Abstract: An additive manufacturing (AM) method is provided. The method includes performing a laser powder bed fusion (L-PBF) process on the powder layer. Then, a first surface roughness value of the powder layer after the L-PBF process is obtained to generate a first surface profile. An absorptivity and a set of re-melting process parameters data are used to perform a heat transfer simulation. A second surface profile of the powder layer after laser re-melting is obtained by using the first surface profile and a low-pass filter. Then, the set of re-melting process parameters data is adjusted iteratively to perform the heat transfer simulation until a second surface roughness value predicted from the second surface profile is smaller than or equal to a surface roughness threshold, thereby obtaining optimal values of re-melting process parameters for performing a re-melting process to reduce a surface roughness of a powder layer after the L-PBF process.

Abstract: An additive manufacturing (AM) method includes using an AM tool to fabricate a plurality of workpiece products; measuring qualities of the first workpiece products respectively; performing a temperature measurement on each of the melt pools on the powder bed during a fabrication of each of the workpiece products; performing photography on each of the melt pools on the powder bed during the fabrication of each of the workpiece products; extracting a length and a width of each of the melt pools; performing a melt-pool feature processing operation; building a conjecture model by using a plurality of sets of first process data and the actual metrology values of the first workpiece products in accordance with a prediction algorithm; and predicting a virtual metrology value of the second workpiece product by using the conjecture model based on a set of second process data.

Abstract: An additive manufacturing (AM) method includes using an AM tool to fabricate a plurality of workpiece products; measuring qualities of the first workpiece products respectively; performing a temperature measurement on each of the melt pools on the powder bed; performing photography on each of the melt pools on the powder bed; extracting a length and a width of each of the melt pools; performing a melt-pool feature processing operation; first converting each of the workspace images to a gray level co-occurrence matrix (GLCM); building a conjecture model by using a plurality of sets of first process data and the actual metrology values of the first workpiece products in accordance with a prediction algorithm; and predicting a virtual metrology value of the second workpiece product by using the conjecture model based on a set of second process data.

Abstract: An additive manufacturing (AM) method includes using an AM tool to fabricate a plurality of workpiece products; measuring qualities of the first workpiece products respectively; performing a temperature measurement on each of the melt pools on the powder bed; performing photography on each of the melt pools on the powder bed; extracting a length and a width of each of the melt pools; performing a melt-pool feature processing operation; first converting each of the workspace images to a gray level co-occurrence matrix (GLCM); building a conjecture model by using a plurality of sets of first process data and the actual metrology values of the first workpiece products in accordance with a prediction algorithm; and predicting a virtual metrology value of the second workpiece product by using the conjecture model based on a set of second process data.

Abstract: An additive manufacturing (AM) method includes using an AM tool to fabricate a plurality of workpiece products; measuring qualities of the first workpiece products respectively; performing a temperature measurement on each of the melt pools on the powder bed during a fabrication of each of the workpiece products; performing photography on each of the melt pools on the powder bed during the fabrication of each of the workpiece products; extracting a length and a width of each of the melt pools; performing a melt-pool feature processing operation; building a conjecture model by using a plurality of sets of first process data and the actual metrology values of the first workpiece products in accordance with a prediction algorithm; and predicting a virtual metrology value of the second workpiece product by using the conjecture model based on a set of second process data.

Abstract: An additive manufacturing (AM) system, an AM method, and an AM feature extraction method are provided. The AM system includes an AM tool, a product metrology system, an in-situ metrology system, a virtual metrology (VM) system, a compensator, a track planner, a controller, a simulator and an augmented reality (AR) device. The simulator is used to find feasible parameter ranges, while the AR device is used to support operations and maintenance of the AM tool. The product metrology system, the in-situ metrology system and the VM system are integrated to estimate the variation of material on a powder bed of the AM tool. The compensator is used for compensating the process variation by adjusting process parameters. The product metrology system is used to measure the quality of products. The in-situ metrology system is used to collect features of melt pools on the powder bed.

