KR20140077866A - Computation of statistics for statistical data decimation - Google Patents

Abstract

Described are systems and methods for statistical data decimation. The method includes the steps of: receiving a variable from an RF system; propagating the variable through a model of the RF system; and counting the output of the model for the variable to generate a count. The method further includes the steps of: determining whether the count satisfies a count threshold value; generating the statistical value of the variable in the output of the model when the count satisfies the count threshold value; and transmitting the statistical value to the RF system to control the variable.

Description

[0001] COMPUTATION OF STATISTICS FOR STATISTICAL DATA DECIMATION [0002]

Embodiments of the present invention are directed to performing statistical data determination and use of statistical values in a plasma system.

In a plasma system, a radio frequency (RF) signal is generated by a generator. The signal is delivered to the plasma reactor to produce a plasma in the plasma reactor. Plasma generated in a plasma reactor is used for a variety of applications, such as wafer cleaning, depositing materials on a wafer, etching a wafer, and the like.

It is desirable to control the properties of the plasma to control the applications. For example, it is desirable to control the plasma uniformity to achieve an etch rate. As another example, it is desirable to control the power of the plasma to achieve the deposition rate.

To control the property, the property is measured using a sensor in the plasma system.

In this context, the embodiments described in the present invention appear.

Embodiments of the present invention provide apparatus, methods and computer programs for generating statistical values to reduce the amount of data associated with a model in a plasma system. It should be appreciated that embodiments of the present invention may be implemented in a number of ways, for example, in a process, apparatus, system, device, or computer-readable medium. Several embodiments are described below.

In some embodiments, the statistics are used to control the plasma chamber or to generate an RF signal. For example, instead of analyzing all values of a variable in the output of a computer-generated model to control the plasma chamber, a statistical value is generated from those values and determines whether the statistical value is within a pre-determined range . When determining that the statistical value is within a pre-determined range, the plasma chamber is not controlled, e.g., the RF signal supplied to the plasma chamber is not changed, and so on. On the other hand, when it is determined that the statistical value is not outside the pre-determined range, the plasma chamber is not controlled using the statistic value, for example, the RF signal supplied to the plasma chamber is generated based on the statistical value, And so on.

In various embodiments, the method includes receiving a variable from a radio frequency (RF) system, propagating the variable via a model of the RF system, and counting the output of the model for the variable to generate a count . The method includes the steps of determining whether the count meets a count threshold, generating a statistical value of the variable at the output of the model in determining whether the count meets the count threshold, And transmitting the data.

In various embodiments, the method includes receiving data associated with a variable from a radio frequency (RF) generator. The RF generator is configured to generate an RF signal to be supplied to the plasma chamber through an impedance matching circuit. The variable is associated with an RF generator, an impedance matching circuit, and an RF system including a plasma chamber. The method includes generating values in an output of the computer-generated model based on received data, counting an amount of values output from the computer-generated model, determining if the amount exceeds a count threshold, Generating statistical values from data output and generated from the computer-generated model in response to determining that the count threshold is exceeded, and transmitting statistical values to the RF generator to adjust the RF signal generated by the RF generator .

In some embodiments, the method includes receiving data associated with a variable from a radio frequency (RF) generator. The RF generator is used to generate an RF signal to be supplied to the plasma chamber through an impedance matching circuit. The variable is associated with an RF generator, an impedance matching circuit, and an RF system including a plasma chamber. The method includes generating values in an output of the computer-generated model based on received data, counting an amount of values output from the computer-generated model, determining if the amount exceeds a count threshold, Generating a statistic value from the values output from the computer-generated model in response to determining that the statistical value exceeds the count threshold; determining if the statistical value is outside a pre-determined range; Adjusting the statistical values to be within a mill-determined range in response to determining that the RF signal is outside the predetermined range, and transmitting the adjusted statistical value to the RF generator to control the RF generator to adjust the RF signal generated by the RF generator .

In many embodiments, a method includes receiving data associated with a variable from a radio frequency (RF) generator. The RF is used to generate an RF signal to be supplied to the plasma chamber through an impedance matching circuit. The variables are associated with an RF generator, an impedance matching circuit, and an RF system including a plasma chamber. The method includes generating values in an output of the computer-generated model based on received data, counting an amount of values output from the computer-generated model, determining if the amount exceeds a count threshold, and Generating a statistic value from the values output from the computer-generated model in response to determining that the amount exceeds the count threshold. The method includes the steps of determining whether the statistical value is outside a pre-determined range, generating an indication of a fault in response to determining that the statistical value is outside a pre-determined range, .

Some advantages of the one or more embodiments described in the present invention include the use of statistical values in place of all values of a variable at the output of a computer-generated model to control the plasma chamber. For example, instead of determining whether values are within a pre-determined range, it is determined whether the statistical value is within a pre-determined range. When determining that the statistical value is within a pre-determined range, no change is made to further control the plasma chamber. On the other hand, when it is determined that the statistical value is outside the pre-determined range, a change is made to the statistical value to control the plasma chamber to achieve the changed statistical value.

The use of statistical values instead of all values in the output of a computer-generated model saves processing costs associated with processing values. For example, instead of using multiple servers, e.g., a server farm, etc., to process the values to generate statistics and control the plasma chamber based on those values, E.g., one, two, etc., are sufficient to generate a statistical value and control the plasma chamber based on the statistical value.

Other advantages of the one or more embodiments described in the present invention include decimating the received data after generating the statistical values of the variables. The decimation of the data creates vacated locations in the storage device of the host controller. The vacated locations are used to receive more data about the variables associated with the plasma system.

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

Embodiments may be best understood by reference to the following description taken in conjunction with the accompanying drawings.

1 is a block diagram of a plasma system for generating statistical values of a variable, in accordance with an embodiment described herein.
2 is a diagram of another plasma system for generating statistical values of a variable, in accordance with an embodiment described in the present invention.
Figure 3 is a diagram of a host system of the plasma system of Figure 1 or Figure 2, in accordance with the embodiment described in the present invention.
Figure 4 is a diagram of another host system of the plasma system of Figure 1 or Figure 2, in accordance with one embodiment described in the present invention.
5 is a diagram of a storage device for illustrating the use of pointers for accessing a memory location, in accordance with one embodiment described in the present invention.
Figure 6 is a diagram of an insertion sort operation, in accordance with one embodiment described in the present invention.
Figure 7 is a diagram of memory arrays for illustrating a merge alignment operation, in accordance with one embodiment described in the present invention.
Figure 8 is a diagram of a storage device for illustrating a comparison operation in a merge sort operation, in accordance with one embodiment described in the present invention.
Figure 9 is a diagram of a statistics determination (DS) module of the plasma system of Figure 1 or Figure 2, in accordance with one embodiment described in the present invention.
10 is a diagram of an SD module of the plasma system of FIG. 1 or FIG. 2, in accordance with one embodiment described in the present invention.
11 is a diagram of one embodiment of a time slice sampling method for compensating for bias and / or detecting a failure in a plasma system, in accordance with one embodiment described in the present invention.
12 is a block diagram of an SD module used to create a mobile variance, in accordance with one embodiment described in the present invention.
13 is a flowchart of a method for generating a statistical value according to an embodiment described in the present invention.

The following embodiments describe systems and methods for performing statistical data decimation. Embodiments of the invention may be practiced without some or all of these specific details. In other instances, well-known process operations are not described in detail in order not to unnecessarily obscure the embodiments of the present invention.

1 is a block diagram of one embodiment of a plasma system 100 for generating statistical values of a variable. The plasma system 100 includes a host system 140, a x MHz radio frequency (RF) generator, a y MHz RF generator, and a z MHz RF generator. Each RF generator includes a controller. For example, an x MHz RF generator includes an x controller, a y MHz RF generator includes a y controller, and a z MHz RF generator includes a z controller. Examples of x MHz, y MHz, or z MHz include 2 MHz, 27 MHz, and 60 MHz. In some embodiments, x MHz is 2 MHz, y MHz is 27 MHz, and z MHz is 60 MHz. The host system 140 also includes a host controller 150.

In some embodiments, the controller includes a processor and a storage device. In some embodiments, the processor is a central processing unit (CPU), or a microprocessor, or an application specific integrated circuit (ASIC), or a programmable logic device (PLD). Examples of storage devices include read-only memory (ROM), random access memory (RAM), or a combination thereof. In various embodiments, the storage device is a flash memory, or a redundant array (RAID) of storage disks, or a hard disk.

x controller is coupled to the host system 140 via a cable 144 that includes a serial connection, or a parallel connection, or a parallel serial parallel interface (PSPI). Similarly, the y MHz RF generator is coupled to the host system via a cable, and the z MHz RF generator is coupled to the host system 140 via a cable. Each cable that couples the RF generator to the host system 140 includes a serial connection, or a parallel connection, or a parallel serial parallel interface (PSPI).

The plasma system 100 further includes an impedance matching circuit 106 and a plasma chamber 111. The impedance matching circuit 106 is connected to the plasma chamber 111 via an RF transmission line 132. In some embodiments, a portion of RF transmit line 132 includes an RF cable surrounded by an insulator surrounded by an RF tunnel, and another portion of RF transmit line 132, which is directed to chuck 152, .

The impedance matching circuit matches the impedance of the load connected to the impedance matching circuit with the impedance of the source connected to the impedance matching circuit. The source provides RF energy to the load that consumes RF energy. Examples of sources include one or more of the x, y, and z RF generators, and RF cables coupling the RF generators to the impedance matching circuit 106. In some embodiments, the source includes other devices (not shown) of the plasma system 100 coupled between the impedance matching circuit 106 and one or more of the x, y, and z MHz RF generators, A filter used to filter the RF signal supplied through the RF cable, and the like. Examples of loads include a plasma chamber 111 and an RF transmission line 132. Other examples of loads may be provided through RF transmit lines 132 of plasma system 100 coupled between other devices (not shown), for example, impedance matching circuit 106 and plasma chamber 111 A filter for filtering an RF signal, and the like.

The plasma chamber 111 includes a chuck 152, for example, an electrostatic chuck (ESC), a magnetic chuck, etc., connected to an RF transmission line 132. The plasma chamber 111 further includes an upper electrode 154 facing the chuck 152. For example, the lower surface 156 of the upper electrode 154 is positioned over and confronting the upper surface 158 of the chuck 152. In various embodiments, the upper electrode 154 is grounded. The chuck 152 includes a lower electrode made of a metal, for example, an anodized aluminum, an alloy of aluminum, or the like. The upper electrode 154 is made of a metal, for example, an alloy of aluminum and aluminum.

