Abstract: System and method for implementing a VM APC platform are described. In one embodiment, the VM APC system comprises a process tool for processing a plurality of wafers, a metrology tool for measuring a sample wafer of the plurality of wafers and generating actual metrology data therefor, and a VM model for predicting metrology data for each of the plurality of wafers. The actual metrology data is received from the metrology tool and used to update the VM model. Key variables of the virtual metrology model are updated only in response to a determination that the VM model is inaccurate and parameters of the VM model are updated responsive to receipt of the actual metrology data for the sample wafer of the plurality of wafers. The system also includes an APC controller for receiving the predicted metrology data and the actual metrology data and controlling an operation of the process tool based on the received data.

Abstract: A wafer fabrication outcome, such as wafer yield or wafer lifetime, is predicted by excluding uncontrollable but measurable internal/external noises of a DOE system, and by rendering relations between wafer design variables and wafer outcome outputs to be more causal, as well as the relations between variances for each of the wafer design variables and the wafer outcome outputs. With the aid of a wafer fabrication outcome predicting model formed by the more causal relations, precision of predicting wafer outcomes can be raised, and performance of wafer fabrication can be thus raised as a result.

Abstract: A computer-implemented initial run module processes manifest variable data using computer-defined model specification parameters stored in a database to provide initial estimates of weights that are associated with latent variables. The initial run module employs a unique value-based weighting partial least squares computer-implemented process. A final run module then operates upon the manifest variable data to determine the importance of the predictor values that are then used to control the industrial, manufacturing or commercial process. The final run module implements a unique patient partial least squares regression model utilizing a boosting learning technique.

Abstract: An electronic lens processing system receives a lens prescription and performs lens calculations to create a work ticket for manufacturing the lens. Information that the system used to create the work ticket, such as data files for lens materials and machine settings for controlling lens manufacturing equipment, are stored. The work ticket includes a form that specifies work ticket calculations and/or a graphic of the lens or lenses to be manufactured. The system displays the work ticket on an electronic screen, and a laboratory technician can select elements from the work ticket to receive supplemental information on those elements to aid in processing the lens or determining why a lens prescription is not manufacturable.

Abstract: System and method for data mining and feature tracking for fab-wide prediction and control are described. One embodiment is a system comprising a database for storing raw wafer manufacturing data; a data mining module for processing the raw wafer manufacturing data to select the best data therefrom in accordance with at least one of a plurality of knowledge-, statistic-, and effect-based processes; and a feature tracking module associated with the data mining module and comprising a self-learning model wherein a sensitivity of the self-learning model is dynamically tuned to meet real-time production circumstances, the feature tracking module receiving the selected data from the data mining module and generating prediction and control data therefrom; wherein the prediction and control data are used to control future processes in the wafer fabrication facility.

Abstract: Engineering requirements are defined in an electronic environment. In one embodiment, a method includes providing at least one of a set of master requirements and a set of version requirements to be applied to the electronic product definition, and referencing an electronic reference document from at least one of the set of master requirements and the set of version requirements, the electronic reference document including one or more particular engineering requirements to be applied to the electronic product definition. Alternately, a method includes defining a callout linked to the at least one of the set of master requirements and the set of version requirements, the callout being adapted to supersede a conflicting engineering requirement set forth in at least one of the set of master requirements and the set of version requirements.

Abstract: Methods for generating predicted product values of a product produced by a machine and for predicting a process of a machine are disclosed. A method for generating predicted product values of a product manufactured by a machine controlled by programmable logic control code includes presenting a machine input fields requesting parameters associated with actuators and mechanical elements, and presenting product input fields requesting desired product properties. The method further includes receiving parameters from the machine input fields, receiving desired product properties from the product input fields, and calculating output response data by an emulation of a mechanical operation of the machine using the parameters and the desired product properties. The output response data is provided to a product model that calculates predicted product values based on the output response data provided. The method further includes presenting the one or more predicted product values.

