Online geometry assurance in individualized production by feedback control and model calibration of digital twins
Artikel i vetenskaplig tidskrift, 2023

In this paper, we consider online calibration of a Digital Twin and its use for control and optimization in the assembly process of sheet metal parts. This calibration is done based on a feedback signal received by calculating the quality of the simulated assemblies as compared to the prediction made by the Digital Twin. We develop a Kalman filter-based approach for online calibration of the Digital Twin, which in turn is used by a one-step look-ahead optimizer to define an online control scheme. This control scheme balances directly predicted quality gains against reduced uncertainty whose purpose is to enable long-term quality gains. The usage of a calibrated model in a one-step look-ahead optimizer as a controller allows to incorporate the benefits of the usage of Digital Twins for individualized control, where the control parameters of a production cell are optimized in a Digital Twin based on measured properties of the production inputs, over nominal control, where control parameters are set with respect to some reference production inputs, in an approach which is able to use measured final production quality for feedback control. The proposed approach is evaluated by computer simulations of two industrial product assembly use cases. In the first case, it demonstrates significant gains in quality of the produced assemblies, while in the second case it shows negligible to small improvements. The second case is, however, rather insensitive to miscalibration, which enables only small gains.

Unscented Kalman filter

Calibration

Digital Twin

Smart assembly 4.0

Författare

Anders Sjöberg

Fraunhofer Center for Machine Learning

Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik

Magnus Önnheim

Fraunhofer Center for Machine Learning

Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik

Otto Frost

Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik

Fraunhofer Center for Machine Learning

Constantin Cronrath

Chalmers, Elektroteknik, System- och reglerteknik

Emil Gustavsson

Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik

Fraunhofer Center for Machine Learning

Bengt Lennartson

Chalmers, Elektroteknik, System- och reglerteknik

Mats Jirstrand

Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik

Chalmers, Elektroteknik, System- och reglerteknik

Fraunhofer Center for Machine Learning

Journal of Manufacturing Systems

0278-6125 (ISSN)

Vol. 66 71-81

Smart Assembly 4.0

Stiftelsen för Strategisk forskning (SSF) (RIT15-0025), 2016-05-01 -- 2021-06-30.

Styrkeområden

Informations- och kommunikationsteknik

Produktion

Ämneskategorier

Reglerteknik

Matematisk analys

DOI

10.1016/j.jmsy.2022.11.011

Mer information

Senast uppdaterat

2023-09-26