A workpiece 160, e.g., a semiconductor wafer, a semiconductor wafer on which the integrated circuit is deployed, etc., is disposed on the top surface 158 for processing of the workpiece 160. Examples of processing the workpiece 160 include cleaning the workpiece 160 or etching the workpiece 160 or depositing films, e.g., oxide films, etc., on the workpiece < RTI ID = , Or a combination thereof. The integrated circuit developed on the workpiece 160 is used in a variety of computing devices such as, for example, cell phones, tablets, smart phones, computers, laptops, networking equipment, and the like.

In some embodiments, the plasma chamber 111 includes other components (not shown), for example, an upper dielectric ring surrounding the upper electrode 156, an upper electrode extension surrounding the upper dielectric ring, a chuck 152 A lower electrode extension surrounding the chuck 152, an upper plasma exclusion zone (PEZ) ring, a lower PEZ ring, and the like.

In various embodiments, the top electrode 154 includes one or more holes coupled to a central gas feed, e. G., A gas supply line (not shown). The central gas feed receives one or more process gases from a gas source (not shown). Examples of process gases include oxygen-containing gases such as O ₂ . Other examples of process gases include fluorine-containing gases, such as tetrafluoromethane (CF ₄ ), sulfohexafluoride (SF ₆ ), hexafluoroethane (C ₂ F ₆ ), and the like. The upper electrode 154 is grounded. The lower electrode 152 is coupled to an x MHz RF generator via an impedance matching circuit 106, to an y MHz RF generator via an impedance matching circuit 106, and to a z MHz RF generator via an impedance matching circuit 106 do.

One or more of the x, y, and z MHz RF generators may be coupled to the chuck 152 via the impedance matching circuit 106 by one or more RF When supplying the signal power, the process gas is ignited to generate a plasma in the plasma chamber 111. For example, the x MHz generator feeds the RF signal 104 to the impedance matching circuit 106 via the RF cable 130. The impedance matching circuit 106 modifies one or more RF signals received from a corresponding one of the x, y, and z RF generators to produce a modified RF signal and provides an impedance match between the chuck 152 and the top electrode 154 Lt; RTI ID = 0.0 > RF < / RTI > transmission line 132 to ignite the process gas to produce a plasma within the gap of the RF transmission line. As another example, the y MHz RF generator supplies the RF signal through an RF cable that couples the y MHz RF generator to an impedance matching circuit 106 that alters the RF signal. In this example, the modified RF signal is further transmitted to the chuck 152 via the impedance matching circuit 106 and the RF transmit line 132 to generate a plasma.

During operation of the plasma system 100 to generate the plasma, each RF controller receives the amount of data of the variable from a sensor (not shown) coupled to the point in the plasma system 100. For example, the x controller receives the values of the variables from the voltage and current probes connected to the RF cable 130. As another example, the y controller receives the values of the variables from the voltage and current probes connected to the RF cable connecting the y MHz RF generator to the impedance matching circuit 106. As another example, the y controller receives the values of the variables from the voltage probes connected to the RF transmit line 132. As another example, the z-controller receives values of an optical sensor optically coupled to a plasma through a window in a plasma chamber.

Examples of variables are the power of the RF signal at one point in the plasma system 100 or the power of the plasma or the frequency of the RF signal or the real part of the load impedance or the imaginary part of the load impedance, The voltage magnitude, or the magnitude of the current at that point, or the phase between the complex voltage and the complex current at that point, or the wafer bias at that point, or the ion energy at that point, or the plasma potential at that point, or The complex current at that point, or the complex voltage at that point, or the load impedance at that point, or a combination thereof.

Examples of load impedances include the impedance of one or more components of the plasma system 100. For example, the load impedance is the impedance at the point in the plasma system 100. As another example, the load impedance may be determined by the RF cable 130, an RF cable coupling the y MHz RF generator to the impedance matching circuit 106, an RF cable coupling the z MHz RF generator to the impedance matching circuit 106, The matching circuit 106, the RF transmission line 132, and the plasma chamber 111.

In some embodiments, the points in the plasma system 100 may be one point at the output of the x MHz RF generator, a point at the output of the y MHz RF generator, or one point at the output of the z MHz RF generator, One point on the cable 130, or one point on the RF cable that couples the y MHz RF generator to the impedance matching circuit 106, or one point on the RF cable that couples the z MHz RF generator to the impedance matching circuit 106 , Or one point at the input of the impedance matching circuit 106 or one point at the output of the impedance matching circuit 106 or one point at the RF transmission line 132 or one point at the chuck 152 .

In various embodiments, the output of the x MHz RF generator is coupled to the input of the impedance matching circuit 106 via an RF cable 130, and the output of the y MHz RF generator is coupled to the input of the impedance matching circuit 106, And the output of the z MHz RF generator is coupled to the input of the impedance matching circuit 106 via an RF cable. In some embodiments, the output of the impedance matching circuit 106 is coupled to the chuck 152 via an RF transmit line 132.

The host controller 150 may include one or more components, such as a variable requestor 170, a variable receiver 110, a model 113, a model value generator 115, a data amount calculator 112, Decision module 114, a statistical data decimation (SDD) module 172, a switch module 180, an RF control block 197, and a transmitter 174. The SDD module 172 includes a statistics determination (SD) module 116 and a data erasure module 120.

In some embodiments, as described herein, one or more components of the host controller are implemented as a computer program on a non-temporary computer-readable medium, such as, for example, a storage device or the like. In various embodiments, one or more components of the host controller are implemented as hardware, e.g., an application specific integrated circuit or the like. For example, the switching module 180 is a transistor or a group of transistors. In some embodiments, as described herein, one or more components of the host controller are implemented as a combination of hardware and computer programs.

The variable requestor 170 requests the data of the variable from the x controller via the communication channel of the cable 144. [ In some embodiments, the variable requestor 170 sends an address of the variable receiver 110, for example, a port address, etc., to the x controller to cause the x controller to transmit the data of the variable to the variable receiver 110 do.

In many embodiments, the host controller 150 excludes the variable requestor 170 and the x controller periodically transmits the data of the variable to the variable receiver 110. Upon receipt of the request, the x controller sends the variable's data over the communication channel 102 of the cable 144 to the variable receiver 110.

In some embodiments, the variable requestor 170 and the variable receiver 110 are implemented as a single component.

Similarly, in some embodiments, the variable receiver 110 receives variable data from a combination of an x controller, a y controller, and a z controller.

The variable receiver 110 receives the data of the variable from one or more of the x, y, and z MHz RF generators and transmits the data to the model 113. Examples of the model 113 include a combination of an RF cable model or an impedance matching model or an RF transmission model or a chuck model or an RF cable model and an impedance matching model or a combination of an RF cable model and an impedance matching model and an RF transmission model , Or a combination of an RF cable model and an impedance matching model and an RF transmission model and a chuck model.

A model of a component of a plasma system is a computer-generated model of the component. For example, the RF transmission model is a computer-generated model of the RF transmission line 132 (FIG. 1). As another example, the RF transmission model includes an electrical circuit that includes electrical components of the RF transmission line 132, e.g., capacitors, or inductors, and the like. For the sake of illustration, if the RF transmit line 132 includes an inductor with the inductance of L Henley and a capacitor with a capacitance of Cfarot, then the RF transmission model would have an inductor with the inductance of L Henley, Capacitors. Also, in the RF transmission model, the components in the electrical circuit are connected in the same manner, for example, in series, parallel, etc., as the electrical components of the electrical circuit of the RF transmission line 132 are connected. For example, when an inductor is connected in parallel with a capacitor in the RF transmit line 132, the RF transmit model includes an inductor connector in parallel with the inductor.

Similarly, an impedance matching model is generated based on the impedance matching circuit 106 in a manner similar to creating an RF transmission model from the RF transmission line 132. The RF cable model is also generated based on an RF cable, e.g., RF cable 130 (FIG. 2), in a manner similar to creating an RF transmission model from RF transmission line 132. The chuck model is also generated based on the chuck 152 in a manner similar to generating the RF transmission model from the RF transmission line 132.

In some embodiments, the model 113 is generated by the processor of the host controller.

Examples of generating a model are described in Application No. 13 / 756,390, filed January 13, 2013, entitled " Using Modeling to Determine Wafer Bias Associated with a Plasma System, " / RTI >

Model value generator 115 may generate a model value based on the values received by variable receiver 110 and the characteristics, e.g., the capacitance, or inductance, or impedance, or complex current, And generates the values of the variables at the output of the model 113. For example, the model value generator 115 propagates the impedance values received from the x controller through the components of the RF cable model and the impedance matching model to produce an impedance value at the output of the impedance matching model. In some embodiments, the impedance value received from the x controller is an impedance value at the output of the x MHz RF generator. As another example, the model value generator 115 may be configured to generate a complex voltage and current value at the output of the RF transmission model, via the components of the RF cable model, the impedance matching model, and the RF transmission model, Current and voltage values. In another example, the model value generator 115 receives from the y controller through the components of the RF cable model, the impedance matching model, the RF transmission model, and the chuck model to generate a complex voltage and current at the output of the chuck model Propagated power value.

In some embodiments, the value of the variable is a function of which the value of the variable propagates when the directed sum of the component's values and features, e.g., impedance value, power consumption value, voltage value, current value, do. An example of directed agreement is provided in Application No. 13 / 756,390.

In various embodiments, the model value generator 115 generates a value of one variable from values of one or more variables. For example, the model value generator 115 may determine the magnitude of the complex voltage and current at the output from the magnitude of the voltage of the complex voltage and current at the output, the magnitude of the complex voltage and current at the output, And generates a value of wafer bias at the output. Other examples of generating wafer biases are provided in Application No. 13 / 756,390. As another example, the model value generator 115 generates a value of the ion energy at the output of the model 113 from the wafer bias at the output and the zero-peak voltage at the output. Other examples of generating ion energy are described in Application Serial No. 61 / 799,969, entitled " Using Modeling to Determine Ion Energy Associated with a Plasma System, " filed March 15, 2013, Lt; / RTI >

In some embodiments, for each value received by the variable receiver 110 from one or more of the x, y, and z MHz RF generators, the value at the output of the model 113 is computed.