Abstract: The present disclosure provides a method of fabricating a semiconductor device. The method includes collecting a plurality of manufacturing data sets from a plurality of semiconductor processes, respectively. The method includes normalizing each of the manufacturing data sets in a manner so that statistical differences among the manufacturing data sets are reduced. The method includes establishing a database that includes the normalized manufacturing data sets. The method includes normalizing the database in a manner so that the manufacturing data sets in the normalized database are statistically compatible with a selected one of the manufacturing data sets. The method includes predicting performance of a selected one of the semiconductor processes by using the normalized database. The selected semiconductor process corresponds to the selected manufacturing data set. The method includes controlling a semiconductor processing machine in response to the predicted performance.

Abstract: System(s) and method(s) for optimizing performance of a manufacturing tool are provided. Optimization relies on recipe drifting and generation of knowledge that capture relationships among product output metrics and input material measurement(s) and recipe parameters. Optimized recipe parameters are extracted from a basis of learned functions that predict output metrics for a current state of the manufacturing tool and measurements of input material(s). Drifting and learning are related and lead to dynamic optimization of tool performance, which enables optimized output from the manufacturing tool as the operation conditions of the tool changes. Features of recipe drifting and associated learning can be autonomously or externally configured through suitable user interfaces, which also can be drifted to optimize end-user interaction.

Abstract: Methods and apparatus are disclosed herein. In some embodiments, methods of controlling process chambers may include predetermining a relationship between pressure in a processing volume and a position of an exhaust valve as a function of a process parameter; setting the process chamber to a first state having a first pressure in the processing volume and a first value of the process parameter, wherein the exhaust valve is set to a first position based on the predetermined relationship to produce the first pressure at the first value; determining a pressure control profile to control the pressure as the process chamber is changed to a second state having a second pressure and a second process parameter value from the first state; and applying the pressure control profile to control the pressure by varying the position of the exhaust valve while changing the process chamber to the second state.

Abstract: A method and system for optimizing modules of a steel manufacturing process includes a plurality of manufacturing modules for a manufacturing process. Each of the modules have a plurality of steps. The plurality of modules include at least an upstream module, a casting module, and a downstream module. Each of the plurality of modules have parameters, and include at least one variable event. The variable event is adjustable for optimization of the manufacturing process while the parameters are being maintained for each of the plurality of modules. A communication system is used for exchanging information between the modules while the manufacturing process is occurring to adjust the at least one variable event for optimizing the manufacturing process.

Abstract: Real-time condition-based analysis is performed on a machine for providing diagnostic and prognostic outputs indicative of machine status includes a signal processor for receiving signals from sensors adapted for measuring machine performance parameters. The signal processor conditions and shapes at least some of the received signals into an input form for a neural network. A fuzzy adaptive resonance theory neural network receives at least some of the conditioned and shaped signals, and detects and classifies a state of the machine based upon the received conditioned and shaped signals, and upon a predetermined ontology of machine states, diagnostics, and prognostics. The neural network can also determine from the machine state a health status thereof, which can comprise an anomaly, and output a signal representative of the determined health status. A Bayesian intelligence network receives the machine state from the neural network and determines a fault probability at a future time.

Abstract: A substrate processing apparatus including a controller connected to a plurality of sub-controllers for controlling a substrate processing, and an operating section having a display unit for showing an operation screen displaying a daily check data for checking utility equipment relating to each part and having a daily check initial parameter file defined in a client type, a presence of an item and unit conversion. The controller is configured to receive the daily check data from a sub-controller, to convert a unit of the received daily check data, and then to transfer the unit-converted daily check data to the operating section, and the operating section is configured to refer to the daily check initial parameter file and to display the daily check data transferred from the controller on the operation screen.

Abstract: In connection with a machining program used in machining a workpiece by means of a machine tool controlled by a numerical controller, interpolation data, a command position point sequence, and a servo position point sequence for each processing period are determined by simulation by designating speed data for giving a machining speed and precision data for giving a machining precision. A predicted machining time for workpiece machining is determined based on the determined interpolation data, and a predicted machining error for workpiece machining is determined based on the determined command and servo position point sequences. Further, the precision data and the speed data are determined for the shortest predicted machining time within a preset machining error tolerance, based on a plurality of predicted machining times and a plurality of predicted machining errors.

