KR20150069549A - Rf impedance model based fault detection - Google Patents

Abstract

A method to detect a potential fault in a plasma system is described. The method includes accessing a model of one or more parts of the plasma system. The method further includes receiving data regarding a supply of RF power to a plasma chamber. The RF power is supplied using a configuration which includes one or more states. The method also includes using the data to produce model data at an output part of the model. The method includes examining the model data. The examination is of one or more variables which characterize performance of a plasma process of the plasma system. The method includes identifying the potential fault for the one or more variables. The method further includes determining that the fault has occurred for a pre-determined period of time such that the fault is identified as an event. The method includes classifying the event.

Description

[0001] RF IMPEDANCE MODEL BASED FAULT DETECTION [0002]

The embodiments are directed to methods and systems for radio frequency (RF) impedance model based fault detection.

In a plasma system, a signal source generates a radio frequency (RF) signal and provides it to the plasma chamber. When this signal is received by the plasma chamber, the gas in the plasma chamber is struck to produce a plasma in the plasma chamber.

Plasma is used for a wide range of operations on a substrate, for example, substrate cleaning, substrate processing, oxide deposition on a substrate, substrate etching, and the like. During the performance of these operations, various obstacles are encountered. For example, it may not be plasma-confined within the plasma chamber. As another example, arc generation or plasma drop-out may be present. These events reduce wafer yield and increase the time and cost associated with performing operations.

In this context, the embodiments described in this disclosure are presented.

Embodiments of the present disclosure provide apparatus, methods and computer programs for radio frequency impedance model based fault detection. The embodiments may be implemented in various ways, for example, as a method on a processor, an apparatus, a system, a device, or a computer readable medium. Some embodiments are described below.

In some embodiments, the systems and methods described herein realize plasma disturbance detection and classification within an RF driven plasma reactor where the RF signals are pulsed waves. An example of a pulsed signal is an amplitude modulated signal in which the amplitude of the RF signal is modulated.

The systems and methods described herein enable the determination of a number of events, such as arcing events, unrestricted plasma events, plasma dropout events, plasma instability events, and the like. Systems and methods that use one or more predefined thresholds to detect faults or events are used during the processing of a workpiece. The predefined thresholds are used to detect faults, which are classified into one of various categories. If it is determined that the classified fault is present for a predetermined period of time or over a predetermined number of times, it is determined that the event has occurred. Events are classified based on fault classification. The detection and classification of faults and events makes it possible to determine whether a plasma process has deviated from its normal operation. The classification of the event also provides for the identification of one or more parts of the plasma system generating the event.

In some embodiments, a method for detecting a potential fault in a plasma system is described. The method includes accessing a model of one or more portions of the plasma system. The plasma system includes a plasma chamber, a radio frequency (RF) generator, and a transmission line between the plasma chamber and the RF generator. The method includes receiving data regarding the supply of RF power to the plasma chamber. The RF power is supplied to the plasma chamber through the transmission line using a configuration that includes one or more states. The one or more states are repeated successively during the supply of RF power to the plasma chamber. The method also includes using data to generate model data at the output of the model during the supply of RF power to the plasma chamber. The model data is associated with one of the one or more states. The method includes examining model data during one of the one or more states. This investigation examines one or more parameters that characterize the performance of a plasma process of a plasma system. The method includes identifying a potential fault for one or more of the variables during one of the one or more states. The method includes determining that a potential fault has occurred over a predetermined period of time during one of the one or more states such that a potential fault is identified as an event. The method includes classifying events.

In various embodiments, a method for determining faults associated with a plasma system is described. The method includes receiving data associated with the supply of radio frequency (RF) power. Data is received from the sensor. The method further includes propagating data through a computer-generated model to determine model data at an output of the computer-generated model of one or more portions of the plasma system. The plasma system includes an RF generator, an impedance matching circuit coupled to the RF generator through an RF cable, and a plasma chamber coupled to the impedance matching circuit through the RF transmission line. The method includes generating values associated with one or more variables from the model data, determining if the values associated with the one or more variables satisfy one or more thresholds corresponding thereto, And generating a fault if it is determined that the values do not satisfy the one or more thresholds corresponding thereto. The method further includes determining whether a fault occurs during a predetermined period of time and generating an event if the fault is determined to occur during a predetermined period of time. The method includes classifying events.

In some embodiments, a plasma system is described. The plasma system includes a radio frequency (RF) generator for generating an RF signal and feeding it at an output. The RF signal is supplied using a configuration that includes one or more states. The one or more states are continuously repeated during the supply of the RF signal. The system further includes an impedance matching circuit coupled to the RF generator for receiving the RF signal from the RF generator to generate a modified RF signal. The system further includes an RF transmission line coupled to the impedance matching circuit for delivering the modified RF signal. The system further includes a plasma chamber connected to the RF transmission line for receiving the modified RF signal through the RF transmission line to generate the plasma. The system further includes a host system coupled to the sensor and sensor coupled to the output of the RF generator. The host system includes a processor, the processor accessing a model of a portion of the plasma system; Receiving data relating to the supply of the RF signal from the sensor; And using the data to generate model data at the output of the model during the supply of the RF signal. The model data is associated with one of the one or more states. The processor performs an operation of examining the model data during one of the one or more states. The investigation examines one or more parameters that characterize the performance of a plasma process within a plasma chamber. The processor performs an operation to identify a potential fault for one or more variables during one of the one or more states. The processor performs an operation to determine that a potential fault has occurred over a predetermined period of time during one of the one or more states such that a potential fault is identified as an event. The processor performs an event classification operation.

Some of the advantages of various embodiments of the systems and methods described herein include that there is no need to use external electrical circuitry to monitor voltage and / or current and / or optical signals. For example, an external monitor that is constrained by pulse compatibility and is suppressed by a frequency tuning of the dual-mode of the RF generators, e.g., multiple states, and by a number of independent non-zero pulse states, For example, voltage probes, current probes, optical sensors, etc. are not needed to determine if a fault has occurred in the plasma system. As another example, the systems and methods described herein reduce the need to use an external monitor at a location sufficiently close to the electrodes of the plasma reactor. The voltage probe provides an inaccurate event because the event is detected by the voltage probe in the state of the RF pulsed signal and is detected during this opposite state even if the event does not occur in the opposite state of the RF pulsed signal. As another example, it may be necessary to couple an external electrical circuit to such a node in order to measure the current or voltage at a node in the plasma system, for example at the input of the impedance matching circuit, at the output of the impedance matching circuit, at the RF transmission line, none. The use of external electrical circuits is sometimes not cost effective.

Other advantages of the systems and methods described herein include the ability to identify changes in complex voltages and currents that are correlated with actual events. For example, the use of models and accurate voltage and current probes, such as NIST probes, etc., helps to reduce the likelihood of detecting unrealistic events. As another example, the RF generator output impedance measured by an internal RF generator complex impedance monitoring circuit, e.g., a NIST probe or the like, may be converted to RF modeled parameters experienced by an RF driven electrode, e.g., a chuck, Conversion to power, current, voltage, and impedance enables plasma fault detection. Plasma fault detection is performed by calculating RF power and impedance parameters at the output of the computer generated model of the plasma system, such as power, current, voltage, impedance, and the like, By correlating it with a fault in the system. The modeled variables are compared to various thresholds associated with different faults to enable identification of faults and events unique to the plasma. The use of precise voltage and current probes, computer generated models, and thresholds associated with different faults improve the likelihood of recognizing actual events.

Other advantages of the systems and methods described herein include providing state-based event detection. For example, different variable thresholds and / or different variable change thresholds are used for each state of the RF signal generated by the RF generator. Different variable thresholds and / or different variable change thresholds help to detect events during different states.

Other advantages of the systems and methods described herein include an RF cable, an impedance matching circuit coupled to the RF cable, an RF transmission line coupled to the impedance matching circuit, and an RF And considering variables along the path. For example, in order to measure a variable at a location close to the impedance matching circuit, the RF path along the RF transmission line is not considered when an external monitor is used without using the computer generated model described herein. This lack of consideration can lead to false event detection.

Other advantages of the systems and methods described herein include determining the type of event, e.g., arcing, plasma dropout, plasma instability, plasma non-confinement, etc., and controlling the plasma system based on this event type . For example, if it is determined that the event is an arc occurrence event, the operation of the plasma system is stopped. As another example, if an event is determined to be a plasma instability event, the operation of the plasma tool is controlled to change the amount of power supplied to the plasma tool.

Other aspects will become apparent from the following detailed description, taken in conjunction with the accompanying drawings.

These embodiments are best understood by reference to the following description taken in conjunction with the accompanying drawings.
1A is a block diagram of a plasma system for radio frequency (RF) impedance model based fault detection, in accordance with the embodiment described in this disclosure.
1B is a block diagram of a plasma system for radio frequency (RF) impedance model based fault detection, in accordance with the embodiment described in this disclosure.
FIG. 1C illustrates graphs illustrating the generation of an event from a fault for multiple states of an RF pulsed signal, in accordance with an embodiment described in this disclosure.
Figure 2 shows a number of graphs illustrating model use in comparison to the use of an arc detection sensor, in accordance with the embodiment described in this disclosure.
3 is a graph used to illustrate failure to detect a fault or event when a sensor is used for detection without using a model, in accordance with the embodiment described in this disclosure;
FIG. 4 is a graph illustrating model usage definitively displaying a fault or event, in accordance with the embodiment described in this disclosure.
5 is a flow diagram of a method for detecting faults in a plasma system, in accordance with an embodiment described in this disclosure;
FIG. 6 illustrates one or more thresholds and / or one or more changes based on changes in the state of the RF signal, changes in operation of the RF generator, and / or changes in sub-states of the RF signal, Lt; / RTI > is a flow chart of a method of illustrating changes in value thresholds.
Figure 7 illustrates a number of graphs illustrating sub-states of an RF signal, in accordance with the embodiment described in this disclosure.

The following embodiments describe systems and methods for radio frequency (RF) impedance model based fault detection. It is to be understood that these embodiments may be practiced without some or all of these specific details. In other instances, well-known process operations have not been described in detail so as not to unnecessarily obscure the embodiments.

1A is a block diagram of an embodiment of a plasma system 100 for fault detection based on RF impedance models. The plasma system 100 includes a plasma chamber 112, an impedance matching circuit 114, one or more RF generators 116, and a host system 120, ). ≪ / RTI > In some embodiments, the model data 124 includes values of variables such as, for example, complex voltage and current, impedance, complex forward power, complex reflected power, complex transmission power, and the like. In some embodiments, the complex voltage and current comprise a voltage magnitude V, a current magnitude I, and a phase between voltage and current.

In various embodiments, when the RF pulsed signals are generated by the RF generators 116, the model data 124 is generated for each state of the RF pulsed signals. For example, a first set of model data is generated for the state S1 of the RF pulsed signal generated by one of the RF generators 116, and a second set of model data is generated for the state SO of the RF pulsed signal do.

The states S1 and S0 are continuous. For example, an instance of state S0 follows instances of state S1 sequentially. In this example, another instance of the S1 state follows an instance of the S0 state sequentially.

The states of the RF signals, e.g., S1, etc., have different power levels, for example, except for the power states of other states of the RF signal, e.g., S0, For example, the state S1 of the RF signal has a number of power values, e.g., sizes, etc., that are different from the multiple power values of state S0 of the RF signal.

In some embodiments, the RF signal generated by one of the RF generators 116 is a continuous wave RF signal and has, for example, one state instead of two or more states. As an example, the continuous wave RF signal has a state S1 or a state S0. In these embodiments, the model data 124 is generated for a continuous wave RF signal.

A process gas, for example, an oxygen-containing gas, a fluorine-containing gas, etc., is supplied between the upper electrode 134 of the plasma chamber 112 and the chuck 136. Examples of chuck 136 include an electrostatic chuck (ESC) and a magnetic chuck. Examples of oxygen-containing gases include oxygen and examples of fluorine-containing gases include tetrafluoromethane (CF ₄ ), sulfur hexafluoride (SF ₆ ), hexafluoroethane ) (C ₂ F ₆ ), and the like. The RF signals generated by the RF generators 116 are also supplied to the ESC 136 through the impedance matching circuit 114 to produce a plasma within the plasma chamber 112.