The data of the variable at the output of the model 113 is transferred from the model value generator 115 to the data amount calculator 112. The data amount calculator 112 counts the number of values of the variable received from the model value generator 115 and sends the count to the limiting crossover determination module 114. [

In some embodiments, the amount of data calculator 112 calculates the number of variable values that do not exceed the maximum storage capacity of the variable receiver 110.

The limiting crossover determination module 114 determines whether the number of values received from the amount of data calculator 112 is greater than a pre-stored threshold value in the crossover determination module 114. Examples of threshold values include 1000 values, or 10,000 values, or 100,000 values, and so on. Other examples of threshold values include 500-1000 values, or 1000-10,000 values, or 10,000-100,000 values, or 100,000-1,000,000 values, or 1,000,000-10,000,000 values.

When determining that the number of values is greater than the threshold, the signal is sent from the limiting crossover determination module 114 to the SD module 116 to begin generating statistics from the values. On the other hand, when determining that the number of values does not exceed the threshold, the signal is not sent from the limiting crossover determination module 114 to the SD module 116, and the SD module 116 begins generating the statistics from the values Do not.

In some embodiments, the threshold is generated based on the storage capacity of the storage device of the host controller 150. For example, if the SD module 116 contains two buffers each storing n values of a variable, then the threshold is n values. If the first of the two buffers is a pool, the SD module 116 copies the data from the first buffer to one of the two buffers and begins to calculate the statistical value of the data. The SD module 16 calculates a statistical value based on the values in the first buffer. In various embodiments, after copying, the data in the first buffer is overwritten with the data generated by the model value generator 115.

In some embodiments, instead of the amount-of-data calculator 112, a rate calculator is located within the host controller 150. The rate calculator is implemented as a computer program, hardware, or a combination thereof. The rate calculator calculates the ratio of the number of values received from the model value generator 115 in the time window to the number of values processed by the processor of the host controller 150 within the time window. In these embodiments, the limiting crossover determination module 114 determines whether the calculated ratio is greater than the pre-stored limit in the storage device of the limiting crossover determination module 114. [ When determining that the calculated ratio is less than the limit, the statistical value is not generated from the values generated by the model value generator 115. On the other hand, when determining that the calculated ratio is greater than or equal to the limit, the statistical value is generated from the values generated by the model value generator 115.

In some embodiments, the processing rate of the processor of the host controller 150 (which is equal to the number of values processed in the time window) may be determined based on several factors, e.g., The time taken to access and calculate the statistical values from the values or the time it takes to achieve the pressure in the plasma chamber 111 after the signal for generating the pressure is transmitted by the processor or the values of the pressure in the plasma chamber 111 Or the time it takes to achieve the temperature in the plasma chamber 111 after the signal for generating the temperature is transmitted by the processor, or the values of the temperature in the plasma chamber 111, Time, or gap, is transferred from the plasma chamber 111 to the upper < RTI ID = 0.0 > It is determined on the basis of the 154 and the time it takes to create a gap between the chuck 152, or the time it takes to detect and receive values of the gap in the plasma chamber 111, or a combination thereof. For example, the processor of the host controller 150 waits to process the pressure value until the pressure value is sensed by a pressure sensor (not shown) and received by the processor. This waiting reduces the processing speed of the processor. As another example, the processor of the host controller 150 may control the temperature of the upper electrode 154 until the pressure and temperature are achieved in the plasma chamber 111, after the signal for achieving pressure and temperature is transmitted by the processor. And to transfer the signal to change the gap between the chuck 152 and the chuck 152. This waiting reduces the processing speed of the processor.

The SD module 116 is responsive to receiving from the limiting crossover determination module 112 a signal that the amount of data of the variable received from the model value generator 115 by the amount of data calculator 112 exceeds a threshold value , The statistical value is determined from the data of the variable. For example, the SD module 116 may perform operations such as, for example, an insertion sort operation, a merge sort operation, or a moving quadrant range (IQR) calculation operation, or a quadrant range calculation operation, Or a moving average value calculation method or an intermediate value calculation method or a dispersion value calculation method or a standard deviation value calculation method or a moving average value calculation method or a moving intermediate value calculation method or a moving standard deviation value calculation method or a moving standard deviation value A statistical value is generated from the values of the variables by applying a statistical operation such as a calculation method, a mode, or a moving mode, or a combination thereof.

After generation of the statistical value, the SD module 116 closes the switch module 180 to couple the variable receiver 110 with the data erasure module 120. When the switch module 180 is closed, the data erasure module 120 accesses the data stored in the storage device of the data receiver 110 and erases, e.g., erases, or resets, the data stored in the storage device , And variable receiver 110 to receive and store additional data of the variable from one or more of the x, y, and z controllers. In this way, the cost associated with implementing a large number of variable receivers to store large amounts of data is reduced. By deleting the data of the variable stored in the variable receiver 110, the variable receiver 110 is used many times for storing the data of the variable.

In some embodiments, the statistical values are provided to the RF control block 197 by the SD module 116. The RF control block 197 determines the statistical value of the variable from the statistical value of the variable or other variable received from the SD module 116. For example, the RF control block 197 determines statistical values of the statistical power and / or frequency from the statistical values of the variables received from the SD module 116. As another example, the RF control block 197 determines the statistical value of the frequency to be the same as that received from the SD module 116. [ As another example, the RF control block 197 receives statistical values of the wafer bias at the output of the model 113, and calculates the magnitude of the complex voltage and current at the output, the magnitude of the complex voltage at the output and the magnitude of the current, The complex voltage at the output and the power magnitude of the current are determined. In this example, the magnitude of the complex voltage and current at the output, the magnitude of the complex voltage at the output and the magnitude of the current, and the magnitude of the complex voltage and current at the output meet the value of the wafer bias at the output. As another example, the RF control block 197 receives statistics of the ion energy at the output of the model 113, and determines the wafer bias value at the output and the zero-peak voltage value at the output. In this example, the wafer bias value and the zero-peak voltage meet the value of the ion energy. The RF control block 197 transmits the statistical value of the variable determined by the RF control block 197 to the transmitter 174.

In various embodiments, the SD module 116 transmits the statistical values of the variables to the transmitter 174 without adding or transmitting the statistics to the RF control block 197.

The transmitter 174 transmits statistics of the variables received from the RF control block 197 and / or from the SD module 116 over the corresponding communication channels to one or more of the x, y, and z controllers. For example, the transmitter 174 may transmit the statistical value of the variable via the communication channel 184 to the x controller, transmit the statistical value of the variable via the communication channel to the y controller, And the like. As another example, the transmitter 174 transmits statistical values of the variables generated from the data of the variables received from the x controller to the x controller via the communication channel 184. As another example, the transmitter 174 transmits the statistical value of the variable generated from the data of the variable received from the y controller to the y controller via the communication channel coupled to the y controller.

The controller of the RF generator receives statistical values of the variables from the transmitter 174 and provides statistical values to the RF generator of the RF generator, e.g., the RF supply 186. The RF supply includes a driver, e.g., transistors, a group of transistors, etc., that generate an RF signal, e.g., RF signal 124, etc., having a statistical value of a variable received from transmitter 174. The RF signal is amplified by an RF amplifier connected to the driver and transmitted to an impedance matching circuit 106 via an RF cable coupled to the RF amplifier.

The impedance matching circuit 106 matches the impedance of the source with the impedance of the source for changing the RF signal received from the RF generator through an RF cable, e.g., the RF cable 130, to generate an RF signal , And transmits the modified RF signal to the chuck 152 via the RF transmission line 182. [ When the process gas is supplied in the plasma chamber 111 and a modified RF signal is received by the chuck 152, plasma is generated in the plasma chamber 111. [ In some embodiments, properties of the plasma, e.g., impedance, power, frequency, and the like, when the plasma is generated before the modified RF signal is received, Is changed.

In some embodiments, the SD module 116 determines statistical values from data of variables received from one or more of the x controller, y controller, and z controller.

In many embodiments, a number of RF generators other than those shown in FIG. 1 are used. For example, the plasma system 100 includes two RF generators or four RF generators.

In some embodiments, instead of receiving values of one or more variables from x, y, and / or z controllers, host controller 150 receives values from one or more sensors. The x, y, and / or z controllers do not act as intermediaries between host controller 150 and one or more sensors.

In various embodiments, variable requestor 170, variable receiver 110, model 113, model value generator 115, data amount calculator 112, restrictive crossover determination module 114, The switch module 180, the data erasure module 120, the RF control block 197, and the transmitter 174 are each implemented as separate processors. For example, the variable requestor 170 is implemented as one processor and the data amount calculator 112 is implemented as another processor.

In many embodiments, variable requestor 170, variable receiver 110, model 113, model value generator 115, data amount calculator 112, limit crossover determination module 114, One or more of module 116, switch module 180, data erasure module 120, RF control block 197 and transmitter 174 are implemented as a single processor and include a variable requestor 170, A statistical decision module 116, a switch module 180, a data deletion module 120, a data coder 110, a model 113, a model value generator 115, a data amount calculator 112, a limitation crossover determination module 114, ), RF control block 197, and transmitter 174 are implemented as separate processors.

In some embodiments, instead of grounding the upper electrode 154, the upper electrode 154 is provided with RF power. In various embodiments, instead of grounding the upper electrode 154, the lower electrode of the chuck 152 is grounded and the RF transmission line is provided with RF power to the upper electrode 154.

In various embodiments, the statistical values are stored in the storage device of the SD module 116. The size of the storage device of the SD module 116 is smaller than the size of the storage device of the variable receiver 110. For example, the storage device of the SD module 116 comprises a single memory location, and the storage device of the variable receiver 110 comprises a plurality of memory locations. As another example, the storage device of the SD module 116 includes fewer memory locations than the number of storage devices of the variable receiver 110.

In some embodiments, the host controller 154 includes a number of processors, e.g., one, two, three, etc., for generating statistics and controlling the plasma chamber 111, Are cost-effective. For example, using a separate processor or a separate server to control the plasma chamber 111, for example, using one processor to control the temperature in the plasma chamber 111, Using a different processor to control the pressure in the plasma chamber 111, using a different processor to control the pressure in the plasma chamber 111, controlling the frequency of the signal received by the plasma chamber 111, Instead of using another processor, using another processor to control the power of the signal, or a combination thereof, one processor may be used to generate statistics and control the plasma chamber 111 do. The processor controls the plasma chamber 111 based on the statistical value.