Abstract: Manufacturing planning data for a production process that is managed by a manufacturing execution system is updated by way of a plurality of steps, which include: Gathering data from a PLC level relevant to the manufacturing planning data and the execution of the production process; mapping the gathered data with the current manufacturing planning data in order to determine suggested changes between the gathered data and the current manufacturing planning data; applying a predetermined update scenario for the manufacturing planning data depending on the suggested changes to update the manufacturing planning data; and adapting the current production process and optionally following production processes according to the updated manufacturing planning data. The reliability of the so-called standard data used in production planning processes is thus dramatically improved.

Abstract: System and method for processing image data between adjacent imaging areas in a lithography manufacturing process are disclosed. In one embodiment, the method includes providing a parallel imaging writer system which has a plurality of spatial light modulator (SLM) imaging units arranged in one or more parallel arrays, receiving a mask data pattern to be written to a substrate, processing the mask data pattern to form a plurality of partitioned mask data patterns corresponding to different areas of the substrate, identifying an overlapping region between adjacent imaging areas to be imaged by corresponding SLMs, determining a stitching path for merging the adjacent imaging areas in the overlapping region in accordance with a set of predetermined cost functions, and controlling the plurality of SLM imaging units to write the plurality of partitioned mask data patterns to the substrate in parallel using the stitching path.

Abstract: For application to analog, mixed-signal, and custom digital circuits, a system and method to extract circuit-specific process/environmental corners that is yield-aware and/or specification-aware. Simulation data from previous Monte Carlo-based verification actions can be re-used.

Abstract: The invention provides a systems and methods for creating Double Pattern (DP) structures on a patterned wafer in real-time using Dual Pattern Contact-Etch (DPCE) processing sequences and associated Contact-Etch-Multi-Input/Multi-Output (CE-MIMO) models. The DPCE processing sequences can include one or more contact-etch procedures, one or more measurement procedures, one or more contact-etch modeling procedures, and one or more contact-etch verification procedures. The CE-MIMO model uses dynamically interacting behavioral modeling between multiple layers and/or multiple contact-etch procedures. The multiple layers and/or the multiple contact-etch procedures can be associated with the creation of lines, trenches, vias, spacers, contacts, and gate structures that can be created during Double Patterning (DP) procedures.

Abstract: The homogenization cycle of an alloy is optimized and controlled by defining a target degree of transformation to achieve at least one metallurgical property for an alloy. The desired metallurgical properties include, but are not limited to, dissolving precipitation hardening phases, transforming insoluble phases into preferred phases and precipitating the dispersoid phases to the proper size and distribution. Using regression analysis, a transformation model is obtained to predict the degree of transformation of an alloy by analyzing the degree of transformation of a plurality of sample alloys subjected to heating at predetermine temperatures for predetermined amounts of time.

Abstract: A method comprises computing respective regression models for each of a plurality of failure bins based on a plurality of failures identified during wafer electrical tests. Each regression model outputs a wafer yield measure as a function of a plurality of device performance variables. For each failure bin, sensitivity of the wafer yield measure to each of the plurality of device performance variables is determined, and the device performance variables are ranked with respect to sensitivity of the wafer yield measure. A subset of the device performance variables which have highest rankings and which have less than a threshold correlation with each other are selected. The wafer yield measures for each failure bin corresponding to one of the selected subset of device performance variables are combined, to provide a combined wafer yield measure. At least one new process parameter value is selected to effect a change in the one device performance variable, based on the combined wafer yield measure.

