Abstract: A semiconductor die package includes an inductor-capacitor (LC) semiconductor die that is directly bonded with a logic semiconductor die. The LC semiconductor die includes inductors and capacitors that are integrated into a single die. The inductors and capacitors of the LC semiconductor die may be electrically connected with transistors and other logic components on the logic semiconductor die to form a voltage regulator circuit of the semiconductor die package. The integration of passive components (e.g., the inductors and capacitors) of the voltage regulator circuit into a single semiconductor die reduces signal propagation distances in the voltage regulator circuit, which may increase the operating efficiency of the voltage regulator circuit, may reduce the formfactor for the semiconductor die package, may reduce parasitic capacitance and/or may reduce parasitic inductance in the voltage regulator circuit (thereby improving the performance of the voltage regulator circuit), among other examples.

Abstract: An electronic device has a narrow viewing angle state and a wide viewing angle state, and includes a panel and a light source providing a light passing through the panel. In the narrow viewing angle state, the light has a first relative light intensity and a second relative light intensity. The first relative light intensity is the strongest light intensity, the second relative light intensity is 50% of the strongest light intensity, the first relative light intensity corresponds to an angle of 0°, the second relative light intensity corresponds to a half-value angle, and the half-value angle is between ?15° and 15°. In the narrow angle state, a third relative light intensity at each angle between 20° and 60° or each angle between ?20° and ?60° is lower than 20% of the strongest light intensity.

Abstract: A semiconductor device includes a plurality of channel layers vertically separated from one another. The semiconductor device also includes an active gate structure comprising a lower portion and an upper portion. The lower portion wraps around each of the plurality of channel layers. The semiconductor device further includes a gate spacer extending along a sidewall of the upper portion of the active gate structure. The gate spacer has a bottom surface. Moreover, a dummy gate dielectric layer is disposed between the gate spacer and a topmost channel layer of plurality of channel layers. The dummy gate dielectric layer is in contact with a top surface of the topmost channel layer, the bottom surface of the gate spacer, and the sidewall of the gate structure.

Abstract: A device includes a semiconductor fin, and a gate stack on sidewalls and a top surface of the semiconductor fin. The gate stack includes a high-k dielectric layer, a work-function layer overlapping a bottom portion of the high-k dielectric layer, and a blocking layer overlapping a second bottom portion of the work-function layer. A low-resistance metal layer overlaps and contacts the work-function layer and the blocking layer. The low-resistance metal layer has a resistivity value lower than second resistivity values of both of the work-function layer and the blocking layer. A gate spacer contacts a sidewall of the gate stack.

Abstract: 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 (TSPMVA) 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.

Abstract: 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.

Abstract: 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.

Abstract: A strike exerciser structure includes: a first rubber pad, defined with a swing space; a second rubber pad, in movable connection with one side of the first rubber pad and positioned inside the swing space, the second rubber pad including a swing portion and connection portion, the connection portion in connection with the first rubber pad, and the swing portion extended from one side of the connection portion; a rod, one end thereof in connection with the swing portion; and a placement portion, configured on one end of the rod away from the swing portion, allowing a placement of a ball. Whereby, if a user uses a bat to hit the rod or drive the rod to move with a swing force upon a strike exercise, the swing portion will be oscillated with the connection portion as a fulcrum and spring back to its original position, thereby increasing service life.

Abstract: 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.

Abstract: 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 DQIx (Process Data Quality Index) model, and a DQIy (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.

Abstract: 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.

Abstract: 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 DQIx (Process Data Quality Index) model, and a DQIy (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.

Abstract: 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 (VMI) 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 (VMII) 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 VMI and VMII are also generated.

Abstract: 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 (VMI) 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 (VMII) 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 VMI and VMII are also generated.