Patent application number | Description | Published |
20090292386 | System and Method for Automatic Virtual Metrology - A server, a system and a method for automatic virtual metrology (AVM) are disclosed. The AVM system comprises a model-creation server and a plurality of AVM servers. The model-creation server is used to construct the first set of virtual metrology (VM) models (of a certain equipment type) including a VM conjecture model, a RI (Reliance Index) model, a GSI (Global Similarity Index) model, a DQI | 11-26-2009 |
20110040596 | Virtual Production Control System and Method and Computer Program Product Thereof - A virtual production control system (VPCS), and a virtual production control method and a computer program product thereof are provided. At first, the VPCS processes historical work-in-process (WIP) information and a current shipping plan sent from a supplier side, thereby obtaining a plurality of sets of WIP input/output historical data and a goods output schedule. Then, the VPCS performs an integer programming (IP) method to find the latest output schedule in accordance to the current shipping plan; uses a genetic algorithm (GA) to fit the historical distributed-parameters; adopts a neural network (NN) method to predict the future distributed-parameters of production; and finally utilizes a Petri Nets to simulate and obtain a latest feasible input schedule and a latest feasible output schedule. | 02-17-2011 |
20110251707 | MANUFACTURING EXECUTION SYSTEM WITH VIRTUAL-METROLOGY CAPABILITIES AND MANUFACTURING SYSTEM INCLUDING THE SAME - A manufacturing execution system (MES) with virtual-metrology capabilities and a manufacturing system including the MES are provided. The MES is built on a middleware architecture (such as an object request broker architecture), and includes an equipment manager, a virtual metrology system (VMS), a statistical process control (SPC) system, an alarm manager and a scheduler. The manufacturing system includes a first process tool, a second process tool, a metrology tool, the aforementioned MES, a first R2R (Run-to-Run) controller and a second R2R controller. | 10-13-2011 |
20120029662 | ADVANCED PROCESS CONTROL SYSTEM AND METHOD UTILIZING VIRTUAL METROLOGY WITH RELIANCE INDEX - An advanced process control (APC) system, an APC method, and a computer program product, which, when executed, performs an APC method are provided for incorporating virtual metrology (VM) into APC. The present inventions uses a reliance index (RI) and a global similarity index (GSI) to adjust at least one controller gain of a run-to-run (R2R) controller when the VM value of a workpiece is adopted to replace the actual measurement value of the workpiece. The RI is used for gauging the reliability of the VM value, and the GSI is used for assessing the degree of similarity between the set of process data for generating the VM value and all the sets of historical process data used for building the conjecturing model. | 02-02-2012 |
20130159226 | Method for Screening Samples for Building Prediction Model and Computer Program Product Thereof - A method for screening samples for building a prediction model and a computer program product thereof are provided. When a set of new sample data is added to a dynamic moving window (DMW), a clustering step is performed with respect to all of the sets of sample data within the window for grouping the sets of sample data with similar properties as one group. If the number of the sets of sample data in the largest group is greater than a predetermined threshold, it means that there are too many sets of sample data with similar properties in the largest group, and the oldest sample data in the largest group can be deleted; if smaller than or equal to a predetermined threshold, it means that the sample data in the largest group are quite unique, and should be kept for building or refreshing the prediction model. | 06-20-2013 |
20130346024 | METHOD FOR FORECASTING WORK-IN-PROCESS OUTPUT SCHEDULE AND COMPUTER PROGRAM PRODUCT THEREOF - A method for forecasting a WIP (work in process) output schedule and a computer program product thereof are provided. A plurality of sets of historical WIP data regarding a product generated in respective historical periods are first collected, in which the product has a maximum historical production cycle. Thereafter, a predetermined time is used to divide the maximum historical production cycle into intervals. Then, the quantities of historical WIPs appearing in the respective intervals are computed in accordance with output times of the historical WIPs recorded in each of the sets of historical WIP data, thereby obtaining output probability density data series. If the number of the historical periods is greater than or equal to a minimum model-building number, a predicted output probability density data series of a next period following the historical periods is conjectured by using the output probability density data series in accordance with a prediction algorithm. | 12-26-2013 |
20140025315 | BASELINE PREDICTIVE MAINTENANCE METHOD FOR TARGET DEVICE AND COMPUTER PROGRAM PRODUCT THEREOF - A baseline predictive maintenance method for a target device (TD) and a computer program product thereof are provided. Fresh samples which are generated when the target device produces workpieces just after maintenance are collected, and a new workpiece sample which is generated when the target device produces a new workpiece is collected. A plurality of modeling samples are used to build a TD baseline model in accordance with a conjecturing algorithm, wherein the modeling samples include the new workpiece sample and the fresh samples. A TD healthy baseline value for the new workpiece is computed by the TD baseline model, and a device health index (DHI), a baseline error index (BEI) and baseline individual similarity indices (ISI | 01-23-2014 |
20140129503 | METHOD FOR PREDICTING MACHINING QUALITY OF MACHINE TOOL - A virtual metrology based method for predicting machining quality of a machine tool is provided. In this method, each product accuracy item is correlated with operation paths of the machine tool. During a modeling stage, the machine tool is operated to process workpiece samples, and sample sensing data of the workpiece samples associated with the operation paths are collected during the operation of the machine tool. The sample sensing data of each workpiece sample is de-noised and converted into the sample feature data corresponding to each feature type. The workpiece samples are measured with respect to the product accuracy item and integrated into the feature data for building a predictive model, thereby obtaining quality predicted data for each product accuracy item. During a usage stage, accuracy item values of a workpiece are predicted using the feature data during processing the workpiece in accordance with the predictive models. | 05-08-2014 |
20140180470 | BIN ALLOCATION METHOD OF POINT LIGHT SOURCES FOR CONSTRUCTING LIGHT SOURCE SETS - A bin allocation method of point light sources for constructing light source sets is provided. In this method, a matching matrix corresponding to each light source set product is provided for showing feasible combinations of bin codes of the point light sources which can be used for constructing the light source sets. Then, for reducing computation loading, the original matching matrix is reduced to a simplified matching matrix according to effective inventories of point light sources. Thereafter, the simplified matching matrix of each light source set product is applied to search for low exchangeable bin codes of the point tight sources among the light source set products. Then, the point light sources with the low exchangeable bin codes are precedently used for constructing the light source set products. | 06-26-2014 |
20140222376 | METHOD FOR SEARCHING, ANALYZING, AND OPTIMIZING PROCESS PARAMETERS AND COMPUTER PROGRAM PRODUCT THEREOF - A method for searching, analyzing, and optimizing process parameters and a computer product thereof are provided. At first, sets of process data that are generated when a process tool processes workpieces are obtained respectively, each set of process data including process parameters. Then, sets of metrology data measured by a metrology tool are obtained, wherein the sets of metrology data are corresponding to the sets of the process data in a one-to-one manner, each workpiece having at least one measurement point, each set of metrology data including at least one actual measurement value of at least one measurement item at the at least one measurement point. Thereafter, critical parameters are selected from the process parameters. Then, values of the critical parameters are adjusted to enable predicted measurement values of the measurement points of one workpiece to meet a quality target value. | 08-07-2014 |