Abstract: A method for computer-aided generation determining of a method plan for the manufacture of sheet-metal forming parts by way of forming processes, comprises the following steps: determining a set of geometry features (11, 12, 13, 14, 15) of a part (10) in a geometry model of the part (10), wherein each of the geometry features (11, 12, 13, 14, 15) is described by a feature type and by way of geometric parameters for describing the geometric shape of the geometry features (11, 12, 13, 14, 15); determining an associated method standard for each of the geometry features (11, 12, 13, 14, 15), wherein a method standard describes one variant for manufacturing the respective geometry feature (11, 12, 13, 14, 15), the selection of the method standards which may be associated with a certain geometry features (11, 12, 13, 14, 15), is dependent on the feature type of the geometry feature (11, 12, 13, 14, 15), and wherein a method standard comprises at least one module, and a module represents a processing unit and des

Abstract: A manufacturing system which can restrain the margin of a semiconductor integrated circuit. The integrated circuit including a fixed circuit unit and a reconfigurable circuit unit outputs, to a configuration determining server, an operation time which was calculated by a detecting unit and a calculating unit. The configuration determining server, by using the operation time obtained from the integrated circuit, calculates performance data which indicates the characteristics of the fixed circuit unit, selects, based on the performance data, a piece of configuration information indicating a circuit configuration that is optimum for the processing of the reconfigurable circuit unit, and outputs the selected piece of configuration information. The integrated circuit builds a circuit in the reconfigurable circuit unit in accordance with the output piece of configuration information.

Abstract: Pattern formation simulations are performed based on design layout data subjected to OPC processing with a plurality of process parameters set in process conditions. A worst condition of the process conditions is calculated based on risk points extracted from simulation results. The design layout data or the OPC processing is changed such that when a pattern is formed under the worst condition based on the changed design layout data or the changed OPC processing a number of the risk points or a risk degree of the risk points of the pattern is smaller than the simulation result.

Abstract: Shape-wise thicknesses of a cover layer and first through (N?1)th intermediate layers of an optical recording medium having refractive indexes nr1, nr2 are converted into thicknesses t1, t2 of the respective layers having a predetermined refractive index which makes a divergent amount equal to a divergent amount of a light beam resulting from the thicknesses tr1, tr2, a difference DFF between the sum of a thickness “ti” through a thickness “tj”, and the sum of a thickness “tk” through a thickness “tm” is set to 1 ?m or more (where i, j, k, and m are each any positive integer satisfying i?j<k?m?N), and the thicknesses t1, t2 are calculated by products of a function f(n) expressed by the following formula (1), and the thicknesses tr1, tr2: f(n)=?1.088n3+6.1027n2?12.042n+9.1007 ??(1) in the formula (1), n=nr1, nr2, . . . , and nrN.

Abstract: The present disclosure provides a method. The method includes gathering advanced process control (APC) data from a subset of available wafers and a subset of available processing chambers. The method includes establishing a matrix that contains a plurality of cells. The cells each correspond to one of the available wafers and one of the available processing chambers. The matrix is partially filled by populating cells for which the APC data has been gathered. The method includes determining a plurality of chamber-coverage-rate (CCR) parameters associated with the matrix. The method includes optimizing the CCR parameters through an iteration process to obtain optimized CCR parameters. The method includes predicting an APC data value for a designated cell of the matrix based on the optimized CCR parameters. The designated cell is an empty cell before the predicting and is populated by the predicting.

Abstract: A method and system for automatically identifying an existing workflow to manufacture a given product type. A workflow description of a workflow can be transformed into a product type description utilizing particular facts associated with the workflow. An inferred product type description can then be at least one product type among a group of product type descriptions representing known product types. A mapping can then be derived of the workflow with respect to product types, in response to comparing the inferred product type description to the product type description(s) among product type descriptions representing known product types. The workflow description can be converted into the product type description utilizing a rule-based expert system. The particular facts can be one or more of the following: processing steps, sequences of processing steps, types of operations to be performed, and outputs produced.

Abstract: A system, method, and computer program product for automated development of templates for knowledge capture for use in computer aided design and manufacturing. A method includes receiving a user selection of one of a plurality of parts to be developed into a product template. The method also includes receiving data about the selected part, the data including a plurality of part components. The method further includes displaying parametric data relating to the part components and connections between the part components. The method still further includes receiving customizations to the parametric data from the user. The method also includes developing program code based on the customizations to the parametric data. The method also includes publishing the program code and the customized parametric data as the product template.

