Hewlett-Packard Development Company, L.p.

Hp Indigo B.v.

Instituto Atlantico

Brian Schmitz Tani

Humberto Cardoso Marchezi

Luciano Alves

Leonardo Marquezini

Nailson Boaz Costa Leite

Eduardo Rodel

Josepe Franco Gerent

Jun Zeng

Scott A White

Michel Assenheimer

Sebastia Cortes I Herms

Vitaly Portnoy

Marcelo Aita Riss

He Luan

Alyne Gomes Soares Cantal

Guilherme Selau Ribeiro

Marlon Gomes Lopez

Marlon Gomes Lopes

Guilherme Selau Riberio

Humberto C Marchezi

Examples of methods for object manufacturing visualization by an electronic device are described herein. In some examples, a predicted thermal image of additive manufacturing is determined using a machine learning model. In some examples, a captured thermal image is obtained. In some examples, a graphical overlay of the predicted thermal image with the captured thermal image is presented.

Object manufacturing visualization

A printing device includes a printing engine to selectively output print material, a replaceable item of the printing engine, and a subsystem for the printing engine. A machine learning model is used to control controllable parameters of the subsystem for the printing engine, based on physical characteristic measurements of the printing device, to maximize a lifespan of the replaceable item.

Printing device parameter control using machine learning model, in order to maximize replaceable item lifespan

Example systems may relate to component failure prediction. A non-transitory computer readable medium may contain instructions to analyze a plurality of features corresponding to a component of a system. The non-transitory computer readable medium may further contain instructions to determine which of the plurality of features to use to model a failure of the component. The non-transitory computer readable medium may contain instructions to generate a plurality of models to model the failure of the component and assemble the plurality of models into a single model for predicting component failure. The non-transitory computer readable medium may further contain instructions to extract data associated with a component failure predicted by the single model and correlate the data associated with the predicted component failure with the single model.

Component failure prediction

In one example, an electromechanical device includes a removable component comprising an electronic identification tag. The apparatus also includes a plurality of tag readers disposed at a plurality of sectors in the apparatus to detect the electronic identification tag and signal strengths associated with the detected electronic identification tag, and send the signal strengths to a tracking system.

Tracking removable components using sectors

Growing community of inventors

Porto Alegre, Brazil

Brian Schmitz Tani