The invention relates to a method for coating eyeglass lenses, in particular for coating the edge of eyeglass lenses by means of a needle metering device or jet metering device, wherein the eyeglass lens and the metering device are moved relative to one another and at the same time a coating material is applied to the eyeglass lens, in particular to the edge thereof, from the metering device. The control data for controlling the movement of the eyeglass lens and/or of the metering device are determined before and/or during the application process on the basis of geometric data of the metering device and geometry data of the eyeglass lens surface to be coated, said geometry data of the eyeglass lens surface to be coated being measured or being drawn from a data store.

Apparel patterns may be generated as a function of custom apparel information provided by a user, such as one or more measurements, colors, etc., such that the user can have apparel custom-knitted to their particular size and shape without having to acquiesce the high expense and long wait times typically associated with custom-fit clothing. After a custom apparel pattern is generated, a custom-knitted article can be manufactured based on the pattern by transmitting appropriate information to a knitting machine. Data produced while generating custom apparel patterns can be stored and used to optimize and improve the manufacturing of customized knitwear for subsequent users. Further, such data can be shared with third parties such that manufacturers or others can utilize one or more beneficial aspects of the present disclosure without having to implement all of the functionality that would otherwise be required to obtain such benefits.

A method for the machining of workpieces that have an unknown workpiece geometry with a tooling machine, said method having the steps of clamping of the workpiece in a clamping device on the tooling machine, execution of a manually guided 3D line scan with a measurement sensor within the tooling machine to determine the workpiece geometry in a first dataset, processing of the first dataset to compensate for errors in the manually guided 3D line scan in order to obtain a second dataset, use of the second dataset for 3D CAD surface generation by the tooling machine for the generation of a rough component geometry, use of the rough component geometry for the generation of scan paths for an automatic 3D line scan, execution of an automatic 3D line scan of the workpiece with the measurement sensor within the tooling machine in order to obtain a third dataset, use of the third dataset for 3D CAD surface generation for the generation of a precise component geometry, and automated machining of the workpiece by the tooling machine based on the precise component geometry, and a tooling machine for the execution of the method are provided.

Examples of methods for part packing based on agent usage are described herein. In some examples, a method includes or methods include determining an agent usage for each of a plurality of packings. In some examples, the method includes or methods include selecting a packing from the plurality of packings based on the agent usages.

Object geometry for three-dimensional printers is described in which a first object to be three-dimensionally printed is identified. Geometry data relating to a geometry of all or part of the first object can be obtained. The geometry data can be compared with a predetermined threshold. A determination can be made as to whether the first object may or may not be adversely affected by a post-processing apparatus that will be used to process the object during a post-processing operation based on the comparison.

A method and a corresponding system and computer program are provided. A model of an object to be manufactured via subtractive manufacturing is obtained. Geometric features to be machined as part of manufacturing the object are identified based on the model. The identified geometric features include a composite geometric feature including a plurality of geometric subfeatures. A database including strategies for machining different geometric features is accessed. The database includes a composite strategy for machining the composite geometric feature and separate strategies for machining the respective geometric subfeatures. Strategies for machining the respective geometric features are selected from the strategies included in the database. Instructions for causing one or more machine tools to manufacture the object in accordance with the selected strategies are provided. Selecting strategies for machining the respective geometric features via subtractive manufacturing includes selecting the composite strategy for machining the composite geometric feature.

An NC device, which is a numerical control device, includes: a program analyzing unit that analyzes a machining program to obtain a movement path along which to move a supply position of a material on a workpiece; a storage temperature extracting unit that extracts, from data on surface temperature of the workpiece, storage temperature in an area including the movement path on the workpiece; a layering volume calculating unit that calculates a volume of a layer forming an object on the basis of a relation between the storage temperature and a volume of the material that solidifies at the storage temperature in a given time; and a layering shape changing unit that changes a shape of the layer on the basis of the volume of the layer.

This tool selection method is provided with: a step for respectively calculating, with respect to a plurality of known workpieces, feature amounts based on the shapes of a plurality of machining surfaces wherein, to each of the plurality of known workpieces, one main tool which is preselected from a tool list that includes a plurality of tools is allocated as being suitable for machining the plurality of machining surfaces; a step for executing, with respect to the plurality of known workpieces, machine learning by taking the feature amounts as inputs and the main tools as outputs; a step for calculating a feature amount for a target workpiece; and a step for selecting, with respect to the target workpiece, a main tool from the tool list on the basis of a machine learning result obtained by using the feature amount of the target workpiece as an input.

A numerical control device includes an NC command decoding unit and a tool information storage/generation unit. The NC command decoding unit has a cut amount decoding unit for decoding the cut amount for rough machining, a machining shape generation unit for generating a finishing shape, a machining pathway generation unit for generating a path for rough machining, a tool direction provisional determining unit for provisionally determining the direction of the tool, a path joining assessment unit for assessing whether or not to omit a round-up operation, a machining path joining unit for generating a new path for directly moving to the end point of the next operation after the round-up operation if the round-up operation is to be omitted, and a tool direction determining unit for determining the direction of the tool at each machining shape change point on a path for rough machining including the new path.

Methods, systems, and devices for determining construction data for producing a forming die are provided. Using an electronic computing device, a simulation is carried out that includes moving die parts of a die toward each other to a closed position, reshaping a workpiece reshaping a workpiece from an initial state to a first deformed state due to the moving of the die parts to the closed position, keeping the die parts at least temporarily in the closed state to maintain the workpiece in the first deformed state, moving the die parts away from each other to an open position, and deforming the workpiece to a second deformed state from the first deformed state due to internal stresses of the workpiece and due to moving of the die parts to the open position. A geometry of a new die part that influences the reshaping is determined.