Abstract: A system is disclosed that simplifies configuring an MES entity corresponding to a SCADA system object representing plant equipment. The system includes an equipment model builder (EMB) that receives a set of configured UCO information for a modeled piece of plant equipment in a SCADA system. The EMB extracts relevant MES information from the utilization capability object and invokes an application interface on an MES database to create a corresponding entity (e.g., a database element). Another aspect of the disclosed system and methods involves the enhancement of a SCADA system object, through a new MES facet, to support acquiring and reporting equipment status received via the SCADA system to a corresponding MES entity. A raw reason code configuration interface is provided by UCO configurator computer software executed on a computer. Each raw reason code is associated with a prioritized logical expression defining circumstances under which the reason code becomes true.

Abstract: Methods and production control systems are presented in which design of experiments are performed in situ and produce model parameter estimates that relate actuator set points to any number of response variables, and the model is periodically updated based on these designed experiments and used as the basis for determining actuator set points.

Abstract: A method and system of optimizing a complex manufacturing process performed to achieve one or more processing objectives for the process and/or a component produced by the process. The system includes a graphical user interface, a process module, and an optimization module. The process module includes a training module, an empirical relationships database, an analytical equations database, a heuristic knowledge database, and a process models database. The graphical user interface is used to input one or more processing variables and constraints for the processing objective. The training module generates empirical relationships from the processing variable and empirical data obtained from the manufacturing process. The process module generates a process model that takes into consideration heuristic knowledge of the manufacturing process, empirical relationships, and optionally analytical equations relating to the manufacturing process.

Abstract: A method for magnetically aligning non-particles within a polymer, involving adding a magnetic nano-particle filler to a plastic material, such as a molten thermoplastic. The magnetic property allows the filler or particles to be aligned through the use of magnetic fields during the molding process. In one embodiment, the nano-particles are synthesized to a specific size, and are made by applying suitable coatings to existing fillers.

Abstract: The invention relates to managing performance of solar devices throughout a manufacturing process with multiple manufacturing steps.

Abstract: A quality control method includes: extracting, from a time series distribution of troubles that have occurred in electronic equipments, a first characteristics of states of occurrence of the troubles; specifying one or more parts included in the electronic equipments, the parts being involved with the troubles; extracting, from another time series distribution of a rate of use corresponding to each of suppliers which supply the specified parts, a second characteristics of the parts; and specifying one or more of the suppliers supplying the parts correlated to the troubles based on a correlation between the extracted first characteristics and the extracted second characteristics.

Abstract: A method of controlling process distribution of a semiconductor process includes receiving process distribution data representing the process distribution of the semiconductor process, receiving a parameter related to the process distribution, generating a virtual metrology model corresponding to the process distribution based on a relationship between the process distribution data and the parameter, and modifying a process variable affecting the process distribution based on the virtual metrology model.

Abstract: A radio frequency identification (RFID) tag is coupled to a circuit board to track the specific operating and environmental conditions of each manufacturing stage as the circuit board passes through the manufacturing stages. An RFID reader and data collector are used at each stage to read the RFID tag and store its identifying information along with processing information, operating conditions, and results for each stage. This permits to quickly and accurately collect manufacturing information for each circuit board at various manufacturing stages as well as the operating conditions for each stage at a particular time. Such manufacturing metrics can then be retrieved on a stage-by-stage basis for a particular circuit board by an identifier printed on the circuit board.

Abstract: The present invention provides a learning method of rolling load prediction which uses a prediction error of a rolling load at an actual pass of a stock in hot rolling to correct a predicted value of rolling load at a subsequent rolling pass. The method comprises changing a gain for multiplying with the prediction error of the rolling load at the actual pass in accordance with a thickness of the stock to thereby set the learning coefficient of the rolling load prediction and improve the precision of the prediction.

