable calibration system 202 can select a calibration recipe from the calibration data 220 and provide it to the on-site manufacturing tool 224. The calibration recipe includes calibration procedures for executing a series of manufacturing processes using the calibration recipe. For example, the series of manufacturing processes includes executing the manufacturing process on two or more substrates, each processed at a different process temperature within a temperature range. The calibration procedure can also include collecting on-site calibration data for the processed substrates, e.g., using a metrology tool described herein.

[0048] The system determines the dependency of the second process parameter on the first process parameter in the manufacturing system (404) from the substrate characteristic data. In some embodiments, the on-site manufacturing tool 224 can provide the on-site characteristic data 226 of the processed substrates to the process variable calibration system 202 via the network 214. The offset generation module 206 can determine a process relationship between the second process parameter and the first process parameter. For example, the process relationship is a linear relationship between etch rate and process temperature. Here, each processed substrate corresponds to a point on a process relationship plot, such as that described with reference to FIG. 5 . The system can generate a plot of etch rate and process temperature in the calibration recipe to determine the process relationship. The system can determine the variability of the process relationship between the first process parameter and the second process parameter from the linear relationship in the on-site manufacturing tool.

[0049] In response to determining that the dependency of the second process parameter on the first process parameter is outside the threshold variation, the system generates (406) an offset calibration value for the manufacturing system. The system can generate a calibration curve for the calibration recipe in the standardized chamber and determine the average etch rate and the etch rate sensitivity to the ESC temperature. For a given on-site manufacturing tool, the system can receive calibration data for the same calibration recipe and compare the difference in etch rate between the on-site manufacturing tool and the standardized manufacturing tool. That is, the system can compare the variability of the process relationship between the first and second process parameters for a set of substrates processed by the on-site manufacturing tool 224 to the threshold variability of a standard manufacturing tool (e.g., a "golden standard" tool) for the calibration recipe. If the system determines that the variability of the process relationship is outside the threshold variability, the system can generate an offset for the on-site manufacturing tool.

[0050] In some embodiments, the system calculates the offset calibration value by dividing the etch rate difference between the on-site manufacturing tool and the standardized manufacturing tool (e.g., the average etch rate difference for multiple temperature points) by the temperature sensitivity determined for the calibration recipe.

[0051] In some embodiments, the offset calibration value can be determined based on the determined variation of the on-site manufacturing tool relative to the threshold variation of the standard manufacturing tool of the calibration recipe. For example, the threshold variation of the standard manufacturing tool of the calibration recipe can be set as X+ / -Y. If the variation value Z of the on-site manufacturing tool is outside the variation range, for example, when Z is out of range, Z>X+Y or Z<-XY, the offset calibration value A can be set as follows: If Z>X+Y, then A=ZY If Z<-XY, then A=YZ Z and Y described here can be absolute or percentage values ​​of the nominal variation.

[0052] In some embodiments, the offset calibration value may be a global offset applied to the control system for one or more process parameters. A global temperature offset may be applied to the temperature control system for the process temperature, for example, as a setpoint change to the process control loop. For example, the offset may be applied as a setpoint offset in a PID loop of a PID controller for the process temperature control system. In another example, the offset calibration value may be used to offset the readings of a temperature probe measuring the process temperature (e.g., backside substrate temperature) in a temperature process controller.

[0053] In some embodiments, for example, the methods described above can be used to select a calibration recipe for calibrating different heating zones of an electrostatic chuck (ESC). For example, a recipe can be selected to perform a zone-by-zone calibration. In this case, characteristic data for each zone in a first state (before) and a second state (after) is collected for a substrate during a manufacturing process. Furthermore, the methods described herein can be used to facilitate microzone adjustment and / or edge quantification of a substrate. In this case, additional calibration data can be collected to describe the etching process at each microzone heater in the recipe and / or at the edge of the substrate. The combined etch rate offset map and etch rate map for the substrate can be compared to a golden etch rate uniformity map for the substrate to adjust the microzone heaters. For example, an overlay of the two calibrations can be used to scale the offset of the microzone heaters and determine what other variables may have a significant impact, such as the position of the electrostatic chuck support structure, the type of support structure, and centering relative to the substrate.