Abstract: An additive manufacturing (AM) system, an AM method, and an AM feature extraction method are provided. The AM system includes an AM tool, a product metrology system, an in-situ metrology system, a virtual metrology (VM) system, a compensator, a track planner, a controller, a simulator and an augmented reality (AR) device. The simulator is used to find feasible parameter ranges, while the AR device is used to support operations and maintenance of the AM tool. The product metrology system, the in-situ metrology system and the VM system are integrated to estimate the variation of material on a powder bed of the AM tool. The compensator is used for compensating the process variation by adjusting process parameters. The product metrology system is used to measure the quality of products. The in-situ metrology system is used to collect features of melt pools on the powder bed.

Abstract: A micro-LED display system is disclosed. The micro-LED display system includes a host, a plurality of row/column drivers and a plurality of ?ICs. The row/column drivers are coupled to the host through serial interfaces and used to provide a plurality of row clock signals and a plurality of column data signals respectively. The ?ICs are arranged as a matrix including columns of ?ICs and rows of ?ICs receiving the column data signals and the row clock signals respectively. All ?ICs in the same column of ?ICs are cascaded in order and all ?ICs in the same row of ?ICs are cascaded in order.

Abstract: A system for sensing concentration is provided. A light source emits at least a light ray which passes through a first polarization state changing module and is directed to a biological tissue to generate a response light ray. The response light ray is received by a sensor after passing through a second polarization state changing module. A calculation circuit calculates a Muller matrix corresponding to the biological tissue according to the response light ray, and calculates a depolarization index of the biological tissue according to the Muller matrix, and calculates an optical path length according to the depolarization index, and calculates the concentration of matter of the biological tissue according to the optical path length.

Abstract: A system for sensing concentration is provided. A light source emits at least a light ray which passes through a first polarization state changing module and is directed to a biological tissue to generate a response light ray. The response light ray is received by a sensor after passing through a second polarization state changing module. A calculation circuit calculates a Muller matrix corresponding to the biological tissue according to the response light ray, and calculates a depolarization index of the biological tissue according to the Muller matrix, and calculates an optical path length according to the depolarization index, and calculates the concentration of matter of the biological tissue according to the optical path length.

Abstract: An additive manufacturing (AM) method is provided. The method includes performing a laser powder bed fusion (L-PBF) process on the powder layer. Then, a first surface roughness value of the powder layer after the L-PBF process is obtained to generate a first surface profile. An absorptivity and a set of re-melting process parameters data are used to perform a heat transfer simulation. A second surface profile of the powder layer after laser re-melting is obtained by using the first surface profile and a low-pass filter. Then, the set of re-melting process parameters data is adjusted iteratively to perform the heat transfer simulation until a second surface roughness value predicted from the second surface profile is smaller than or equal to a surface roughness threshold, thereby obtaining optimal values of re-melting process parameters for performing a re-melting process to reduce a surface roughness of a powder layer after the L-PBF process.

Abstract: A method of performing powder bed fusion process is provided. A powder bed and a group of information of the powder bed are obtained. A powder bed simulation is performed to obtain a thickness of the powder bed and a packing density. Then, a group of parameters of a laser is obtained. A Ray Tracing simulation for the powder layer and a heat transfer simulation are performed. A first surrogate model is constructed to obtain first processing maps. The points in the first processing maps with the depths of the melt pool that are greater than a predetermined depth value and smaller than a laser beam radius are a first group of parameter values. A parameter setting operation is performed by using the first group of parameter values. A laser melting operation is performed, and a temperature distribution is measured by using an infrared thermal camera.

Abstract: A micro-LED display system is disclosed. The micro-LED display system includes a host, a plurality of row/column drivers and a plurality of ?ICs. The row/column drivers are coupled to the host through serial interfaces and used to provide a plurality of row clock signals and a plurality of column data signals respectively. The ?ICs are arranged as a matrix including columns of ?ICs and rows of ?ICs receiving the column data signals and the row clock signals respectively. All ?ICs in the same column of ?ICs are cascaded in order and all ?ICs in the same row of ?ICs are cascaded in order.

