Abstract: A ceramic matrix composite component includes a first substrate and a second substrate each formed of a silicide-containing ceramic matrix composite, silicon carbide layers respectively coating a bonding surface of the first substrate and a bonding surface of the second substrate, and a bonding layer formed of a silicon-containing alloy and provided between the silicon carbide layer coating the bonding surface of the first substrate and the silicon carbide layer coating the bonding surface of the second substrate.

Abstract: A tooth contact position adjustment amount estimation device that performs processing with respect to estimating a tooth contact position adjustment amount for dimensional data of parts constituting a power transmission mechanism according to the present invention, comprising: a machine learning device that performs processing with respect to estimating the tooth contact position adjustment amount for the dimensional data of parts constituting the power transmission mechanism, wherein the machine learning device observes part dimensional data, which is the dimensional data of parts constituting the power transmission mechanism, as a state variable indicating a current state of an environment, and performs processing with respect to estimating the tooth contact position adjustment amount for the dimensional data of parts constituting the power transmission mechanism in assembling the power transmission mechanism by performing processing with respect to machine learning based on the observed state variable.

Abstract: A machine learning apparatus that can quantitatively and accurately evaluate the state of a cable in a robot. A machine learning apparatus for learning a state of a cable mounted in a robot includes a learning data acquisition section that acquires, as a learning data set, image data of the cable captured by a camera while the robot performs a predetermined operation, and data representing a state of the cable while the robot performs the predetermined operation, and a learning section that generates a learning model representing a correlation between the image data and the state of the cable, using the learning data set.

Abstract: A machine learning apparatus that can quantitatively and accurately evaluate the state of a cable in a robot. A machine learning apparatus for learning a state of a cable mounted in a robot includes a learning data acquisition section that acquires, as a learning data set, image data of the cable captured by a camera while the robot performs a predetermined operation, and data representing a state of the cable while the robot performs the predetermined operation, and a learning section that generates a learning model representing a correlation between the image data and the state of the cable, using the learning data set.

Abstract: A tooth contact position adjustment amount estimation device that performs processing with respect to estimating a tooth contact position adjustment amount for dimensional data of parts constituting a power transmission mechanism according to the present invention, comprising: a machine learning device that performs processing with respect to estimating the tooth contact position adjustment amount for the dimensional data of parts constituting the power transmission mechanism, wherein the machine learning device observes part dimensional data, which is the dimensional data of parts constituting the power transmission mechanism, as a state variable indicating a current state of an environment, and performs processing with respect to estimating the tooth contact position adjustment amount for the dimensional data of parts constituting the power transmission mechanism in assembling the power transmission mechanism by performing processing with respect to machine learning based on the observed state variable.