Hybrid Quality Inspection for the Automotive Industry: Replacing the Paper-Based Conformity List through Semi-Supervised Object Detection and Simulated Data

Hybrid Quality Inspection for the Automotive Industry: Replacing the Paper-Based Conformity List through Semi-Supervised Object Detection and Simulated Data

The still prevalent use of paper conformity lists in the automotive industry has a serious negative impact on the performance of quality control inspectors. We propose instead a hybrid quality inspection system, where we combine automated detection with human feedback, to increase worker performance...

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Bibliographic Details
Main Authors:	Isabel Rio-Torto, Ana Teresa Campaniço, Pedro Pinho, Vitor Filipe, Luís F. Teixeira
Format:	Article
Language:	English
Published:	MDPI AG 2022-06-01
Series:	Applied Sciences
Subjects:	automotive industry hybrid assembly lines Industry 4.0 information visualization quality inspection semi-supervised cross domain object detection
Online Access:	https://www.mdpi.com/2076-3417/12/11/5687

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