The invention relates to a computer-assisted method for generating a control data set for an additive layer manufacturing device. In a first step, a layer data set is accessed, wherein points are marked in the data model which correspond to an object cross-section and at which the bid-up material should be solidified. In a second step, the layer data set is modified in such a way that for at least a portion of the object cross-section, the number of beams required for solidifying the build-up material inside said portion is determined preferably automatically, according to quality specifications of the portion and/or a manufacturing time of the object. In a third step, the modified layer data set is provided as a control data set for the additive layer manufacturing device.

A laser powder bed fusion additive manufacturing system for producing a part by creating a power map that is an intelligent feed forward model to control the laser powder bed fusion additive manufacturing for producing the part and using the power map to control the laser powder bed fusion additive manufacturing for producing the part. This includes an apparatus for producing a part including a powder bed, a laser that produces a laser beam, a proportional integral derivative controller that creates a power map that describes laser power requirements as the laser moves along a path, wherein the laser power requirements prevent defects in the part.

Disclosed is a method for providing a control command set for an additive manufacturing device. The method includes providing a parameter set consisting of a number of parameters, and a construction rule, which is suitable for describing at least one section of the object by the parameter set geometrically as a number of linear or flat elements in space; generating a computer-based layer model of the section of the object by determining, for each layer, the position and shape of a cross-section of the section of the object within the layer, generating a control command set for an additive manufacturing device by which the production of the section of the object is implemented on the basis of the layer model.

A manufacturing facility of a sintered product according to one aspect of the present disclosure includes: a molding apparatus configured to press-mold raw material powder containing metal powder to fabricate powder compacts; a marking apparatus configured to mark a product ID including a serial number on each of the powder compacts; a batch processing apparatus configured to perform a predetermined batch process on intermediate materials which are the powder compacts or sintered articles of the powder compacts; a reader apparatus configured to read the product ID of each of the intermediate materials loaded in a batch case of the batch processing apparatus; and a server apparatus configured to communicate with the apparatuses. The server apparatus includes: a communication unit configured to receive a read value of the product ID from the reader apparatus; and a control unit configured to specify a load position of each of the intermediate materials in the batch case based on the received read value.

Methods for control of post-design free form deposition processes or joining processes are described that utilize machine learning algorithms to improve fabrication outcomes. The machine learning algorithms use real-time object property data from one or more sensors as input, and are trained using training data sets that comprise: i) past process simulation data, past process characterization data, past in-process physical inspection data, or past post-build physical inspection data, for a plurality of objects that comprise at least one object that is different from the object to be fabricated; and ii) training data generated through a repetitive process of randomly choosing values for each of one or more input process control parameters and scoring adjustments to process control parameters as leading to either undesirable or desirable outcomes, the outcomes based respectively on the presence or absence of defects detected in a fabricated object arising from the process control parameter adjustments.

A method for manufacturing a custom-fit surgical glove for a particular user includes constructing a personal three dimensional digital model of the custom-fit surgical glove using a processing computer. The method further includes translating the personal three dimensional digital model into manufacturing instructions using the processing computer, and the method includes constructing the custom-fit surgical glove using at least an additive manufacturing process and using the manufacturing instructions.

A method for the additive construction of a structure for a component includes the following steps: providing a prefabricated component for the component on a building board, wherein the component has a separating plane, providing a powder bed from a base material for the structure, moving the building board closer to a coating device, aligning a processing surface and the separating plane of the component for preventing adhesion between the component and the coating device, and optically measuring a surface of the powder bed.

A method for producing a three-dimensional shaped product having an undercut region on the upper side and an interior space forming region on the lower side, by lamination of powder, sintering of a laminated layer and cutting of the sintered layer, includes the steps of, when a cutting path where the side is a location of the top edge of the interior space that has been created during creation of horizontal cutting paths for cutting of the interior space forming region, setting by the CAD/CAM system a command for carrying out further lamination at the location of the top edge, or creating a horizontal cutting path on a location on an upper side above the horizontal cutting path by a cutting width and setting a command to the cutting tool for terminating cutting along the cutting path, thereby avoiding having to cut a created horizontal cutting path.

The present disclosure provides methods of defining internal secondary structures of an object to be formed at least in part by additive manufacturing. The object may include a primary structure having a volume. The methods may include applying a balancing parameter within an axis-aligned bounding box that encompasses the primary structure. The methods may further include refining the balancing parameter until the volume is delimited into a plurality of the internal structures. The plurality of internal structures may be oriented at an angle to a global z-axis that is substantially parallel to a build direction, such as angled in a range of 40 degrees to 70 degrees to the z-axis.

According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a part parameter dictionary module comprising a processor, geometry data for a plurality of geometric structures forming a plurality of parts, wherein the parts are manufactured with an additive manufacturing machine; determining, using the processor of the part parameter dictionary module, a feature set for each geometric structure; generating, using the processor of the part parameter dictionary module, one of a coupon and a coupon set for the feature set; generating an optimized parameter set for each coupon, using the processor of the part parameter dictionary module, via execution of an iterative learning control process for each coupon; mapping, using the processor of the part parameter dictionary module, one or more parameters of the optimized parameter set to one or more features of the feature set; and generating a dictionary of optimized scan parameter sets to fabricate geometric structures with a material used in additive manufacturing. Numerous other aspects are provided.