Examples of controlling the plasma chamber 111 include changing the frequency of the RF signal generated by the RF generator or changing the power of the RF signal or changing the temperature in the plasma chamber 111, Changing the gap in the plasma chamber 111, or changing the pressure in the plasma chamber 111, or a combination thereof.

In some embodiments, the processor of the host controller 150 controls a gas supply valve (not shown) that facilitates the supply of gas from the gas reservoir (not shown) to the gas inlets of the upper electrode 154 . For example, the processor of the host controller 150 may be configured to supply a current to open or close the gas supply valve by an amount for controlling the supply of gas, e.g., process gas, to the plasma chamber 111 Drivers, for example, transistors, control a group of transistors. Control of the supply also allows the processor to control the pressure in the plasma chamber 111 to which the gas is supplied.

In various embodiments, the upper electrode 154 is lifted up or down using a motor-driven screw mechanism (not shown). The processor of the host controller 150 moves the upper electrode 154 up or down to control, e.g., change, increase, decrease, etc., the gap between the upper electrode 154 and the chuck 152 To control the motor-driven screw mechanism through a driver, e.g., a transistor, a group of transistors, or the like.

In some embodiments, the heater is included in the chuck 152, and the heater is controlled by a driver, e.g., a transistor, for example, to control, e.g., change, increase, Lt; RTI ID = 0.0 > 150 < / RTI >

In many embodiments, a heat transfer mechanism, e.g., a duct, etc., is provided in the plasma chamber 11 and the flow of cooling liquid is controlled by a valve and driver to control the temperature in the plasma chamber 111, For example, by a transistor, a group of transistors, and the like.

2 is a diagram of one embodiment of a plasma system 151 for generating statistical values of a variable. The plasma system 151 includes a plasma chamber 111, an impedance matching circuit 106, x, y, and z MHz RF generators, and a host system 190. The host system 190 includes a host controller 192.

1), except that the plasma system 151 includes a host system 190 in place of the host system 140 (FIG. 1). In some embodiments, the plasma system 151 is a plasma system, . For example, the plasma system 151 may include a plasma system 100 (FIG. 1) and a plasma system 100, except that the plasma system 151 includes a host controller 192 in place of the host controller 150 Structurally the same.

The host controller 190 is similar to the host controller 150 (FIG. 1) except that the host controller 190 includes a bias compensation module 196, an event detection module 198, and a communication block 191 Do. The RF control block 197 is connected to the bias compensation module 196 and the event detection module 198. The SD module 116 is connected to the bias compensation module 196 and the event detection module 198.

The bias compensation module 196 determines whether the statistical value of the variable received from the RF control block 197 or SD block 116 is within a pre-stored range pre-stored in the storage device of the bias compensation module 196 .

In some embodiments, the bias compensation module 196 has a number of pre-determined ranges for multiple statistical values of a variable. For example, the storage device of the bias compensation module 196 stores a first pre-determined range of statistical values of variables generated from data of variables received from the x controller. As another example, the storage device of the bias compensation module 196 stores a second pre-determined range of statistical values of the variables generated from the data of the variables received from the y controller. In various embodiments, the first pre-determined range is the same as the second pre-determined range. In some embodiments, the first pre-determined range is different from the second pre-determined range.

The bias compensation module 196 includes a transmitter 122 for transmitting statistics values over one or more communication links to a corresponding one of the x, y, and z controllers, ). On the other hand, when determining that the statistical value of the variable is not within a pre-determined range, the bias compensation module 196 adjusts the statistical value to be within a pre-determined range, e.g., And provides the adjusted statistical value to the transmitter 122.

The transmitter 122 transmits the adjusted statistical value of the variable over one or more communication channels to a corresponding one of the x, y, and z controllers.

The controller of the RF generator receives the adjusted statistical value of the variable from the transmitter 122 via the communication channel coupling the controller to the transmitter 122 and provides the adjusted statistical value to the RF generator of the RF generator. For example, the x controller receives the adjusted statistical value of the variable and provides the adjusted statistical value to the RF supplier 186. The RF supply of the RF generator produces an RF signal, e.g., RF signal 155, containing the adjusted statistical value. For example, the RF signal 155 has a power of the adjusted statistical value. As another example, the RF signal 155 has a frequency of the adjusted statistical value.

In a manner analogous to that described above, the impedance matching circuit 106 receives one or more RF signals from corresponding one or more RF cables coupled to a corresponding one or more of the x, y, and z MHz RF generators. The impedance matching circuit 106 generates a modified RF signal based on the received one or more RF signals and transmits the modified RF signal to the chuck 152 via the RF cable 132. Based on the received modified RF signal, the plasma is generated in the plasma chamber 111, or if the plasma is already generated upon reception of the altered RF signal, the properties of the plasma are altered based on the altered RF signal.

The event detection module 198 receives statistics of the variables from the RF control block 197 or the SD module 116 and determines whether there are statistical values within a pre-stored range pre-stored in the storage device of the event detection module 198 . In some embodiments, the pre-determined degree is the same as the pre-determined range. In various embodiments, the pre-determined degree is a range that differs from the pre-determined range.

In some embodiments, event detection module 198 has a number of pre-determined degrees of multiple statistical values of a variable. For example, the storage device of the event detection module 198 stores a first pre-determined degree of statistical value of a variable generated from data of a variable received from the x controller. As another example, the storage device of the event detection module 198 stores a second pre-determined degree of statistical value of a variable generated from data of a variable received from the y controller. In various embodiments, the first pre-determined degree is the same as the second pre-determined degree. In some embodiments, the first pre-determined degree differs from the second pre-determined degree.

A failure signal is not generated by the event detection module 198 when determining that the statistical value of the variable is within a pre-determined degree. On the other hand, when it is determined that the statistical value of the variable is outside the pre-determined extent, a failure signal is generated by the event detection module 198 and provided to the transmitter 122.

The transmitter 122 transmits a failure signal over one or more communication channels to the corresponding x, y, and z controllers. For example, the transmitter 122 transmits a failure signal to the x controller over the communication channel 202 and a failure signal over the communication channel to the y controller.

The controller of the RF generator receives the failure signal and responds to the failure signal. For example, the controller of the RF generator sends a signal to the RF generator of the RF generator to stop generating the RF signal for transmission to the impedance matching circuit 106. As another example, the controller of the RF generator may control the RF signal for transmission to the impedance matching circuit 106 until the adjusted statistical value compensated for the bias is received via the transmitter 122 from the bias compensation module 196. [ To the RF generator of the RF generator in order to stop the generation of the RF generator.

In some embodiments, the event detection module 198 sends a failure detection signal to the remote computer system via the communication block 191 to notify the remote computer system of the failure in the statistical value of the variable. Examples of communication block 191 include a network interface controller, such as, for example, a network interface adapter or a network interface card.

Examples of remote computer systems include computers, servers, processors, cell phones, smart phones, tablets, etc., operated by the user. The user decides to take the action to view the notification and resolve the failure on the display device of the remote computer system, for example, a cathode ray tube display, a liquid crystal display device, a light emitting diode display device, a plasma display device or the like.

In various embodiments, the SD module 116 is connected to the communication block 191 to transmit the statistics of the variables to the remote computer system.

In various embodiments, variable requestor 170, variable receiver 110, data amount calculator 112, model 113, limit crossover determination module 114, model value generator 115, And the communication block 191 are connected to the control module 116, the switch module 180, the data deletion module 120, the bias compensation module 196, the event detection module 198, the RF control block 197, the transmitter 174, Are implemented as separate processors. For example, the variable requestor 170 is implemented as one processor and the data amount calculator 112 is implemented as another processor.

In many embodiments, variable requestor 170, variable receiver 110, data amount calculator 112, model 113, limit crossover determination module 114, model value generator 115, Module 116, a switch module 180, a data erasure module 120, a bias compensation module 196, an event detection module 198, an RF control block 197, a transmitter 174, and a communication block 191, At least one of which is implemented as a single processor and includes a variable requestor 170, a variable receiver 110, a data amount calculator 112, a model 113, a restrictive crossover determination module 114, a model value generator 115 A statistical determination module 116, a switch module 180, a data deletion module 120, a bias compensation module 196, an event detection module 198, an RF control block 197, a transmitter 174, Any remaining portion of block 191 is implemented as another processor.

In some embodiments, the host controller 192 excludes the data erase module 120 and the switch 180. In these embodiments, decimation is not performed in the host system 190. In these embodiments, all values of the variable may be stored in one or more storage devices of the host system 190, transmitted to the remote computer system for storage via the communication block 191, ) For storage.

FIG. 3 is a diagram of one embodiment of a host system 400 that is an example of a host system 190 (FIG. 2). The host system 400 includes a field programmable gate array (FPGA) 402 and a microprocessor 404. It should be noted that instead of the FPGA 402, any other integrated circuit, for example an ASIC, may be used. Also, instead of the microprocessor 404, any other integrated circuit, such as an FPGA, an ASIC, etc., may be used.

The FPGA 402 includes a plurality of serial parallel interface (SPI) (MSPI) 406 including one or more PSPIs. MSPI 406 includes 27 pins each including 9 pins for PSPI. For example, MSPI 406 includes a PSPI connected to an x controller, a PSPI connected to a y controller, and a PSPI connected to a z controller (FIG. 2). MSPI 406 may read back from the SDO ports of power, x, y, and z controllers, back read from the serial data output (SDO) ports of the data, e.g., x, y, The real part of the plasma impedance read back from the SDO ports of the x, y, and z controllers, the imaginary part of the plasma impedance read back from the SDO ports of the x, y, and z controllers, And other variables from the PSPIs of the z controllers, and transmits data to the soft-core digital signal processor (DSP) 408 and / or the high-speed port 410. [

The soft-core DSP 408 includes a model 131 and a model value generator 115. For example, the FPGA 402 implements an electrical circuit that includes electrical components of the RF transmit line 132, e.g., capacitors, or inductors, and the like. The FPGA 402 also connects the components in the electrical circuit in the same manner as the electrical components of the electrical circuit of the RF transmit line 132 are connected, for example, in series, parallel, and the like.

