34results about "PIc I-O input output" patented technology

A method and apparatus for data analysis according to various aspects of the present invention is configured to automatically identify a characteristic of a component fabrication process guided by characteristics of the test data for the components. A method and apparatus according to various aspects of the present invention may operate in conjunction with a test system having a tester, such as automatic test equipment (ATE) for testing semiconductors.

A yield patrolling system, which monitors production yield of a manufacturing line, has at least one product measurement and test device. The product measurement and test device measures yield determining parameters of product at completion of process steps executed by equipment within the manufacturing line. The system further has a test database in communication with the product measurement and test device to receive and retain the measured yield determining parameters. A statistical calculator is in communication with the test database to receive the measured yield determining parameters. The statistical calculator then calculates from the measured yield determining parameters production yield statistics indicating an amount of the product being fabricated on the manufacturing line. A yield-warning device is in communication with the statistical calculator to receive the production yield statistics and to provide a yield warning alert to a responsible person indicating that the manufacturing line is not fabricating product with a sufficient yield. Further, a yield information interface receives a compilation of the production yield statistics for each process step from the statistical calculator.

A method for monitoring a manufacturing process features acquiring metrology data for semiconductor wafers at the conclusion of a final process step for the manufacturing process (“Step a”). Data is acquired for a plurality of process variables for a first process step for manufacturing semiconductor wafers (“Step b”). A first mathematical model of the first process step is created based on the metrology data and the acquired data for the plurality of process variables for the first process step (“Step c”). Steps b and c are repeated for at least a second process step for manufacturing the semiconductor wafers (“Step d”). An nth mathematical model is created based on the metrology data and the data for the plurality of process variables for each of the n process steps (“Step e”). A top level mathematical model is created based on the metrology data and the models created by steps c, d and e (“Step f”). The top level mathematical model of Step f is based on those process variables that have a substantial effect on the metrology data.

The present invention is generally directed to various methods and systems for fault detection control of multiple tools based upon external data. In one illustrative embodiment, the method includes monitoring each of a plurality of tools to determine if a fault condition occurs in any of the tools, each of the tools being comprised of at least one integrated metrology device, monitoring external data regarding at least one parameter that may impact an operation performed in each of the tools, and determining if an indicated fault condition in at least one of the tools is a valid fault condition or a systemic fault condition associated with a change in a value of the at least one parameter.

A method and apparatus for data analysis according to various aspects of the present invention is configured to automatically identify a characteristic of a component fabrication process guided by characteristics of the test data for the components.

Manufacturing execution systems relating to methods, systems, and software program for validation of pharmaceutical manufacturing processes and quality assurance process are described and disclosed herein. Consequently, the methods provide a means to perform validation on an integrated level whereby the quality control unit can ensure data and product integrity and minimize cost.

A method for distinguishing between sources of process variation includes processing a plurality of manufactured items in a process flow; storing a set of production environment data associated with each of the manufactured items; identifying manufactured items associated with a process drift; generating a plurality of characteristic threads based on the production environment data; comparing the characteristic threads for at least those manufactured items associated with the process drift; and determining at least one potential cause for the process drift based on the comparison of the characteristic threads. A manufacturing system for distinguishing between sources of process variation is also provided. The manufacturing system includes a plurality of tools for processing manufactured items in a process flow, a database server, and a drift monitor.

An abnormality detection system includes a measurement unit, a decision unit, an alarm unit, and storage units, and serves to detect the abnormality in a control characteristic value of a plurality of products manufactured on the same production line. The decision unit receives the control characteristic value stored in the storage unit, and decides whether an abnormality exists, based on that value. More specifically, the decision unit decides that the control characteristic value is abnormal when, with respect to m (m is a natural number) pieces of the products that are consecutively manufactured, an absolute value of a difference in control characteristic value between each of the products and another manufactured immediately before the former is equal to or less than a predetermined constant.

Manufacturing execution systems relating to methods, systems, and software program for validation of pharmaceutical manufacturing processes and quality assurance process are described and disclosed herein. Consequently, the methods provide a means to perform validation on an integrated level whereby the quality control unit can ensure data and product integrity and minimize cost.

