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A novel quality prognostics scheme (QPS) for plasma sputtering in TFT-LCD manufacturing processes is proposed. The QPS consists of a conjecture model and a prediction model. The conjecture model can use processing parameters and sensor data to estimate the processing quality (sputtering thickness) in real time. This conjecture function is also called virtual metrology. On the other hand, the prediction model is capable of predicting the processing quality of the next-lot glasses. Neural networks and weighted moving average algorithms are applied to construct the QPS. In particular, a reliance index is developed such that online evaluation of whether the conjecture results of the QPS are trustworthy or not is possible. For increasing the accuracy of the QPS, a self-searching mechanism is designed to automatically search the best set of parameters and functions used by the conjecture and prediction algorithms for cases that the processing properties vary or the recipe changes. Also, an auto-adjusting mechanism is developed for tuning the system parameters of the QPS and bringing the conjecture accuracy within an acceptable bound. Thorough tests using normal and abnormal processing data on one set of plasma sputtering equipment in a TFT-LCD plant show that the values of the mean absolute percentage error of both the conjecture and the prediction results are less than 2%, which validates the effectiveness of the proposed QPS.Index Terms-Conjecture model, neural networks (NNs), prediction model, quality prognostics scheme (QPS), reliance index, virtual metrology.

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One of the important applications for the resolution of redundant manipulators is torque optimization, due to the fact that the actuators used for driving a manipulator have finite power ratings. Nevertheless, not many algorithms have been proposed to accomplish this objective. A survey of the existing local torque optimization control schemes is given in this article. It will be shown that all of them either encounter instability problems for long trajectories or fail in certain cases. For remedying these problems, the authors present the Minimum Velocity Norm (MVN) method, which is the most common approach for kinematic redundancy resolution and has never been adopted for torque optimization by other researchers. Simulation results show that the simple MVN method is moderate for short movements and is stable for long movements. Also, the MVN method can be applied to cases that may not be accomplished by some other approaches. Therefore, the MVN method is better than the other existing approaches for torque optimization. © 1994 John Wiley & Sons, Inc.

Recently, the emerging Web-Services technology has provided a new and excellent solution to the data integration among heterogeneous systems. In this paper, a Web-Services-based e-diagnostics framework (WSDF) is proposed. It can achieve the automation of diagnostic processes and diagnostics information integration for semiconductor equipment. First, the system framework and the system component model are designed. Then, the object-oriented analysis and design of system components are accomplished. In particular, for the purpose of code reuse, several common functions, such as simple object access protocol communication, universal description discovery and integration registration, security mechanism, data exchange mechanism, and local database access, are built into a generic component called Web-Service agent. By inheriting the Web-Service agent, other system components can be constructed and have these common functions. In addition, a unified authentication-service mechanism and a safe network connection are also designed in the framework. WSDF is intended to support the e-diagnostics functions defined by International SEMATECH. It is believed that WSDF can be applied to construct e-diagnostics systems for the semiconductor manufacturing industry.Index Terms-Authentication service, Web-Service agent, Web-Services-based e-diagnostics framework (WSDF).