Data of the variables received by the MSPI 406 is transferred from the MSPI 406 to the soft-core DSP 408. The model value generator 115 of the soft-core DSP 108 generates values of variables in the output of the model 113 based on the values received from the MSPI 406, And high speed bus 412 to the high speed bus port 412 of the microprocessor 404. Examples of high-speed buses include buses that transfer data at 500 MHz, or 400 MHz, or 300 MHz, or 600 MHz, or between 5 MHz and 500 MHz. The data of the variables is communicated through the high speed port 415 to the SDD logic block 416, which is an example of the SDD 172 (FIG. 2).

In some embodiments, the logic block is a computer program that is executed by one or more processors, for example, the SDD logic block 416 is executed by the microprocessor 404. In some embodiments, the logic block is implemented as hardware in an integrated circuit. In various embodiments, the logic blocks are implemented as a combination of computer programs and hardware.

The SDD logic block 416 applies statistical transforms to the data of the variables received via the high speed port 415 from the soft-core DSP 408 to generate statistical values. For example, the SDD logic block 416 may generate an average, a median, or a mode, or a standard deviation, from the data of the variables received via the high speed port 415 from the soft-core DSP 408, , Or a maximum value, a minimum value, or a quadrant range (IQR). As another example, the SDD logic block 416 generates a moving average of a plurality of values of power received from the soft-core DSP 408. As another example, the SDD logic block 416 generates a moving intermediate value of a plurality of values of the real part of the plasma impedance received from the soft-core DSP 408. As another example, the SDD logic block 416 may generate a statistical value from the data values of the variables from the soft-core DSP 408, such as a moving IQR, or IQR, or a maximum, minimum, or average value, , Or variance, or standard deviation, or moving average, or moving median, or moving dispersion, or moving standard deviation, or mode, or moving mode, or combinations thereof.

In many embodiments, the SDD logic block 416 deletes one or more values of the received variable over the time window, excluding the statistical value of the variable. For example, the SDD logic block 416 removes from the storage device, in the host system 400, the values of the imaginary part of the plasma impedance except for the median of the values. As another example, the SDD logic block 416 removes frequency values from the storage device, except for the mode of values, in the host system 400.

In some embodiments, decimation is not performed in the host system 400. In these embodiments, all values of the variables may be stored in one or more storage devices of the host system 400, transmitted to the remote computer system for storage via the VME communication block 422, Or transferred to a virtual machine for storage via the Internet, or the like. Examples of VME communication block 422 include an Ethernet communication block, an Ether CAT communication block, a universal serial bus (USB) port, a network interface controller, a serial port, and a parallel port. The VME communication block is an example of communication block 191 (FIG. 2).

Bias compensation module 418, an example of bias compensation module 196 (FIG. 2), determines the amount of bias based on the statistics received from SDD logic block 416 to compensate for bias. For example, when determining that the statistical value is outside a pre-determined range, the bias compensation module 418 adjusts the statistical value to be within a pre-determined range.

In some embodiments, the bias compensation module 418 provides the adjusted statistical values via the high speed port 415, the high speed bus 412, the high speed port 410, the MSPI 406, . In various embodiments, the bias compensation module 418 may send the adjusted statistics via the VME communication block 422 to a port of the RF generator, e.g., an Ethernet port, an Ether CAT port, a USB port, a parallel port, Or to a port of a remote computer system.

The microprocessor 404 may be connected to the RF transmission line 132 at a point within the plasma system 151 (FIG. 2), for example a point in the plasma chamber 111 or a point in the impedance matching circuit 106, Point in the x MHz RF generator, point in the y MHz RF generator, or point in the z MHz RF generator, or point on the RF cable that couples the RF generator to the impedance matching circuit 106, For example, an event / failure detection module 420 for detecting a failure or the like. For example, when determining that the statistic value received from the SD logic block 416 is outside a pre-determined range, the event / failure detection module 420 determines whether the event is within the plasma system 151 (FIG. 2) . An indication of the occurrence of the event may be received from the event / failure detection module 420 via the VME communication block 422, for example, one or more devices, such as an x MHz RF generator, a y MHz RF generator, a z MHz RF generator, . The event / failure detection module 420 is an example of the event / failure detection module 198 (FIG. 2).

4 is a block diagram of one embodiment of a host system 405 that is another example of the host system 190 (Fig. 2). The host system 450 is similar to the host system 400 (FIG. 4) except that the host system 450 includes a microprocessor 454 and an FPGA 403. The microprocessor 452 is similar to the microprocessor 404 (FIG. 3) except that the microprocessor 452 includes a variable module 454. The FPGA 403 is also similar to the FPGA 402 except that the FPGA 403 excludes the soft-core DSP 408 (FIG. 3).

The model value generator 115 of the variable module 454 receives data of one or more variables from the MSPI 406 via the high speed port 410, the high speed bus 412, and the high speed port 415. The model value generator 115 of the variable module 454 receives the data and characteristics of the variables received from the MSPI 406 at the output of the model 113 based on, for example, the capacitance, Determine the data of the variables. For example, if the plasma impedance received via the MSPI 406 is Z1 and the impedance of the elements of the RF transmission model is Z2, then the model value generator 115 generates an impedance at the output of the RF transmission model to be a directional sum of Z1 and Z2 . As another example, if the complex voltage and current received over the three communication channels is a complex V < RTI ID = 0.0 > I1 < / RTI > and the complex voltage and current in the RF transmission model is a complex V & The complex V & I is determined at the output of the transmission model.

The SDD logic block 416 receives the data of the variables generated by the variable module 454 and determines the statistical values from the data in a manner similar to that described above. The bias compensation module 418 also receives statistics from the SDD logic block 416 and determines the bias to apply to the plasma chamber 111 (Figure 1) based on the statistics. For example, when determining that the statistical value is outside a pre-determined range, the bias compensation module 418 adjusts the statistical value to be within a pre-determined range.

The bias compensation module 418 sends the adjusted statistical values in one or more of the x, y, and z controllers to the one or more PSPIs in a manner similar to that described above (FIG. 2). For example, the bias compensation module 418 may determine the adjusted statistical value of the power and the adjusted statistical value of the frequency, and determine the adjusted statistical value of the frequency of the high speed port 415, the high speed bus 412, the high speed port 410, the MSPI 406 ), And statistical values adjusted via communication channels to the x controller. In some embodiments, the bias compensation module 418 may communicate the adjusted statistical values via the VME communication block 422 to a port of the RF generator, e.g., an Ethernet port, an Ether CAT port, a USB port, a parallel port, Or to a port of a remote computer system.

The event / failure detection module 420 detects an event within the plasma system 151 (FIG. 2) based on the statistics received from the SDD logic block 416. For example, when determining that the statistical value is outside a pre-determined degree, the event / failure detection module 420 determines that an event occurs in the plasma system 151. [ The statistical values are generated from the data of the variables generated by the variable module 454.

An indication of the occurrence of the event may be received from the event / failure detection module 420 via the VME communication block 422, such as one or more devices, e.g., a remote computer system, an x MHz RF generator, a y MHz RF generator, . The user may view the display on the display device of the remote computer system and decide to take action to resolve the failure.

5 is a diagram of one embodiment of a storage device 500 for illustrating the use of pointers for accessing a memory location. The storage device 500 is present in the variable receiver 110 (FIGS. 1 and 2). In some embodiments, the storage device 500 is in the data amount calculator 112 or the limiting crossover determination module 114, or the SD module 116. [

The storage device 500 includes a memory array 1 and a memory array 2. The memory array 1 stores the data of the variables, and the memory array 2 stores the memory addresses of the locations in the memory array 1. Examples of data for variables are shown as Index 0, Index 1, Index 2, Index 3, and Index 4.

As shown, the data of the variable is received in memory array 1 and stored at memory addresses 0x0, 0x1, 0x2, 0x3, and 0x4. A pointer to the data may be stored in a processor, for example a processor of the amount of data calculator 112, or a processor of the limited crossover decision module 114, or a module of the SD module 116, Lt; RTI ID = 0.0 > 2 < / RTI > The 0x0 pointer is stored at memory address 0x5 and points to the value index 0. The 0x1 pointer is stored at memory address 0x6 and points to the value index 1. The 0x2 pointer is also stored in the memory address 0x7 and points to the value index 2, the 0x3 pointer is stored in the memory address 0x8 and points to the value index 3, the 0x4 pointer is stored in the memory address 0x9, and the value index 4 is pointed .

Although five values are shown in FIG. 5, in some embodiments, more or less than five values are stored in memory array 1.

It should be noted that, in some embodiments, pointers are used to point to the memory address to access, change, or delete the data of the variable at the memory address. In various embodiments, the pointer is used to change the position of the value in the storage device. Each location in the storage device, e.g., a memory array, a group of memory arrays, etc., is identified by a memory address.

Figure 6 is a diagram of one embodiment of an insertion alignment operation. The data of the variable is stored in the memory array 502, which is an example of the memory array 1 (Fig. 5). For example, 1, 2, 5, 3, and 4 are the values of the variables stored in the memory array 502. Between the respective values of the memory array 502 and the remaining values of the memory array 502 in order to align the values of the memory array 502 from the lowest value of all values to the highest of all values Lt; / RTI > For example, 5 is compared to 2. 5 is greater than 2, it is determined that the pointer pointing to the third position from the left in the memory array 502 still points to the third position. As another example, 5 is compared to 1. 5 is greater than one, it is determined that the pointer pointing to the third position from the left in the memory array 502 still points to the third position. As another example, 3 is compared to 5, and 3 is determined to be less than 5. Also, the pointer pointing to the third position from the left in the memory array 502 is changed to a point for the fourth position from the left in the memory array 502, and the pointer pointing to the fourth position is now shifted to the third position As shown in FIG. In this example, 3 is to switch places to 5 in memory array 502.

Alignment is performed to align the values in the memory array 502 from the lowest of the values to the highest of the values to determine the minimum and maximum values from the values.

Although five values are shown in Figure 6, in some embodiments, values greater than or less than five are stored in the memory array 502. [

FIG. 7 is a diagram of one embodiment of three memory arrays 504, 506, and 508 for illustrating a merge alignment operation. The memory arrays 504, 506, and 508 are portions of the storage device 510. Storage device 510 resides within variable receiver 110 (FIGS. 1 and 2). In some embodiments, the storage device 510 is present in the data amount calculator 112, or the limiting crossover determination module 114, or the SD module 116. [ In various embodiments, memory arrays 504 and 506 reside within the storage device of variable receiver 110 and merged memory array 508 resides within the storage device of SD module 116. [

The values of the variables in the memory arrays 504 and 506 are generated after performing the insertion sort operation. For example, the values of the variables in the memory array 504 are sorted from the lowest value of all values in the memory array 504 to the highest value of all values in the memory array 504. [ As another example, the values of the variables in the memory array 506 are sorted from the lowest value of all values in the memory array 506 to the highest of all values in the memory array 506.

