A fast and robust decision support system for in-line quality assessment of resistance seam welds in the steelmaking industry (bibtex)
by Julio Molleda, Juan Luis Carús, Rubén Usamentiaga, Daniel Fernando García, Juan Carlos Granda and José Luis Rendueles
Abstract:
Assessing the quality of a weld in the steelmaking industry is a complex task. The level of complexity increases when the assessment is based on non-destructive tests. Skilled technicians are often required to make a decision based on automatic assessments of welds. Technicians consider the results of the automatic assessments and use their expert knowledge in order to make a final decision about the quality of the weld. In this paper we propose a decision support system to assess the quality of resistance seam welds of steel strips based on statistical analysis of both the mechanical and electrical variables involved in the welding process to be assessed as well as previously recorded historical data of similar welds. The proposed system is designed following component model based software architecture. The system consists of a set of orthogonal modules: welding variable measurement, welding variable processing and welding quality assessment, communicated by means of dedicated interfaces. The proposed system has been installed in three steel manufacturing lines. With the reduction in the time spent by technicians to make a decision about each weld, the productivity of the manufacturing line has greatly improved. Furthermore, production costs have been reduced since the number of defective welds assessed as non-defective was reduced, and thus the failures in the manufacturing lines due to weld breakages. The experimental results after two years of use in a steel strip galvanizing line are shown. 2011 Elsevier B.V.
Reference:
A fast and robust decision support system for in-line quality assessment of resistance seam welds in the steelmaking industry (Julio Molleda, Juan Luis Carús, Rubén Usamentiaga, Daniel Fernando García, Juan Carlos Granda and José Luis Rendueles), In Computers in Industry, volume 63, 2012.
Bibtex Entry:
@article{molleda2012ci,
  author       = {Julio Molleda and Juan Luis Carús and Rubén Usamentiaga and Daniel Fernando García and Juan Carlos Granda and José Luis Rendueles},
  title        = {A fast and robust decision support system for in-line quality assessment of resistance seam welds in the steelmaking industry},
  volume       = {63},
  number       = {3},
  pages        = {222--230},
  issn         = {0166-3615},
  abstract     = {Assessing the quality of a weld in the steelmaking industry is a complex task. The level of complexity increases when the assessment is based on non-destructive tests. Skilled technicians are often required to make a decision based on automatic assessments of welds. Technicians consider the results of the automatic assessments and use their expert knowledge in order to make a final decision about the quality of the weld. In this paper we propose a decision support system to assess the quality of resistance seam welds of steel strips based on statistical analysis of both the mechanical and electrical variables involved in the welding process to be assessed as well as previously recorded historical data of similar welds. The proposed system is designed following component model based software architecture. The system consists of a set of orthogonal modules: welding variable measurement, welding variable processing and welding quality assessment, communicated by means of dedicated interfaces. The proposed system has been installed in three steel manufacturing lines. With the reduction in the time spent by technicians to make a decision about each weld, the productivity of the manufacturing line has greatly improved. Furthermore, production costs have been reduced since the number of defective welds assessed as non-defective was reduced, and thus the failures in the manufacturing lines due to weld breakages. The experimental results after two years of use in a steel strip galvanizing line are shown. 2011 Elsevier B.V.},
  author+an    = {5=highlight},
  date         = {2012},
  year         = {2012},
  doi          = {10.1016/j.compind.2012.01.003},
  journal      = {Computers in Industry},
  keywords     = {Artificial intelligence, Automatic assessment, Complex task, Component model, Decision support systems, Expert knowledge, Final decision, Galvanizing lines, Historical data, In-line, Manufacture, Manufacturing lines, Nondestructive examination, Non-destructive test, Orthogonal modules, Production cost, Quality assessment, Quality inspection, Resistance seam welding, Robust decisions, Seam weld, Signal processing, Software architecture, Statistical analysis of historical data, Statistical methods, Steelmaking, Steel-making industries, Steel manufacturing, Steel strip, Strip metal, Time spent, Weld assessment, Weld breakage, Welding, Welding process, Welding quality, Welding variables, Welds},
  shortjournal = {Comput Ind},
  url          = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857794019&doi=10.1016%2fj.compind.2012.01.003&partnerID=40&md5=734574a2a094f7e4b360ff5dd52c69c7},
  jcr          = {1.709 -- Q2 [2012]},
}
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