Deng-Lin Zeng

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A method for evaluating reliance level of a virtual metrology system (VMS) is proposed. This method calculates a reliance index (RI) value between 0 and 1 by analyzing the process data of production equipment to decide if the virtual metrology result is reliable. A RI threshold is also defined in this method. If a RI value is higher than the threshold, the(More)
This paper proposes a selection scheme (S-scheme) between neural-network (NN) and multiple-regression (MR) outputs of a virtual metrology system (VMS). Both NN and MR are applicable algorithms for implementing VM conjecture models. But a MR algorithm may achieve better accuracy only with a stable process, whereas a NN algorithm may has superior accuracy(More)
Selection schemes between neural-network (NN) and multiple-regression (MR) outputs of a virtual metrology system (VMS) are studied in this paper. Both NN and MR are applicable algorithms for implementing virtual-metrology (VM) conjecture models. A MR algorithm may achieve better accuracy only with a stable process, whereas a NN algorithm may have superior(More)
Advanced Studies of selection schemes between neural-network (NN) and multiple-regression (MR) outputs of a virtual metrology system (VMS) are presented in this paper. Both NN and MR are applicable algorithms for implementing VM conjecture models. But a MR algorithm may achieve better accuracy only with a stable process, whereas a NN algorithm may has(More)
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