Patent application number | Description | Published |
20080276128 | Metrics independent and recipe independent fault classes - A method and apparatus for diagnosing faults. Process data is analyzed using a first metric to identify a fault. The process data was obtained from a manufacturing machine running a first recipe. A fault signature that matches the fault is identified. The identified fault signature was generated using a second metric and/or a second recipe. At least one fault class that is associated with the fault signature is identified. | 11-06-2008 |
20080276136 | Graphical user interface for presenting multivariate fault contributions - Methods and apparatuses for presenting multivariate fault contributions in a user interface are described. A user interface is provided to illustrate a fault for a sample manufactured by a process containing multiple variables, each having at least two components. The user interface presents one group of components of the multiple variables in a first axis and a second group of components of the multiple variables in a second axis and graphically illustrates contributions to the fault associated with the multiple variables by associating a contribution of each component in the one group of components of the multiple variables to each corresponding component in the second group of components of the multiple variables. | 11-06-2008 |
20080276137 | Graphical user interface for presenting multivariate fault contributions - Recipe steps of a manufacturing process run that generated a fault are displayed in a current view of a user interface, the recipe steps being displayed in association with a first axis. At least one of measured parameters or calculated parameters of the manufacturing process run are displayed in the current view, where at least one of the measured parameters and the calculated parameters are displayed in association with a second axis. A plurality of intersections of the recipe steps with at least one of the measured parameters or the calculated parameters are displayed in the current view, each of the plurality of intersections including a representation of a fault contribution attributable to at least one of a distinct measured parameter or a distinct calculated parameter at a distinct recipe step. | 11-06-2008 |
20080294281 | Dynamic inline yield analysis and prediction - In one embodiment, a method for predicting yield includes calculating a criticality factor (CF) for each of a plurality of defects detected in an inspection process step of a wafer, and determining a yield-loss contribution of the inspection process step to the final yield based on CFs of the plurality of defects and the yield model built for a relevant design. The yield-loss contribution of the inspection process step is then used to predict the final yield for the wafer. | 11-27-2008 |
20080295047 | Stage yield prediction - In one embodiment, a method for predicting yield during the design stage includes receiving defectivity data identifying defects associated with previous wafer designs, and dividing the defects into systematic defects and random defects. For each design layout of a new wafer design, yield is predicted separately for the systematic defects and the random defects. A combined yield is then calculated based on the yield predicted for the systematic defects and the yield predicted for the random defects. | 11-27-2008 |
20080295048 | Inline defect analysis for sampling and SPC - In one embodiment, an inline defect analysis method includes receiving geometric characteristics of individual defects and design data corresponding to the individual defects, determining which of the individual defects are likely to be nuisance defects using the geometric characteristics and the corresponding design data, and refraining from sampling the defects that are likely to be nuisance defects. | 11-27-2008 |
20080295063 | Method and apparatus for determining factors for design consideration in yield analysis - Embodiments of the present invention provide methods and apparatuses for determining factors for design consideration in yield analysis of semiconductor fabrication. In one embodiment, a computer-implemented method for determining factors for design consideration in yield analysis of semiconductor fabrication includes obtaining a geometric characteristic of a defect on a chip and obtaining design data of the chip, where the design data is associated with the defect. The method further includes determining a criticality factor of the defect based on the geometric characteristic and the design data, and outputting the criticality factor. | 11-27-2008 |
20110060443 | SCHEDULING MODELING SYSTEM FOR ADAPTIVE, AUTOMATED DATA COLLECTION AND PERFORMANCE ANALYSIS OF MANUFACTURING SYSTEM FOR OPTIMAL SCHEDULING - A scheduler system obtains a basic model of a manufacturing process for the production of one or more products. The basic model is based on a first set of data collected at a point in time from a plurality of tools used to manufacture the one or more products. The system incorporates a second set of data, which is collected from the plurality of tools after the first set of data, into the basic model to generate a comprehensive model of the manufacturing process. The second set of data reflects a current state of a factory. The system evaluates a plurality of scheduling policies using the comprehensive model and selects an optimal scheduling policy from the plurality of scheduling policies based on the comprehensive process model evaluation to achieve a manufacturing objective. | 03-10-2011 |
20120130520 | FACTORY LEVEL PROCESS AND FINAL PRODUCT PERFORMANCE CONTROL SYSTEM - A factory control server stores module configuration data for modules. The modules include processes for producing a final product and have corresponding module requirements. The factory control server analyzes in real-time actual product output data that is generated by a final product tester after a factory produces at least one final product to determine whether the actual product output data meets an expected product output. The factory control server analyzes actual module data in real-time to determine a new module requirement to cause new actual product output data for a subsequent final product to meet the expected product output in response to a determination that the actual product output data does not meet the expected product output. The factory control server notifies a module controller in real-time of the new module requirement. The module controller changes parameters in real-time to manufacture the subsequent final product. | 05-24-2012 |