US 12,462,159 B2
Methods and systems for training a machine learning model with measurement data captured during manufacturing process
Filipe J. Cabrita Condessa, Pittsburgh, PA (US); Devin T. Willmott, Pittsburgh, PA (US); Ivan Batalov, Pittsburgh, PA (US); João D. Semedo, Pittsburgh, PA (US); Wan-Yi Lin, Wexford, PA (US); Jeremy Kolter, Pittsburgh, PA (US); and Jeffrey Thompson, Stuttgart (DE)
Assigned to Robert Bosch GmbH, (DE)
Filed by Robert Bosch GmbH, Stuttgart (DE)
Filed on Jun. 16, 2022, as Appl. No. 17/842,041.
Prior Publication US 2023/0409916 A1, Dec. 21, 2023
Int. Cl. G06F 16/00 (2019.01); G06N 3/084 (2023.01)
CPC G06N 3/084 (2013.01) 20 Claims
OG exemplary drawing
 
1. A computer-implemented method of training a machine learning model with measurement data captured during a manufacturing process, the method comprising:
receiving measurement data regarding a physical characteristic of a plurality of manufactured parts as measured by a plurality of sensors at various manufacturing stations;
via a time-series dynamics machine learning model, encoding the measurement data into a latent space having a plurality of nodes, each node associated with the measurement data of one of the manufactured parts as measured at one of the manufacturing stations;
via a prediction machine learning model, determining a predicted measurement of a first of the manufactured parts at a first of the manufacturing stations based on the latent space of at least some of the measurement data not including the measurement data corresponding to the first manufactured part at the first manufacturing station;
via the machine learning model, comparing the prediction measurement of the first manufactured part to the measurement data of the first manufactured part at the first manufacturing station;
based on a difference between the prediction measurements and the actual measurement data, updating parameters of the machine learning model until convergence; and
based upon the convergence, outputting a trained machine learning model with the updated parameters.