A computer-assisted method for determining dimensional properties of a measurement object using a coordinate measuring machine. An image representation of the measurement object is shown to a user and the user selects a first geometric element of the measurement object, resulting in the display of eligible test features for the selected first geometric element. The eligible test features are automatically determined from a plurality of typical test features stored in a database, by the selected first geometric element being assigned to one of a plurality of predefined measurement elements stored in the database. A defined measurement sequence is generated in a computer-assisted manner based on the test feature selected by the user. Individual measured values are recorded on the first geometric element using the defined measurement sequence. A numerical value based on the individual measured values is determined, which represents a dimensional property of the first geometric element corresponding to the selected test feature.

A machine learning apparatus includes a first information acquiring unit that acquires first information including at least one of a shape of a workpiece, a material of the workpiece, a cutting path of a cutting process, a type of a tool, and an amount of wear of the tool; a second information acquiring unit that acquires second information correlated with an evaluation of a burr occurring on the workpiece due to the cutting process; and a learning unit that executes learning processing using a plurality of pieces of the first information and a plurality of pieces of the second information, and generates a learning model that outputs a cutting condition, according to another piece of first information that is different from the plurality of pieces of first information.

This control device of a machine tool is provided with: a storage unit which stores in advance a nominal diameter and a nominal length of a blade part of a rotary tool; an image-capturing instruction unit which outputs an image-capturing instruction to an image-capturing device; a model creation unit which generates model data of the blade part of the tool on the basis of the nominal diameter and the nominal length stored in the storage unit, generates model data of a tool shank and holder on the basis of an image stored in the image-capturing device, and creates model data of the rotary tool on the basis of the generated model data of the blade part and the generated model data of the tool shank and holder.

A method for CNC manufacturing is provided. The method includes computer-reading a digital model of a 3D part within a first topological space. An offset surface for the digital model in the first topological space is computer-generated. The offset surface in the first topological space is computer-transformed to a transformed offset surface in a second topological space embedded in the first topological space. A plurality of contours are computer-identified, at which a corresponding plurality of embedded parallel planes intersect the transformed offset surface in the second topological space. The plurality of contours in the second topological space are computer-transformed into a corresponding plurality of transformed contours in the first topological space. A CNC toolpath is computer-generated that traces each of the plurality of transformed contours in the first topological space, the CNC toolpath useable by a CNC machine to manufacture the 3D part.

Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes. A method includes: obtaining a design space and design criteria for a modeled object including a design constraint on an acceptable likelihood of failure, wherein a statistical model that relates a structural performance metric to specific likelihoods of failure for material(s) is used to translate between the acceptable likelihood of failure and a value for the structural performance metric; iteratively modifying a generatively designed shape of the modeled object in the design space in accordance with the design criteria including the design constraint to stay under the acceptable likelihood of failure for the physical structure, wherein the numerical simulation includes computing the structural performance metric, which is evaluated against the design constraint; and providing the generatively designed shape of the modeled object for use in manufacturing a physical structure.

In accordance with some embodiments, systems, methods, and media for controlling support structures and build orientation are provided. In some embodiments, a method for additive manufacturing a part using a three dimensional (3D) printing system, the 3D printing system including a print head and a build plate is provided, the method comprising: receiving a plurality of physical constraints associated with the part; optimizing a build orientation of the part to identify an optimized build orientation b* for the part with respect to a design domain defined by the physical constraints based on the plurality of physical constraints, and a plurality of design constraints using at least one variable associated with build orientation as an optimization variable, the plurality of design constraints comprising: an initial build orientation b.sup.0; and a critical surface slope angle and generating a part model based on the optimized build orientation b*.

A method and device capable of calculating required material properties from a part shape, and determining a set of manufacturing conditions for a material satisfying the material properties are provided. A product information determining method includes a property acquisition step (S300) for acquiring, based on input information including shape data on a part, material properties required to work a material of the part into the part; and a product information determination step (S400) for determining product information including chemical compositions and a set of manufacturing conditions to manufacture the material satisfying the material properties.

The disclosed technology relates to an intelligent motion control system that utilizes onboard sensors and processing to guide a surface manipulation machine along a path of travel on a surface, confirm a position of the machine with respect to the surface, and actuate a surface manipulation tool to achieve a desired surface profile or locate a point of interest. The system may include a first and second surface profiler that is configured to scan a surface on which the system travels and a positional sensor configured to generate positional data representing a position of the machine. The processor is configured to generate topography data based on output received from the first surface profiler, generate intermediate data based on output received from the second profiler, compare the intermediate data with the topography data to calculate an offset; and control motion of the system based on the offset.

In a machining system that conducts nesting to arrange parts over a workpiece and machines the workpiece with a machine tool according to a result of the nesting, there is an automatic programming device for preparing a nesting machining program for the machine tool, wherein nested workpiece information relating to the workpiece nested is acquired according to the information relating to the parts and the information relating to the workpiece, sections that require no re-nesting in the nested workpiece information are locked according to the operator's designation, re-nesting is conducted on sections other than the locked sections.

An information processing apparatus includes a processor, and the processor is configured to acquire, in printing processing for modeling a three-dimensional modeled object by forming respective images on recording media and stacking the recording media, a print job including at least one of two-dimensional image data for forming a two-dimensional image and three-dimensional image data for modeling a three-dimensional modeled object, an instruction of a user for the print job, and attribute information of a plurality of printing apparatuses that are candidates to perform the print job, and select a printing apparatus to perform the acquired print job from the plurality of printing apparatuses based on whether the image data contained in the print job is two-dimensional image data or three-dimensional image data, the attribute information, and the instruction of the user.