Siemens Aktiengesellschaft

Mitchell Joblin

Andreas Graichen

Siegmund Düll

Clemens Otte

Jonas Eriksson

Jerry Fornander

Felix Buggenthin

Axel Reitinger

Michael Caelers

Steffen Lamparter

Michal Skubacz

Ingo Thon

Serghei Mogoreanu

Marcel Hildebrandt

Victor Balanica

Vincent Sidenvall

Maja Milicic Brandt

Dianna Yee

Sunil Viswanathan

Yi Huang

Chandra Sekhar Akella

Yushan Liu

Siegmund DÜLL

A method including providing a graph database representation, wherein the graph database representation represents a plurality of nodes in a graph which are interconnected by respective edges, wherein each node of the plurality of the nodes represents a data sample and is assigned to at least one node feature, wherein each edge of the plurality of the edges represents a relationship between the data samples, transforming the graph database representation into a data matrix using a first machine learning algorithm suitable for graph data and an architecture as first layers of a joint machine learning architecture, determining at least one node of the plurality of nodes based on the transformed data matrix using a second machine learning algorithm and a second architecture as second layers of a joint machine learning architecture, and providing the at least one determined node. Further, a computing unit and a computer program product is provided.

Determining at least one node

An apparatus and method for monitoring a quality of an object of a 3D-print job series of identical objects, each object built from a multitude of stacked 2D-layers printed by a 3D-printer in an additive manufacturing process, including: determining a layer quality indicator of a currently printed layer of an object, comparing the determined layer quality indicator of the currently printed layer with a predetermined lower confidence limit of the layer, the predetermined lower confidence limit being calculated depending on layer quality indicators of previously completely manufactured objects complying with predefined quality requirements, and generating a warning signal, if the layer quality indicator of the currently printed layer has a value equal or lower than the lower quality limit is provided.

Method and apparatus for monitoring a quality of an object of a 3D-print-job series of identical objects

A method and system for automatic maintenance of a machine () comprising the steps of receiving (S) at least one maintenance relevant event (E) from a controller () of the machine (); augmenting (S) the received event (E) with the event's machine context read from a machine maintenance ontology; matching (S) the event's machine context with maintenance rules to generate at least one maintenance task (T) comprising an associated task description; and providing (S) a maintenance schedule for the machine () assigning the generated maintenance task (T) to suitable maintenance executing entities () on the basis of the task description of the respective maintenance task (T).

Method and system for automatic maintenance of a machine

Provided is a method for computer-aided processing of quality information of an object manufactured by stacked printed layers in an additive manufacturing system, including the steps of: receiving a quality indicator for each printed layer of the object from the manufacturing system, assigning a color out of a predefined set of colors to each quality indicator depending on the value of the quality indicator, visualizing the quality indicators of the received manufactured layers as a sequence of colored bars ordered according to the sequence of the manufactured layers the color of each bar indicating the value of the quality indicator of the respective printed layer on a graphical user interface.

Method for computer-aided processing of quality information of an object and a respective assistance apparatus

The present invention provides an enhanced setup of a 3D-printing device, especially to a laser powder bed fusion 3D-printing device. It is for this purpose, that data relating to previously printed products are stored in a database. When a new product is to be printed, the features of the new product are matched with features of previously printed products stored in the database. Accordingly, a suggestion for setting-up the 3D-printing device based on corresponding previously printed products and their setup parameters can be automatically determined and applied to the 3D-printing device.

Method and apparatus for controlling a 3D-printing device and 3D-printing device

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Erlangen, Germany

Mitchell Joblin