A control data generation device includes a computation unit calculating a control command based on rotational information or temporal information. The rotational information specifies a relationship between a specific rotation angle or specific rotational position during one spindle revolution and a position of the driven device. The temporal information specifies a relationship between a specific elapsed time during one spindle revolution and the position of the driven device. It also includes a display control unit controlling displaying the control command. Upon reception of an order to display temporal information during displaying rotational information, the rotational information is converted into the temporal information, and the obtained temporal information is displayed on the display device. Upon reception of an order to display rotational information during displaying temporal information, the computation unit converts the temporal information into the rotational information, and displays the rotational information obtained by the conversion.

In an example, a method includes operating, by a processor, on object model data. The object model data describes at least part of an object to be generated in additive manufacturing. The method also includes determining, by a processor, pattern data. The pattern data comprising areas of variable reflectance intended to be formed on a portion of the object. The method includes determining, by a processor, object generation instructions to apply a fusing agent to at least part of a layer of build material corresponding to the portion of the object in a density corresponding to the reflectance of the generated pattern data.

This specification describes systems, methods, devices, and other techniques for planning workspaces for automated fabrication processes. A computing system facilitates planning by receiving a set of parameters for planning a layout of a workspace for an automated fabrication process, and generating a plurality of candidate workspace layouts, including selecting, for each candidate workspace layout, (i) one or more robots for performing tasks in the automated fabrication process and (ii) corresponding locations for the one or more robots within the workspace. The system determines an optimal workspace layout based on the plurality of candidate workspace layouts, generates a workspace layout specification for the optimal workspace layout, and provides the workspace layout specification to one or more second computing systems.

To provide processing information to a CAM that generates an NC program of a processing machine for processing an object to be processed with a tool, a processing support system comprises, in a cloud storage device installed on a processing tool manufacturer side, a user knowledge database of a storage unit that stores processing information so as to be unshareble with other users and a sharing knowledge database of the storage unit that stores processing information so as to be sharable with other user, wherein a user side transmits and receives, by a transmitting/receiving unit, extended STEP-NC data of processing information via a network.

In an example, a method includes operating, by a processor, on object model data and operating, on a processor, on pattern data. The object model data describes at least part of an object to be generated in additive manufacturing and the pattern data describes an object pattern intended to be formed on at least a portion of the part of the object to be generated in additive manufacturing. The method includes determining, by a processor, control data to control a print agent applicator to apply a pattern of fusing agent onto a part of a layer of build material. The pattern of fusing agent comprises a fusing agent area and a gap area that lacks fusing agent. The gap area corresponds to the object pattern such that no fusing agent is applied to a part of the layer of build material that corresponds to the object pattern.

A machine learning device includes: a data extraction unit that extracts a first parameter and a second parameter from each of a plurality of machining programs for numerically controlling a machine tool, the first parameter being a parameter to be adjusted, the second parameter being a parameter to be used for adjusting the parameter to be adjusted; and a machine learning unit that learns a value of the first parameter according to a data set including the first parameter and the second parameter extracted by the data extraction unit.

Embodiments of techniques for inverse design of physical devices are described herein, in the context of generating designs for photonic integrated circuits (including a multi-channel photonic demultiplexer). In some embodiments, an initial design of the physical device is received, and a plurality of sets of operating conditions for fabrication of the physical device are determined. In some embodiments, the performance of the physical device as fabricated under the sets of operating conditions is simulated, and a total performance loss value is backpropagated to determine a gradient to be used to update the initial design. In some embodiments, instead of simulating fabrication of the physical device under the sets of operating conditions, a robustness loss is determined and combined with the performance loss to determine the gradient.

A computer-based design system for an electric drive system includes: a cam editor having a graphical user interface, wherein the graphical user interface sets values of parameters of a motion profile of the electric drive system on the basis of user inputs, a limit value memory, which stores limit values of the motion profile, and a limit value monitoring device, which monitors whether a value of a parameter inputted by a user input causes one or more of the stored limit values to be violated by the resulting motion profile and, in the case that one or more of the stored limit values are violated by the resulting motion profile, to adjust the inputted value of the parameter to such a value of the parameter that none of the stored limit values are violated by the resulting motion profile.

An object recognition apparatus for automatic detection of an abnormal operation state of a machine including a machine tool operated in an operation space monitored by at least one camera configured to generate camera images of a current operation scene is provided. The generated camera images are supplied to a processor configured to analyze the current operation scene using a trained artificial intelligence module to detect objects present within the current operation scene. The processor is also configured to compare the detected objects with objects expected in an operation scene in a normal operation state of the machine to detect an abnormal operation state of the machine.

A system allows a user to create new designs for apparel and preview these designs before manufacture. Software and lasers are used in finishing apparel to produce a desired wear pattern or other design. The user's preview may be based upon a two-dimensional image of a wear pattern in a laser input file and, from a set of two-dimensional images of a base garment, create a three-dimensional view of the base garment with the wear pattern.