While the workpiece 138 is being processed in the plasma chamber 112, one or more sensors, such as probes in the RF generators 116, voltage and current probes, etc., And generates data representing a variable. For example, the probe 118 senses the RF signal at the output of one of the RF generators 116 and produces data representative of the complex voltage and current or impedance at that output. The output from one of the RF generators 116 is used to provide the RF signal to the impedance matching circuit 114. The RF generators 116 transmit data to the host system 120 via corresponding communication cables 117.

During state S1 or state SO, host system 120 generates model data 124 based on data received from RF generators 116, when a plasma is generated in plasma chamber 112. [ The received data includes the values of the variables, and an example of these variables is provided above. Model data 124 is generated at the output of the model 126, which is stored in the memory device of the host system 120. Examples of memory devices include read-only memory (ROM), random access memory (RAM), hard disk, volatile memory, non-volatile memory, redundant array of storage disks (RASD), flash memory, and the like.

The model 126 is a computer-generated model of one or more portions of the plasma tool 130. For example, the model 126 may be a computer-generated model of one or more RF cables coupling a corresponding one or more of the RF generators 116 to the impedance matching circuit 114, or a computer of the impedance matching circuit 114 A computer-generated model of at least a portion of the RF transmission line 127 coupling the generated model or impedance matching circuit 114 to the plasma chamber 112 or a computer-generated model of the lower electrode of the chuck 136 to be. As another example, the model 126 may include computer-generated models or RF cables of a combination of one or more RF cables and an impedance matching circuit 114, at least a portion of the impedance matching circuit 114 and the RF transmission line 127 Generated model of a combination of at least a portion of the impedance matching circuit 114 and the RF transmission line 127 and the lower electrode of the chuck 136. The computer- As another example, the model 126 may include at least a computer-generated model or combination of impedance matching circuit 114 and RF transmission line 127 of a combination of impedance matching circuit 114 and at least a portion of RF transmission line 127 Is a computer-generated model of a combination of a portion and a lower electrode of the chuck 136.

One of the RF cables couples one of the RF generators 116 to the impedance matching circuit 114 and the other one of the RF cables connects the other of the RF generators 116 to the impedance matching circuit 114 And the other one of the RF cables couples another one of the RF generators 116 to the impedance matching circuit 114. [

The RF transmission line 127 includes a transmission line portion and a cylinder portion. The transmission line portion includes an RF rod surrounded by an RF sheath. The cylinder portion includes an RF cylinder connected to the RF rod through an RF strap.

The processor of the host system 120 generates the model 126 based on the parameters of one or more portions of the plasma tool 130. For example, the model 126 of one or more portions may be used to determine the characteristics of one or more portions, such as resistors, capacitances, inductances, impedances, voltages, currents, complex voltages and currents, Have similar characteristics. As another example, the model 126 may have the same number of capacitors and / or inductors as the capacitors and / or inductors in one or more portions of the plasma tool 130, and / or the capacitors of the model 126 and / The inductors are connected to one another in series, in parallel, for example, in the same manner as the capacitors and / or inductors are connected together in one or more portions. For example, to illustrate, when the impedance matching circuit 114 includes a capacitor connected in series with an inductor, the model 126 also includes a capacitor connected in series with the inductor.

As another example, one or more portions of the plasma tool 130 may include one or more electrical components, e.g., capacitors, inductors, resistors, etc., and the model 126 may include one or more portions of a design, Includes a computer-generated model. In some embodiments, the computer-generated model may be generated by a host system 120 based on input signals received from an input device of the host system 120, e.g., a mouse, keyboard, stylus, touchpad, keypad, Lt; / RTI > The input device is connected to the CPU 156 through an input / output interface. One or more selections are made by the user to generate the input signals. The input signals identify the electrical components to include within the model 126 and identify the manner in which the electrical components are coupled to each other, e.g., serial, parallel, and so on. As another example, one or more portions of the plasma tool 130 include hardware connections between electrical components and electrical components, and the model 126 of one or more portions includes a software representation of the electrical components and a software representation of the hardware connections. do. In some embodiments, the electrical components include a connection between the resistors, a connection between the inductors and / or a connection between the capacitors.

Based on the characteristics received from the sensor 118 via the RF cable and the characteristics of the elements within the model 126, such as inductors, capacitors, resistors, etc., Calculates one or more variable values at the output of the model data 124, e.g., the model 126. For example, the processor of the host system 120 computes the sum of the impedances of the components of the model 126 connected in series with each other and adds this sum to the impedance value received from the sensor 118. As another example, the processor of the host system 120 may calculate the ratio between the product of the impedances of the components of the model 126 connected in parallel with each other and the sum of the impedances of the components of the model 126 connected in parallel with each other And adds this ratio to the impedance value received from the sensor 118. As another example, the processor of the host system 120 computes gamma from the complex voltage and current received from the sensor 118. Other examples of model data 124 include power, wafer bias, ion energy, power variation, voltage variation, current variation, and the like. Other examples of model data 124 are provided below. Further examples of variations of the variables are provided below.

In some embodiments, the variables of the model data 124 have the same type as the variables received from the sensor 118. For example, the variables of the model data 124 and the variable received from the sensor 118 are complex reflected power. As another example, the variables of the model data 124 and the variables received from the sensor 118 are complex forward power or complex transmission power or complex voltage and current.

The processor of the host system 120 accesses, i.e. reads, acquires, etc., the model data 124 from the memory device of the host system 120 and generates one or more variable thresholds, e.g., a power threshold, a voltage threshold, At operation 128, it is determined whether a fault has occurred in the plasma tool 130 by applying a threshold, an ion energy threshold, a wafer bias threshold, an impedance threshold, a gamma threshold, etc., and / or one or more variable change thresholds to the model data 124 .

In some embodiments, each threshold value described herein is predetermined.

In various embodiments, different thresholds are used for different states of the RF pulsed signals generated by the RF generators 116. For example, a first value of the transmission power threshold is used when the RF pulsed signal is in state 1 and a second value of the transmission power threshold is used when the RF pulsed signal is in state 0.

In some embodiments, the host system 120 may generate a statistical value from the model data 124 and apply the one or more variable thresholds to this statistical value in a manner similar to the manner in which one or more of the variable thresholds are applied to the model data 124 To determine if a fault has occurred in the plasma tool 130. < RTI ID = 0.0 > For example, the host system 120 determines whether the statistical value of the current is greater than a threshold associated with this current.

Examples of statistical values include a median of the mean and multiple values of the largest or a plurality of values of the plurality of values of the plurality of values of the model data 124, Or a moving average of a plurality of values or a moving median of a plurality of values or a moving variance value of a plurality of values, a moving standard variation value of a plurality of values or a mode of movement of a plurality of values or a plurality of values, An interquartile range (IQR) generated from a plurality of values, or combinations thereof.

In some embodiments, the processor of the host system 120 calculates the IQR as a difference between the statistical values of the upper distribution range of the plurality of values of the model data 124 and the statistical values of the lower distribution range. For example, the processor of the host system 120 divides the distribution of multiple values of the model data 124 generated during a predetermined period into a first range, a second range, and a third range. The processor of the host system 120 calculates the first median of the first range and the second median of the third range and calculates the IQR as the difference between the second median and the first median.

 At operation 131, the host system 120 sorts the faults determined at operation 128. Examples of the various classes of faults include faults that occur as a result of plasma arc generation in the plasma chamber 112, faults that result from plasma nondetermination, faults that occur based on plasma instability, or faults that occur as a result of plasma dropout, do. It should be noted that arc generation, plasma confinement, plasma instability, and plasma dropout are illustrative examples of the performance of a plasma process occurring in the plasma chamber 112. For example, during arc generation, or plasma non-confinement, or plasma instability, or plasma dropout, the efficiency of the workpiece 138 during processing is reduced.

In some embodiments, the plasma non-confinement is a plasma leakage from the area surrounded by the chuck 136, the top electrode 134, and the limiting rings (not shown) located within the plasma chamber 112. A reaction chamber, such as a plasma reactor, is formed by chuck 136, upper electrode 134 and confinement rings. In various embodiments, the reaction chamber may include additional portions, such as an upper electrode extension surrounding the upper electrode 134, a lower electrode extension surrounding the chuck 136, an upper electrode 134, A dielectric ring between the extension portions, a dielectric ring between the lower electrode extension portion and the chuck 136, and the like. The confinement rings are located at the edges of the upper electrode 134 and the chuck 136 to enclose the region where the plasma is to be formed. In some embodiments, plasma inefficiency may occur during processing of the workpiece 138 due to plasma nonspinning, and portions of the plasma, such as, for example, the walls of the plasma chamber 112 where the unconstrained plasma comes into contact, The pedestal deteriorates. This deterioration shortens the lifetime of these parts of the plasma chamber 112.

In various embodiments, the plasma instability is a change in plasma equilibrium resulting from a change in factors affecting the plasma. Factors affecting the plasma include temperature, pressure, electric field, magnetic field, etc. in the plasma chamber 112. In some embodiments, the temperature and pressure are controlled through the temperature and pressure settings controlled by the processor of the host system 120.

In some embodiments, the plasma arc is generated in the plasma formed between the lower electrode and the upper electrode 134 of the chuck 136 or between the upper electrode 134 and the chuck 136, in the presence of charge carriers, And thermionic emission of electrons and the like. In some embodiments, plasma arc generation increases the inefficiency in processing the workpiece 138 by deteriorating the workpiece 138, components of the reaction chamber, and the like. In addition, plasma arc generation reduces the lifetime of parts of the reaction chamber. In various embodiments, arc generation refers to transient high-density plasma filaments carrying current between two surfaces within or within the plasma chamber 112.

In various embodiments, the plasma dropout occurs when the plasma can not be maintained in the reaction chamber.

A fault determined during operation 128 may be determined by the processor of the host system 120 based on criteria such as, for example, the magnitude of the variable, the direction of magnitude change, the combination of two or more variables, . To illustrate the fault classification, the processor of the host system 120 determines whether the impedance at the output of the model 126 is less than a predetermined impedance threshold, whether the voltage at the output is less than a predetermined voltage threshold, And determines whether the current at the output is greater than a predetermined current threshold. If the impedance at the output of the model 126 is less than the predetermined impedance threshold, the voltage at the output is less than the predetermined voltage threshold, and the current at the output is greater than the predetermined current threshold, 120 determines that the fault determined at operation 128 is classified as arcing within the plasma chamber 112. It should be noted that a change in voltage lower than a predetermined voltage threshold is an example of the direction of the magnitude of the variable. The voltage varies downward below the predetermined voltage threshold. Similarly, it should be noted that the change in current above the predetermined current threshold is an example of the direction of the magnitude of the variable. The current changes upwardly above the predetermined current threshold. In some embodiments, the impedance at the output of the model 126 is lower than a predetermined impedance threshold when the impedance reaches zero, e.g., within a predetermined range of zero.

As another example of a classification of faults determined at operation 128, the processor of the host system 120 may determine whether the calculated impedance at the output of the model 126 is below a predetermined impedance threshold or changes less than or greater than a predetermined impedance threshold . If the processor 126 determines that the calculated impedance at the output of the model 126 changes beyond the predetermined impedance threshold, the processor of the host system 120 determines that the fault determined during operation 128 is a plasma non-limiting fault.

As another example of the classification of faults determined at operation 128, the processor of the host system 120 may determine that the voltage calculated at the output of the model 126 is less than the predetermined voltage threshold and the current calculated at the output of the model 126 Is less than a predetermined current threshold. If the voltage is determined to be less than the predetermined voltage threshold and the current is determined to be less than the predetermined current threshold, the processor of host system 120 determines that the fault determined during operation 128 is a plasma non-limiting fault.

