Upon performing diagnosis of a machine tool, etc., data suited to diagnosis is acquired while also reducing the burden on the user. A diagnostic data acquisition system that acquires diagnostic data for diagnosing a machine tool includes: a control unit that controls driving of a mobile part of the machine tool based on control data; a timing generation unit that generates an acquisition timing for the diagnostic data based on the control data; and a diagnostic data acquisition unit that acquires data which varies accompanying driving of the mobile part according to control by the control unit, as the diagnostic data.

A state identification device includes: a feature amount extraction unit that extracts a feature amount from physical data of a machine tool unit which shifts to a plurality of operation states; a feature amount storage unit in which a region is provided as a storage destination of the extracted feature amount for each of the plurality of operation states to which the machine tool unit shifts; a similarity calculation unit that calculates a similarity between the extracted feature amount and a feature amount stored in the feature amount storage unit; a state determination unit that determines an operation state of the machine tool unit based on the calculated similarity; and a storage destination determination unit that determines the region serving as the storage destination of the extracted feature amount based on a determination result of the state determination unit.

Upon performing diagnosis of a machine tool, etc., data suited to diagnosis is acquired while also reducing the burden on the user. A diagnostic data acquisition system that acquires diagnostic data for diagnosing a machine tool includes: a control unit that controls driving of a mobile part of the machine tool based on control data; a timing generation unit that generates an acquisition timing for the diagnostic data based on the control data; and a diagnostic data acquisition unit that acquires data which varies accompanying driving of the mobile part according to control by the control unit, as the diagnostic data.

Methods and metrology tool modules embodying the methods are provided. Methods comprise measuring characteristics of intermediate features such as guiding lines in a directed self-assembly (DSA) process, deriving exposure parameters from the measured characteristics; and adjusting production parameters for producing consecutive target features according to the derived exposure parameters. The methods and modules enhance the accuracy of the DSA-produced structures and related measurements.

A robot system and a maintenance method, capable of easily managing maintenance information and/or predicting a failure, with respect to each module constituting a robot. The robot system includes a plurality of robots each having an arm configured as an exchangeable module. The robot system also includes: a robot information storing section configured to store robot information including at least one of an operational status, failure prediction information, failure diagnosis information and maintenance history information of each module; a reading section configured to read a unique identifiable information of the module; a robot information referring section configured to refer to the stored robot information with respect to the module corresponding to the read unique identifiable information; and a robot information outputting section configured to output the robot information with respect to each module of the robot.

A method (1000) of diagnosis of operation of a machine tool (10, 100) that includes one or more axes (X, Y, Z) moved by one or more actuators (101, 102, 104) and at least one sensor (30) coupled to the machine tool (10, 100), the method (1000) comprising operations of: generating (1200) a programming sequence of movement of the axes (X, Y, Z) of the machine tool (10, 100); controlling (1210) the movement of the axes (X, Y, Z) of the machine tool (10, 100) according to the programming sequence; receiving (1220) a read-out signal (S) of the at least one sensor (30) coupled to the machine tool (10, 100); and processing (1230) the read-out signal (S) of the at least one sensor (30) coupled to the machine tool (10, 100). The programming sequence comprises instructions that are such as to apply (T) at least one single impulsive variation of a kinematic quantity that regards one or more actuators (101, 102, 104). The operation (1230) of processing the read-out signal (S) comprises processing a response of the machine tool (10, 100) to at least one single impulsive variation. The operation (1230) of processing the read-out signal (S) comprises artificial-neural-network processing (206) via one or more artificial neural networks (206, 2060) configured for analysing operating profiles in particular, one or more signals indicative of the status of the machine tool (W) in the read-out signal (S).