Robert Boschgmbh

Ivan Batalov

Filipe J Cabrita Condessa

Devin T Willmott

Wan-Yi Lin

Jeremy Zieg Kolter

João D Semedo

Jeffrey Thompson

Methods and systems for training a machine learning model with measurement data captured during a manufacturing process. Measurement data regarding a physical characteristic of a plurality of manufactured parts is received as measured by a plurality of sensors at various manufacturing stations. A time-series dynamics machine learning model encodes the measurement data into a latent space having a plurality of nodes. Each node is associated with the measurement data of one of the manufactured parts and at one of the manufacturing stations. A batch of the measurement data can be built, the batch include a first node and a first plurality of nodes immediately connected to the first node via first edges, and measured in time earlier than the first node. A prediction machine learning model can predict measurements of a first of the manufactured parts based on the latent space of the batch of nodes.

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Pittsburgh, PA, United States of America

Ivan Batalov