@inproceedings{8404b2edb8004a089b726105f219019d,
title = "A Quality Inspection System for Resistance Seam Welds in Endless Production of Steel Coils Using Anomaly Detection Techniques",
abstract = "Endless strip generation is the key to productivity and quality in several types of steel coil production lines. Coil-to-coil 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 in order 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 paper 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 in a conventional computer. For this reason, the high-performance computing facilities at the Edinburgh Parallel Computing Center were used to cut down the tuning time.",
author = "Julio Molleda and Granda, {Juan C.} and Rub{\'e}n Usamentiaga and Garc{\'i}a, {Daniel F.} and David Laurenson",
year = "2012",
doi = "10.1109/IAS.2012.6374073",
language = "English",
series = "Conference Record of the IEEE Industry Applications Conference",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "1--8",
booktitle = "2012 IEEE Industry Applications Society Annual Meeting (IAS)",
address = "United States",
note = "Industry Applications Society Annual Meeting (IAS) ; Conference date: 07-10-2012 Through 11-10-2012",
}