[0054] In some embodiments, real-time in-situ temperature measurements, for example, using an interferometer etalon, can be combined with the etch rate signal to build a composite model of the relationship between etch rate and temperature. This composite model can be used to generate a real-time wafer temperature map, which can be used to adjust process parameters in real time during the manufacturing process. For example, the real-time wafer temperature map can be used in a control loop (e.g., closed-loop feedforward control) to adjust the set points of various components during the manufacturing process. In-situ metrology tools (e.g., interferometers) can be used to collect a higher density of data points and build a higher density temperature map across the entire substrate surface. Real-time measurements can be used, for example, to build algorithms that automatically update offsets between processed substrates. Real-time measurements can be used to capture manufacturing tool drift between processing runs, implement offsets more quickly, and reduce chamber-to-chamber variations (e.g., between manufacturing tools or between chambers within a manufacturing tool).

[0055] 6 is a block diagram illustrating an example of a computer system 600 that can be used to perform the operations described above, such as those performed by an electrostatic chuck model. System 600 includes a processor 610, a memory 620, a storage device 630, and an input / output device 640. Each of the components 610, 620, 630, and 640 can be interconnected using, for example, a system bus 650. Processor 610 can process instructions executed within system 600. In one embodiment, processor 610 is a single-threaded processor. In another embodiment, processor 610 is a multi-threaded processor. Processor 610 can process instructions stored in memory 620 or storage device 630.

[0056] Memory 620 stores information within system 600. In one embodiment, memory 620 is a computer-readable medium. In one embodiment, memory 620 is a volatile memory unit. In other embodiments, memory 620 is a non-volatile memory unit.

[0057] Storage device 630 can provide mass storage for system 600. In one embodiment, storage device 630 is a computer-readable medium. In various embodiments, storage device 630 can include, for example, a hard disk device, an optical disk device, a storage device shared over a network by multiple computing devices (e.g., a cloud storage device), or other mass storage device.

[0058] Input / output device(s) 640 provide input / output operations for system 600. In one embodiment, input / output device(s) 640 may include one or more of a network interface device (e.g., an Ethernet card), a serial communication device (e.g., an RS-232 port), and / or a wireless interface device (e.g., an 802.11 card). In other embodiments, input / output device(s) may include driver devices configured to receive input data and send output data to peripherals 660 (e.g., keyboards, printers, and display devices). However, other embodiments, such as mobile computing devices, mobile communication devices, set-top boxes, television client devices, etc., are also possible.

[0059] Although FIG. 6 illustrates an example processing system, the subject matter and functional operations described herein can be implemented in other types of digital electronic circuitry, including the structures disclosed herein and their structural equivalents, or in computer software, firmware, or hardware, or in combinations of one or more of these.

[0060] Aspects of the subject matter described herein, and acts and operations, e.g., a computing device such as controller 165, and processes performed by controller 165 (e.g., controlling etching gas switching in a plasma processing chamber, etc.), can be implemented by digital electronic circuitry, embodied computer software or firmware, computer hardware including the structures described herein and their structural equivalents, or one or more combinations thereof. The subject matter, acts and operations described herein can be implemented as or in one or more computer programs, e.g., one or more modules of computer program instructions, encoded on a computer program carrier for execution by or control the operation of a data processing apparatus. The carrier may be a tangible non-transitory computer storage medium. Alternatively, or additionally, the carrier may be an artificially generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal, generated to encode information for transmission to an appropriate receiving device for execution by the data processing apparatus. The computer storage medium may be, or a portion of, a machine-readable storage device, a machine-readable storage substrate, a random access memory device, or a serial access memory device, or a combination of one or more of these. The computer storage medium is not a propagated signal.

