A display panel and manufacturing method thereof, and a display device. The display region includes first wire and second wire. The non-display region includes third wire and fourth wire. The first wire includes first-type first wire, first-type first wire including first sub wire and second sub wire spaced apart between third wire and fourth wire. The second wire includes first-type second wire; third wire includes first repair line. The fourth wire includes second repair line, and the first sub wire and second sub wire are electrically connected to second repair line through first repair line and first-type second wire. The first wire includes second-type first wire, and second-type first wire is continuous between third wire and fourth wire; second wire includes second-type second wire, second-type second wire transmitting first common signal.

A semiconductor device has a substrate with first and second conductive layers formed over first and second opposing surfaces of the substrate. A plurality of bumps is formed over the substrate. A semiconductor die is mounted to the substrate between the bumps. An encapsulant is deposited over the substrate and semiconductor die. A portion of the bumps extends out from the encapsulant. A portion of the encapsulant is removed to expose the substrate. An interconnect structure is formed over the encapsulant and semiconductor die and electrically coupled to the bumps. A portion of the substrate can be removed to expose the first or second conductive layer. A portion of the substrate can be removed to expose the bumps. The substrate can be removed and a protection layer formed over the encapsulant and semiconductor die. A semiconductor package is disposed over the substrate and electrically connected to the substrate.

A system for monitoring one or more conditions of an automation system of a semiconductor factory includes one or more instrumented substrates, one or more sealable containers and one or more system servers. The one or more instrumented substrates include one or more sensors. The one or more sensors measure one or more conditions of the one or more instrumented substrates as the one or more sealable containers transport the one or more instrumented substrates through the semiconductor factory. The one or more sealable containers also receive sensor data from the one or more sensors included on the one or more instrumented substrates. The one or more system servers are configured to receive the sensor data from the one or more sealable containers. The one or more servers are configured to identify one or more deviations in the measured one or more conditions.

An apparatus for chemical mechanical polishing of a wafer includes a process chamber and a rotatable platen disposed inside the process chamber. A polishing pad is disposed on the platen and a wafer carrier is disposed on the platen. A slurry supply port is configured to supply slurry on the platen. A process controller is configured to control operation of the apparatus. A set of microphones is disposed inside the process chamber. The set of microphones is arranged to detect sound in the process chamber during operation of the apparatus and transmit an electrical signal corresponding to the detected sound. A signal processor is configured to receive the electrical signal from the set of microphones, process the electrical signal to enable detection of an event during operation of the apparatus, and in response to detecting the event, transmit a feedback signal to the process controller. The process controller is further configured to receive the feedback signal and initiate an action based on the received feedback signal.

A substrate processing apparatus includes a temperature detector and a controller. The temperature detector detects a temperature of processing liquid before the temperature of the processing liquid in pre-dispensing in progress reaches a target temperature. The controller sets discharge stop duration of the processing liquid in the pre-dispensing based on target temperature prediction duration. The target temperature prediction duration is prediction duration until the temperature of the processing liquid reaches the target temperature from a detection temperature. The detection temperature is the temperature of the processing liquid detected by the temperature detector before the temperature of the processing liquid reaches the target temperature. The target temperature prediction duration is determined based on a temperature profile. The temperature profile indicates a record of the temperature of the processing liquid changing over time when the pre-dispensing processing was performed in the past according to the pre-dispensing condition.

A wafer bonding apparatus including: a first chuck in a processing chamber, the first chuck being configured to hold a first wafer, the first chuck including: a chuck body, and a tunable stiffness layer including a plurality of actuators, the plurality of actuators including a tunable stiffness material, the tunable stiffness layer being disposed below the chuck body; a controller configured to send control signals to one or more of the plurality of actuators; and a vacuum line on the chuck body configured to apply a vacuum pressure from a vacuum pump to the first wafer; and a second chuck in the processing chamber, the second chuck being configured to hold a second wafer to be bonded with the first wafer; and where a stiffness of the plurality of actuators is configured to change based on the control signals from the controller.

Systems and methods for determining a diagnosis of a screening system are disclosed. Such systems and methods include identifying defect results based on inline characterization tool data, identifying electrical test results based on electrical test data, generating one or more correlation metrics based on the defect results and the electrical test results, and determining at least one diagnosis of the screening system based on the one or more correlation metrics, the diagnosis corresponding to a performance of the screening system.

A training method of a semiconductor process prediction model, a semiconductor process prediction device, and a semiconductor process prediction method are provided. The training method of the semiconductor process prediction model includes the following steps. The semiconductor process was performed on several samples. A plurality of process data of the samples are obtained. A plurality of electrical measurement data of the samples are obtained. Some of the samples having physical defects are filtered out according to the process data. The semiconductor process prediction model is trained according to the process data and the electrical measurement data of the filtered samples.

A substrate processing system includes a process chamber, one or more robot, a substrate measurement system, and a computing device. The process chamber may process a substrate that will comprise a film and/or feature after the processing. The one or more robot, to move the substrate from the process chamber to a substrate measurement system. The substrate measurement system may measure the film and/or feature on the substrate and generate a profile map of the film and/or feature. The computing device may process data from the profile map using a first trained machine learning model, wherein the first trained machine learning model outputs a first chamber component condition estimation for a first chamber component of the process chamber. The computing device may then determine whether to perform maintenance on the first chamber component of the process chamber based at least in part on the first chamber component condition estimation.

A method of detecting a polishing endpoint includes storing a plurality of library spectra, measuring a sequence of spectra from the substrate in-situ during polishing, and for each measured spectrum of the sequence of spectra, finding a best matching library spectrum from the plurality of library spectra to generate a sequence of best matching library spectra. Each library spectrum has a stored associated value representing a degree of progress through a polishing process, and the stored associated value for the best matching library spectrum is determined for each best matching library spectrum to generate a sequence of values representing a progression of polishing of the substrate. The sequence of values is compared to a target value, and a polishing endpoint is triggered when the sequence of values reaches the target value.