Method and system for analyzing data from a plasma process

Abstract

A method and system for analyzing multivariate data of plasma processes in which response surface and neural networks are utilized to improve or find optimal process settings of the plasma process such that performance measurements are compared against model measurements to modify a current plasma process to achieve optimized processing performance.

1 . A system for monitoring and analyzing multivariate plasma processing data, comprising: 
 a processing chamber configured to facilitate generation of plasma in a processing region;    a first mechanism configured to measure at least one processing parameter;    a second mechanism configured to measure at least one performance parameter;    a device configured to analyze data from the first mechanism and the second mechanism based upon a mathematical model to improve performance of the system; and    a device configured to adjust the at least one processing parameter based upon performance parameters applied to the mathematical model.    
     
     
         2 . The system of  claim 1 , wherein the processing chamber is an etch chamber.  
     
     
         3 . The system of  claim 1 , wherein the processing chamber comprises: 
 a substrate positioned for processing;    a gas injection mechanism configured to introduce process gas into the processing region; and    a vacuum pumping mechanism, wherein the at least one performance parameters includes a characteristic of the process gas and pressure in the processing chamber.    
     
     
         4 . The system of  claim 3 , wherein the substrate is one of a wafer and a liquid crystal display.  
     
     
         5 . The system of  claim 3 , further comprising a device configured to control the temperature of the substrate, wherein the at least one processing parameters includes a measure of substrate temperature.  
     
     
         6 . The system of  claim 1 , further comprising: 
 an RF generator configured to couple energy to the processing chamber to generate plasma in the processing region;    a gas injection mechanism coupled to the processing chamber; and    a pressure measuring device coupled to the processing chamber and configured to measure pressure in the processing chamber,    wherein the at least one processing parameters includes characteristics of process gas introduced to the processing region by gas injection mechanism.    
     
     
         7 . The system of  claim 1 , further comprising one of a mechanically and electrically rotating magnetic field mechanism disposed about the processing chamber.  
     
     
         8 . The system of  claim 1 , wherein the mathematical model includes one of a response surface model and a neural network model.  
     
     
         9 . A method for monitoring and analyzing multivariate data from a plasma process, comprising: 
 measuring performance parameters of the plasma process;    measuring a number of harmonic parameters of the plasma process;    determining a mathematical model of the plasma process;    applying the measured performance parameters and harmonic parameters to the mathematical model of the plasma process;    predicting process parameters based upon the performance parameters, harmonic parameters, and the applied mathematical model; and    adjusting the processing parameters in response to the applied mathematical model.    
     
     
         10 . The method of  claim 9 , wherein the mathematical model is one of a response surface model and a neural network model.  
     
     
         11 . The method of  claim 9 , wherein the process parameters are predicted in-situ.  
     
     
         12 . The method of  claim 9 , wherein performance parameters include at least one of etch rate, deposition rate, etch selectivity, etch critical dimension, etch feature anisotrophy, plasma density, ion energy, mask film thickness, mask pattern critical dimension, self-induced DC substrate bias, and peak-to-peak RF substrate bias.  
     
     
         13 . The method of  claim 9 , wherein the process parameters include at least one of process pressure, process gas flow rate, upper electrode RF power, process gas, lower electrode RF power, substrate temperature, electrode sizing, film material viscosity, film material surface tension, exposure time, and depth of focus.