Object Detection for Smart Factory Processes by Machine Learning
Series
Procedia Computer Science
Type
conference contribution
Date Issued
2021-05
Author(s)
Abstract
The production industry is in a transformation towards more autonomous and intelligent manufacturing. In addition to more flexible production processes to dynamically respond to changes in the environment, it is also essential that production processes are continuously monitored and completed in time. Video-based methods such as object detection systems are still in their infancy and rarely used as basis for process monitoring. In this paper, we present a framework for video-based monitoring of manufacturing processes with the help of a physical smart factory simulation model. We evaluate three state-of-the-art object detection systems regarding their suitability to detect workpieces and to recognize failure situations that require adaptations. In our experiments, we are able to show that detection accuracies above 90% can be achieved with current object detection methods.
Language
English
HSG Classification
contribution to scientific community
Publisher
Elsevier
Volume
184
Pages
581
Official URL
Subject(s)
Division(s)
Additional Information
See for a demo video: https://doi.org/10.6084/m9.figshare.13240784
Eprints ID
263172
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Name
1-s2.0-S1877050921007821-main.pdf
Size
684.72 KB
Format
Adobe PDF
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