National Cheng-Kung University

Hsien-Cheng Huang

Fan-Tien Cheng

Chin-Yi Lin

Yu-Ming Hsieh

Chi-An Kao

Yung-Cheng Chang

Yi-Ting Huang

Jia-Mau Jian

Embodiments of the present invention provide a multiple-variable predictive maintenance method for a component of a production tool and a computer program product thereof, in which a multiple-variable time series prediction (TSP) and an information criterion algorithm are adapted to build a best vector autoregression model (VAR), thereby forecasting the complicated future trend of accidental shutdown of the component of the production tool. Therefore, the multiple-variable prediction of the present invention can improve the accuracy of prediction compared with the single-variable prediction.

Multiple-variable predictive maintenance method for component of production tool and non-transitory tangible computer readable recording medium thereof

Embodiments of the present invention provide a predictive maintenance method for a component of a production tool, in which a time series prediction (TSP) algorithm and an information criterion algorithm are adapted to build a TSP model, thereby forecasting the complicated future trend of accidental shutdown of the component of the production tool. In addition, an alarm scheme is provided for performing maintenance immediately when the component is very likely to enter a dead state, and a death related indicator (DCI) is provided for quantitatively showing the possibility of the component entering the dead state.

Predictive maintenance method for component of production tool and computer program product thererof

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.

Manufacturing execution system with virtual-metrology capabilities and manufacturing system including the same

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(Process Data Quality Index) model, and a DQI(Metrology Data Quality Index) model. In the AVM method, the model-creation server also can fan out or port the first set of VM models generated to other AVM servers of the same process apparatus (equipment) type, and each individual fan-out-acceptor's AVM server can perform automatic model refreshing processes so as to gain and maintain its VM models' accuracy.

System and method for automatic virtual metrology

A dual-phase virtual metrology method is disclosed for considering both promptness and accuracy by generating dual-phase virtual metrology (VM) values, wherein a Phase-I conjecture step emphasizes promptness by immediately calculating the Phase-I virtual metrology value (VM) of a workpiece once the entire process data of the workpiece are completely collected; and a Phase-II conjecture step intensifies accuracy, which does not re-calculate the Phase-II virtual metrology values (VM) of all the workpieces in the cassette until an actual metrology value (required for tuning or re-training purposes) of a selected workpiece in the same cassette is collected. Besides, the accompanying reliance index (RI) and global similarity index (GSI) of each VMand VMare also generated.

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Taoyuan, Taiwan

Hsien-Cheng Huang