The data of the variable is received in the memory arrays 504 and 506. During the merge alignment operation, the maximum value of all values of the memory array 504 is determined, and the minimum value of all values of the memory array 506 is determined. It is additionally determined whether the minimum value in the memory array 506 is greater than the maximum value of the memory array 504. [

Each value of the memory array 504 is compared to a respective value in the memory array 506 when determining that the minimum value in the memory array 506 is not greater than the maximum value in the memory array 504. [ On the other hand, when determining that the minimum value in the memory array 506 is greater than the maximum value in the memory array 504, a comparison is made between the values in the memory arrays 504 and 506. [ If the comparison is not performed, a merged memory array 508 containing all the values of the memory arrays 504 and 506 is generated. For example, the values of memory arrays 504 and 506 are written into a merged memory array 508 in a sequence of values in memory arrays 504 and 506.

In various embodiments, the memory address of the memory array 506 in which the value "7" is stored is stored immediately after the memory address of the memory address 504 where the value "6 & exist. In some embodiments, the memory array of the memory array 506 in which the value "7" is stored is stored after the memory address of the memory array 504 in which the value "6 " is stored, for example, Or within its two memory addresses, or within its multiple memory addresses.

In various embodiments, the memory arrays 504 and 506 are separated by the number of vacated memory addresses, e.g., 1, 2, and so on.

It should be noted that although each memory array 504 and 506 includes six values, in some embodiments, each memory array 504 and 506 includes a different number of values of the variable.

In various embodiments, the merged memory array 508 has the same size as the total number of memory addresses in the memory arrays 504 and 506, e.g., the number of memory addresses, and so on.

8 is a diagram of one embodiment of a storage device 550 for illustrating comparison operations within a merge sorting operation. The storage device 550 includes memory arrays 552 and 554, and a merged memory array 556. [ The memory arrays 553, 554, and 556 are portions of the storage device 550 located within the variable receiver 11 (FIGS. 1 and 2). In some embodiments, the storage device 550 resides in the data amount calculator 112, or the limiting crossover determination module 114, or the SD module 116. In various embodiments, the memory arrays 552 and 554 reside in the storage device of the variable receiver 110 and the merged memory array 556 resides in the storage device of the SD module 116.

During the one-to-one comparison between the values of the memory arrays 552 and 554, it is determined whether the value in the memory address of the memory array 552 is less than the value in the memory address of the memory array 554. [ For example, it is determined if the value "4" in the memory array 552 is less than the value "3" in the memory array 554. As another example, each value of a variable in memory array 552 is compared to a respective value of a variable in memory array 554 in the order of memory addresses in memory arrays 552 and 554. The value "1" in memory address MA1 of memory array 552 is equal to the value "1 " in memory addresses MA5, MA6, MA7, and MA8 of memory array 554, Quot ;, "5 "," 6 ", and "8" The value "2" in the memory address MA2 of the memory array 552 is then reset to the values 3, 5, Quot; 6 "and" 8 ". The memory address MA1 is smaller than the memory address MA2.

When determining that the value in the memory address of one of the memory arrays 552 and 554 is less than the value in the remaining memory address of the memory arrays 552 and 554, It is determined to insert a small value, for example, to perform writing or the like. 3 "in the memory array 554 is less than the value" 4 "in the memory array 552, the value" 3 " . 4 "in the memory array 552 is less than the value" 5 "in the memory array 554, the value 4 is stored as the memory address 560 of the merged memory array 556 . The vacated memory addresses in the merged memory array 556 are contiguous to the occupied memory addresses of the merged memory array 556.

Any value of the memory array 554 that has not been written into the merged array 556 may be stored in the memory array 554 after the comparison between the values of the memory arrays 552 and 554 is performed during the merge alignment operation Compared to unprinted values. For example, the value "5" of the memory array 554 is compared to the value "6" A comparison is performed in the order of the memory addresses of the memory array 554 including the values not yet written into the merged memory array 556. [ 5 ", " 6 ", and "8" are stored in the memory array 554 when the values "5 ", & The value "5" in the smallest memory address from the memory addresses stored in < / RTI > The memory address of the value "6" is larger than the memory address of the value "8"

During the merge alignment operation, while comparing the uncommitted values, the smaller of the uncommitted values is written into the merged memory array 556. For example, if a comparison is made between the values "5" and "6" in the memory array 554, the value "5" is written into the merged memory array 556. As another example, if a comparison is made between values "6" and "8" in memory array 554, the value "6" is written into memory array 556. Any remaining values after the comparison of the un-written values are written to the vacated address of the merged memory array 556 contiguous to the memory address written using the value. For example, the value "8" of the memory array 554 is written to the memory address 562 of the memory array 556.

At the end of the merge alignment operation, the merged memory array 556 is aligned to the highest of all values of the memory arrays 552 and 554 from the lowest of all values in the memory arrays 552 and 554 .

It should be noted that although each memory array 552 and 554 includes four values, in some embodiments, each memory array 552 and 554 includes a different number of values of the variable.

In various embodiments, the memory arrays 552 and 554 are separated by the number of vacated memory addresses, e.g., 1, 2, and so on. In some embodiments, the memory address MA5 is contiguous to the memory address MA4 of the memory array 552. [

In various embodiments, the merged memory array 556 has the same size as the size of the total number of memory addresses in the memory arrays 552 and 554.

FIG. 9 is a diagram of one embodiment of an SD module 580, which is an example of the SD module 116 (FIGS. 1 and 2). The SD module 580 includes a mobile IQR module, an IQR module, an insertion alignment module, a merge alignment module, a mode module, a movement mode module, an average module, an intermediate value module, a dispersion module, a standard deviation module, , A mobile dispersion module, and a mobile standard deviation module.

The mobile IQR module may be implemented as a memory array, e.g., a memory array 502 (FIG. 6), or a memory array 504 (FIG. 7), or a memory array 506 Determine the moving IQR of the values of the variables in the memory array 552 (FIG. 7), or the memory array 552 (FIG. 8), or the memory array 554 (FIG. 8), or the merged memory array 556 do. Similarly, the IQR module calculates the IQR of the values of the variables in the memory array. The insertion alignment module also applies an insertion sort operation to the values of the variables in the memory array. The merge sort module applies a merge sort operation to the values of the variables in the memory array. The mode module determines the mode of the values of the variables in the memory array. Similarly, the movement mode module determines the mode of movement of the values of the variables in the memory array. The average module calculates the average of the values of the variables in the memory array. The median module generates a median of the values of the variables in the memory array.

The distribution module calculates the variance of the values in the memory array, and the standard deviation module determines the standard deviation of the values in the memory array. The moving average module calculates a moving average of the values of the variables in the memory array, and the moving intermediate module determines the moving intermediate value of the values of the variables in the memory array. The mobile distribution module calculates the mobile dispersion of the values in the memory array, and the mobile dispersion module determines the mobile dispersion of the values in the memory array. The moving standard deviation produces a moving standard deviation of the values in the memory array.

For example, the motion statistics value, e.g., a moving IQR value, or a moving mode value, or a moving average value, or a moving intermediate value, or a moving variance value, or a moving standard deviation value, (Fig. 1 & Fig. 2), values that dynamically consider the values of the variables as values received from the model value generator 115 (Figs. For example, a moving average of values "1", "2", and "5" in memory array 502 (FIG. 6) Is different from the moving average of the values "1", "2", "5", "3" and "4". As another example, values in the memory array 556 (FIG. 8) merged at times when the remainder values "3" and "4" of the merged memory array 556 are not generated in the merged memory array 556, The moving standard deviation of the merged memory array 556 is different from the moving average of the values 1, 2, 3, 3 and 4 of the merged memory array 556 Do.

In various embodiments, the rate of reception of the values in the buffer of the SD module 116 from the model value generator 115 is equal to the rate of reception of the values by the variable receiver 110 (FIGS. 1 and 2).

In some embodiments, the SD module 580 may be a mobile IQR module, or an IQR module, or an insertion alignment module, or a merge alignment module, or a mode module, or a mobile mode module, or an average module, Module, or a standard deviation module, or a moving average module, or a moving intermediate value module, or a mobile dispersion module, or a moving standard deviation module, or a combination thereof. For example, the SD module 580 includes a mobile IQR module and an insertion alignment module. As another example, the SD module 580 includes a merge alignment module and a moving average module and a moving standard deviation module.

In various embodiments, a mobile IQR module, and an IQR module, and an insertion alignment module, and a merge alignment module, and a mode module, and a moving mode module, and an average module, and an intermediate value module, , And the moving average module, and the moving intermediate value module, and the mobile dispersion module, and the moving standard deviation module, respectively, are implemented as separate processors. For example, the mobile IQR module is implemented as one processor, and the mode module is implemented as another processor.

In many embodiments, a mobile IQR module, an IQR module, an insertion alignment module, a merge alignment module, a mode module, a movement mode module, an average module, an intermediate value module, a distribution module, a standard deviation module, One or more of the modules, the mobile distributed module, and the mobile standard deviation module are implemented as a single processor and include a mobile IQR module, an IQR module, an insertion alignment module, a merge alignment module, a mode module, , Distributed module, standard deviation module, moving average module, moving intermediate value module, mobile distributed module, and moving standard deviation module are implemented as separate processors.

The mobile IQR module, the IQR module, the insertion alignment module, the merge alignment module, the mode module, the movement mode module, the average module, the median module, the dispersion module, the standard deviation module, the moving average module, Each of the moving standard deviation modules is implemented as a computer program, or hardware, or a combination of hardware and computer programs stored in a non-transitory computer-readable medium.

In some embodiments, the average is calculated in parallel with performing the insertion alignment operation. For example, the values of a variable are summed in parallel with aligning values from a minimum of values to a maximum of values.

In some embodiments, the IQR or median value is determined after performing the insert alignment operation. After the insertion sort operation is performed, the values of the variables are sorted from the lowest value of the values to the highest value of the values. If the number of values is odd, the middle value of the aligned values is the middle value. If the number of values is an even number, the mean of the two values located in the middle of the sorted values is the median value. The calculated median value is used to determine the IQR.