As another example of the classification of faults determined at operation 128, the processor of the host system 120 may determine that the magnitude of the gamma calculated at the output of the model 126 is greater than the predetermined gamma threshold and computed at the output of the model 126 And determines whether the magnitude of the power that is generated is less than a predetermined power threshold. If the gamma magnitude is determined to be greater than the predetermined gamma threshold and the magnitude of the power is less than the predetermined power threshold, the processor of the host system 120 determines that the determined fault during operation 128 is a plasma dropout fault. It should be noted that, in some embodiments, when the gamma magnitude is greater than the predetermined gamma threshold, most of the power supplied by the RF generator 118 is reflected towards the RF generator 118. Also, in various embodiments, the gamma magnitude is greater than the predetermined gamma threshold during periods when the RF generators 116 are turned on and, for example, become operational and generate RF signals, etc. [

In many embodiments, the amount of power used to determine whether a plasma dropout fault is present in the plasma tool is determined based on the intensity of the optical signal instead of being calculated at the output of the model 126. This intensity is measured using an optical sensor, for example, an optical emission spectroscopy (OES) meter or the like. The optical sensor senses the optical signals of the plasma generated in the plasma chamber 112 to produce electrical signals indicative of the intensity and provides the electrical signal to the processor of the host system 120. The processor of the host system 120 accesses the correlation between the strength and the power from the memory device of the host system 120 to determine the fault.

As another example of the classification of faults determined at operation 128, the host system 120 may determine a change in the magnitude of the power computed at the output of the model 126, for example, standard deviation, variance, IQR, And the like are greater than a predetermined power change value threshold value. If it is determined that the magnitude of the power is greater than the predetermined power change threshold, the host system 120 determines that the fault determined at operation 128 is a plasma instability fault.

As another example of the classification of faults determined at operation 128, the host system 120 determines whether the rate of change in impedance is greater than a predetermined rate threshold. If it is determined that the rate of change of impedance is greater than the predetermined rate threshold, the processor of host system 120 classifies the fault determined at operation 128 into a plasma non-qualified fault. On the other hand, if it is determined that the rate of change of the impedance is less than the predetermined rate threshold, the CPU 158 classifies the fault as a plasma instability fault. In some embodiments, instead of an impedance change rate, other variables, such as the rate of change of power, voltage, current, may be used to determine whether a fault is classified as a plasma unrestrike event or a plasma instability event .

In various embodiments, in addition to the rate of change of the variables, those described above may be used to determine whether other criteria, e.g., plasma non-confinement or plasma instability, have occurred so that plasma non-confinement or plasma instability has occurred Can be determined. For example, if the voltage is less than the predetermined voltage threshold and the current is less than the predetermined current threshold and the impedance change rate is determined to be greater than the predetermined rate threshold, the processor of the host system 120 determines that a plasma non- do.

 It is determined that the processor of the host system 120 is determined at operation 128 and that the fault classified at operation 131 lasts for a period 132 of a period 132 or that this fault is a predetermined number of times the thresholds are compared against variables or variable variations The processor of host system 120 determines during operation 140 that an event has occurred in the plasma tool. For example, the processor of the host system 120 determines whether a fault determined at operation 128 is determined based on a predetermined number of values of one or more variables calculated at the output of the model 126, and if so The processor of the host system 120 determines that an event has occurred.

The host system 120 performs a classification operation 142 on the event determined during operation 140 to classify the event. Examples of classes of events include an arc occurrence event, a plasma non-confining event, a plasma instability event, and a plasma dropout event. The class of the event is the same as the class of the fault for which this event is determined. For example, if it is determined that a fault has occurred due to an arc occurrence, the event determined based on this fault is an arc occurrence event. As another example, if it is determined that a fault has occurred due to plasma instability, the event determined based on this fault is a plasma instability event.

In various embodiments, a fault determined during operation 128, operation 131, an event determined during operation 140, and / or a classification operation 142 are used to resolve or mitigate the effects of faults and / or events.

 In some embodiments, a classification operation 142 is used to determine the portion of the tool 130 that generates the classified event. For example, by classifying an event as a plasma unrestricted event, the processor of host system 120 determines that an event is generated by the defining rings of tool 130. As another example, if the event is determined to be an arcing event, the processor of the host system 120 may generate the event by the upper electrode 134, by the lower electrode of the chuck 136, . As another example, if the event is determined to be a plasma instability event, the processor of the host system 120 determines whether the event is one of the RF generators 116, one of the RF cables, or the impedance matching circuit 114, The RF transmission line 127, or the temperature setting in the plasma chamber 112, or the pressure setting in the plasma chamber 112, or a combination thereof. As another example, if an event is classified as a plasma dropout event, the processor of the host system 120 determines whether the event is one of the RF generators 116, one of the RF cables, or the impedance matching circuit 114, Or the RF transmission line 127, or the power settings of the RF generator, or a combination thereof.

In some embodiments, the sorting operation 142 is used to determine whether to turn off the power supplied to the plasma tool 130 or to change the amount or frequency of the power supplied to the plasma tool 130. For example, if an event is determined to be an arcing event, the processor of the host system 120 transmits a control signal to one or more of the RF generators 116 to turn off the one or more RF generators 116. As another example, if it is determined that the event is a plasma dropout or a plasma instability event, the processor of the host system 120 may send a control signal to one or more of the RF generators 116 to generate the corresponding one or more RF generators 116 ) Or the frequency of one or more RF signals. In another example, if the event is determined to be a plasma dropout event, the processor of the host system 120 may transmit a control signal in one or more of the RF generators 116 to turn off the one or more RF generators 116 . As another example, if the event is determined to be a plasma dropout event, the processor of the host system 120 may transmit a control signal to the power supplied by the corresponding one or more RF generators 116 and / or the frequency of one or more RF signals .

In some embodiments, when the event is determined to be an arcing event, such as a fine arcing event, etc., the processor of the host system 120 may generate a control signal by the corresponding one or more RF generators 116 To the one or more RF generators 116 to vary the amount of power supplied and / or the frequency of one or more RF signals.

In various embodiments, after performing the classification operation 142 on the state of the RF pulsed signal, the model data may be sent to different continuous states of the RF pulsed signal by the processor of the host system 120, for example, states S1, State S0, and so on. The consecutive state is different from the preceding state, and the preceding state precedes the continuous state. For example, when the preceding state is state S1, the continuous state is state S0. As another example, when the preceding state is the state S0, the continuous state is the state S1. The model data is used to determine faults during consecutive states and to be classified during a series of faults. Also, the classified faults are used to determine whether an event occurred during a contiguous state, or whether the event was classified during a contiguous state.

In some embodiments, after performing the classification operation 142 for the state of the continuous wave RF signal, the model data is generated again for the same state of the processor continuous wave RF signal of the host system 120, and operations 128, 131, 140 , And 142 are repeated for this state. The repetition of the model data 124 and the operations 128, 131, 140, and 142 for this state are performed after a predetermined period of time, synchronized with the clock signal, or after the operation 142 is performed.

In some embodiments, the processor of the host system 120 may execute or operate the controller logic 122 of the host system 120 to generate the model data 124, generate a fault during the operation 128, 132, or during a predefined number of times, to generate an event during operation 140, and to perform a sort operation 142. < RTI ID = 0.0 > In various embodiments, the controller logic 122 may be implemented using an application specific integrated circuit (ASIC) (ASIC), or using a programmable logic device (PLD), or using a field programmable gate array Is executed using the processor of the host system 120 or as software stored on a computer readable medium. In some embodiments, the controller logic 122 is implemented using hardware or software or a combination thereof.

1B is a block diagram of an embodiment of a plasma system 144 for radio frequency (RF) impedance model based fault detection. Plasma system 144 is an example of plasma system 100 (FIG. 1A). Plasma system 144 includes one or more RF generators 146, for example, an x MHz RF generator, a y MHz RF generator, and a z MHz RF generator. RF generators 146 are examples of RF generators 116 (FIG. 1A). An example of an x MHz RF generator includes an RF generator with an operating frequency of 2 MHz, an example of a y MHz RF generator includes an RF generator with an operating frequency of 27 MHz, and an example of a z MHz RF generator has an operating frequency of 60 MHz Lt; / RTI >

The pulsing RF generators 146 are coupled to the impedance matching network 148 via one or more corresponding RF cables 147. The impedance matching network 148 is an example of the impedance matching circuit 114 (FIG. 1A).

The impedance matching network 148 is connected to the electrostatic chuck 152 of the plasma chamber 156 via an RF transmission line 150 and the plasma chamber 156 is an example of the plasma chamber 112 (FIG. RF transmission line 150 is an example of RF transmission line 127 (FIG. 1A). The ESC 152 is an example of the chuck 136 (FIG. 1A). The ESC 152 includes a lower electrode. In some embodiments, the ESC 152 includes a bottom electrode and a ceramic layer disposed thereon, for example, on top of the bottom electrode. In various embodiments, the ESC 152 includes a lower electrode, a ceramic layer, and a fixture plate disposed thereunder, for example, against the lower electrode.

In some embodiments, the RF transmission line 150 includes an RF tunnel and a bias housing. In various embodiments, an RF rod extends through the RF tunnel and is coupled to the bias housing via an RF strap. In these embodiments, the bias housing includes an RF cylinder, one end of which is coupled to the RF strap and the other end of which is coupled to the ESC 152.

In various embodiments, the bottom electrode of the ESC 152 is comprised of a metal, for example, an anodized aluminum, an alloy of aluminum, or the like. The upper electrode 134 (Fig. 1A) is also made of aluminum, an alloy of aluminum, or the like. The upper electrode 134 is located opposite the lower electrode of the ESC 152 facing it.

A wafer 154 is disposed on the top surface 156 of the ESC 152 for processing and such processing may be performed by depositing material on the wafer 154 or by cleaning the wafer 154, Or to deposit the wafers 154 or to implant ions into the wafers 154 or to create lithographic patterns on the wafers 154 or to deposit the wafers 154 on the wafers 154, Or sputtering the wafer 154, or a combination thereof. In some embodiments, a workpiece, e.g., a wafer on which vias or communication media are placed, is used in place of the wafer to process the workpiece.

The upper electrode 134 is grounded facing the ESC 152, for example, coupled to a reference voltage, coupled to a zero voltage, or coupled to a negative voltage or the like. For example, the lower surface of the upper electrode 134 may be suspended to face the upper surface 156 of the ESC 152.

The plasma system 144 further includes a central processing unit (CPU) 158, which is coupled to the RF generators 146 via one or more cables. As used herein, in some embodiments, a computer, processor, controller, ASIC, or PLD is used instead of a CPU, and such terms are used interchangeably herein. In various embodiments, the CPU 158 is part of the host system 162 or part of the RF generator of the plasma system 144, or within the computer, or within the server, or within the cloud network. Host system 162 is an example of host system 120 (FIG. 1A). Examples of host system 162 include computers, e.g., desktop computers, cell phones, smart phones, laptop computers, tablets, and the like.

In some embodiments, a server or a virtual machine is used instead of the host system. For example, the server or virtual machine executes the same functions described herein that are performed by the host system 162. The computer-generated model is generated by the processor of the host system 162 and stored in the memory device of the host system 162. [ Examples of computer-generated models include a model of the RF cables 147, or a model of the impedance matching network 148, or a model of the RF transmission line 150, or a model of the ESC 152, . The computer-generated model generated by the CPU 158 is an example of the model 126 (FIG. 1A).

CPU 158 generates pulsed signal 164 and provides this pulsed signal 164 to RF generators 146. [ The RF generators 146 generate one or more RF signals, e.g., an RF signal 166, based on the pulsed signal 164. For example, the RF signal 166 is generated by this RF generator at the same time one of the RF generators 146 receives the pulsed signal 164. As another example, the phase of the envelope of the RF signal 166 is the same as the phase of the envelope of the pulsed signal 164. In some embodiments, each RF signal is sinusoidal or substantially sinusoidal during states S1 and S0, respectively. In various embodiments, the pulsed signal 164 is a transistor-transistor logic (TTL) signal.

