Fanuc Corporation

Hiroshi Abe

Hideki Otsuki

A measurement operation parameter adjustment apparatus that enables efficient measurement of the placement position of an object to be measured even in the case where there are variations in the placement positions, the sizes, and the product types of objects to be measured includes a machine learning device. The machine learning device observes measurement operation parameter data representing the measurement operation parameter of the measurement operation and measurement time data representing time taken to perform the measurement operation as a state variable representing a current environmental state and performs learning or decision-making using a learning model obtained by modeling adjustment of the measurement operation parameter based on the state variable.

Measurement operation parameter adjustment apparatus, machine learning device, and system

A machine learning device includes: a state observation unit that observes component arrangement data representing an arrangement of components on a component serving place, component data representing information of the components, and operator status data representing status information of an operator, as state variables representing a current state of an environment; a determination data acquisition unit that acquires product quality determination data for determining quality of the product which is assembled based on an arrangement of the components and takt time determination data for determining takt time for assembly of the product as determination data; and a learning unit that performs learning based on the state variables and the determination data in a manner to associate information of the components used for assembling the product and status information of the operator with respect to an arrangement of the components on the component serving place.

Control device and machine learning device

A control device and a machine learning device enable control for gripping an object having small reaction force. The machine learning device included in the control device includes a state observation unit that observes gripping object shape data related to a shape of the gripping object as a state variable representing a current state of an environment, a label data acquisition unit that acquires gripping width data, which represents a width of the hand of the robot in gripping the gripping object, as label data, and a learning unit that performs learning by using the state variable and the label data in a manner to associate the gripping object shape data with the gripping width data.

To provide a controller for reducing a burden to be imposed on an operator in applying force with a finger during operation on a machine tool or a robot, and for associating an operation history with identification information about the operator. A controller for a robot or a machine tool comprises a fingerprint detection unit and a control unit. The control unit comprises: a key information receiving part that receives input key information; a key information transmission part that transmits the input key information linked in advance with the fingerprint detection unit to the key information receiving part if an operator makes a finger touch the fingerprint detection unit; and an individual identification information specification part that specifies identification information about the operator based on fingerprint information about the finger having touched the fingerprint detection unit.

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Yamanashi, Japan

Hiroshi Abe