A method and printing system for printing a three-dimensional structure, in particular an optical component, by depositing droplets of printing ink side by side and one above the other in several consecutive depositing steps by means of a print head. In each depositing step a plurality of droplets is ejected simultaneously by a plurality of ejection nozzles of the print head. The print head is moved relative to the deposited droplets in a moving step performed between at least two consecutive depositing steps in such a manner that the droplets deposited in the same position in the at least two consecutive depositing steps are ejected at least partly from two different ejection nozzles.

A 3D printing apparatus and method confirms that one or more print parameters was satisfied in the printing of a 3D object. Sensor readings are obtained during the printing of the 3D object. Based on sensor data corresponding to the sensor readings, a confirmation is made as to whether the one or more print parameters was satisfied in the printing of the 3D object.

A method of forming a balanced rotor blade assembly includes measuring a weight of a plurality of sub-components of the rotor blade assembly excluding a core. A configuration of a core of the rotor blade assembly is determined. In combination, the core and the plurality of sub-components achieve a target weight distribution and moment. The core is then fabricated and assembled with the plurality of sub-components to form a rotor blade sub-assembly.

A method of forming a balanced rotor blade assembly includes measuring a weight of a plurality of sub-components of the rotor blade assembly excluding a core. A configuration of a core of the rotor blade assembly is determined. In combination, the core and the plurality of sub-components achieve a target weight distribution and moment. The core is then fabricated and assembled with the plurality of sub-components to form a rotor blade sub-assembly.

A method for producing a three-dimensional component by means of a laser melting process, in which the component is produced by consecutively solidifying individual layers made of building material by melting the building material, wherein said building material can be solidified by the action of radiation, wherein the melting area produced by a punctiform and/or linear energy input is detected by a sensor device and sensor values are derived therefrom in order to evaluate the component quality. The sensor values detected in order to evaluate the component quality are stored together with the coordinate values that locate the sensor values in the component and are displayed by means of a visualization unit in two- and/or multi-dimensional representation with respect to the detection location of the sensor values in the component.

A method for producing a three-dimensional component by means of a laser melting process, in which the component is produced by consecutively solidifying individual layers made of building material by melting the building material, wherein said building material can be solidified by the action of radiation, wherein the melting area produced by a punctiform and/or linear energy input is detected by a sensor device and sensor values are derived therefrom in order to evaluate the component quality. The sensor values detected in order to evaluate the component quality are stored together with the coordinate values that locate the sensor values in the component and are displayed by means of a visualization unit in two- and/or multi-dimensional representation with respect to the detection location of the sensor values in the component.

A method of making a workpiece in an additive manufacturing process includes determining a preferred angular orientation of the grid array about a build axis extending perpendicular to a layer to be built for a first layer of a workpiece. The preferred angular orientation is selected to align an edge of one or more pixels with an edge of the layer of the workpiece being built. The method further includes orienting a patterned image of radiant energy to the preferred angular orientation by rotating a projector before solidifying a portion of a resin that forms the first layer of the workpiece.

A method of making a workpiece in an additive manufacturing process includes determining a preferred angular orientation of the grid array about a build axis extending perpendicular to a layer to be built for a first layer of a workpiece. The preferred angular orientation is selected to align an edge of one or more pixels with an edge of the layer of the workpiece being built. The method further includes orienting a patterned image of radiant energy to the preferred angular orientation by rotating a projector before solidifying a portion of a resin that forms the first layer of the workpiece.

A process for support material removal for 3D printed parts wherein the part is placed in a media filled tank and support removal is optimized in a multi-parameter system through an artificial intelligence process which may include, but is not limited to, the use of historical data, parametric testing data, normal support removal data, and outputs from other support removal AI models to generate optimally efficient use of each parameter in terms of pulse repetition interval (PRI) and cycle time as defined by pulse width (PW). The input parameters may include heat, circulation, ultrasound and chemical reaction, which are used in sequence and/or in parallel, to optimize efficiency of support removal. Sequentially and/or in parallel, heat, pump circulation and ultrasound may vary in application or intensity. Selection of means of agitation depends on monitored feedback from the support removal tank and application of a statistically dynamic rule based system (SDRBS).

A process for support material removal for 3D printed parts wherein the part is placed in a media filled tank and support removal is optimized in a multi-parameter system through an artificial intelligence process which may include, but is not limited to, the use of historical data, parametric testing data, normal support removal data, and outputs from other support removal AI models to generate optimally efficient use of each parameter in terms of pulse repetition interval (PRI) and cycle time as defined by pulse width (PW). The input parameters may include heat, circulation, ultrasound and chemical reaction, which are used in sequence and/or in parallel, to optimize efficiency of support removal. Sequentially and/or in parallel, heat, pump circulation and ultrasound may vary in application or intensity. Selection of means of agitation depends on monitored feedback from the support removal tank and application of a statistically dynamic rule based system (SDRBS).