Abstract: A method includes controlling a process control system for coordinating the operation of a liquefied natural gas (LNG) process.

Abstract: In a method for designing a formed sheet-metal part performed by a processor of a computing system, by means of: a numerical model of a geometry of the part, a numerical simulation of a forming process, and local property variables associated with points of the part and computed from results of the numerical simulation, a method for managing problem zones of the formed sheet-metal part comprises the steps of: determining problem zones of the sheet-metal part based on the results of the numerical simulation; determining a visual representation of the sheet-metal part, and displaying this visual representation on a display operatively coupled to the processor; indicating the location of the problem zones on the sheet-metal part; and displaying on the display device information associated with the at least one problem zone whose location is indicated.

Abstract: A manufacturing executing system (MES) contains computing devices and software tools to control machines involved in a production process. The MES is configured to realize production requirements having at least one segment requirement. The MES further contains measures for a user to define whether a segment requirement is repeatable, and a database configured to store segment requirements. The database contains for each segment requirement: a dedicated area to store each segment requirement repeatability status; a dedicated area to store at least a current value of a parameter acquired during an execution of the segment requirement and representing the result of the execution of the segment requirement; and a dedicated area to store expected values of the parameter. Finally, the MES contains a coordinator operable to communicate with the database to access the segment requirement, and operable to determine whether the execution of a segment requirement has to be repeated.

Abstract: A set of optical rule checker (ORC) markers are identified in a simulated lithographic pattern generated for a set of data preparation parameters and lithographic processing conditions. Each ORC marker identifies a feature in the simulated lithographic pattern that violates rules of the ORC. A centerline is defined in each ORC marker, and a minimum dimension region is generated around each centerline with a minimum width that complies with the rules of the ORC. A failure region is defined around each ORC marker by removing regions that overlap with the ORC marker from the minimum dimension region. The areas of all failure regions are added to define a figure of demerit, which characterizes the simulated lithographic pattern. The figure of demerit can be evaluated for multiple simulated lithographic patterns or iteratively decreased by modifying the set of data preparation parameters and lithographic processing conditions.

Abstract: A method models a defect management routine. Both the modeling and a handling are executed within a manufacturing execution system. During an engineering phase: modeling the production process and creating a library of possible defect types which may occur; assigning the defect types to at least one defect group; creating a library of defect specifications; creating a library of defect type specification details; creating at least one runtime defect criteria that is used to link the defect type to a certain production volume; and creating a runtime defect measurement routine that monitors a corrective measure. During a runtime production phase evaluating the product produced; identifying the respective defect type out of the library of defect types; and using the identified defect type to determine a corrective measure, a runtime defect criteria identifying the resource causing the defect type, a production volume, and to run the respective runtime defect management routine.

Abstract: Methods and apparatus for predicting viscosities of glass materials as a function of temperature and composition are provided. Two fitting parameters (fitting coefficients) are used for each of the viscosity-affecting components contained in the material. The parameters can accurately cover a wide range of temperatures (i.e., a wide range of viscosities) and a wide range of compositions. The viscosity predictions can be used as a guide for glass research as well as in feedback control systems for glass manufacturing processes. Methods and apparatus for predicting glass resistivity are also disclosed.

Abstract: System, method and computer program product for combined scheduling of two different slab sequences by a rational technique. A two-dimensional grid graph having a direct slab sequence as a first dimension and an inventory slab sequence as a second dimension is prepared by processing of a computer as a data structure represented on a memory or a hard disk drive of the computer. A processing program of the computer generates two child nodes corresponding to a direct slab and an inventory slab, in each node of the two-dimensional graph according to a predetermined algorithm. By defining an appropriate weighting function, the processing program of the computer weights edges between nodes in the two-dimensional grid graph. After forming the weighted graph on a storage device of the computer such as the memory or the hard disk drive, the processing program of the computer calculates a path from a start point to an end point as a shortest path search problem.

