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Researchers Submit Patent Application, "Method and Apparatus for Autonomous Tool Parameter Impact Identification System for Semiconductor...

June 4, 2014

Researchers Submit Patent Application, "Method and Apparatus for Autonomous Tool Parameter Impact Identification System for Semiconductor Manufacturing", for Approval

By a News Reporter-Staff News Editor at Electronics Newsweekly -- From Washington, D.C., VerticalNews journalists report that a patent application by the inventors Kaushal, Sanjeev (San Jose, CA); Patel, Sukesh Janubhai (Cupertino, CA); Polak, Wolfgang (Sunnyvale, CA); Waterman, Aaron Archer (Mountain View, CA); Wolfe, Orion (Oakland, CA), filed on November 9, 2012, was made available online on May 22, 2014.

The patent's assignee is Tokyo Electron Limited.

News editors obtained the following quote from the background information supplied by the inventors: "Progressive technological evolution of electronics and computing devices motivates advances in semiconductor technology. Growing consumer demand for smaller, higher performance, and more efficient computer devices and electronics has led to down-scaling of semiconductor devices. To meet device demand while restraining costs, silicon wafers upon which semiconductor devices are formed have increased in size.

"Fabrication plants working with large wafer sizes utilize automation to implement and control wafer processing. Such plants can be capital intensive, and accordingly, it is desirable to maintain highly efficient operation of fabrication equipment to minimize downtime and maximize yields. To facilitate these goals, measurement equipment is often employed to monitor fabrication equipment during wafer processing and to acquire measurement information on both the equipment and the processed wafer. The measurement information can then be analyzed to optimize fabrication equipment.

"According to an example, measurement information can include tool level information, which indicates a state or condition of fabrication equipment or a portion thereof, wafer metrology information specifying physical and/or geometric conditions of wafers being processed, electrical text information, and the like. In addition, spectroscopic data (e.g., spectral line intensity information), can be gathered to facilitate identification of etch endpoints by process engineers. However, in conventional fabrication environments, various measurement data is handled independently of one another for different purposes. As such, inter-relationships among various measurement data are not leveraged for advanced optimization of fabrication processes.

"The above-described deficiencies of today's semiconductor fabrication measurement and optimization systems are merely intended to provide an overview of some of the problems of conventional systems, and are not intended to be exhaustive. Other problems with conventional systems and corresponding benefits of the various non-limiting embodiments described herein may become further apparent upon review of the following description."

As a supplement to the background information on this patent application, VerticalNews correspondents also obtained the inventors' summary information for this patent application: "The following presents a simplified summary in order to provide a basic and general understanding of some aspects of exemplary, non-limiting embodiments described herein. This summary is not an extensive overview nor is intended to identify key/critical elements or to delineate the scope of the various aspects described herein. Instead, the sole purpose of this summary is to present some concepts in a simplified form as a prelude to the more detailed description of various embodiments that follow.

"One or more embodiments of the present disclosure relate to techniques for autonomously identifying relative impacts of tool parameter on selected tool performance indicators of a semiconductor fabrication system. To this end, a parameter impact identification system is provided that can leverage measured tool parameter data and tool performance data to identify the most critical tool parameters that influence a particular tool performance metric. The parameter impact identification system can also rank these critical parameters in order of their relative impact on the selected tool performance metric, providing maintenance personnel with a useful guide for identifying which critical tool parameters should be the focus of maintenance efforts to optimize the selected tool performance metric.

"The parameter impact identification system can determine the relative impacts of the respective tool parameters by separately analyzing each tool parameter and, for each parameter, attempting to predict the behavior of a selected tool performance indicator using the separated parameter. This reduces the complex dimensionality of semiconductor tool parameters into a single-input-single-output (SISO) problem, in which the tool performance indicator is described as a function of only a single tool parameter. The impact of each parameter on the performance indicator can then be determined based on an analysis of the resulting functions (e.g., by calculating a derivative of each function, by determining a predictive accuracy at each function, etc.), and the tool parameters ranked according to relative impact.

"In some embodiments, the parameter impact identification system can also generate a function that characterizes the selected tool performance indicator in terms of only the most important tool parameters as determined by the aforementioned ranking. By eliminating tool parameters having negligible impact on the performance indicator, the resulting function can greatly simplify the problem space for the end user and allow sharper focus on the critical tool parameters.

"To the accomplishment of the foregoing and related ends, certain illustrative aspects are described herein in connection with the following description and the annexed drawings. These aspects are indicative of various ways which can be practiced, all of which are intended to be covered herein. Other advantages and novel features may become apparent from the following detailed description when considered in conjunction with the drawings.


"FIG. 1 is block diagram illustrating an exemplary system for collecting and analyzing information relating to semiconductor production.

"FIG. 2 is a block diagram of an exemplary parameter impact identification system that can autonomously identify tool parameters that impact selected tool performance metrics.

"FIG. 3 is a block diagram illustrating processing functions performed by an exemplary parameter impact identification system.

"FIG. 4 illustrates an exemplary interface for selecting a tool performance indicator to be analyzed.

"FIG. 5 illustrates an exemplary interface for selecting one or more tool parameters that are to be considered by parameter impact identification system.

"FIG. 6 illustrates generation of a set of isolated parameter functions given a set of tool parameter and performance data.

"FIG. 7 illustrates assignment of quality scores to respective tool parameters based on isolated parameter functions.

"FIG. 8 illustrates assignment of sensitivity scores to respective tool parameters based on isolated parameter functions.

"FIG. 9 illustrates ranking of tool parameters according to relative impact on a tool performance indicator.

"FIG. 10 illustrates filtering of ranked tool parameters to identify a set of critical tool parameters having the highest impact on a tool performance indicator.

"FIG. 11 illustrates an exemplary interface for configuring tool parameter filtering criteria.

"FIG. 12 graphically summarizes identification of critical tool parameters according to one or more embodiments of the parameter impact identification system.

"FIG. 13 illustrates generation of a composite function that characterizes a tool performance behavior in terms of a reduced set of critical tool parameters.

"FIG. 14 illustrates updating of tool performance function in a continuously iterative manner.

"FIG. 15 is a flowchart of an example methodology for modeling a functional relationship between a tool performance indicator and a set of tool parameters of a semiconductor fabrication system.

"FIG. 16 is a flowchart of an example methodology for autonomously identifying and modeling tool parameter impact on a tool performance metric.

"FIG. 17 is an example computing environment.

"FIG. 18 is an example networking environment."

For additional information on this patent application, see: Kaushal, Sanjeev; Patel, Sukesh Janubhai; Polak, Wolfgang; Waterman, Aaron Archer; Wolfe, Orion. Method and Apparatus for Autonomous Tool Parameter Impact Identification System for Semiconductor Manufacturing. Filed November 9, 2012 and posted May 22, 2014. Patent URL:

Keywords for this news article include: Electronics, Semiconductor, Tokyo Electron Limited.

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Source: Electronics Newsweekly

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