Advanced Micro Devices Corporation

Qingsu Wang

Michael Lee Miller

Terrence J Riley

Elfido Coss, Jr

Michael R Conboy

Glen W Scheid

Thomas J Sonderman

William Jarrett Campbell

Yi Cheng

Craig William Christian

Si-Zhao J Qin

John G Zvonar

Gerald W Barnett

W Jarrett Campbell

Kent F Knox

Denver L Dolman

Mike Simpson

R Michael Greig

John B Crowley

Jeff Thompson

A method is provided for configuring a final data set to use for modeling a manufacturing process, the method including requesting a real-time data set from a real-time database, requesting an historical data set from an historical database, and defining a required format for the final data set. The method also includes combining the real-time data set from the real-time database with the historical data set from the historical database using the required format for the final data set.

Automated system for extracting and combining tool trace data and wafer electrical test (WET) data for semiconductor processing

A method for identifying faulty wafers includes processing a set of wafers in a tool; collecting tool state information during the processing of the set of wafers; generating a tool state information baseline; comparing the tool state information for each wafer to the tool state information baseline to identify any wafers with outlying tool state information; and designating a particular wafer in the set as suspect in response to identifying outlying tool state information for the particular wafer. A processing line includes a tool adapted to process a set of wafers, and a process controller. The process controller is adapted to collect tool state information during the processing of the set of wafers, generate a tool state information baseline, compare the tool state information for each wafer to the baseline tool state information to identify any wafers with outlying tool state information, and designate a particular wafer in the set as suspect in response to identifying outlying tool state information for the particular wafer.

Method and apparatus for using tool state information to identify faulty wafers

A method and apparatus for providing fault detection in an Advanced Process Control (APC) framework. A first interface receives operational state data of a processing tool related to the manufacture of a processing piece. The state data is sent from the first interface to a fault detection unit. A fault detection unit determines if a fault condition exists with the processing tool based upon the state data. A predetermined action is performed on the processing tool in response to the presence of a fault condition. In accordance with one embodiment, the predetermined action is to shutdown the processing tool so as to prevent further production of faulty wafers.

Method and apparatus for fault detection of a processing tool and control thereof using an advanced process control (APC) framework

The present invention provides for a method and an apparatus for fault model analysis in manufacturing tools. A sequence of semiconductor devices is processed through a manufacturing process. Production data resulting from the processing of the semiconductor devices is acquired. A fault model analysis is performed using the acquired production data.

Method and apparatus for fault model analysis in manufacturing tools

A metbod for perforning a wafer-less qualification of a processing tool includes creating a wafer-less qualification model for the processing tool. Qualification data is generated from the processing tool iiiring a wafer-less qualification process. The qualification data is compared with the wafer-less qualification model. The processig tool is determined to be operating in a predefined state based on the comparison of the qualification data with the wafer-less qualification model.

Wafer-less qualification of a processing tool

A method and apparatus for performing manufacturing system analysis upon a manufacturing network. Real-time production data is collected. The real-time production data is stored in a static file database. A real-time data flow is emulated using said real-time production data from said static file database. A reactive function analysis is performed.

Method and apparatus for generating real-time data from static files

The present invention provides a method and apparatus for performing automated development and updating of a manufacturing model for a manufacturing process. An initial manufacturing model is developed. Tolerances of the manufacturing model are expanded using additional production data. The manufacturing model is then re-developed using the expanded tolerances.

Method and apparatus for updating a manufacturing model based upon fault data relating to processing of semiconductor wafers

Method and apparatus for fault detection of a processing tool in an advanced process control (APC) framework

A method and apparatus for providing near real-time fault detection in a manufacturing process is provided. The apparatus includes a processing tool adapted to manufacture a processing piece and an interface, coupled to the processing tool, for receiving operational data from the processing tool related to the manufacture of the processing piece, and product data defining characteristics of the processing piece. In one embodiment, the processing tool is in the form of semiconductor fabrication equipment and the processing piece is a silicon wafer. A fault detection unit is provided to determine if a fault condition exists with the processing tool from the operational data or with the processing piece from the product data. An Advanced Process Control (APC) framework is further provided to receive the operational and product data from the first interface, and to send the data to the fault detection unit.

Method and apparatus for integration of real-time tool data and in-line metrology for fault detection in an advanced process control (APC) framework

A method is provided, the method comprising preheating a rapid thermal processing chamber according to a preheating recipe and processing a first plurality of workpieces in the rapid thermal processing chamber. The method also comprises performing first parameter measurements on first and second workpieces of the first plurality of workpieces, the first parameter measurements indicative of first processing differences between the first and second workpieces, and forming a first output signal corresponding to the first parameter measurements. The method further comprises adjusting the preheating recipe based on the first output signal and using the adjusted preheating recipe to preheat the rapid thermal processing chamber for processing a second plurality of workpieces in the rapid thermal processing chamber to reduce second processing differences between first and second workpieces of the second plurality of workpieces.