In some embodiments, each RF signal generated by each one of the RF generators 146 has two states, e.g., state 1 and state 0, a high state and a low state, and so on. For example, multiple power values of an RF signal generated by one of the RF generators 146 during state 1 do not include multiple power values of the RF signal generated by this RF generator during state 0. In some embodiments, the transition between one state and another state of the RF signal generated by one of the RF generators 146 is a vertical transition having an infinite slope. In various embodiments, the transition between one state and the other state of the RF signal generated by one of the RF generators 146 results in an upward tilted slope greater than 45 degrees from state 0 to state 1, Lt; / RTI > is a substantially vertical chuck with a slope tilted downwardly to less than -45 degrees to zero.

It should be noted that state 0 and low state are examples of state S0, and state 1 and high state are instances of state S1.

In some embodiments, each RF signal generated by each of the RF generators 146 is a continuous wave RF signal, which has a single state, e. G., State S0 or state S1, and so on.

The impedance matching network 148 receives the RF signals from the RF generators 146 and provides the impedance of the load connected to the output of the impedance matching network 148 to the impedance of the source connected to the input of the impedance matching network 148 And generates a modified RF signal. Examples of this source include RF generators 146 and RF cables 147. Examples of loads include an RF transmission line 150 and a plasma chamber 156. The modified RF signal is provided by the impedance matching network 148 to the ESC 152 via the RF transmission line 150.

The ESC 152 receives the modified RF signal and introduces process gases into the plasma chamber 112 to plasma strike the plasma chamber 112. Plasma is used to process the wafer 154.

RF generators 146 include sensors that measure variables, e.g., complex voltages and currents, impedances, etc., at corresponding outputs of RF generators 146. For example, at least one of the RF generators 146 includes a National Institute of Standards and Technology (NIST) probe, which is connected to the output of the RF generator to measure voltage magnitude, current magnitude, The sensors measuring the complex voltage and current at the output of one of the RF generators 146 may be used by the National Institute of Standards and Technology (NIST) For example, a sensor can be NIST-traceable when the measured variable by this sensor has an error.This variable and the error are measured by a probe that strictly follows the NIST standard Variable and error. When the probe corresponds to a widely known and widely adopted standard developed by NIST, this probe is NIST Sensors that measure the complex voltage and current at the output of one of the RF generators 146 are located outside the RF generator and are coupled to the output of the RF generator 146. The NIST- As another example, one of the RF generators 146 may be a NIST-probe or a NIST-traceable probe that measures complex power, e.g., complex reflected power, complex power supply, complex transmit power, .

The CPU 158 receives variables measured by the sensors via the communication cables which couple the corresponding sensors to the host system 162 and the CPU 158 controls the computer- (E.g., complex voltages and currents, complex reflected power, complex forward power, complex transmit power, etc.) by accessing the memory 126 of the host system 162 from the memory device of the host system 162, And the like are propagated through a computer-generated model to generate model data 124 (FIG. 1A). For example, the directional sum of the complex voltages and currents of the complex voltage and current at the input model node of the model 126 and of the components of the model 126, e.g., capacitors, inductors, resistors, directional sum) is calculated by the CPU 158 to generate the complex voltage and current at the output model node of the model 126. The complex voltage and current at the input model node of the model 126 is received from one of the sensors. As another example, one type of complex power at the input model node of the model 126, e.g., complex reflected power, complex forward power, complex forward power, etc., and the components of the model 126, The directional sum of the complex power of the same type, such as capacitors, inductors, resistors, etc., is calculated by the CPU 158 to generate the complex power at the output model node of the model 126. The complex power at the input model node of the model 126 is received from one of the sensors. As another example, the sum of the impedances of the components of the serial model 126 is calculated by the CPU 158 and added by the CPU 158 to the impedance measured by the NIST-traceable probe, Impedance is forward-profiled through model 126. As another example, the ratio of the product of the impedances of the components of the model 126 in parallel to the sum of the impedances is added by the CPU 158 to the impedance measured by the NIST-traceable probe, ≪ / RTI > 126). In this example, the sum of the ratios and impedances is calculated by the CPU 158.

Various embodiments, variables, such as model bias, modeled wafer DC voltage, complex power, complex voltage, complex current, complex transfer power, complex supply power, complex reflected power, impedance, gamma, ion Energy, voltage standing wave ratio (VSWR), etc. are calculated by the CPU 158 on the basis of the complex voltage and current at this model node, e.g., at the output of the model 126, and so on.

In some embodiments, the complex power at the model node, e.g., the complex transmit power, etc., is a function of the complex current at the model node and the complex voltage at the model node by the CPU 158, And so on. In various embodiments, the complex power delivered by the RF generator is a difference between the complex power of the RF signal supplied by one of the RF generators 146 by the CPU 158 and the complex power reflected towards the RF generator < RTI ID = 0.0 > . In some embodiments, the complex impedance at the model node is calculated by the CPU 158 as the ratio of the complex voltage at the model node to the complex current at the model node. In various embodiments, the gamma square is calculated by the CPU 158 to be the same as the ratio to the complex power supplied by the RF generator of the complex power reflected towards the RF generator. In some embodiments, the complex voltage or complex current at the model node is extracted, e.g., parsed, from the complex voltage and current at the model node.

In some embodiments, the wafer bias, e.g., model bias, wafer Vdc, etc., is used by the CPU 158 to calculate the value of the equation a2 * V2 where "*" refers to multiplication, "sqrt" refers to the square root, "V2" refers to the 2 MHz RF generator is on and 27 and < RTI ID = 0.0 & Represents the voltage at the output of the model 126 when the 60 MHz RF generators are off, and "I2" represents the voltage at the output of the model 126 when the 2 MHz RF generator is on and the 27 and 60 MHz RF generators are off. P2 "represents the power at the output of the model 126 when the 2 MHz RF generator is on and the 27 and 60 MHz RF generators are off," a2 " Quot; b2 "is a predetermined coefficient, and" c2 "is a predetermined coefficient , And "d2" is a predetermined constant value.

In various embodiments, when 2 MHz and 27 MHz RF generators are used and a 60 MHz RF generator is not used, the wafer bias is calculated by the CPU 158 from the equation a227 * V2 + b227 * I2 + c227 * sqrt (P2) + V27 "is determined using the model 27 MHz when the 27 MHz RF generator is in the on state and the 2 MHz and 60 MHz RF generators are in the off state. " d227 * V27 + e227 * I27 + f227 * sqrt "I27" represents the current at the output of the model 126 when the 27 MHz RF generator is on and the 2 MHz and 60 MHz RF generators are off, , "P27" represents the power at the output of the model 126 when the 27 MHz RF generator is on and the 2 MHz and 60 MHz RF generators are off, and "a227", "b227", "c227 d227 ", "e227 ", and" f227 "are predetermined coefficients and" g (304) "is a predetermined constant value.

In some embodiments, when 2 MHz, 27 MHz, and 60 MHz RF generators are used, the wafer bias is determined by the CPU 158 by the equation a22760 * V2 + b22760 * I2 + c22760 * sqrt (P2) + d22760 * V60 + e22760 * I60 + f22760 * sqrt (P60) + g22760 * V27 + h22760 * I27 + i22760 * sqrt (P27) + j22760 where V60 is the 60 MHz RF generator is on and 2 &Quot; I60 "represents the voltage at the output of the model 126 when the MHz and 27 MHz RF generators are in the off state," I60 " represents the voltage at which the 60 MHz RF generator is on and the 2 MHz and 27 MHz RF generators are off Represents the current at the output of the model 126 and "P60" represents the current at the output of the model 126 when the 60 MHz RF generator is on and the 2 MHz and 27 MHz RF generators are off Quot ;, " a22760 ", "b22760 "," c22760 ", "d22760 "," e22760 ", and "f22760 "," g22760 ", " h22760 & Can deulyimyeo "j22760" is a predetermined constant value.

In some embodiments, the ion energy is determined by the CPU 158 as a function of the wafer bias and the RF voltage used to calculate the wafer bias, e.g., V2, V27, V60, and so on. For example, the CPU 158 determines the ion energy as Ei = (-1/2) Vdc + (1/2) Vpeak, where Ei is the ion energy and Vpeak is the peak voltage, Peak-to-peak voltage, and V2, V27, V60, etc. are used to calculate the wafer bias.

The CPU 158 determines whether a fault has occurred in the plasma system 144 based on one or more of the variables generated at the output of the model 126. [ For example, the CPU 158 determines that a fault has occurred in the plasma system 144 when the change value of the variable exceeds the change threshold. In this example, the CPU 158 determines that a fault has not occurred in the plasma system 144 if the variable value of the variable does not exceed the change threshold. Examples of variable values include variable standard deviation, variable variance, and variable error. As another example, the CPU 158 determines that a fault has occurred in the plasma system 144 when the change value of the variable does not exceed the change threshold. In this example, the CPU 158 determines that no fault has occurred in the plasma system 144 when the variable value of the variable exceeds the change threshold.

As another example, the CPU 158 determines that a fault has occurred in the plasma system 144 when one or more of the changes in the corresponding one or more variables are greater than the one or more corresponding change thresholds. In this example, the CPU 158 determines that a fault has not occurred in the plasma system 144 if one or more of the changes in the corresponding one or more variables are not greater than the one or more corresponding change thresholds. As another example, the CPU 158 may cause a fault in the plasma system 144 if, for example, the one or more changes in the corresponding one or more of the variables are not greater than the one or more corresponding change thresholds . In this example, the CPU 158 determines that a fault has not occurred in the plasma system 144 if one or more of the changes in the corresponding one or more variables are greater than the one or more corresponding change thresholds.

In another example, the CPU 158 determines that a fault has occurred in the plasma system 144 if the variable is less than the threshold. In another example, the CPU 158 determines that a fault has occurred in the plasma system 144 if the variable is not greater than the threshold. As another example, the CPU 158 determines that a fault has occurred in the plasma system 144 if one or more of the variables is greater than one or more corresponding thresholds. In another example, the CPU 158 determines that a fault has occurred in the plasma system 144 if, for example, the one or more variables are not greater than one or more corresponding thresholds.

As another example, the CPU 158 may cause a fault in the plasma system 144 when one or more of the changes in the corresponding one or more variables are greater than the one or more corresponding change thresholds and one or more of the variables is greater than the corresponding one or more thresholds Has occurred. In such instances, the CPU 158 may determine that one or more of the changes in the corresponding one or more variables are not greater than the one or more corresponding change thresholds and that the one or more variables are not greater than the corresponding one or more thresholds. ) Determines that no fault has occurred. As another example, the CPU 158 may determine that one or more of the changes in the corresponding one or more variables are not greater than one or more corresponding change thresholds, and that the one or more variables are greater than the corresponding one or more thresholds It is determined that a fault has occurred. In these instances, the CPU 158 is configured to determine whether the one or more changes in the corresponding one or more variables are greater than the one or more corresponding change thresholds and the one or more variables are not greater than the corresponding one or more thresholds. It is determined that no fault has occurred. As another example, the CPU 158 may determine that the one or more changes in the corresponding one or more variables are greater than the one or more corresponding change thresholds and that the one or more variables are not greater than the corresponding one or more thresholds It is determined that a fault has occurred. In this example, the CPU 158 may determine that one or more of the variations in the corresponding one or more variables are not greater than the one or more corresponding change thresholds, and that the one or more variables are greater than the corresponding one or more thresholds It is determined that no fault has occurred. As another example, the CPU 158 may determine that one or more changes in one or more corresponding variables are not greater than one or more corresponding change thresholds and that one or more of the variables are not greater than the corresponding one or more thresholds, The plasma system 144 determines that a fault has occurred. In this example, the CPU 158 may cause a fault in the plasma system 144 when one or more of the changes in the corresponding one or more variables are greater than the one or more corresponding change thresholds and one or more of the variables is greater than the corresponding one or more thresholds Has not occurred.

