The present invention relates to a method, and a system employing the method, for analyzing process module performance in semiconductor manufacturing, and more specifically, for analyzing process module performance using data collection and data analysis during semiconductor manufacturing.
Current microelectronics and submicron manufacturing includes semiconductor processing which may have multiple tools and processing chambers or process modules employed to produce high volume parts. As a result of greater manufacturing productivity requirements, tools and/or process module performance varying or shifting from base line performance may result in yield or reliability degradation. Current manufacturing processes are lacking the ability to diagnose undesirable process variations from specifications (i.e., base line parameters). Further, current manufacturing processes are lacking in the ability to compare and detect differences between like process tools. Additionally, there is a need in the industry to provide diagnostics which determine one or more causes of the undesirable variations. Further, there is also a need for improving data collection during a process to facilitate determining appropriate action during the process, which may include corrective action or termination of the process.
It would therefore be desirable to provide a method, and system employing the same, for capturing data for diagnosing base line variations during microelectronic manufacturing, e.g., semiconductor processing. It would further be desirable to provide data for diagnosing base line variations within process tool groups during manufacturing. Additionally, it would also be desirable to provide a diagnostic which determines one or more causes of undesirable variations from a base line. It would also be desirable to detect tools and/or processing modules having performance varying or shifting from base line performance specifications which may result in yield or reliability degradation
In an aspect of the invention a method for analyzing process module performance in semiconductor manufacturing includes: providing a plurality of process modules as part of at least one processing tool, the process modules including function specifications; initiating a process in the process module including steps, each step including performance parameters; detecting at least one predetermined measurement in the process module; generating data about the process module and the process steps; performing a statistical analysis of the process modules and the process steps using the generated data, and the performance parameters; determining variations in the data from the performance parameters of the steps and the function specifications of the process modules; computing process module mis-match statistics (PMMS); determining when a specified variation of PMMS occurs between the process modules function specifications and the step performance parameters; identifying and corresponding at least one process step and process module with the specified variation from the step performance parameters and the function specifications when the specified variation occurs; and presenting the specified variation with the corresponding process step and the process module having the specified variation.
In a related aspect, the PMMS computation uses multivariate data analysis. The step of generating data may include using historical data. The method may further include presenting data of the process steps with the specified variations from the performance parameters. The step of generating data may include collecting multi-variate metrics from a plurality of process modules running the same process. The tool may be part of a tool group, and the function specifications are for the tool group. The method may further include a plurality of process modules all of the same tool group. The method may also further include presenting process module data for each of the process steps. The plurality of processing tools may each include a plurality of process modules. The plurality of process modules may run the same processes. Each of the tool groups may include function specifications. The method ma further include: communicating the corresponding process step and process module to a process control device; determining a corrective action using the process control device; and modifying the process steps and the process module environment in the corresponding process module using the process control device. The data from the process module may include environmental data of an inner cavity of the process module.
In another aspect of the invention, a computer program product comprising a computer readable medium has recorded thereon a computer program for enabling a processor in a computer system to analyze process module performance in semiconductor manufacturing. A plurality of process modules are part of at least one processing tool and the process modules include function specifications. The computer program performs the steps of: initiating a process in the process module including steps, each step including performance parameters; detecting at least one predetermined measurement in the process module; generating data about the process module and the process steps; performing a statistical analysis of the process modules and the process steps using the generated data, and the performance parameters; determining variations in the data from the performance parameters of the steps and the function specifications of the process modules; computing process module mis-match statistics (PMMS); determining when a specified variation of PMMS occurs between the process modules function specifications and the step performance parameters; identifying and corresponding at least one process step and process module with the specified variation from the step performance parameters and the function specifications when the specified variation occurs; and presenting the specified variation with the corresponding process step and the process module having the specified variation.
In another aspect of the invention, a system for analyzing process module performance in semiconductor manufacturing includes a processing tool and a plurality of process modules as part of the processing tool. The process modules include function specifications, and the process modules run processes including steps wherein each step includes performance parameters. A detection device detects at least one predetermined measurement in the process module. A computing device uses a program stored on computer readable medium for generating data about the process module and the process steps. The computing device performs a statistical analysis of the process modules and the process steps using the generated data, and the performance parameters. The computing device determines variations in the data from the performance parameters of the steps and the function specifications of the process modules. The computing device computes process module mis-match statistics (PMMS) and determines when a specified variation of PMMS occurs between the process modules function specifications and the step performance parameters. The computing device identifies and corresponds at least one process step and process module with the specified variation from the step performance parameters and the function specifications when the specified variation occurs.
In a related aspect, the computing device presents the specified variation with the corresponding process step and the process module having the specified variation. The system may further include a second computing device communicating with the first computing device, the second computing device controlling the process modules and process steps. The second computing device may modifies the process steps in response to the statistical analysis from the first computing device.
These and other objects, features and advantages of the present invention will become apparent from the following detailed description of illustrative embodiments thereof, which is to be read in connection with the accompanying drawings, in which:
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The program 54 of computer 50 performs a data analysis embodied as a multivariate analysis 130, shown in
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The method of the present invention may also collect data for a plurality of tools in a tool group and analyze the data for anomalies which indicate that one or more tools are performing poorly, e.g., outside of specification. Thereby, the present invention can use data from tool groups to better indicate when a tool is malfunctioning or performing below standards.
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The method 100 performs the statistical analysis 130 (
While the present invention has been particularly shown and described with respect to preferred embodiments thereof, it will be understood by those skilled in the art that changes in forms and details may be made without departing from the spirit and scope of the present application. It is therefore intended that the present invention not be limited to the exact forms and details described and illustrated herein, but falls within the scope of the appended claims.