Abstract: An additive manufacturing (AM) system, an AM method, and an AM feature extraction method are provided. The AM system includes an AM tool, a product metrology system, an in-situ metrology system, a virtual metrology (VM) system, a compensator, a track planner, a controller, a simulator and an augmented reality (AR) device. The simulator is used to find feasible parameter ranges, while the AR device is used to support operations and maintenance of the AM tool. The product metrology system, the in-situ metrology system and the VM system are integrated to estimate the variation of material on a powder bed of the AM tool. The compensator is used for compensating the process variation by adjusting process parameters. The product metrology system is used to measure the quality of products. The in-situ metrology system is used to collect features of melt pools on the powder bed.

Abstract: A method of performing powder bed fusion process is provided. A powder bed and a group of information of the powder bed are obtained. A powder bed simulation is performed to obtain a thickness of the powder bed and a packing density. Then, a group of parameters of a laser is obtained. A Ray Tracing simulation for the powder layer and a heat transfer simulation are performed. A first surrogate model is constructed to obtain first processing maps. The points in the first processing maps with the depths of the melt pool that are greater than a predetermined depth value and smaller than a laser beam radius are a first group of parameter values. A parameter setting operation is performed by using the first group of parameter values. A laser melting operation is performed, and a temperature distribution is measured by using an infrared thermal camera.

Abstract: An additive manufacturing (AM) system, an AM method, and an AM feature extraction method are provided. The AM system includes an AM tool, a product metrology system, an in-situ metrology system, a virtual metrology (VM) system, a compensator, a track planner, a controller, a simulator and an augmented reality (AR) device. The simulator is used to find feasible parameter ranges, while the AR device is used to support operations and maintenance of the AM tool. The product metrology system, the in-situ metrology system and the VM system are integrated to estimate the variation of material on a powder bed of the AM tool. The compensator is used for compensating the process variation by adjusting process parameters. The product metrology system is used to measure the quality of products. The in-situ metrology system is used to collect features of melt pools on the powder bed.

Abstract: A method for measuring a temperature of a process area is provided. A simulation computation is performed to obtain a simulation temperature. A ratio-pyrometer with two one-color modes is used to measure the temperature of the process area, and a first emissivity value and a second emissivity value are acquired. An emissivity ratio is set to a ratio of the second emissivity value to the first emissivity value, and the ratio-pyrometer in the two-color mode is used to measure the temperature of the process area.

Abstract: A method for measuring a temperature of a process area is provided. A simulation computation is performed to obtain a simulation temperature. A ratio-pyrometer with two one-color modes is used to measure the temperature of the process area, and a first emissivity value and a second emissivity value are acquired. An emissivity ratio is set to a ratio of the second emissivity value to the first emissivity value, and the ratio-pyrometer in the two-color mode is used to measure the temperature of the process area.

Abstract: A system for sensing glucose concentration is provided and includes following components. A light source generates a light beam. The system may include a polarization state generator (PSG) for changing the polarization of the light beam, and then the light beam is emitted to a biological tissue. A polarization state analyzer (PSA) receives the light beam reflected from the biological tissue, and the received light beam is used to calculate Stokes vectors. A Mueller matrix is calculated according to the Stokes vectors. In some embodiments, the system includes an optical coherence tomography (OCT) in which the light beam is sensed by a detector for calculating the Mueller matrix. An optical rotation angle and a depolarization index are calculated in accordance with the differential Mueller matrix formalism. The glucose concentration is calculated in accordance with the optical rotation angle and the depolarization index.

Abstract: A system for sensing glucose concentration is provided and includesZZ following components. A light source generates a light beam. The system may include a polarization state generator (PSG) for changing the polarization of the light beam, and then the light beam is emitted to a biological tissue. A polarization state analyzer (PSA) receives the light beam reflected from the biological tissue, and the received light beam is used to calculate Stokes vectors. A Mueller matrix is calculated according to the Stokes vectors. In some embodiments, the system includes an optical coherence tomography (OCT) in which the light beam is sensed by a detector for calculating the Mueller matrix. An optical rotation angle and a depolarization index are calculated in accordance with the differential Mueller matrix formalism. The glucose concentration is calculated in accordance with the optical rotation angle and the depolarization index.