[0061] The term "data processing apparatus" encompasses all types of apparatus, devices, and machines that process data, including, for example, a programmable processor, a computer, or multiple processors or computers. Data processing apparatus can include special purpose logic circuitry such as FPGAs (field programmable gate arrays), ASICs (application-specific integrated circuits), and GPUs (graphics processing units). In addition to hardware, the apparatus can also include code that creates an execution environment for computer programs, such as code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or one or more combinations of these.

[0062] Computer programs may be written in any type of programming language, including compiled or interpreted, declarative or procedural, and may be deployed in any form, either as stand-alone programs (e.g., apps) or as modules, components, engines, subroutines, or other units suitable for execution in a computing environment. A computing environment may include one or more computers interconnected by a data communications network at one or more locations.

[0063] A computer program can, but need not, correspond to a file in a file system. A computer program can be stored as part of a file that contains other programs and data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program, or in multiple, linked files (e.g., a file containing one or more modules, subprograms, or portions of code).

[0064] The processes and logic flows described herein may be implemented by one or more computers running one or more computer programs to perform operations based on input data and generate output. These processes and logic flows may also be implemented by special purpose logic circuitry, such as an FPGA, an ASIC, or a GPU, or a combination of special purpose logic circuitry and one or more programmed computers.

[0065] Computers suitable for running computer programs can be built based on general-purpose microprocessors, special-purpose microprocessors, or both, and other types of central processing units (CPUs). Typically, the central processing unit receives instructions and data from read-only memory, random-access memory, or both. The basic components of a computer are a central processing unit, which executes instructions, and one or more memory devices, which store instructions and data. The central processing unit and memory can be supplemented by, or incorporated into, special-purpose logic circuitry.

[0066] Typically, a computer includes or is operatively coupled to one or more mass storage devices and is configured to transfer data to and from the mass storage devices. Mass storage devices may be, for example, magnetic disks, magneto-optical disks, optical disks, or solid-state drives. However, a computer need not necessarily include these devices. Furthermore, a computer may be incorporated into other devices, such as a mobile phone, a personal digital assistant (PDA), a portable audio / video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive.

[0067] To provide for user interaction, the subject matter described herein can be implemented on one or more computers having or configured to communicate with a display device (e.g., an LCD (liquid crystal display) monitor, a virtual reality (VR) display, or an augmented reality (AR) display) for displaying information to a user and an input device (e.g., a keyboard and a pointing device such as a mouse, trackball, or touchpad) for a user to provide input to the computer. Other types of devices can also be used to provide for user interaction. For example, feedback and responses provided to a user can be any form of sensory feedback, such as visual, auditory, audio, or tactile. Also, input from a user can be received in any form, including acoustic, speech, or tactile input, including touch actions or gestures, motor actions or gestures, or directional actions or gestures. Furthermore, a computer can interact with a user by sending and receiving documents to and from a device used by the user. For example, a computer can send a web page to a web browser on a user's device in response to a request received from the web browser, or can interact with an app running on a user device, such as a smartphone or tablet. The computer can also interact with the user by sending text messages and other types of messages to a personal device, such as a smartphone running a messaging application, and receiving reply messages from the user.

[0068] The term "configuration" is used herein in connection with systems, devices, and computer program components. When one or more computer systems are configured to perform a particular operation or action, it means that the system has installed on it software, firmware, hardware, or a combination thereof that, when operated, causes the system to perform the operation or action. When one or more computer programs are configured to perform a particular operation or action, it means that the one or more programs contain instructions that, when executed by a data processing device, cause the device to perform the operation or action. When special-purpose logic circuitry is configured to perform a particular operation or action, it means that the circuitry comprises electronic logic that performs the operation or action.

