This paper introduces a system for fault detection and classification in AC motors based on soft computing. The kernel of the system is a neuro-fuzzy system, FasArt (Fuzzy Adaptive System ART-based), that permits the ...
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This paper introduces a system for fault detection and classification in AC motors based on soft computing. The kernel of the system is a neuro-fuzzy system, FasArt (Fuzzy Adaptive System ART-based), that permits the detection of a fault if it is in progress and its classification, with very low detection and diagnosis times that allow decisions to be made, avoiding definitive damage or failure when possible. The system has been tested on an AC motor in which 15 nondestructive fault types were generated, achieving a high level of detection and classification. The knowledge stored in the neuro-fuzzy system has been extracted by a fuzzy rule set with an acceptable degree of interpretability and without incoherency amongst the extracted rules. (c) 2005 Elsevier Ltd. All rights reserved.
In this paper, we are going to propose the new algorithms to detect, classify, discriminate the transient and the reflected signal from noise and thus discriminate the fault section and locate the fault accurately on ...
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ISBN:
(纸本)078039156X
In this paper, we are going to propose the new algorithms to detect, classify, discriminate the transient and the reflected signal from noise and thus discriminate the fault section and locate the fault accurately on underground power cable system. Actually, at this system, it's very difficult to discriminate the transient because of the reflected signal including many noises. Therefore, how to solve the noise interference is a big problem. In this paper, authors present a solution based on multiple scales correlation of the transient using stationary wavelet transform. It's simple, quick and straightforward. For applying all algorithms, we just use the signal captured in single end.
As a part of the APC project at Infineon, an automated machine-alarm and -event analysis tool was developed to analyze machine- and process problems. This software is used in the high volume fabs in Munich, Regensburg...
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ISBN:
(纸本)0780383125
As a part of the APC project at Infineon, an automated machine-alarm and -event analysis tool was developed to analyze machine- and process problems. This software is used in the high volume fabs in Munich, Regensburg, Villach, Dresden and Richmond. It is a built-in part in the "APC-Trend" software[1], which shows trends and systematic deviations of machine and process parameters like temperature, pressure, gas flows and so on. This new tool gives excellent information about machine-problems and the relationship to product logistics, thereby flagging potentially bad lots and wafers for inspection and further analysis.
The semiconductor industry is going through a technology transition from 200mm to 300mm wafers to improve manufacturing efficiency and reduce manufacturing cost per chip. These technological changes present a unique o...
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The semiconductor industry is going through a technology transition from 200mm to 300mm wafers to improve manufacturing efficiency and reduce manufacturing cost per chip. These technological changes present a unique opportunity to optimally design the process control systems for the next generation fabs. In this paper we first propose a hierarchical fab-wide control framework with the integration of 300mm equipment and metrology tools and highly automated material handling system. Relevant existing run-to-run technology is reviewed and analyzed in the fab-wide control context, process and metrology data monitoring are discussed with an example, and missing components are pointed out as opportunities for future research and development. Concluding remarks are given at the end of the paper.
This paper details an advanced set of analyses designed to drive specific process variable setpoint adjustments or maintenance actions required for cost effective process control using the Dynamic Neural Controller(TM...
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ISBN:
(纸本)0780376730
This paper details an advanced set of analyses designed to drive specific process variable setpoint adjustments or maintenance actions required for cost effective process control using the Dynamic Neural Controller(TM) (DNC) wafer-to-wafer advisories for semiconductor manufacturing advanced process control. The new analytic displays and metrics are illustrated using data obtained on a LAM 4520XL at STMicroelectronics as part of a SEMATECH EPIT beta test evaluation. The DNC represents a comprehensive modeling environment that uses as its input extensive process chamber information and history of the time since maintenance actions occurred. The DNC uses a neural network to predict multiple quality output metrics and a closed-loop risk-based optimization to maximize process quality performance while minimizing overall cost of tool operation and machine downtime. The software responds in an advisory mode on a wafer-to-wafer basis as to the optimal actions to be taken. In this paper, we present three specific instances of patterns arising during wafer processing over time that signal the process or equipment engineer to the need for corrective action: either a process setpoint adjustment or specific maintenance actions. Based on the controller's recommended corrective action set with the overall risk reduction predicted by such actions, a metric of corrective action "urgency" can be created. The tracking of this metric over time yields different pattern types that signify a quantified need for a specific type of corrective action. Three basic urgency patterns are found: 1. a pattern in a given maintenance action over time showing increasing urgency or "risk reduction" capability for the action;2. a pattern in a process variable specific to a given recipe indicating a chronic request over time to only adjust the variable setpoint either above or below the cur-rent target;3. a pattern in a process variable existing over all recipes processed through the chamber indicating
A real-time wavelet multiresolution analysis (MRA)-based fault detection and classification algorithm is proposed in this paper. The first stage MRA detail signals extracted from the original signals are used as the c...
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A real-time wavelet multiresolution analysis (MRA)-based fault detection and classification algorithm is proposed in this paper. The first stage MRA detail signals extracted from the original signals are used as the criteria for this problem. By measuring the sharp variation values of the MRA detail signals, faults in the power system can be detected The fault type is then identified by the comparison of the three-phase MRA sharp variations. The effects of the fault distance, fault inception angle and fault impedance are examined, and the faultclassification routine is designed to overcome their effects. Simulation results show that this algorithm is effective and robust, and it is promising in high impedance faultdetection. (C) 1998 Elsevier Science Ltd. All rights reserved.
This paper discusses the integration and development of advanced process control technologies with AMD's Fab25 factory systems using the Advance Process Control Framework. The Framework is an open software archite...
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ISBN:
(纸本)0819434795
This paper discusses the integration and development of advanced process control technologies with AMD's Fab25 factory systems using the Advance Process Control Framework. The Framework is an open software architecture that allows the integration of existing factory systems, such as the manufacturing execution systems, configurable equipment interfaces, recipe management systems, metrology tools, process tools, and add-on sensors, into a system which provides advanced process control specific functionality. The Advanced Process Control Framework project was formulated to enable effective integration of Advanced Process Control applications into a semiconductor facility to improve manufacturing productivity and product yields. The main communication link between the factory system and the Framework is the Configurable Equipment Interface. It interfaces through a specialized component in the framework, the Machine Interface, which converts the factory system communication protocol, ISIS, to the Framework protocol, CORBA. The Framework is a distributed architecture that uses CORBA as a communication protocol between specialized components. A generalized example of how the Framework is integrated into the semiconductor facility is provided, as well as a description of the overall architecture used for process control strategy development. The main development language, Tcl/Tk, provides for increased development and deployment over traditional coding methods.
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