Abstract: Properties of an end product, such as paper, paperboard or board, are important for the user of the end product. To be able to manufacture an end product of desired quality, it is important to know what kind of paper pulp used for manufacturing the end product results in a particular kind of property of the end product. Embodiments provide a method and an apparatus for generating a model, which model connects at least one property of the end product with at least one property of the paper pulp. On the basis of the model, also the manufacturing process can be controlled.

Abstract: A method is disclosed for optimization of continuous digestion process. Exemplary embodiments can control a delignification process in a continuous pulp digester in an optimal way for different pulp grades taking into account process disturbances and model uncertainties. This can be achieved by customizing a generic mathematical model for a continuous digestion process which runs through a software application on a dedicated electronic device. The model can be updated periodically based on on-line information, and used with a plant optimization component involving multiobjective optimization to evaluate optimal set points for the controllers. A system is also disclosed for optimizing control of a continuous pulp digester.

Abstract: A method and a system for optimization of parameters for a recovery boiler in a pulp mill are disclosed. An exemplary method is based on use of a first principle mathematical model to estimate parameters that are otherwise not measurable, to accurately control the performance of the recovery boiler. In addition, a method is disclosed to use estimated parameters of a recovery boiler to control and stabilize the processes downstream of the recovery boiler. A system is also disclosed to carry out a method for control and optimization of performance and operational parameters of a recovery boiler.

Abstract: A method of controlling surface non-uniformity of a wafer in a polishing operation includes (a) providing a model for a wafer polishing that defines a plurality of regions on a wafer and identifies a wafer material removal rate in a polishing step of a polishing process for each of the regions, wherein the polishing process comprises a plurality of polishing steps, (b) polishing a wafer using a first polishing recipe based upon an incoming wafer thickness profile, (c) determining a wafer thickness profile for the post-polished wafer of step (b), and (d) calculating an updated polishing recipe based upon the wafer thickness profile of step (c) and the model of step (a) to maintain a target wafer thickness profile. The model can information about the tool state to improve the model quality. The method can be used to provide feedback to a plurality of platen stations.

Abstract: Methods and apparatus for automated validation of semiconductor process steps are provided herein. In some examples, a method for validating a semiconductor process recipe includes: selecting a rule set describing an operating window for a semiconductor process tool; checking parameter values defined by steps in the semiconductor process recipe against limit-checking rules of the rule set to produce first results; determining step types from the steps in the semiconductor process recipe using step definition rules of the rule set to produce second results; checking transitions between the step types against step transition rules of the rule set to produce third results; and generating, using the computer, validation data for use of the semiconductor process recipe with the semiconductor process tool based on the first, the second, and the third results.

Abstract: The present invention applies the data mining methodology by which the wafer exposure effectiveness and efficiency are predictable in terms of the chip size, chip length and chip width. More specifically, in the present invention, an index, named “Mask-field-utilization weighted Overall Wafer Effectiveness” (MOWE), integrates the two parameters of “Overall Wafer Effectiveness” (OWE) and “Mask-Field-Utilization” (MFU), mainly regarding the wafer exposure effectiveness and efficiency respectively, in order to construct a model tree of the MOWE to achieve the data mining. By the MOWE model tree, the causal relationship between design independent variables and fabrication dependent variables is constructed, which can be accordingly applied as design guidelines in the design phase to improve the chip layout in order to produce a better wafer exposure effectiveness and efficiency.

Abstract: A system and related method for improving tire uniformity includes providing a number (n) of test tires manufactured in a known order and identifying at least one candidate cyclic process effect with a corresponding frequency of introduction (f). A given uniformity parameter, such as radial or lateral run-out, balance, mass variation, radial lateral or tangential force variation, is measured for each tire in the test set, and measured data points are combined into a concatenated composite waveform. At least one process harmonic associated with each identified cyclic process effect is separated from the tire harmonics, for example, by Fourier transformation with identification of the process harmonics as positive integer multiples of the mth harmonic of the measured uniformity parameter where m=n/f. Once the process harmonics are extracted, filtered uniformity measurements can be provided or new tires can be built with the process effect minimized.