In some embodiments, the CPU 158 determines that an event has occurred if a fault occurs during a predetermined period of time, or if the fault is repeated for a predetermined number of times. For example, the CPU 158 determines whether the number of samples of complex transmit power is greater than a threshold for a predetermined period of time. If it is determined that the number of samples of the complex transmission power is greater than the threshold value for a predetermined period, the CPU 158 determines that the event has occurred. On the other hand, if it is determined that the number of samples of the complex transmission power is not greater than the threshold value for the predetermined period, the CPU 158 determines that the event has not occurred. As another example, the CPU 158 determines whether a predetermined number of samples of complex transmit power is greater than a threshold. If it is determined that the predetermined number of samples of the complex transmission power is greater than the threshold, the CPU 158 determines that the event has occurred. On the other hand, if it is determined that the predetermined number of samples of the complex transmission power is not greater than the threshold, the host system 162 determines that the event has not occurred.

In various embodiments, in the above-described instances of determining whether an event has occurred, instead of performing a decision to be greater, a determination that it is not greater than, for example, less than or equal to, Is determined.

In some embodiments, in the examples described above that determine whether an event has occurred, instead of comparing the number of samples of the variable with the threshold, the number of samples of the variable's variance is compared to the variation threshold.

In various embodiments, event generation is used to compensate for the event. For example, if it is determined that an event has occurred when the variable is greater than the threshold, then the variable is controlled to be less than or equal to this threshold. As another example, if it is determined that an event has occurred when the variable is less than the threshold, the variable is controlled to be greater than or equal to this threshold. In another example, if it is determined that an event has occurred when the change value of the variables is less than the change value threshold, the change value is controlled to increase the change value to be greater than or equal to the change value threshold. As another example, if it is determined that an event has occurred when the change value of the variables is greater than the change value threshold, the change value is controlled to decrease the change value such that the change value is less than or equal to the change value threshold

In some embodiments, once it is determined that an event has occurred, the CPU 158 generates an alarm. For example, the CPU 158 displays on the display device of the host system 162 that an event has occurred. Examples of display devices include cathode ray tube (CRT), light emitting diode (LED) display devices, liquid crystal display (LCD) devices, plasma display devices, and the like. In some embodiments, the display device enumerates the amount of time since the occurrence of the event and the type of event, e.g., class, etc. As another example, the CPU 158 generates an audio alarm through an audio playback device, audio speakers, or the like to indicate that an event has occurred. As another example, the CPU 158 sends an alarm to the remote host system via a computer network, e.g., LAN, WAN, etc., to indicate that an event has occurred. The remote host system receives this signal through the computer network to indicate that an event has occurred on the display device of the remote host system.

In various embodiments, the variable is controlled by controlling the amount of power supplied by the RF generator. For example, the CPU 158 identifies the amount of complex power to be supplied by the x MHz RF generator from the memory device of the host system 162 based on the value of the variable and supplies this amount to the x MHz RF generator. The digital signal processor (DSP) of the x MHz RF generator receives this amount and provides this amount to the RF power supply in the x MHz RF generator. The RF power supply generates an RF signal based on this amount of power and transmits the RF signal to the impedance matching network 148 through one of the RF cables 147 connected to the x MHz RF generator. The impedance matching network 148 matches the impedance of the load with the impedance of the source to produce a modified RF signal based on the RF signal received from the RF power supply of the x MHz RF generator. The ESC 152 of the plasma chamber 156 receives the modified RF signal from the impedance matching network 148 and corrects the plasma in the plasma chamber 156 to achieve the variable value.

1C illustrates embodiments of graphs 168 and 170 for illustrating the generation of events based on faults for different states of the RF pulsed signal of the RF generator. Graph 168 plots the signal 121 of the variable for time t, and graph 170 plots the envelope of the amplitude of the RF pulsed signal 123 over time t. In some embodiments, graphs 168 and 170 are plotted over the same period.

The RF pulsed signal 123 has a plurality of alternating successive states, e.g., state S1, state S0, and so on. For the state S1, a fault is generated for the period tS11, a fault is generated for the period tS01 for the state S0 continuing to the state S1, and a fault occurs for the period tS12 in the next state S1 following the state S0 , A fault occurs during the period tS02 in the next state S0 continuous to the state S1.

In some embodiments, the CPU 158 (FIG. 1B) determines whether an event has occurred for each state of the RF pulsed signal. For example, the CPU 158 sums periods tS11 and tS12 for state S1 and determines whether the sum exceeds a predetermined amount of time. If it is determined that the sum exceeds the predetermined amount of time, the CPU 158 determines that the event has occurred. On the other hand, if it is determined that the sum does not exceed the predetermined amount of time, the CPU 158 determines that the event has not occurred. As another example, CPU 158 sums periods tS01 and tS02 for state S0 and determines whether the sum exceeds a predetermined amount of time. If it is determined that the sum exceeds the predetermined amount of time, the CPU 158 determines that the event has occurred. On the other hand, if it is determined that the sum does not exceed the predetermined amount of time, the CPU 158 determines that the event has not occurred.

In various embodiments, the CPU 158 determines whether an event has occurred for a plurality of states of the RF pulsed signal. For example, the CPU 158 sums periods tS11 and tS01 for states S1 and S0 and determines whether the sum exceeds a predetermined amount of time. If it is determined that the sum exceeds the predetermined amount of time, the CPU 158 determines that the event has occurred. On the other hand, if it is determined that the sum does not exceed the predetermined amount of time, the CPU 158 determines that the event has not occurred.

In some embodiments, the predetermined number of times used to determine whether an event has occurred includes a predetermined number of times that a fault has been generated for a state, e.g., S 1 or S 0. For example, if a fault is generated for two consecutive states where both states are S1, the CPU 158 determines that the fault has occurred twice.

In various embodiments, the predetermined number of times used to determine whether an event has occurred includes a predetermined number of times that a fault has been generated for a number of states, e.g., S1 and S0. For example, if a fault is generated for two consecutive states where the first state is S1 and the second state is S0, the CPU 158 determines that the fault has occurred twice.

Figure 2 illustrates embodiments of graphs 202 and 204 illustrating model usage as compared to using an arc detection sensor. In some embodiments, an arc detection sensor is optically coupled to the ESC 152 (FIG. 1B) to detect the occurrence of an arc generation event within the plasma chamber 112 (FIG. 1A). The graph 202 is generated by the CPU 158 (FIG. 1B) when an event or a fault is detected based on the variable measured by the arc detection sensor. The graph 204 is generated by the host system 162 when a fault or event is determined by the CPU 158 based on the model 126 (FIG. 1A).

Each graph 202 and 204 plots a fault signal, e.g., a variable signal, etc., over time. Each of the graphs 202 and 204 plots the fault signal over time according to two different conditions, for example, a tool stress condition and a nominal tool condition. For example, plots 206A and 206B are plotted when a fault is not detected in plasma system 144, for example, when plasma system 144 (FIG. 1B) is in a nominal tool condition. As another example, plots 208A and 208B are plotted when, for example, a fault is detected in the plasma system 144 when the plasma system 144 is under tool stress conditions.

It should be noted that the event or fault is easily detected in the graph 204 relative to the event or fault in the graph 202. For example, the magnitude of the fault signal on the plot 208B at the time of the fault occurrence, e.g., amplitude, etc., is greater than the magnitude of the fault signal on the plot 208A at the fault occurrence. As another example, the peak-to-peak voltage of the fault signal in plot 208B at the fault occurrence is greater than the peak-to-peak voltage of the fault signal in plot 208A at the fault occurrence.

It should also be noted that the peak-to-peak voltage indicative of the event or fault at plot 208B occurs earlier than the peak-to-peak voltage indicative of the event or fault at plot 208A. Using the modeled approach to display events earlier than this saves time in detecting faults or events.

In some embodiments, the arc detection sensor is used in conjunction with the model 126 to affirm or deny the accuracy of the arc detection event. For example, when the arc detection sensor indicates that a plasma arc has occurred, the model 126 is used to affirm or deny whether or not this arc occurrence has occurred. As another example, when the model 126 indicates that an arc occurrence event has occurred, the arc detection sensor is used to affirm or deny the accuracy of the model 126. [

Figure 3 is an example of a graph 302 used to illustrate that an OES meter can not detect a fault if it is used for detection. Graph 302 plots a number of OES signals 304 and 306 generated by the OES meter over time. The OES signal 304 is generated when the plasma is confined within the plasma chamber 112 (FIG. 1A) and there is less disturbance in the plasma than a minimal amount of disturbance. In addition, the OES signal 306 is generated when the plasma is confined within the plasma chamber 112. It should be noted that there is a slight change in the OES signal 306 when a minimal amount of disturbance is detected in the plasma. Further, neither the upper threshold 308 nor the lower threshold 310 are crossed during plasma confinement. Thus, the fault is not detected when the OES meter is used.

FIG. 4 is an example of a graph 402 illustrating the use of model 126 (FIG. 1A) to provide a recognizable indication of a fault or event. The graph 402 plots an RF fault signal, e.g., a signal of a variable, for a time measured in seconds (s). A perceptible indication of the non-confinement of the plasma within the plasma chamber 112 (FIG. 1A) is indicated by the RF fault signal when the RF fault signal is greater than the threshold value 404.

5 is a flow diagram of an embodiment of a method 500 for detecting faults within plasma system 144 (FIG. 1B). The method 500 is executed by the CPU 158 (FIG. 1B). As shown in method 500, at act 502, it is determined whether the magnitude of the gamma at the output of model 126 (Fig. 1A) is less than a gamma magnitude threshold. In some embodiments, if the gamma magnitude is not less than the gamma magnitude threshold, it is determined that no faults have occurred in the plasma system 144. On the other hand, if it is determined that the gamma size is smaller than the gamma size threshold, then operation 504 is performed.

In some embodiments, instead of the gamma magnitude, any other variable at the model node at the output of the model 126 is used in operation 502 to determine whether this variable is less than the threshold.

At operation 504, it is determined whether the minimum of the plurality of magnitudes of the complex transmit power at the model node at the output of the model 126 is greater than the transmit power magnitude threshold. If it is determined that the minimum magnitude of the complex transmission power is not greater than the transmitted power magnitude threshold, it is determined that there is no fault in the plasma system 144. On the other hand, if it is determined that the minimum magnitude of the complex transmission power is greater than the transmission power magnitude threshold, then operation 506 is performed.

In various embodiments, at operation 504, the complex forward power at the model node at the output of the model 126 is used, instead of the complex forward power, to determine whether the complex forward power magnitude is greater than the complex forward power threshold do. In various embodiments, complex supply power and complex forward power are used interchangeably herein.

In some embodiments, at operation 504, instead of the complex transmission power, the complex reflected power at the model node at the output of the model 126 is used to determine whether the complex reflected power magnitude is greater than the complex reflected power threshold do.

In various embodiments, at operation 504, the maximum magnitude of the complex transmit power at the model node at the output of the model 126 is used, instead of the minimum magnitude of the complex transmit power, such that the magnitude is greater than the transmit power magnitude threshold It is determined whether or not it is large.

In some embodiments, at operation 504, instead of the complex transmission power, any other variable at the model node at the output of the model 126 is used to determine whether this variable is greater than the threshold.

At operation 506, it is determined whether the magnitude of the magnitude of the complex transfer power at the model node at the output of the model 126 is less than the magnitude threshold. If it is determined that the magnitude of the magnitude of the complex transmission power is not less than the variation threshold, it is determined that a fault is not present in the plasma system 144. On the other hand, if it is determined that the change value of the magnitude of the complex transmission power is smaller than the change threshold value, an operation 508 is performed.

 In some embodiments, instead of a change in the magnitude of the complex transmit power, a magnitude of the magnitude of the complex power supply at the model node at the output of the model 126 is used in operation 506, Is less than the complex supply power change threshold. In various embodiments, a change in the magnitude of the complex reflected power at the model node at the output of the model 126, instead of the magnitude of the magnitude of the complex transmission power, is used in operation 506, Is less than the complex reflected power change threshold.