[0069] While this specification contains many specific implementation details, these should not be construed as limiting the scope of the claims (as defined by the claims themselves), but rather as descriptions of features specific to particular embodiments of a particular invention. Certain features that are described herein in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment may also be implemented in multiple embodiments separately or in any suitable subcombination. Furthermore, even if features are described above as functioning in particular combinations and are originally claimed as such, one or more features may optionally be deleted from the claimed combination, and the claims may cover subcombinations or variations of the subcombinations.

[0070] Similarly, although the figures and claims describe operations in a particular order, this should not be understood as requiring that such operations be performed in the particular order or sequence illustrated, or that all of the illustrated operations be performed, to achieve desirable results. In certain situations, multitasking and parallel processing may be advantageous. Furthermore, the separation of various system modules and components in the above embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems may generally be integrated into a single software product or packaged into multiple software products.

[0071] Specific embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. For example, the operations recited in the claims can be performed in a different order and still achieve desirable results. As an example, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some cases, multitasking and parallel processing may be advantageous.

Claims

1. 1. A method of calibrating a manufacturing system, comprising: selecting a calibration recipe from the plurality of recipes, the calibration recipe including first process parameters for performing a manufacturing process on the substrate; Each recipe of the multiple recipes is receiving, for two or more substrates, characteristic data representative of a manufacturing process performed on the two or more substrates using the recipe, the manufacturing process for each of the two or more substrates including a different value of a first process parameter, and the characteristic data representative of the manufacturing process on each of the two or more substrates including a first state of the substrate before the manufacturing process and a second state of the substrate after the manufacturing process; determining a second process parameter from the first and second states of the substrate; using the recipe to determine a process relationship between a first process parameter and a second process parameter of the recipe for a manufacturing process to be performed on two or more substrates; selecting a calibration recipe from the plurality of recipes based on a process relationship for each of the plurality of recipes; determining a threshold variation in a process relationship between a first process parameter and a second process parameter for a calibration recipe; A method comprising providing a calibration recipe and threshold variations for calibrating a manufacturing system.

2. The method of claim 1 , wherein the first process parameter comprises a substrate temperature of the substrate during the manufacturing process.

3. The method of claim 1 , wherein the second process parameter comprises an etch rate of the substrate during the manufacturing process.

4. 10. The method of claim 1, wherein determining the process relationship comprises extracting a slope of a linear relationship between a first process parameter and a second process parameter for a manufacturing process performed on two or more substrates.

5. 2. The method of claim 1, wherein selecting a calibration recipe from a plurality of recipes comprises selecting one recipe of the plurality of recipes having at least a threshold dependency between a first process parameter and a second process parameter.

6. 6. The method of claim 5, wherein selecting a calibration recipe from the plurality of recipes comprises selecting a recipe from the plurality of recipes that has the greatest dependency on the first process parameter relative to the second process parameter.

7. 7. The method of claim 6, wherein selecting a calibration recipe from the plurality of recipes comprises selecting a recipe from the plurality of recipes that has the greatest dependence of the substrate etch rate on substrate temperature.

8. 2. The method of claim 1, wherein the calibration recipe includes a plurality of process parameters, and selecting a calibration recipe from the plurality of recipes includes selecting a plurality of recipes having a dependency of a second process parameter on a first process parameter that is greater than a determined dependency of each other of the plurality of process parameters on the second process parameter by a specified threshold amount.

9. Providing a calibration recipe and threshold variations for calibrating the manufacturing system includes: providing a calibration recipe to a manufacturing system for performing a set of manufacturing processes on each substrate using the calibration recipe, each manufacturing process using a different first process parameter value of the set of first process parameter values; determining a dependency of a second process parameter on a first process parameter of the manufacturing system from the characteristic data of the substrate; 10. The method of claim 1, further comprising generating an offset calibration value for the manufacturing system in response to determining that the dependency of the second process parameter on the first process parameter is outside a threshold variation.

