A machine learning device that acquires state information from a robot control inspection system. The system has a robot hand to hold a workpiece or camera. The state information includes a flaw detection position of the workpiece, a movement route of the robot hand, an imaging point of the workpiece, and the number of imaging by the camera. A reward calculator calculates a reward value in reinforcement learning based on flaw detection information including the flaw detection position. A value function updater updates an action value function by performing the reinforcement learning based on the reward value, the state information, and the action.

Embodiments of the present disclosure provide systems and methods for enhancing the semiconductor manufacturing yield. Embodiments of the present disclosure provide a yield improvement system. The system comprises a training tool configured to generate training data based on receipt of one or more verified results of an inspection of a first substrate. The system also comprises a point determination tool configured to determine one or more regions on a second substrate to inspect based on the training data, weak point information for the second substrate, and an exposure recipe for a scanner of the second substrate.

The present disclosure is directed to a computer-implemented method of sensor planning for acquiring samples via an apparatus including one or more sensors. The computer-implemented method includes defining, by one or more computing devices, an area of interest; identifying, by the one or more computing devices, one or more sensing parameters for the one or more sensors; determining, by the one or more computing devices, a sampling combination for acquiring a plurality of samples by the one or more sensors based at least in part on the one or more sensing parameters; and providing, by the one or more computing devices, one or more command control signals to the apparatus including the one or more sensors to acquire the plurality of samples of the area of interest using the one or more sensors based at least on the sampling combination.

A machine learning device that acquires state information from a robot control inspection system. The system has a robot hand to hold a workpiece or camera. The state information includes a flaw detection position of the workpiece, a movement route of the robot hand, an imaging point of the workpiece, and the number of imaging by the camera. A reward calculator calculates a reward value in reinforcement learning based on flaw detection information including the flaw detection position. A value function updater updates an action value function by performing the reinforcement learning based on the reward value, the state information, and the action.

An information processing apparatus includes a processor and a memory. The memory stores three-dimensional data describing a real device including an object, a source of an acting factor that acts on the object and causes a detectable change at the object, and a detector that detects the change in a specified detection range. The processor produces a virtual device that represents the real device in a virtual space, based on the three-dimensional data in the memory. With this virtual device, the processor simulates the change caused by the acting factor, and calculates a region of the object in which the simulated change satisfies a specified condition.

An inspection management system manages, in a production line for a product including a plurality of processes, a final inspection for a product finished through the plurality of processes and a plurality of intermediate inspections before the final inspection. The production line includes a plurality of manufacturing apparatuses and a plurality of inspection apparatuses corresponding to the plurality of processes. The inspection management system includes an inspection data obtainer, an inspection result obtainer, and an inspection setting supporter that generates an inspection record diagram showing, as information about an inspection item in one of the plurality of intermediate inspections, a presence or an absence of a product determined defective in the final inspection and information identifying whether the product determined defective in the final inspection is determined defective under an inspection item in another of the plurality of intermediate inspections, and displays the inspection record diagram.

The present disclosure is directed to a computer-implemented method of sensor planning for acquiring samples via an apparatus including one or more sensors. The computer-implemented method includes defining, by one or more computing devices, an area of interest; identifying, by the one or more computing devices, one or more sensing parameters for the one or more sensors; determining, by the one or more computing devices, a sampling combination for acquiring a plurality of samples by the one or more sensors based at least in part on the one or more sensing parameters; and providing, by the one or more computing devices, one or more command control signals to the apparatus including the one or more sensors to acquire the plurality of samples of the area of interest using the one or more sensors based at least on the sampling combination.

A system is provided for programming workpiece feature inspection operations for a coordinate measuring machine. The system includes a computer-aided design (CAD) file processing portion and a user interface including a workpiece inspection program simulation portion, an editing user interface portion, and a simulation status and control portion. The simulation status and control portion is configured to respond to selection of workpiece features or inspection operation representations (e.g., as selected in the workpiece inspection program simulation portion or editing user interface portion). The simulation status and control portion response to the selection includes altering a simulation status portion (e.g., altering a numerical time representation or a position of a current time indicator) to characterize a state of progress through a current workpiece feature inspection plan corresponding to the portion of the current workpiece feature inspection plan directed to the selected workpiece feature or inspection operation representation.