In many embodiments, at operation 506, the change value of another variable at the model node at the output of the model 126 is used instead of the change in the magnitude of the complex transmit power, so that the change value of this other variable is greater than the change threshold Whether it is small or not is determined.

It should be noted that operations 502, 504, and 506 are designed as fault-predetermining operations or as event-predetermining operations.

In some embodiments, comparisons between variables and their corresponding thresholds and / or comparisons between the change values of the variables and the corresponding change thresholds are made in three operations 502, 504, and 506 Instead of being performed once, an arbitrary number of times, for example, one time, two times, four times, six times, etc., can be performed. For example, in operations between operations 502 and 504, the complex supply power and the complex supply power threshold can be compared.

At operation 508, it is determined whether the change in magnitude of the complex voltage at the model node at the output of the model 126 is greater than the complex voltage change threshold. If it is determined that the change in the magnitude of the complex voltage is not greater than the complex voltage change threshold, it is determined that a fault is not present in the plasma system 144. On the other hand, if it is determined that the change in magnitude of the complex voltage is greater than the complex voltage change threshold, operation 510 is performed.

In many embodiments, at operation 508, a change in another variable at the model node at the output of the model 126 is used instead of a change in the magnitude of the complex voltage to determine whether the change in such other variable is greater than the threshold Is determined.

At operation 510, it is determined whether the change in magnitude of the complex current at the model node at the output of the model 126 is greater than the complex current change threshold. If it is determined that the change in the magnitude of the complex current is not greater than the complex current change threshold, it is determined that the fault is not present in the plasma system 144. On the other hand, if it is determined that the change in the magnitude of the complex current is greater than the complex current change threshold, operation 512 is performed.

In many embodiments, at operation 510, a change in another variable at the model node at the output of the model 126 is used instead of a change in the magnitude of the complex current to determine whether the change in such other variable is greater than the threshold Is determined.

At operation 512, it is determined whether the change in magnitude of the complex transfer power at the model node at the output of the model 126 is greater than the complex supply power variation threshold. If it is determined that the change in the magnitude of the complex transmission power is not greater than the complex supply power variation threshold, then it is determined that a fault is not present in the plasma system 144. On the other hand, if it is determined that the change in the magnitude of the complex transmission power is greater than the complex supply power variation threshold, operation 514 is performed.

At operation 512, instead of a change in the magnitude of the complex supply power, in many embodiments, a change in the magnitude of another variable at the model node at the output of the model 126, for example, A change in the complex reflected power magnitude, etc. are used so that the magnitude of these other variables determines whether the change is greater than the threshold.

At operation 514, it is determined whether the change in magnitude of the complex impedance at the model node at the output of the model 126 is greater than the complex impedance threshold. If it is determined that the change in the magnitude of the complex impedance is not greater than the complex impedance threshold, it is determined that a fault is not present in the plasma system 144. On the other hand, if it is determined that the change in the magnitude of the complex impedance is greater than the complex impedance threshold, then operation 516 is performed.

In many embodiments, at operation 514, a change in the magnitude of another variable at the model node at the output of the model 126 is used, instead of a change in the magnitude of the complex impedance, Is greater than a threshold value.

At operation 516, it is determined whether the change in model bias at the model node at the output of the model 126 is greater than the bias threshold. If it is determined that the change in the model bias is not greater than the bias threshold, it is determined that a fault is not present in the plasma system 144. On the other hand, if it is determined that the change in the model bias is greater than the bias threshold, then a fault is determined to be present in the plasma system 144.

In many embodiments, at operation 516, a change in another variable at the model node at the output of the model 126 is used, instead of a model bias change, to determine whether the change in this other variable is greater than a threshold do.

In some embodiments, at operation 518, an output of ESC 152, such as an input of ESC 152, for example, optically, electrically, etc., coupled to ESC 152, It is determined whether the change in the measured variable, such as by an OES meter, a voltage sensor, a current sensor, a power sensor, etc., is greater than a threshold. For example, the OES meter senses the optical emission of the plasma within the plasma chamber 156 (FIG. 1B) to produce electrical signals representative of the plasma charge values. If it is determined that the change in the measured variable is not greater than the threshold, it is determined that a fault is not present in the plasma system 144. On the other hand, if it is determined that the change in the measured variable is greater than the threshold, then a fault is determined to be present in the plasma system 144.

In various embodiments, operation 518 is performed by adding one or more of operations 502, 504, 506, 508, 510, 512, 514, and 516 to determine whether a fault is present in plasma system 144 . For example, operation 518 may be used to verify that a fault exists in the plasma system 144.

In some embodiments, operation 518 is optional and is not performed within method 500 to determine if a fault is present in plasma system 144.

In various embodiments, one or more of operations 502, 504, 506, 508, 510, 512, 514, 516, and 518 are performed to determine whether a fault is present in the plasma system 144.

In some embodiments, one or more of operations 502, 504, 506, 508, 510, 512, 514, 516, and 518 may be performed by CPU 158 to determine if a fault is present in plasma system 144 It is repeated over a predetermined number of times. Over the number of times that one or more of operations 502, 504, 506, 508, 510, 512, 514, 516, and 518 are repeated by CPU 158, CPU 158 determines that a fault is present in plasma system 144, It is determined by the CPU 158 that an event has occurred in the plasma system 144. On the other hand, over the number of times that one or more of the operations 502, 504, 506, 508, 510, 512, 514, 516, and 518 are repeated by the CPU 158, a fault is not present in the plasma system 144, Is determined by the CPU 158 that the event has not occurred in the plasma system 144,

In some embodiments, one or more of operations 502, 504, 506, 508, 510, 512, 514, 516, and 518 may be performed by a CPU (not shown) to determine whether an event has occurred in the plasma system 144. [ 158 over a predetermined period of time. Over a predetermined period of time during which one or more of operations 502, 504, 506, 508, 510, 512, 514, 516, and 518 are iteratively performed by the CPU 158 that a fault is present in the plasma system 144 Once determined, the CPU 158 determines that an event has occurred in the plasma system 144. On the other hand, over a predetermined period of time during which one or more of operations 502, 504, 506, 508, 510, 512, 514, 516, and 518 are iteratively performed, a fault is not present in the plasma system 144, , It is determined by the CPU 158 that an event did not occur in the plasma system 144.

It should be noted that one or more of operations 508, 510, 512, 514, 516, and 518 are designed as fault decision operations or event decision operations.

In some embodiments, fault-pre-determination operations occur during plasma strike, and fault determination operations are performed after the plasma is struck and generated, for example, when the plasma is in a steady state. In some embodiments, fault-pre-determination operations occur during striking and also during transition of a period from plasma strike to plasma to steady state, and fault determination operations are performed when the plasma is in a steady state do. In various embodiments, fault-pre-determination operations may occur during a period immediately prior to a transition from a first state, e.g., S1, S0, etc., to a second state, e.g., a normal state of S0, S1, State, and event determination operations occur during the steady state. The second state sequentially follows the first state. An example of a period immediately prior to the transition includes a time window in which a change in the power level of the RF signal generated by one of the RF generators 116 (FIG. 1A) occurs. This power level change occurs to change the state of the RF signal from state S1 to state S0 or from state S0 to state S1. Another example of a period immediately prior to a transition includes a state S1 or a portion of state S0.

In some embodiments, the threshold window for a period immediately prior to the transition from the first state to the second state is modified by the CPU 158 to be different from the threshold window during this transition. For example, the threshold value of the variable during this transition is changed by the CPU 158 to be greater than the threshold value of the variable for the immediately preceding period. There is a change in the state of the RF signal that occurs during this transition. This threshold window modification can cause a state change to occur without triggering a false alarm of the fault.

In various embodiments, fault-pre-determination operations are performed to determine whether a fault is present in the plasma system 144. [ In these embodiments, fault determination operations are not performed. For example, the plasma dropout fault is determined based on fault-pre-determination operations without performing fault determination operations. As another example, a plasma instability fault is determined based on fault-pre-determination operations without performing fault determination operations.

In some embodiments, instead of performing the comparison operations in six operations 508, 510, 512, 514, 516, and 518, any number of comparison operations, e.g., one, two, four, Five, seven, ten, etc. comparison operations are performed. For example, a comparison between ion energy and ion energy thresholds is performed in operations between operations 510 and 512.

In some embodiments, the operations of method 500 are performed in a different order than the order shown in FIG. For example, operation 512 may be performed before operation 510 or concurrently with operation 510. As another example, operation 514 may be performed after operation 516 or at the same time.

It is noted that in some embodiments, the method 500 is repeated by the CPU 158 for different states of the pulsed signal of the RF generator. For example, operations 502, 504, 506, 508, 510, 512, 514, 516, and 518 are performed for the state S0 of the signal pulsed by the CPU 158 and for signals pulsed by the CPU 158 Is repeated for the state S1 of FIG.

In various embodiments, different thresholds are used for each state of the pulsed signal of the RF generator. For example, the threshold value of the variable is used for state S1 of the RF pulsed signal at operation 508 and a different threshold value is used for state S0 of the RF pulsed signal at operation 508. [ As another example, a change threshold value is used for state S0 of the RF pulsed signal at operation 508 and a different change value threshold value is used for state S1 of the RF pulsed signal at operation 508. [

In some embodiments, a change value threshold of a value that is different from the value of the change value threshold for the variable used during one of the event-predetermining operations is used for the variable used during one of the event determination operations . For example, the threshold power change used during operation 512 is different from the threshold power change used during operation 506. In various embodiments, a threshold of a value that is different from the value of the threshold for the variable used during one of the event-predetermining operations is used for the variable used during the operation of one of the event-determining operations.

It is further noted that, in various embodiments, the method 500 is repeated for the same state of the continuous wave RF signal generated by the RF generator by the CPU 158. For example, operations 502, 504, 506, 508, 510, 512, 514, 516, and 518 are performed by the CPU 158 on the state S0 of the continuous wave RF signal, The state S0 of the continuous wave RF signal is repeated. As another example, operations 502, 504, 506, 508, 510, 512, 514, 516, and 518 are performed by the CPU 158 on the state S1 of the continuous wave RF signal and thereafter by the CPU 158 Is repeated for the state S1 of the continuous wave RF signal.

In some embodiments, the presence of a fault during state S1 is determined by CPU 158 independent of the presence of a fault during state S0. For example, when determined by the CPU 158 that a fault exists based on the use of a threshold and / or a change threshold associated with a variable during state S 1 of the RF signal, an addition associated with a variable during state S 0 of the RF signal May be determined by the CPU 158 that there is no fault based on the use of the threshold and / or further change threshold. As another example, when determined by the CPU 158 that a fault exists based on the use of a threshold and / or a change threshold associated with a variable during state S0 of the RF signal, an addition associated with the variable during state S1 of the RF signal May be determined by the CPU 158 that there is no fault based on the use of the threshold and / or further change threshold.

 In various embodiments, a fault exists in the plasma system 144, when a fault is determined during both states S1 and S0 of the RF pulsed signal using method 500. In some embodiments, a fault is not present in the plasma system 144, when a fault is determined during both states S1 and S0 of the RF pulsed signal using method 500.

In various embodiments, the value of the variable does not satisfy the threshold when the value is greater than the threshold, and it is predetermined by the CPU 158 (FIG. 1B) that the value is equal to or less than the threshold. In some embodiments, the value of the variable does not satisfy the threshold when the value is less than the threshold, and it is predetermined by the CPU 158 (FIG. 1B) that the value is equal to or greater than the threshold.

6 illustrates changes in one or more thresholds and / or one or more change thresholds based on the state of the RF signal, changes in operation at one of the RF generators 146 (FIG. 1B) Lt; RTI ID = 0.0 > 600 < / RTI > The method 600 is executed by the CPU 158 (FIG. 1B). Method 600 is performed during execution of method 500 (FIG. 5).