10. receiving, for two or more substrates, characteristic data representative of a manufacturing process performed on the two or more substrates using the recipe; performing a manufacturing process using a recipe for two or more substrates, the manufacturing process for each of the two or more substrates including a different value for a first process parameter; The method of claim 1 , comprising characterizing two or more substrates to extract characterization data.

11. The method of claim 10 , wherein the manufacturing process comprises an etching process.

12. 1. A system comprising: one or more computers and one or more storage devices, the storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations, the operations including: selecting a calibration recipe from the plurality of recipes, the calibration recipe including first process parameters for performing a manufacturing process on the substrate; Each recipe of the multiple recipes is receiving, for two or more substrates, characteristic data representative of a manufacturing process performed on the two or more substrates using the recipe, the manufacturing process for each of the two or more substrates including a different value of a first process parameter, and the characteristic data representative of the manufacturing process on each of the two or more substrates including a first state of the substrate before the manufacturing process and a second state of the substrate after the manufacturing process; determining a second process parameter from the first and second states of the substrate; using the recipe to determine a process relationship between a first process parameter and a second process parameter of the recipe for a manufacturing process to be performed on two or more substrates; selecting a calibration recipe from the plurality of recipes based on a process relationship for each of the plurality of recipes; determining a threshold variation in a process relationship between a first process parameter and a second process parameter for a calibration recipe; A system comprising providing a calibration recipe and threshold variations for calibrating a manufacturing system.

13. The system of claim 12 , wherein the first process parameter comprises a substrate temperature of the substrate during the manufacturing process.

14. The system of claim 12 , wherein the second process parameter comprises an etch rate of the substrate during the manufacturing process.

15. 13. The system of claim 12, wherein determining the process relationship comprises extracting a slope of a linear relationship between the first process parameter and the second process parameter for the manufacturing process performed on the two or more substrates.

16. 13. The system of claim 12, wherein selecting a calibration recipe from a plurality of recipes comprises selecting one recipe of the plurality of recipes having at least a threshold dependency between a first process parameter and a second process parameter.

17. 17. The system of claim 16, wherein selecting a calibration recipe from the plurality of recipes includes selecting a recipe from the plurality of recipes that has the greatest dependency on the first process parameter relative to the second process parameter.

18. 20. The system of claim 17, wherein selecting a calibration recipe from the plurality of recipes comprises selecting a recipe from the plurality of recipes that has the greatest dependence of the etch rate of the substrate on substrate temperature.

19. 13. The system of claim 12, wherein the calibration recipe includes a plurality of process parameters, and selecting a calibration recipe from the plurality of recipes includes selecting a plurality of recipes having a dependency of a second process parameter on a first process parameter that is greater than a determined dependency of each other of the plurality of process parameters on the second process parameter by a specified threshold amount.

20. one or more non-transitory computer storage media encoded with computer program instructions that, when executed by one or more computers, cause the one or more computers to perform operations, the operations including: selecting a calibration recipe from the plurality of recipes, the calibration recipe including first process parameters for performing a manufacturing process on the substrate; Each recipe of the multiple recipes is receiving, for two or more substrates, characteristic data representative of a manufacturing process performed on the two or more substrates using the recipe, the manufacturing process for each of the two or more substrates including a different value of a first process parameter, and the characteristic data representative of the manufacturing process on each of the two or more substrates including a first state of the substrate before the manufacturing process and a second state of the substrate after the manufacturing process; determining a second process parameter from the first and second states of the substrate; using the recipe to determine a process relationship between a first process parameter and a second process parameter of the recipe for a manufacturing process to be performed on two or more substrates; selecting a calibration recipe from the plurality of recipes based on a process relationship for each of the plurality of recipes; determining a threshold variation in a process relationship between a first process parameter and a second process parameter for a calibration recipe; A computer storage medium comprising steps for providing a calibration recipe and threshold variations for calibrating a manufacturing system.

Images