A method of monitoring a processing system in real-time using low-pressure based modeling techniques that include processing one or more of wafers in a processing chamber; determining a measured dynamic process response for a rate of change for a process parameter; executing a real-time dynamic model to generate a predicted dynamic process response; determining a dynamic estimation error using a difference between the predicted dynamic process response and the expected process response; and comparing the dynamic estimation error to operational limits.

Methods, systems, and software program for validation of pharmaceutical manufacturing processes and quality assurance process are described and disclosed herein. Consequently, the methods provide a means to perform validation on an integrated level whereby the quality control unit can ensure data and product integrity and minimize cost.

Method and system for defect detection in manufacturing integrated circuits. In an embodiment, the invention provides a method for identifying one or more sources for possible causing manufacturing detects in integrated circuits. The method includes a step for providing a plurality of semiconductor substrates. The method includes a step for processing the plurality of semiconductor substrates in a plurality of processing steps using a plurality of processing tools. The method additionally includes a step for providing a database, which includes data associated with the processing of the plurality of semiconductor substrates. The method further includes a step for testing the plurality of semiconductor wafers after the processing of the plurality of semiconductor substrates. Additionally, the method includes a step for detecting at least one defect characteristic associated with the plurality of the semiconductor substrates that have been processed. Moreover, the method includes a step for identifying a set of processing steps. For example, the set of processing step are possibly associated with the defect characteristic.

System and method for detecting suspicious process faults. A preferred embodiment comprises determining a strength relationship between wafer acceptance test (WAT) parameters and process steps. The strength relationships indicate the affect of a failed process step on the value of a WAT parameter. Thus, if a WAT parameter is not within the parameters set in the WAT, then the suspicious process steps that caused the failure are the process steps that had a strength relationship with the failed WAT parameter. Furthermore, in a preferred embodiment, negative inferences are determined and utilized to determine a degree of suspiciousness. The degree of suspiciousness is used to determine a total degree of suspiciousness.

The invention discloses a process quality prediction system and a method thereof. When a processing apparatus performs a process on a target, the process is measured by a measurement apparatus to receive a process value. The process value and several previous quality data collected from the measurement apparatus are used to predict the quality of the product which is processing inline. The method is composed of a moving window, a stepwise regression scheme and an analysis of covariance (ANCOVA). The drift and shift of process are overcome by the moving window. A key variable set is selected by the stepwise regression scheme and a virtual model is identified by the analysis of covariance.

Embodiments of the present invention pertain to methods of evaluating processes for manufacturing components. In one embodiment, an average probability of a first component to fail is calculated based on a measurement of a parameter where the first component was built using a new process. Another average probability of a second component to fail is calculated based on a measurement of the parameter where the second component was built using an existing process. A process index is calculated by determining a difference between the average probabilities for the second component and the first component. An estimation is made as to whether the new process is better than the existing process based on the process index.

The invention relates to a method and a system for detecting deflects in the manufacture of an integrated circuit. In one embodiment, the invention provides a method for detecting one or more sources possibly causing manufacturing deflects of the integrated circuit. The method comprises a step of providing a plurality of semiconductor substrates, a step of using a plurality of processing devices to process the plurality of semiconductor substrates in a plurality of processing steps, a step of providing a data base including the data related to the processing of the plurality of semiconductor substrates, a step of detecting a plurality of semiconductor chips after the processing of the plurality of semiconductor substrates, a step of detecting at least one defective feature related to the plurality of processed semiconductor substrates and a step of detecting a processing step collection, for example, the processing step collection is possibly related to the defective feature.

A method for inputting a foreign substance inspection map created by foreign substance inspection for a wafer surface after each processing process in a wafer processing process, inputting a die sort map created by a die sort test after the wafer processing process, setting region segments in the wafer, setting a region number for each segment, calculating foreign substance density of the region segments, based on the foreign substance inspection map, and plotting the foreign substance density, using the region numbers, to calculate a foreign substance inspection map waveform characteristic amount, calculating failure density in the region segments, based on the die sort map, and plotting the failure density, using the region numbers, to calculate a die sort map waveform characteristic amount, calculating similarity between the foreign substance inspection map waveform characteristic amount and the die sort map waveform characteristic amount, and identifying a processing process cause of failure occurrence.