In operation 602 of method 600, the CPU 158 determines whether the RF signals generated by the RF generators 146 are transitioning from state S1 to state S0, or from state S0 to state S1, or from states S0 to states S0 and S1 To a transition state, or to a transition state between states S1 and S0 from state S1. For example, the CPU 158 may determine from the memory device of the host system 162 (FIG. 1B) that the power level setting of the RF signal generated by one of the RF generators 146 corresponds to a power level It is determined from the setting items that the power level setting item corresponding to the state S1 has been changed to determine that there is a state change of the RF signal from the state S0 to the state S1. As another example, the CPU 158 may determine from the memory device of the host system 162 (FIG. 1B) that the power level setting is increasing at a predetermined rate from the power level for the state SO, ≪ / RTI > changes from the state SO to the transition state. In another example, the CPU 158 may determine from the memory device of the host system 162 (FIG. 1B) that the power level setting is decreasing from the power level for state S1 to a predetermined rate, 146 < / RTI > changes from state S1 to a transition state.

Note that in some embodiments, the power level settings for each state S1, S0, etc. are received by the CPU 158 from the user via the input device of the host system 162. [ Examples of input devices of the host system 162 are the same as those of the input device of the host system 120 (FIG. 1A).

The determination of the state transition is made during execution of the method 500. 5), or operation 504, or operation 506, or operation 508, or operation 510, or operation 512, or operation 502 Operation 514, or operation 516, or operation 518, or between performances of operations 502 and 504 or between performances of operations 504 and 506 or between performances of operations 506 and 508, or between performances of operations 508 and 510 To determine whether a transition occurs between the performance of operations 510 and 512 or between the performance of operations 512 and 514 or between the performance of operations 514 and 516 or between the performance of operations 516 and 518 between states S1 and S0.

If at operation 604 it is determined that the state of the RF signals from operation 602 is to be changed, then the CPU 158 receives from the memory device of the host system 120 (Figure 1A) a changed state, e.g., state S1, state S0, States, and the like of one or more thresholds and / or one or more thresholds of changes. For example, if it is determined that the state of the RF signals has changed during operation 502, the CPU 158 may determine a gamma size threshold to use during operation 502 from the memory device of the host system 162, a transmission power threshold to use during operation 504, The current change value threshold to use during operation 510, the power change value threshold to use during operation 512, the impedance change value threshold to use during operation 514, the wafer bias change threshold to use during operation 516, Read the change threshold to be used.

At operation 606 of method 600, method 500 is repeated by CPU 158 using one or more thresholds and / or one or more thresholds of values accessed in operation 604. For example, operation 502 is repeated using the gamma magnitude threshold accessed in operation 604, operation 504 is repeated using the transmitted power threshold accessed in operation 604, and operation 506 is repeated using the power change value threshold accessed in operation 604 Operation 508 is repeated using the voltage change value threshold accessed in operation 604 and operation 510 is repeated using the current change value threshold accessed in operation 604 and operation 512 is repeated using the power change value threshold accessed in operation 604. [ Operation 514 is repeated using the impedance change threshold value accessed in operation 604 and operation 516 is repeated using the wafer bias change threshold value accessed in operation 604 and operation 518 is repeated using the change value < RTI ID = 0.0 > It is repeated using the threshold value.

In another operation 608 of method 600, the CPU 158 determines if the operation of one or more of the RF generators 116 has changed. For example, from the memory device of the host system 162, it is identified whether one of the RF generators 146 is turned off or turned on. It should be noted that, in some embodiments, when the RF generator is turned off, the RF generator does not supply the RF signal and the RF generator supplies the RF signal when the RF generator is turned on.

Operation 608 is performed during execution of method 500. For example, operation 608 may be performed during execution of any of operations 502, 504, 506, 508, 510, 512, 514, 516 and 518, or during operations of method 500, operations 502, 504, 506, 508, 510, 512, 514, 516, and 518. In this embodiment,

If it is determined that the operation of one or more of the RF generators 116 has changed, then at operation 610, the CPU 158 accesses one or more thresholds and / or one or more thresholds of change values for the changed operation. Operation 610 differs from operation 604 in that one or more thresholds accessed in operation 610 are mapped into one or more changed operations of the RF generators 116 in the memory device of the host system 162. For example, there is a virtual link between the threshold and the operation of one of the RF generators 146, e.g., a turn-on operation, a turn-off operation, etc., in the memory device of the host system 162, Is stored in the memory device of the system 162.

Also, operation 612 of method 600 is similar to operation 608, except that during operation 612, method 500 is repeated by CPU 158 using one or more thresholds accessed during operation 610 and / or one or more change thresholds It is different. During operation 612, instead of using thresholds for one or more operational states of the RF generators 146 prior to the change in one or more of the RF generators 146, one or more thresholds for the changed operation may be used, 500 < / RTI >

At operation 614 of method 600, the CPU 158 receives a change in the sub-states of the RF signal generated by one of the RF generators 146, e.g., S01, S02, S03, S11, S12, S13, Or not. For example, the CPU 158 may identify, from the memory device of the host system 162, the power level setting of the RF signal generated by one of the RF generators 146 so that the change in the sub- Or not. As another example, the CPU 158 determines whether the sub-status changes from the first sub-status to a second sub-status that follows this first sub-status in succession. For example, the CPU 158 determines whether the sub-state changes from the sub-state S01 to the sub-state S02. As another example, the CPU 158 determines whether the sub-status changes from S12 to S13. Operation 614 is performed during execution of method 500.

Examples of sub-states are provided in FIG. FIG. 7 shows an embodiment of graph 702 and another embodiment of graph 704. Graph 702 plots the clock signal with respect to time t. The clock signal is generated by a clock source of the host system 162 (FIG. 1B), e.g., an oscillator, an oscillator with a phase locked loop, and is provided to one or more of the RF generators 146 Thereby synchronizing the generation of one or more RF signals generated by the corresponding one or more of the RF generators 146. In some embodiments, the clock signal is generated by a master RF generator, e. G., An x MHz RF generator, to provide it to y and z MHz RF generators to generate by x, y, and z MHz RF generators Lt; RTI ID = 0.0 > RF < / RTI > Graph 794 also plots the RF signal generated by one of the RF generators 146 for time t.

As shown, during state S0 of the clock signal 702, the power level of the RF signal 704 is determined by one of the RF generators 146 that generated the RF signal 704, from the state S01 to the state S02 And is further changed from being associated with state S02 to being associated with state S03. Similarly, during state S1 of the clock signal 702, the power level of the RF signal 704 is reduced by one of the RF generators 146 that generated the RF signal 704 from the sub- State S12 and is further changed from being associated with sub-state S12 to being associated with sub-state S13.

The power level associated with the first sub-state, e.g., sub-state S02, etc., that follows the second sub-state, e. G., Sub-state S01, is different from the power level associated with the second sub- , For example, it does not include it. In some embodiments, the power level associated with sub-state S03 is equal to the power level associated with sub-state S01.

From operation 614, if it is determined that there is a change in the sub-status of the RF signal generated by one of the RF generators 146, then at operation 616, the CPU 158 determines one or more thresholds for this changed sub- / RTI > and / or one or more change thresholds from the memory device of host system 162. < RTI ID = 0.0 > Operation 616 is similar to operation 604, except that during operation 616, one or more thresholds mapped to the changed sub-state and / or one or more change thresholds are accessed from the memory device of the host system 162.

At operation 618 of method 600, CPU 158 repeats method 500 using one or more thresholds and / or one or more change thresholds accessed during operation 616. For example, using thresholds for one or more of the RF generators 162 prior to the change in the sub-state of the RF signal generated by one of the RF generators 162, One or more thresholds for the state are used to implement the method 500. Operation 618 is similar to operation 608 except that one or more thresholds and / or one or more change thresholds accessed during operation 614 are used to perform operation 618.

Although the embodiments described above refer to providing an RF signal to the lower electrode of the chuck 136 (FIG. 1A) and grounding the upper electrode 134 (FIG. 1A), in some embodiments, 134 and the lower electrode of the chuck 136 is grounded. In some embodiments, faults and potential faults are used interchangeably herein.

The embodiments described herein may be practiced using various computer system configurations, including but not limited to hand-held hardware units, microprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, Frame computers, and the like. The embodiments described herein may also be practiced in distributed computing environments where tasks are performed by remotely processing linked hardware units through a computer network.

In some embodiments, the controller is part of a system, which may be part of the above-described instances. The system includes semiconductor processing equipment including processing tools and tools, chambers or chambers, platforms or platforms for processing and / or specific processing components (e.g., wafer pedestal, gas flow system, etc.). The system is integrated with electronic devices for controlling its operation before, during, or after the processing of the semiconductor wafer or substrate. These electronic devices may be referred to as "controllers" that can control various components or sub-components of the system. The controller is programmed to control any of the processes described herein in accordance with processing requirements and / or system type, and such processes may include, but are not limited to, transfer of process gases, temperature setting (e.g., heating and / , Vacuum setting, power setting, RF generator setting, RF matching circuit setting, frequency setting, flow rate setting, emulsion delivery setting, position and operation setting, and tools and other delivery tools connected to the system and / Wafer transfer into and out of locks, and the like.

In general, in various embodiments, the controller is defined as electronic devices having various integrated circuits, logic, memory, and / or software, which receive instructions, issue instructions, control operations, And enables endpoint measurement. The integrated circuit includes chips, DSPs, chips defined as ASICs, PLDs, one or more microprocessors executing program instructions (e.g., software), or microcontrollers in firmware form for storing program instructions do. The program instructions are instructions that are transmitted to the controller in the form of various individual settings (or program files) that specify operating parameters for executing the process on or on the semiconductor wafer. The operating parameters may be used in some embodiments to achieve one or more processing steps during fabrication of one or more layers, materials, metals, oxides, silicon, silicon dioxide, surfaces, circuits and / It is part of the recipe specified by the process engineers.

The controller is, in some embodiments, coupled to or coupled to a computer that is integrated into the system, coupled to the system, or otherwise networked to the system, or a combination thereof. For example, the controller may be within the " cloud "or some or all of the fab host computer system, which enables remote access for wafer processing. The controller enables remote access to the system to monitor the current progress of manufacturing operations, inspects the history of post-production operations, examines trends or performance measurements from a plurality of manufacturing operations, To change the parameters, to set the processing steps to follow the current processing, and to start the new process.

In some embodiments, a remote computer (e.g., a server) provides process recipes to a system via a computer network, which includes a local network or the Internet. The remote computer includes user interfaces, which enable input or programming of parameters and / or settings, which are then transmitted from the remote computer to the system. In some instances, the controller receives instructions in the form of settings to process wafers. It should be understood that the settings are specific to the type of process to be performed on the wafer and the type of tool that the controller interfaces or controls. Thus, as described above, the controller is distributed by operating for a common purpose, for example, including one or more individual controllers networked together and completing the processes described herein, for example. Examples of decentralized controllers for this purpose include one or more integrated on a chamber communicating integrated circuits located in one or more remotely (e.g., on a platform label or as part of a remote computer) coupled together to control the process within the chamber Circuits.

For example, in various embodiments, the system includes a plasma etch chamber, a deposition chamber, a spin-rinse chamber, a metal plating chamber, a cleaning chamber, a bevel edge etch chamber, a physical vapor deposition (PVD) chamber, a chemical vapor deposition (CVD) A chamber, an atomic layer deposition (ALD) chamber, an atomic layer etch (ALE) chamber, an ion implantation chamber, a tracking chamber, and any other semiconductor processing chamber used or associated with processing and / or manufacturing semiconductor wafers.

Although the above-described operations have been described with reference to a parallel plate plasma chamber, for example, a capacitively coupled plasma chamber, etc., in some embodiments, the above-described operations may be performed using other types of plasma chambers, It is also noted that the present invention is also applicable to plasma chambers including plasma (ICP) reactors, transformer coupled plasma (TCP) reactors, conductor tools, plasma chambers including dielectric tools, electron cyclotron resonance (ECR) do. For example, an x MHz RF generator, a y MHz RF generator, and a z MHz RF generator are coupled to an inductor in the ICP plasma chamber.

