A thermal displacement compensation apparatus includes a temperature measuring unit, a thermal displacement estimating unit, a thermal displacement compensation unit, a displacement measuring unit, a data recording unit, a thermal displacement compensation learning unit, and a displacement measurement timing diagnostic unit. The displacement measuring unit measures a displacement of a machine tool after compensating an axis command value. The thermal displacement compensation learning unit determines a thermal displacement estimation formula based on temperature information and the displacement recorded in the data recording unit. The displacement measurement timing diagnostic unit compares the temperature information at a past displacement measurement recorded in the data recording unit with current temperature information obtained from the temperature measuring unit, and determines whether to measure the displacement by the displacement measuring unit or not at a predetermined diagnosis timing.

A cooling arrangement for an electronic device comprises a primary cooling device and a secondary cooling device. The primary cooling device includes a fluidic input line receiving a cooling fluid from a cooling fluid source and a fluidic output line returning the cooling fluid toward a drain. The primary cooling device is thermally connected to the electronic device, receives the cooling fluid from the fluidic input line and transfers heat from the electronic device to the cooling fluid before returning the cooling fluid via the fluidic output line. A flow detection device monitors a flow of the cooling fluid in the primary cooling device. The secondary cooling device is thermally connected to the electronic device. A processor activates the secondary cooling device to absorb and dissipate heat from the electronic device when the flow detection device detects a lack of flow of the cooling fluid in the primary cooling device.

The present disclosure relates to a device for reading from and/or writing to a removable storage card. The device can comprise a housing including a wall defining a housing opening sized to receive a removable storage card. The device can also comprise a thermal management system attached to at least a part of the wall of the housing. Additionally, the device can comprise a biasing mechanism interoperable with the housing and configured to bias a card surface of the removable storage card into thermal communication with the thermal management system in response to insertion of the removable storage card into the housing opening. In some aspects, the biasing mechanism includes one or more elastic members configured to apply a biasing force to the removable storage card in response to the insertion of the removable storage card into the housing opening.

A numerical control system according to the present invention controls machine drive systems included in a machine tool that performs machining using a tool, according to a numerical control program, and includes a coordinate transformation unit that acquires a disturbance force or a disturbance torque applied to each machine drive system, and coordinate-transforms the disturbance force or the disturbance torque into a tool reference coordinate system for output, and an identification unit that calculates cutting process parameters that determine characteristics of a cutting process model and dynamic characteristic parameters that determine characteristics of a dynamics model of the machine tool, using the disturbance force or the disturbance torque output from the coordinate transformation unit, states of the machine drive systems, predetermined equation models, and cutting conditions. The equation models define relationships between the cutting process parameters, the dynamic characteristic parameters, and the disturbance force or the disturbance torque.

A machine learning device includes: a measured data acquisition unit that acquires a measured data group; a thermal displacement acquisition unit that acquires a thermal displacement actual measured value about a machine element; a storage unit that uses the measured data group acquired by the measured data acquisition unit as input data, uses the thermal displacement actual measured value about the machine element acquired by the thermal displacement acquisition unit as a label, and stores the input data and the label in association with each other as teaching data; and a calculation formula learning unit that performs machine learning based on the measured data group and the thermal displacement actual measured value about the machine element, thereby setting a thermal displacement estimation calculation formula used for calculating the thermal displacement of the machine element based on the measured data group.

A 3D printing apparatus and method corrects for skew in the motion components of the apparatus without the use of an independent reference object. A calibration object having features therein or thereon is printed. A user rotates the calibration object by a certain angle after it is printed. The features in/on the calibration object are measured, and an amount of skew is determined based on the measurements. In addition, a 3D printing operation is compensated based on the effects of a coefficient of thermal expansion and/or moisture absorption on dimensional changes.

A numerical control system according to the present invention controls machine drive systems included in a machine tool that performs machining using a tool, according to a numerical control program, and includes a coordinate transformation unit that acquires a disturbance force or a disturbance torque applied to each machine drive system, and coordinate-transforms the disturbance force or the disturbance torque into a tool reference coordinate system for output, and an identification unit that calculates cutting process parameters that determine characteristics of a cutting process model and dynamic characteristic parameters that determine characteristics of a dynamics model of the machine tool, using the disturbance force or the disturbance torque output from the coordinate transformation unit, states of the machine drive systems, predetermined equation models, and cutting conditions. The equation models define relationships between the cutting process parameters, the dynamic characteristic parameters, and the disturbance force or the disturbance torque.

The invention relates to a machining tool for machining a workpiece, including a main spindle with a driven shank, a tool holder which can be clamped in the shank, a cutting tool which is arranged on the tool holder, a distance sensor for determining a distance of the shank of the main spindle in relation to a reference point, and a control unit which is configured to perform compensation of the tool path during machining of the workpiece based on an elongation and displacement of the shank and an elongation of the tool holder holding the cutting tool, wherein the elongation and displacement of the shank is determined based on the distance determined using the distance sensor, and wherein the elongation of the tool holder holding the cutting tool is determined based on a rotational speed of the shank.

An information processing device includes a parameter selection method determination unit that selects a hyperparameter of a thermal displacement amount prediction formula as a first hyperparameter, a parameter selection unit that sets/changes the value of the first hyperparameter and fixes remaining hyperparameter values as second hyperparameter values, a machine learning unit that generates a thermal displacement amount prediction formula for each value of the first hyperparameter based on thermal displacement teacher data, and a model evaluation unit that stores the first hyperparameter values together with evaluation values which are the difference between the thermal displacement amounts estimated by each thermal displacement amount prediction formula and measured thermal displacement amounts. The parameter selection method determination unit uses a history of the values of the first hyperparameter and the evaluation values to set the value of the first hyperparameter when the evaluation value is smallest as an optimal value.

A crossflow air deflector part for directing airflow includes a front central spine, a first arcuate wall extending from the spine to a first back lateral edge of the airflow deflector, and a second arcuate wall extending from the spine to a second back lateral edge of the airflow deflector opposing the first back lateral edge. Such an airflow deflector can be implemented into a storage server, positioned between a laterally adjacent pair of data storage device (DSD) chambers and a pair of vertically stacked fans, such that the crossflow air deflector functions to direct airflow from one of the lateral DSD chambers into the lower fan and to direct airflow from the other lateral DSD chamber into the upper fan. Independent airflow control for each DSD chamber and each corresponding DSD is thereby provided.