General Electric Company

United Technologies Corporation

Anthony Joseph Vinciquerra

Laura Cerully Dial

Vipul Kumar Gupta

Timothy Hanlon

Voramon Supatarawanich Dheeradhada

Natarajan Chennimalai Kumar

Joshua Tyler Mook

Lembit Salasoo

Subhrajit Roychowdhury

Paul Edward Cuddihy

Scott Andrew Weaver

Arvind Rangarajan

Kareem Sherif Aggour

Brian Scott McCarthy

Scott Michael Oppenheimer

Xiaohu Ping

Jenny Marie Weisenberg Williams

Christina Margaret Vasil

Vijay Shiv Kumar

Bernard Patrick Bewlay

Changjie Sun

Ananda Barua

Justin John Gambone, Jr

Shenyan Huang

Min Zou

Vandana Prabhakar Rallabandi

Wanming Zhang

Frank J Euvino, Jr

Justin John Gambone

Jenny Marie Williams

Paul Cuddihy

Frank J Jnr Euvino

Methods for manufacturing dual phase soft magnetic components include combining a plurality of soft ferromagnetic particles with a plurality of paramagnetic particles to form a component structure, wherein the plurality of soft ferromagnetic particles each comprise an electrically insulative coating, and, heat treating the component structure to consolidate the plurality of soft ferromagnetic particles with the plurality of paramagnetic particles.

Dual phase soft magnetic particle combinations, components and manufacturing methods

According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a parameter development module comprising a processor, a defined geometry for one or more parts, wherein the parts are manufactured with an additive manufacturing machine, and wherein a stack is formed from one or more parts; fabricating the one or more parts with the additive manufacturing machine based on a first parameter set; collecting in-situ monitoring data from one or more in-situ monitoring systems of the additive manufacturing machine for one or more parts; determining whether each stack should receive an additional part based on an analysis of the collected in-situ monitoring data; and fabricating each additional part based on the determination the stack should receive the additional part. Numerous other aspects are provided.

In-situ monitoring system assisted material and parameter development for additive manufacturing

A method for fabricating a component of with an additive manufacturing system include entraining a first portion of first material particles in an airflow generated by a vacuum source and engaging the first portion of the first material particles against an air permeable screen. The first portion of the first material particles is deposited onto a build platform. The method also includes entraining a second portion of second material particles in the airflow and engaging the second portion of the second material particles against the air permeable screen. The second portion of the second material particles is deposited onto the build platform. An energy source transfers heat to at least a portion of at least one of the first portion of the first material particles or the second portion of the second material particles to facilitate consolidating material particles to fabricate the component.

Methods and systems for vacuum powder placement in additive manufacturing systems

A method, medium, and system including determining a material property value to assign to each of the plurality of 3D volume elements, wherein the material property values assigned to the plurality of 3D volume elements are classified into a predetermined number of bins that correspond to a plurality of different additive manufacturing (AM) print parameter sets, generating a plurality of transfer functions to determine relationships between the material property values assigned to the plurality of 3D volume elements and a plurality of desired AM print parameter sets, automatically determining, based on the plurality of transfer functions, an assignment of one of the plurality of different AM print parameter sets to each of the plurality of 3D volume elements, and validating the determined assignments of the plurality of different AM print parameter sets for the plurality of 3D volume elements based on the plurality of transfer functions.

Autozoning of additive manufacturing print parameters

Methods and systems for optimizing additive process parameters for an additive manufacturing process. In some embodiments, the process includes receiving initial additive process parameters, generating an uninformed design of experiment utilizing a specified sampling protocol, next generating, based on the uninformed design of experiment, response data, and then generating, based on the response data and on previous design of experiment that includes at least one of the uninformed design of experiment and informed design of experiment, an informed design of experiment by using the machine learning model and the intelligent sampling protocol. The last process step is repeated until a specified objective is reached or satisfied.

Machine learning assisted development in additive manufacturing

A method, medium, and system to automatically determine parameter sets for an additive manufacturing (AM) of a part, the method including executing a load analysis on a model of a part to emulate a load on each of a plurality of regions of the part; determining a representation of the model of the part as a plurality of discrete three-dimensional (3D) volume elements; determining, based on an output of the load analysis, a life or material property value to assign to each of the plurality of 3D volume elements; automatically determining an assignment of one of a plurality of additive manufacturing (AM) print parameter sets to each of the plurality of 3D volume elements; and saving a record of the determined assignments of the AM print parameter sets to each of the plurality of 3D volume elements.

A system for querying a federated data store includes a metadata knowledge graph describing the contents and relationships among one or more underlying data stores, an interactive user interface receiving requests from a data consumer, a predefined constrainable query ('nodegroup') store containing predefined constrainable queries that define data subsets of interest across one or more of the underlying data repositories, a knowledge-driven querying layer generating and executing queries against the federated data store and merging responsive results, a scalable analytic execution layer receiving the search results from the federated data store and applying machine learning/artificial intelligence techniques to analyze the results, and a user interface presenting visualizations of raw or analyzed results to the consumer. A method and a non-transitory computer-readable medium are also disclosed.

Knowledge-driven federated big data query and analytics platform

A system to generate and run federated queries against a plurality of data stores storing disparate data types, the system including a user interface receiving query details from a data consumer, a metadata knowledge graph containing metadata for links and relationships of the data stores, a knowledge-driven querying layer accessing the graph and selecting predefined constrainable queries from a nodegroup store and applying the metadata links/relationships to the predefined constrainable queries to assemble subqueries, a query and analysis platform providing the subqueries to some of the data stores for execution, a scalable analytic execution layer receiving and aggregating search results from the data stores into a merged search result and/or obtaining analytic results by applying machine learning and artificial intelligence techniques to the distributed data, the user interface presenting visualizations generated from the merged search results, and/or the analytic results. A system and a non-transitory computer-readable medium are also disclosed.

A powder quality control system includes a powder container, a piston, and at least one sensor. The powder container is configured to contain a powder sample. The piston is configured to compact the powder sample in the powder container. The at least one sensor is configured to measure at least one parameter when the piston compacts the powder sample to facilitate determining a powder quality measurement for the powder sample.

Systems and methods for additive manufacturing powder assessment

Additive manufacturing apparatus including a build module is presented. The build module includes a support structure; a powder supply chamber formed in the support structure; and powder applicator disposed on the support structure and located proximate to the powder supply chamber. The build module further includes a powder recovery chamber and a plurality of build plates spatially disposed around the powder recovery chamber, the plurality of build plates configured to move around the powder recovery chamber. The build module is configured such that during an additive manufacturing process step, a build plate of the plurality of build plates is disposed between the powder supply chamber and the powder recovery chamber, and the powder applicator is configured to distribute a required amount of the powder material from the powder supply chamber on the build plate and deposit any excess powder material in the powder recovery chamber. Related processes are also presented.

Additive manufacturing apparatus and related process

A modular fan inlet ice protection system includes a center ring, an outer ring and a plurality of struts. The struts are each coupled at a first end to the center ring, and at a second end to the outer ring. A plurality of shell members are each configured to be removably coupled to a corresponding strut. Moreover, the shell members each include an electrothermal heater element. Preferably the system further includes a plurality of inlet guide vanes each including an electrothermal heater element.

Growing community of inventors

Rexford, NY, United States of America

Anthony Joseph Vinciquerra