As discussed above, depending on the process operations to be performed by the tool, the controller may be located across other tool circuits or modules, other tool components, cluster tools, other tool interfaces, adjacent tools, neighboring tools, Tools, main computer, other controller, or semiconductor fabrication factory with tools used to transfer the containers of wafers to and / or from tool positions and / or load ports.

With the above embodiments in mind, it should be understood that some embodiments employ various computer-implemented operations involving data stored in computer systems. These computer-implemented operations are those that manipulate physical quantities.

Some embodiments also relate to a hardware unit or device for performing these operations. Such a device is specifically configured for a particular purpose computer. When defined as a special purpose computer, the computer may perform other processing, program executions or routines that are capable of operating for this particular purpose, but which are not part of a particular purpose.

In some embodiments, the operations described above may be performed by a selectively activated computer, by one or more computer programs stored in a computer memory, or through a computer network. In the case where data is obtained through a computer network, the data may be processed by a computer network, for example, other computers on the cloud of computing resources.

One or more embodiments described herein may also be processed as computer-readable code on non-volatile computer-readable media. The non-volatile computer-readable medium is any data storage hardware unit, such as a memory device, that stores data that is thereafter read by a computer system. Examples of non-transitory computer-readable media include, but are not limited to, hard drives, network attached storage, ROM, RAM, compact disc-ROMs, CD- rewritables (CD-RWs), magnetic tapes, and other optical and non-optical data storage hardware units. In some embodiments, non-transitory computer-readable media includes a computer-readable type of medium distributed via a computer-coupled computer system in which computer readable code is stored and executed in a distributed manner.

Although some of the method operations described above are provided in a particular order, in various embodiments, other housekeeping operations may be performed between method operations, or method operations may be adjusted to occur at slightly different times, It should be understood that the method operations are distributed in the system to occur at intervals, or are performed in a different order than described above.

It should also be understood that, in one embodiment, one or more of the features from any of the embodiments described above may be embodied in one or more of any other embodiments without departing from the scope of the various embodiments described herein It can be combined with features.

While the foregoing embodiments have been described in some detail for purposes of clarity of understanding, it will be apparent that certain changes and modifications may be practiced within the scope of the appended claims. Accordingly, the embodiments should be construed as illustrative and not restrictive, and the embodiments should not be limited to the details given herein, but instead may be modified within the scope and equivalence of the appended claims.

Claims (28)

Accessing a model of one or more portions of a plasma system, said plasma system comprising a plasma chamber, a radio frequency (RF) generator and a transmission line between the plasma chamber and the RF generator;
Receiving data relating to the supply of RF power to the plasma chamber, wherein the RF power is supplied to the plasma chamber through the transmission line using a configuration comprising one or more states, The method comprising: receiving the data, wherein the data is repeated successively during the supply of RF power to the plasma chamber;
Using the data to generate model data at an output of the model during the supply of RF power to the plasma chamber, the model data comprising at least one of: using the data associated with one of the one or more states ;
Examining the model data during the one of the one or more states, the method comprising: examining one or more variables that characterize the performance of a plasma process of the plasma system; step;
Identifying a potential fault for the one or more variables during the one of the one or more states;
Determining that the potential fault occurred during the one of the one or more states over a predetermined period of time such that the potential fault is identified as an event; And
And classifying the event. The method according to claim 1,
Wherein the model comprises a model of the transmission line. The method according to claim 1,
Wherein the step of examining the model data comprises determining whether the one or more variables satisfy one or more variable thresholds corresponding thereto and whether one or more variations of the one or more variables satisfy one or more variation thresholds corresponding thereto And determining whether or not the < RTI ID = 0.0 >
Wherein identifying the potential fault comprises:
Determining that the one or more variables do not satisfy one or more corresponding variable thresholds; And
Determining that one or more variations of the one or more variables do not satisfy the one or more change value thresholds corresponding thereto. The method according to claim 1,
Wherein examining the model data comprises determining whether one or more variations of the one or more variables satisfy one or more variation thresholds corresponding thereto,
Determining that one or more variations of the one or more variables do not satisfy the one or more change value thresholds corresponding thereto. The method according to claim 1,
Wherein illuminating the model data during the one of the one or more states comprises examining the model data during a first state and a second state,
Wherein the step of examining the model data during the first state and the second state comprises:
Determining, during the first state, whether the one or more variables satisfy a first set of one or more corresponding variable thresholds and whether one or more variations of the one or more variables correspond to a first set of one or more change thresholds Determining if the set satisfies one set; And
Determining, during the second state, whether the one or more variables satisfy a second set of one or more corresponding variable thresholds and whether one or more variations of the one or more variables correspond to one or more variation thresholds 2 < / RTI > The method according to claim 1,
Wherein the at least one portion of the plasma system is coupled to an RF cable or impedance matching circuit or a combination of the transmission line or the lower electrode of the plasma chamber or the RF cable and the impedance matching circuit or the RF cable and the impedance matching circuit A combination of the transmission lines or a combination of the RF cable and the impedance matching circuit and the transmission line and the lower electrode,
The RF cable couples the RF generator to the impedance matching circuit,
Wherein the transmission line couples the impedance matching circuit to the plasma chamber. The method according to claim 1,
Wherein receiving the data for the supply of RF power comprises receiving a complex voltage and current measured by a sensor coupled to an output of the RF generator. The method according to claim 1,
Wherein the configuration comprises a pulsed configuration synchronous with a clock signal provided by the clock generator to the RF generator. The method according to claim 1,
Wherein the one or more states are successively repeated when an instance of the first state precedes an instance of the second state and an instance of the second state precedes an instance of the first state. 10. The method of claim 9,
Wherein the power level of the RF signal having the RF power during the first state excludes a power level of the RF signal during the second state,
Each power level comprising a plurality of power magnitudes. The method according to claim 1,
The configuration comprising a pulsed configuration, wherein the one or more states comprise a first state and a second state,
The method comprises:
Determining if the pulsed configuration is in the first state or the second state; And
Changing a threshold associated with one of the variables if the pulsed configuration is determined to be in the first state, wherein the threshold corresponds to the first state after the change and to the second state prior to the change And changing the corresponding threshold value. The method according to claim 1,
Wherein the step of generating the model data using the data includes generating the model data by propagating the received data through the model,
Wherein the programming computes a product between the received data and a variable of a component of the plasma system or computes a sum between the received data and the variable of the component of the plasma system or computing both the enemy and the sum. The method according to claim 1,
Further comprising determining the one or more variables from the model data,
Wherein determining the one or more variables comprises:
Extracting the one or more variables from the model data; And
Computing a ratio or product between one of the variables and the other of the variables. The method according to claim 1,
Wherein classifying the event comprises determining if the event is an arcing event or a plasma unconfinement event or a plasma drop-out event or a plasma instability event. The method according to claim 1,
Wherein the one or more states comprise a first state and a second state,
The method comprises:
The method of claim 1, further comprising: after the step of examining, the step of identifying, the step of determining and the step of classifying for the first state, the step of examining, the step of identifying, And performing the classifying step. The method according to claim 1,
Further comprising classifying the potential fault based on a magnitude of one of the variables or a direction of a change in the magnitude or a rate at which at least two of the variables or the magnitude changes or a combination thereof . The method according to claim 1,
The configuration includes a pulsed configuration,
Wherein identifying the potential fault includes identifying the potential fault during a pre-event determination state of the pulsed configuration,
Wherein the event-prone state is performed to strike a plasma in the plasma chamber. The method according to claim 1,
Wherein identifying the potential fault comprises identifying the potential fault during an event determination state associated with a steady-state plasma generated in the plasma chamber. The method according to claim 1,
The configuration includes a pulsed configuration,
The method further comprises modifying a value of a threshold associated with one of the variables based on a change in the pulsed configuration from an event-pre-determined state to an event-determined state,
Wherein the plasma is struck in the plasma chamber during the event-preseason state and the plasma is in a steady state during the event determination state. The method according to claim 1,
Wherein the at least one state includes a first state and a second state,
Wherein the first state or the second state is determined from a power level setting of the RF generator. The method according to claim 1,
The configuration includes a pulsed configuration,
Wherein the at least one state includes a first state and a second state,
The method further comprises modifying a value of a threshold associated with one of the variables based on a change in the pulsed configuration from the first state or the second state to a transition state,
Wherein the plasma is struck in the plasma chamber during the first state,
Wherein the pulsed configuration changes from the first state to the second state or from the second state to the first state during the transition state. The method comprising: receiving data associated with a supply of radio frequency (RF) power, the data being received from a sensor;
Propagating data through the computer-generated model to determine model data at an output of a computer-generated model of one or more portions of the plasma system, the plasma system comprising an RF generator, an RF An impedance matching circuit coupled to the RF generator through a cable, and a plasma chamber coupled to the impedance matching circuit through an RF transmission line;
Generating values associated with one or more variables from the model data;
Determining whether values associated with the one or more variables satisfy one or more thresholds corresponding thereto;
Generating a fault if it is determined that the values associated with the one or more variables do not satisfy the one or more corresponding thresholds;
Determining whether the fault occurs during a predetermined period of time;
Generating an event if the fault is determined to occur during a predetermined period of time; And
And classifying the event. 23. The method of claim 22,
Wherein determining if the values associated with the one or more variables satisfy one or more thresholds corresponding thereto,
Determining whether one of the values satisfies one of the thresholds; And
Determining whether a remaining one of the values of one of the variables satisfies the other of the thresholds,
And the other one of the thresholds comprises a change threshold. 23. The method of claim 22,
Wherein determining if the values associated with the one or more variables satisfy one or more thresholds corresponding thereto,
Determining whether the values of the variables of the variables satisfy the one or more change thresholds corresponding thereto. 23. The method of claim 22,
Wherein classifying the event based on the one or more thresholds comprises determining whether the event is an arcing event or an unspecified event or a dropout event or a plasma instability event. A plasma system comprising:
CLAIMS 1. A radio frequency (RF) generator for generating and supplying an RF signal at an output, the RF signal being supplied using a configuration comprising one or more states, the one or more states being continuously repeated during the supply of the RF signal The radio frequency generator;
An impedance matching circuit coupled to the RF generator for receiving the RF signal from the RF generator to generate a modified RF signal;
An RF transmission line coupled to the impedance matching circuit for delivering the modified RF signal;
A plasma chamber connected to the RF transmission line for receiving the modified RF signal through the RF transmission line to generate plasma;
A sensor coupled to an output of the RF generator; And
A host system coupled to the sensor,
The host system comprising a processor,
The processor comprising:
Accessing a model of a portion of the plasma system;
Receiving data relating to the supply of the RF signal from the sensor;
Using the data to produce model data at an output of the model during the supply of the RF signal, the model data being associated with a state of one of the one or more states;
Examining the model data during the one of the one or more states, the method comprising: examining one or more parameters characterizing the performance of a plasma process in the plasma chamber; action;
Identifying a potential fault for the one or more variables during the one of the one or more states;
Determining that said potential fault occurred during said one of said one or more states over a predetermined period of time such that said potential fault is identified as an event; And
And perform an operation of classifying the event. 27. The method of claim 26,
To examine the model data, the processor determines whether the one or more variables satisfy one or more corresponding variable thresholds and whether one or more variations of the one or more variables correspond to one or more change thresholds corresponding thereto And if so,
The processor determines that the one or more variables do not satisfy the one or more variable thresholds corresponding thereto, and the one or more variations of the one or more variables correspond to one or more change thresholds Are not satisfied. ≪ / RTI > 27. The method of claim 26,
Wherein the processor is configured to classify the potential fault based on a magnitude of one of the variables or a direction of a change in the magnitude or a combination of at least two of the variables or a rate at which the magnitude changes, system.

Images