by Julio Molleda, Juan Carlos Granda, Rubén Usamentiaga, Daniel Fernando García and David Laurenson
Abstract:
Endless strip generation is the key to productivity and quality in several types of steel coil production lines. Coil-tocoil joining by means of welding machines provides such a strip. Since the joint is the weakest area of the strip, its quality must be assessed for the production line to accept it. Therefore, it is necessary to inspect the quality of the weld in the welding-cycle time. Based on our knowledge acquired in the previous development of quality assessment prototypes for steel strips, we present in this article an improved inspection system to detect defective resistance seam welds based on anomaly detection techniques. This system does not rely on the weld classifications done in production lines based on welding control programs. Therefore, it is immune to the influence of both incorrectly configured welding control programs and chemical composition variations from coil to coil of the same steel grade. Tuning the inspection system required a fully experimental design, which would have taken several months using a conventional computer. For this reason, the high-performance computing (HPC) facilities at the Edinburgh Parallel Computing Center were used to cut down the tuning time. 2014 IEEE.
Reference:
Optimizing steel coil production: an enhanced inspection system based on anomaly detection techniques (Julio Molleda, Juan Carlos Granda, Rubén Usamentiaga, Daniel Fernando García and David Laurenson), In IEEE Industry Applications Magazine, volume 20, 2014.
Bibtex Entry:
@article{molleda2014iam,
author = {Julio Molleda and Juan Carlos Granda and Rubén Usamentiaga and Daniel Fernando García and David Laurenson},
title = {Optimizing steel coil production: an enhanced inspection system based on anomaly detection techniques},
volume = {20},
number = {2},
pages = {35--43},
issn = {1077-2618},
abstract = {Endless strip generation is the key to productivity and quality in several types of steel coil production lines. Coil-tocoil joining by means of welding machines provides such a strip. Since the joint is the weakest area of the strip, its quality must be assessed for the production line to accept it. Therefore, it is necessary to inspect the quality of the weld in the welding-cycle time. Based on our knowledge acquired in the previous development of quality assessment prototypes for steel strips, we present in this article an improved inspection system to detect defective resistance seam welds based on anomaly detection techniques. This system does not rely on the weld classifications done in production lines based on welding control programs. Therefore, it is immune to the influence of both incorrectly configured welding control programs and chemical composition variations from coil to coil of the same steel grade. Tuning the inspection system required a fully experimental design, which would have taken several months using a conventional computer. For this reason, the high-performance computing ({HPC}) facilities at the Edinburgh Parallel Computing Center were used to cut down the tuning time. 2014 {IEEE}.},
author+an = {2=highlight},
date = {2014},
year = {2014},
doi = {10.1109/MIAS.2013.2288385},
journal = {{IEEE} Industry Applications Magazine},
shortjournal = {{IEEE} Ind Appl Mag},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894585626&doi=10.1109%2fMIAS.2013.2288385&partnerID=40&md5=d4044def326ce1c0b915aa7f94b7ca88},
jcr = {0.352 -- Q4 [2014]},
}