In various embodiments, the average is calculated in parallel to performing the merge sort operation. The average is calculated from all values aligned after the merge sort operation.

In some embodiments, the IQR or median value is determined after performing the merge sorting operation. After the merge sort operation is performed, the values of the variables are sorted from the lowest value of the values to the highest value of the values. If the number of values is odd, the middle value of the aligned values is the middle value. If the number of values is an even number, the mean of the two values located in the middle of the sorted values is the median value. The calculated median value is used to determine the IQR.

FIG. 10 is a diagram of one embodiment of an SD module 590, which is an example of the SD module 116 (FIGS. 1 and 2). The SD module 590 includes a mobile IQR module, an IQR module, an insertion alignment module, a merge alignment module, a mode module, a movement mode module, an average module, an intermediate value module, a dispersion module, a standard deviation module, , A mobile dispersion module, and a mobile standard deviation module.

In addition, in the SD module 590, the merge alignment module may include a mobile IQR module, an IQR module, an insertion alignment module, a mode module, a movement mode module, an average module, an intermediate value module, a dispersion module, a standard deviation module, An intermediate value module, a mobile dispersion module, and a moving standard deviation module.

The mobile IQR module computes the mobile IQR of the values in the merged memory array, e.g., the merged memory array 508 (FIG. 7) or the merged memory array 556 (FIG. 8) Similarly, the IQR module calculates the IQR of the values in the merged memory array. The average module also calculates the average of the values in the merged memory array. The intermediate value module generates an intermediate value of the values in the merged memory array. A mode module generates a mode of values in the merged memory array, and a shift mode module calculates a shift mode of values in the merged memory array. The distribution module also calculates the variance of the values in the merged memory array. The standard deviation module calculates the standard deviation of the values in the merged memory array, and the moving average module calculates the moving average of the values in the merged memory array. The moving intermediate value module determines the moving intermediate value of the values in the merged memory array and the mobile distribution module calculates the moving dispersion of the values in the merged memory array. The moving standard deviation module generates a moving standard deviation of the values in the merged memory array.

In some embodiments, the SD module 590 may be a mobile IQR module, or an IQR module, or an insertion alignment module, or a merge alignment module, or a mode module, or a mobile mode module, or an average module, Module, or a standard deviation module, or a moving average module, or a moving intermediate value module, or a mobile dispersion module, or a moving standard deviation module, or a combination thereof.

11 is a diagram of one embodiment of a system 601 for applying a time slice sampling method. The system 601 includes a bias compensation module 196 and an event detection module 198. The bias compensation module 196 and / or the event detection module 198 receives the generation time of the value of the variable from the SD module 116 (FIGS. 1 and 2). For example, the time t1 is the generation time of the variable value V21 by the SD module 116. As another example, the time t2 is the generation time of the variable value V22 by the SD module 116, the time t2 is the generation time of the variable value V23 by the SD module 116, and the time t4 is the time Variable value V24). As another example, the time t5 is the generation time of the variable value V25 by the SD module 116, and the generation time of the variable value V11 by the SD module 116. Time t1 to time t5 are calculated by the SD module 115. [ In some embodiments, time t1 is the time of generation of variable value V15 and variable V21.

In some embodiments, the variable values V11, V12, V13, V14, and V15 are the values of the first variable, The variable values V21, V22, V23, V24, and V25 are the values of the second variable, Variable 1 is different from Variable 2. For example, variable 1 is power and variable 2 is voltage. As another example, variable 1 is the current and variable 2 is the voltage.

In various embodiments, variable 1 and variable 2 are the same value and are generated based on values from different RF generators. For example, variable 1 is generated from the voltage values of the x MHz RF generator, and variable 2 is generated from the voltage values of the y MHz RF generator. As another example, variable 1 is generated from the frequency values of the y MHz RF generator and variable 2 is generated from the frequency values of the z MHz RF generator.

Variables V11 through V15 are stored in the memory array of the SD module 116 (FIGS. 1 and 2), for example, an array of interleaved arrays, a merged array, or the like. For example, the variable values V11 to V15 are sorted from the lowest value of the values to the highest value of the values. In this example, V11 is the lowest value and V15 is the highest value. Variables V21 through V25 are also stored in the memory array of the SD module 116 (FIGS. 1 and 2), for example, an array of interleaved arrays, a merged array, or the like. For example, the variable values V21 to V25 are sorted from the lowest value of the values to the highest value of the values. In this example, V21 is the lowest value and V25 is the highest value. In addition, times tl through t5 are stored in the bias compensation module 196 and / or the memory array 607 of the event detection module 198. Times tl through t5 are received by the bias compensation module 196 and / or the event detection module 198 from the SD module 116 for storage in the memory array 607.

The bias compensation module 196 determines whether the generation time t1 of the variable value V21 is equal to the generation time of the variable value V15. When it is determined that the generation time t1 of the variable value of V21 is equal to the generation time of the variable value V15, the variable values V21 and V15 are used to determine whether or not a bias exists in the plasma system. For example, when determining that the variable value V21 is outside the pre-determined range and the variable value V15 is outside the pre-determined range, it is determined that a bias exists. In this example, both the values V15 and V21 are adjusted by the bias compensation module 196 to generate biased adjusted statistical values. As another example, when determining that the variable value V21 is within a pre-determined range and that the variable value V15 is within a pre-determined range, it is determined that a bias is present in the plasma system. As another example, when determining that the variable value V21 is within a pre-determined range and that the variable value V15 is outside a pre-determined range, it is determined that no bias exists or a bias is present in the plasma system.

Similarly, the bias compensation module 196 determines whether the generation time t5 of the variable value V25 is equal to the generation time of the variable value V11. When it is determined that the generation time t5 of the variable value V25 is equal to the generation time of the variable value V11, the variable values V25 and V11 are used to determine whether or not the bias exists in the plasma system.

Further, in some embodiments, the event detection module 198 determines whether the generation time t1 of the variable value V21 is equal to the generation time of the variable value V15. When it is determined that the generation time t1 of the variable value V21 is equal to the generation time of the variable value V15, the variable values V21 and V15 are used to determine whether there is a failure in the plasma system. For example, when determining that the variable value V21 is outside the pre-determined extent and that the variable value V15 is outside the pre-determined extent, it is determined that a failure exists. As another example, when determining that the variable value V21 is within a pre-determined degree and that the variable value V15 is within a pre-determined degree, it is determined that no failure is present in the plasma system. As another example, when it is determined that the variable value V21 is within a pre-determined degree and the variable value V15 is outside a pre-determined degree, it is determined that there is no failure or there is a failure in the plasma system.

Similarly, the event detection module 198 determines whether the generation time t5 of the variable value V25 is equal to the generation time of the variable value V11. When it is determined that the generation time t5 of the variable value V25 is equal to the generation time of the variable value V11, the variable values V25 and V11 are used to determine whether a failure exists in the plasma system.

12 is a block diagram of one embodiment of an SD module 600 used to create a mobile distribution 602. [ The SD module 600 includes a plurality of adders A1, A2, A3, A4 and A5, a multiplier MU1, divider units D1 and D2 and a square root calculator SQRT1. The SD module 600 is an example of the SD module 116 (FIGS. 1 and 2).

SD module 600 may be implemented as a memory array, e.g., memory array 502 (Figure 6), or memory array 504 (Figure 7), or memory array 506 (Figure 7) The current values of the variables in array 508 (FIG. 7), or memory array 552 (FIG. 8), or memory array 554 (FIG. 8), or merged memory array 556 And a current average calculator that calculates the average. Further, for a current data point x in the memory array for which the current average is computed, e.g., a value in the memory array, a value in the merged memory array, etc., the current average may be subtracted from the current data point to produce a delta value of the variance A1. The adder A2 adds the current average and the delta value to produce a result and the result is divided by the total number n of data points in the memory array in which the current average value is generated. The data point calculator calculates the total number of data points. Division of the result by the total number of data points is performed by the divider D1 to produce the next average value of the variable. In some embodiments, the following average value is a statistical value.

The next average value is subtracted by the adder A4 from the current data point x to produce a result and the result is multiplied by a delta value and a multiplier MU1 to produce a result value. The resultant value is added to the current instantaneous average M2 by the adder A5 so as to generate the following instantaneous average M2. In some embodiments, the following instantaneous average (M2) is a statistical value.

The next instantaneous value M2 is divided by the divider D2 by the number that is less than the total number of data points in the memory array to create the mobile variance 602. [ In various embodiments, the mobile variance 602 is a statistical value.

The square root of the mobile variance 602 is calculated by the square root calculator SQRT1 to produce the moving standard deviation 604. [ In some embodiments, the moving standard deviation 604 is a statistical value.

It should be noted that for each different value in the memory array, the next average value, the next instantaneous average, and the mobile variance 602 are different. The mobile dispersion 602 varies with changes in the values in the memory array.

A pseudocode for generating mobile distribution 602 is provided below.

In the pseudocode, the total number n of data points, the current average, and the current instantaneous average are initialized to zero.

13 is a flow diagram of one embodiment of a method 700 for generating statistics values. In method 700, a variable is determined from a RF system, e.g., x controller, or y controller, or z controller, or a combination thereof, to a host controller, e.g., host controller 150 The host controller 192 (Fig. 2) or the like. In operation 702, the variable is propagated through the model 113 (Figs. 1 to 4). For example, a directed sum is calculated. In this example, the directional summation has values of the variables, and values of the components of the model 113 in which the values of the variables propagate. In some embodiments, operation 702 is performed by model value generator 115 (Figs. 1-4).

The method 700 further includes an act 704 of counting the output of the model 113 for the variable. For example, the number of values generated after propagating the variable through the model 113 is counted. Values are generated at the output of the model 113 and are calculated by the data amount calculator 112 (Figures 1 and 2). In some embodiments, the output of the model 113 being counted includes a directed sum.

At operation 706 of method 700, it is determined by the limit crossover determination module 114 whether the count meets the count threshold, which is a pre-stored number of values stored in the storage device of the limit crossover determination module 114 . The counting of operation 704 continues until the count does not meet the count threshold, e. G., Below the count threshold, or the like. On the other hand, at operation 708, the statistical value may be stored in the memory of the model 113 (e.g., the model 113) calculated by the model value generator 115, if the count meets the count threshold, e.g., greater than or equal to the count threshold, ≪ / RTI > For example, a statistical value is generated from the directed summations of the values.

