Abstract: An abnormality detection apparatus is provided. The abnormality detection apparatus includes a first generation part configured to generate pseudo-abnormal image data by synthesizing a substantially circular image at a random position of an image of normal image data obtained by photographing equipment that includes a liquid supply and supplies a liquid from the liquid supply without an abnormality, a second generation part configured to generate a determination model for determining whether the equipment is normal or abnormal by performing learning of the normal image data and the pseudo-abnormal image data, an acquisition part configured to acquire image data obtained by photographing the equipment, and a detection part configured detect an abnormality in the equipment from the image data acquired by the acquisition part using the determination model.

Abstract: According to an aspect of the present disclosure, a substrate state determining apparatus includes: an image capturing unit that captures an image of a substrate placed on a stage; a learning unit that executes a machine learning using training data in which information indicating a state of the substrate is attached to the image of the substrate, so as to generate a substrate state determination model in which the image of the substrate is taken as an input and a value related to the state of the substrate corresponding to the image of the substrate is taken as an output; and a determination unit that determines the state of the substrate corresponding to the image of the substrate captured by the image capturing unit, using the substrate state determination model generated by the learning unit.

Abstract: A monitoring apparatus for a substrate processing apparatus includes: an imaging unit that captures an image of a nozzle of the substrate processing apparatus and a surface of a substrate held by a substrate holder of the substrate processing apparatus; a monitoring data generation unit that generates monitoring video data based on imaging video data captured by the imaging unit during an execution of a substrate process performed by the substrate processing apparatus including a first process and a second process; and a monitoring condition changing unit that changes a generation condition of the monitoring video data during the execution of the substrate process so that at least a resolution or a number of frames of the monitoring video data during an execution of the second process is different from the monitoring video data during an execution of the first process.

Abstract: A state determination device determines the state of a drive mechanism configured to operate while holding a substrate in a substrate processing apparatus. The state determination part includes: an acquisition part configured to acquire operation data for the drive mechanism; a model generation part configured to generate a monitoring model for the drive mechanism by executing machine learning using an auto-encoder based on normal operation data that is derived from the operation data acquired by the acquisition part when the drive mechanism is operating normally; and a first determination part configured to determine the state of the drive mechanism based on first output data obtained by inputting, to the monitoring model, evaluation data that is derived from the operation data acquired by the acquisition part when the drive mechanism is being evaluated.

Abstract: An abnormality detection apparatus is provided. The abnormality detection apparatus includes a first generation part configured to generate pseudo-abnormal image data by synthesizing a substantially circular image at a random position of an image of normal image data obtained by photographing equipment that includes a liquid supply and supplies a liquid from the liquid supply without an abnormality, a second generation part configured to generate a determination model for determining whether the equipment is normal or abnormal by performing learning of the normal image data and the pseudo-abnormal image data, an acquisition part configured to acquire image data obtained by photographing the equipment, and a detection part configured detect an abnormality in the equipment from the image data acquired by the acquisition part using the determination model.

Abstract: According to an aspect of the present disclosure, a substrate state determining apparatus includes: an image capturing unit that captures an image of a substrate placed on a stage; a learning unit that executes a machine learning using training data in which information indicating a state of the substrate is attached to the image of the substrate, so as to generate a substrate state determination model in which the image of the substrate is taken as an input and a value related to the state of the substrate corresponding to the image of the substrate is taken as an output; and a determination unit that determines the state of the substrate corresponding to the image of the substrate captured by the image capturing unit, using the substrate state determination model generated by the learning unit.

Abstract: Disclosed is monitoring device of monitoring a state of a substrate processing process in a substrate processing apparatus. The monitoring device includes: an imaging unit configured to image a processing state of the substrate processing process; a storage unit; a storage control unit configured to store a moving picture imaged by the imaging unit after adding a time stamp to the moving picture; a group classification unit configured to group a plurality of moving pictures stored in the storage unit into moving pictures of a normal group and moving pictures of a group other than the normal group; and a threshold generation unit configured to generate a threshold for detecting an abnormal moving picture based on the moving pictures of the normal group grouped by the group classification unit.

Abstract: Provide is a process monitoring device in a semiconductor manufacturing apparatus that can readily and reliably monitor the process in the semiconductor manufacturing apparatus. The process monitoring device includes a storage unit that stores a normal state moving image data indicating a normal state of the process; an image capturing unit that captures an image of a state of the process to be monitored to acquire a moving image data; an abnormality level calculation unit configured to extract a feature amount for each frame of the moving image data and the normal state moving image data, and calculate an abnormality level based on the extracted feature amount; and a display unit that displays the abnormality level calculated by the abnormality level calculation unit in association with a frame position of the moving image data.

Abstract: Disclosed is monitoring device of monitoring a state of a substrate processing process in a substrate processing apparatus. The monitoring device includes: an imaging unit configured to image a processing state of the substrate processing process; a storage unit; a storage control unit configured to store a moving picture imaged by the imaging unit after adding a time stamp to the moving picture; a group classification unit configured to group a plurality of moving pictures stored in the storage unit into moving pictures of a normal group and moving pictures of a group other than the normal group; and a threshold generation unit configured to generate a threshold for detecting an abnormal moving picture based on the moving pictures of the normal group grouped by the group classification unit.

Abstract: Provide is a process monitoring device in a semiconductor manufacturing apparatus that can readily and reliably monitor the process in the semiconductor manufacturing apparatus. The process monitoring device includes a storage unit that stores a normal state moving image data indicating a normal state of the process; an image capturing unit that captures an image of a state of the process to be monitored to acquire a moving image data; an abnormality level calculation unit configured to extract a feature amount for each frame of the moving image data and the normal state moving image data, and calculate an abnormality level based on the extracted feature amount; and a display unit that displays the abnormality level calculated by the abnormality level calculation unit in association with a frame position of the moving image data.

Abstract: A vibrating bowl and the like are provided which are capable of accurately counting the number of objects to be fed. The vibrating bowl (10) includes: a concave portion (10a) capable of storing therein collectivity of objects (15) to be fed; a feed passage (20) capable of feeding the objects (15) within the concave portion (10a) by vibrating the objects (15); and a step portion (26) configured to cause the objects to be ejected outside of the concave portion (10a) in a direction substantially perpendicular and downwardly oblique to a feed direction in which those objects (15) which are present in the vicinity of a termination of the feed passage (20) are fed.

Abstract: A starter of single-phase induction motor having main winding and auxiliary winding energized by alternating current power source, including a casing, a positive characteristic thermistor connected in series to the auxiliary winding, an auxiliary positive characteristic thermistor connected parallel to the positive characteristic thermistor, a bimetal, and an enclosed compartment accommodated in the casing for enclosing the snap action bimetal and auxiliary positive characteristic thermistor.

Abstract: When a starting current flows in an auxiliary winding S, a main PTC 12 and an auxiliary PTC 14 generate heat by themselves and the electrical resistance value increases. When the auxiliary PTC 14 reaches 140 deg. C., the snap action bimetal 18 is turned off, and no current flows into the main PTC 12, and starting of the single-phase induction motor 70 is complete. When the snap action bimetal 18 is cut off, slight current continues to flow only into the auxiliary PTC 14 side, and by the slight generated heat, the snap action bimetal 18 is kept in OFF state.