Lot-to-lot rapid thermal processing (RTP) chamber preheat optimization

Methods of optimizing a preheat recipe for rapid thermal processing workpieces are provided. In one aspect, a method of manufacturing is provided that includes preheating a rapid thermal processing chamber according to a preheating recipe and processing a first plurality of workpieces in the rapid thermal processing chamber. Parameter measurements are performed on a first workpiece and a second workpiece of the first plurality of workpieces. The parameter measurements are indicative of processing differences between the first and second workpieces. An output signal is formed corresponding to the parameter measurements and a control signal based on the output signal is used to adjust the preheating recipe for preheating the rapid thermal processing chamber for processing a second plurality of workpieces in the rapid thermal processing chamber to reduce processing differences between first and second workpieces of the second plurality of workpieces.

A system and method for calculating the performance of a cluster tool using a weighted configuration matrix. The system includes a computer system which maintains a database of entities corresponding to semiconductor wafer processing modules in a fab. A user 'clusters' the entities, i.e., selects entities to reflect the relationship of the constituent modules physically linked together which form the cluster tool. The user also designates a main module against which the main performance events of the cluster tool, such as begin run and end run, are logged in the database. The computer system configures all of the 'up' and 'down' state configuration combinations of the cluster tool modules and displays the configurations for the user. The user specifies a weight for each of the configurations based upon an estimate of the performance the cluster tool while in the respective configuration relative to the performance of the cluster tool in a fully operable configuration. For example, the user may choose the weights based upon the throughput of wafers capable of being processed by the cluster tool in each of the respective configurations, the number of wafer processes capable of being performed by the cluster tool in each of the respective configurations, or the economic value added (EVA) by the wafer processes capable of being performed by the cluster tool in each of the respective configurations. The computer system compiles the configurations and received weights into a weighted configuration matrix which is used to calculate the performance of the cluster tool. In particular, the E10 metrics and OEE metric components are calculated as a measure of the reliability, availability, maintainability, operational efficiency and utilization aspects of performance of the cluster tool over a total period of time. Formulas for calculating various of the metrics using the configuration matrix are provided. The method is applicable to both sequential and parallel type cluster tools and does not require additional data tracking beyond currently tracked data.

System and method for calculating cluster tool performance metrics using

A system and method for detecting faults in wafer fabrication process tools by acquiring real-time process parameter signal data samples used to model the process performed by the process tool. The system includes a computer system including a DAQ device, which acquires the data samples, and a fault detector program which employs a process model program to analyze the data samples for the purpose of detecting faults. The model uses data samples in a reference database acquired from previous known good runs of the process tool. The fault detector notifies a process tool operator of any faults which occur thus potentially avoiding wafer scrap and potentially improving mean time between failures. The fault detector also receives notification of the occurrence of process events from the process tool, such as the start or end of processing a wafer, which the fault detector uses to start and stop the data acquisition, respectively. The fault detector also receives notification of the occurrence of a new process recipe and uses the recipe information to select the appropriate model for modeling the data samples. The fault detector employs a standard data exchange interface, such as DDE, between the fault detector and the model, thus facilitating modular selection of models best suited to the particular fabrication process being modeled. Embodiments are contemplated which use a UPM model, a PCA model, or a neural network model.

System and method for performing real time data acquisition, process

Method and system for automatically and accurately generating E10 reports based on a user-selected set of parameters, including date range, equipment and other parameters, are disclosed. In a preferred embodiment, the system of the present invention performs three primary functions; namely, a mapping function, a data extraction function and a reporting application function. The mapping function enables users to map WorkStream events into E10 defined states outside of the WorkStream database. The reporting application function provides several major functional capabilities, particularly, enabling a user to formulate restriction information, or 'E10 data requests,' for data extraction and reporting purposes. Each E10 data request identifies, as a function of facility (or manufacturing area), module, family and/or equipment, the equipment list for which data is to be accumulated, as well as a time period for reporting and duration type to report on. In addition, the reporting application function enables the user to display all E10 calculations for each piece of equipment in the extracted data set and to generate and display via a video terminal, printer and/or plotter, standard and custom graphic reports from the extracted E10 data calculations. The data extraction function provides the necessary data extraction capabilities and E10 data request management by managing and executing the requests submitted by users and purging old requests from the queue. In one aspect of the invention, the system comprises a user interface for facilitating the user's formulation of requests, mapping of WorkStream events to E10 states and substates, and viewing and/or printing reports in textual and graphical formats.

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Austin, TX, United States of America

Qingsu Wang