The statistical values are generated by the SD module 116 (Figures 1 and 2). At operation 710, the statistics are sent to the RF system by transmitter 174 (FIGS. 1 and 2) to adjust the variables. For example, the statistical values are transmitted to the x, y, and / or z controllers to generate an RF signal based on the statistical values.

Although the above-described embodiments have been described with reference to a parallel plate plasma chamber, in one embodiment, the embodiments described above may be applied to other types of plasma chambers, for example, a plasma comprising an inductively coupled plasma (ICP) Chamber, a plasma chamber including an electron-cyclotron resonance (ECR) reactor, and the like. For example, the x MHz, y MHz, and z MHz RF generators are coupled to an inductor in an ICP plasma chamber.

In some embodiments, a kilohertz (kHz) RF generator is used instead of a MHz RF generator. For example, instead of an x MHz RF generator, a 400 kHz RF generator is used.

In various embodiments, the MHz RF generator has an operating frequency in MHz and the kHz RF generator has an operating frequency in kHz.

Some of the embodiments described herein utilize various computer system configurations including hand-held devices, microprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, . Some of the embodiments described herein are implemented in distributed computing environments where tasks are performed by remote processing devices that are linked through a network.

With the above embodiments in mind, it should be understood that some of the embodiments described herein utilize various computer-implemented operations involving data stored in computer systems. These operations are operations that require physical manipulation of physical quantities. Any of the operations described herein that form part of the embodiments are useful machine operations. Some of the embodiments described herein also relate to a device or apparatus for performing these operations. In some embodiments, the device is specifically configured for a special purpose computer. If defined as a special-purpose computer, the computer may still operate for special purposes, while performing other processing, program execution, or routines that are not part of a particular purpose. In various embodiments, operations are processed by a general purpose computer selectively activated or configured by one or more computer programs stored in a computer memory, a cache, or obtained via a network. When data is acquired over the network, the data is processed by the cloud of other computers on the network, e.g., computing resources.

Some of the embodiments are fabricated as computer-readable code on non-transitory computer-readable media. A non-transient computer-readable medium is any data storage device capable of storing data, which data can thereafter be read by a computer system. Examples of non-transitory computer-readable media include hard drives, network attached storage (NAS), ROM, RAM, compact disk-ROMs (CD-ROMs), CD- ), CD-rewritable (CD-RWs), magnetic tapes, and other optical and non-optical data storage devices. In some embodiments, the non-transitory computer-readable medium includes a computer-readable type of medium distributed over a network-coupled computer system in which the computer-readable code is stored and executed in a distributed manner do.

Although method operations have been described in a particular order, in some embodiments, as long as the processing of the overlay operations is performed in a desired manner, other housekeeping operations may be performed between operations, or operations may be performed at slightly different times Or distributed in a system that allows the generation of processing operations at various intervals associated with processing.

In some embodiments, one or more characteristics from any embodiment are combined with one or more characteristics of any other embodiment, without departing from the scope of the various embodiments described herein.

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, it is to be understood that the embodiments of the invention are to be considered illustrative rather than limiting, and the embodiments are not intended to be limited to the details given herein, but may be modified within the scope and equivalence of the appended claims.

Claims (26)

As a method,
Receiving a variable from a radio frequency (RF) system;
Propagating the variable through a model of the RF system;
Counting the output of the model for the variable to produce a count;
Determining if the count satisfies a count threshold;
Generating a statistical value of the variable at the output of the model when determining that the count satisfies the count threshold; And
And transmitting the statistical value to the RF system to adjust the variable. The method according to claim 1,
Wherein the variable comprises power, or frequency, or voltage magnitude, or current magnitude, or phase between complex voltage and complex current, or complex current, or complex voltage, or a combination thereof. The method according to claim 1,
Wherein the RF system comprises an RF generator. The method according to claim 1,
The model is a computer-generated model,
Wherein propagating a variable through the model comprises generating a directional sum of variable values associated with components of the model and a value of the variable. The method according to claim 1,
Wherein the output comprises a plurality of values of the variable. 6. The method of claim 5,
Wherein the statistical value is an interquartile range of the values or a quadrant of the values or a maximum value of the values or a minimum value of the values or an average of the values or an intermediate value of the values, Or the standard deviation of the values or the moving average of the values or the moving intermediate value of the values or the moving dispersion of the values or the moving standard deviation of the values or the mode of the values, Or a combination thereof. ≪ RTI ID = 0.0 > As a method,
Receiving data associated with a variable from a radio frequency (RF) generator, wherein the RF generator is configured to generate an RF signal to be supplied to the plasma chamber via an impedance matching circuit, the variable being associated with an RF system, The RF system includes receiving data associated with a variable from the radio frequency (RF) generator, the RF generator, the impedance matching circuit, and the plasma chamber;
Generating values output from the computer-generated model based on the received data;
Counting the amount of values output from the computer-generated model;
Determining if the amount exceeds a count threshold;
Generating a statistic value from the values output from the computer-generated model, in response to determining that the amount exceeds the count threshold; And
And transmitting the statistical value to the RF generator to adjust the RF signal generated by the RF generator. 8. The method of claim 7,
The adjusted RF signal is provided to the plasma chamber through an RF cable, the impedance matching circuit, and an RF transmission line,
The RF cable couples the RF generator to the impedance matching circuit,
Wherein the RF transmission line couples the impedance matching circuit to the plasma chamber. 8. The method of claim 7,
Wherein the variable comprises power, or frequency, or voltage magnitude, or current magnitude, or phase between complex voltage and complex current, or complex current, or complex voltage, or a combination thereof. 8. The method of claim 7,
The impedance matching circuit matches the impedance of the source with the impedance of the load,
The source comprising an RF generator coupling the RF generator to the impedance matching circuit,
Wherein the rod comprises the plasma chamber and an RF transmission line,
Wherein the RF transmission line couples the plasma chamber to the impedance matching circuit. 8. The method of claim 7,
Wherein the plasma chamber comprises a chuck and an upper electrode facing the chuck. 8. The method of claim 7,
Wherein the variable comprises a complex voltage and current at a point in the plasma system. 8. The method of claim 7,
The amount includes the number of values,
The statistical value may be a moving range of the values or a quadrant of the values or a maximum value of the values or a minimum value of the values or an average of the values or an intermediate value of the values, Or a standard deviation of said values or a moving average of said values or a moving intermediate value of said values or a moving variance of said values or a moving standard deviation of said values or a mode of said values, , Or a combination thereof. 8. The method of claim 7,
And decimating the received data after generating the statistical value. 8. The method of claim 7,
Wherein generating the values at the output of the computer-generated model comprises propagating the received data through components of the computer-generated model. As a method,
Receiving data associated with a variable from a radio frequency (RF) generator, wherein the RF generator is configured to generate an RF signal to be supplied to the plasma chamber via an impedance matching circuit, the variable being associated with an RF system, The RF system includes receiving data associated with a variable from the radio frequency (RF) generator, the RF generator, the impedance matching circuit, and the plasma chamber;
Generating values in an output of the computer-generated model based on the received data;
Counting the amount of values output from the computer-generated model;
Determining if the amount exceeds a threshold;
Generating a statistic value from the values output from the computer-generated model in response to determining that the amount exceeds the threshold;
Determining whether the statistical value is outside a pre-determined range;
Adjusting said statistical value to be within said pre-determined range, in response to determining that said statistical value is outside said pre-determined range; And
And transmitting the adjusted statistical value to the RF generator to control the RF generator to adjust the RF signal generated by the RF generator. 17. The method of claim 16,
The adjusted RF signal is provided to the plasma chamber through an RF cable, the impedance matching circuit, and an RF transmission line,
The RF cable couples the RF generator to the impedance matching circuit,
Wherein the RF transmission line couples the impedance matching circuit to the plasma chamber. 17. The method of claim 16,
Wherein the variable comprises power, or frequency, or voltage magnitude, or current magnitude, or phase between complex voltage and complex current, or complex current, or complex voltage, or a combination thereof. 17. The method of claim 16,
The impedance matching circuit matches the impedance of the source with the impedance of the load,
The source comprising an RF generator coupling the RF generator to the impedance matching circuit,
Wherein the rod comprises the plasma chamber and an RF transmission line,
Wherein the RF transmission line couples the plasma chamber to the impedance matching circuit. 17. The method of claim 16,
Wherein the plasma chamber comprises a chuck and an upper electrode facing the chuck. 17. The method of claim 16,
Wherein the variable comprises a complex voltage and current at a point in the plasma system. As a method,
Receiving data associated with a variable from a radio frequency (RF) generator, wherein the RF generator is configured to generate an RF signal to be supplied to the plasma chamber via an impedance matching circuit, the variable being associated with an RF system, The RF system includes receiving data associated with a variable from the radio frequency (RF) generator, the RF generator, the impedance matching circuit, and the plasma chamber;
Generating values in an output of the computer-generated model based on the received data;
Counting the amount of values output from the computer-generated model;
Determining if the amount exceeds a count threshold;
Generating a statistic value from the values output from the computer-generated model, in response to determining that the amount exceeds the count threshold;
Determining if the statistical value is outside a pre-determined extent;
Generating an indication of a fault in response to determining that the statistical value is outside the pre-determined degree; And
And transmitting an indication of the failure to the RF generator. 23. The method of claim 22,
Determining if the statistical value is within a pre-determined range;
Adjusting said statistical value to be within said pre-determined range, in response to determining that said statistical value is outside said pre-determined range; And
Further comprising transmitting the adjusted statistical value to the RF generator to control the RF generator to produce an adjusted RF signal to provide to the plasma chamber via the impedance matching circuit. 23. The method of claim 22,
The adjusted RF signal is provided to the plasma chamber through an RF cable, the impedance matching circuit, and an RF transmission line,
The RF cable couples the RF generator to the impedance matching circuit,
Wherein the RF transmission line couples the impedance matching circuit to the plasma chamber. 23. The method of claim 22,
The variable may be a power, or a frequency, or a real part of a load impedance, and an imaginary part of the load impedance, or a voltage magnitude, or a magnitude, or a phase between complex voltage and complex current, or wafer bias, A plasma potential, a complex current, or a complex voltage, or a load impedance, or a combination thereof. 23. The method of claim 22,
Wherein the variable comprises a complex voltage and current at a point in the plasma system.

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