A monitoring and control framework for lost foam casting manufacturing processes using genetic programming

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@Article{journals/ijbic/ShetaRA12,
  author =       "Alaa F. Sheta and Peter Rausch and Alaa S. Al-Afeef",
  title =        "A monitoring and control framework for lost foam
                 casting manufacturing processes using genetic
                 programming",
  journal =      "International Journal of Bio-Inspired Computation",
  year =         "2012",
  number =       "2",
  volume =       "4",
  pages =        "111--118",
  keywords =     "genetic algorithms, genetic programming, electrical
                 capacitance tomography, ECT, process tomography, image
                 reconstruction, quality management, lost foam casting,
                 process monitoring, process control, manufacturing
                 industry, production activity control, PAC, enterprise
                 resource planning, ERP, business intelligence",
  DOI =          "doi:10.1504/IJBIC.2012.047182",
  ISSN =         "1758-0374",
  URL =          "https://sites.google.com/site/alaaalfeef/home/IJBIC040206_RAUSCH.pdf?attredirects=0&d=1",
  size =         "8 pages",
  abstract =     "Monitoring and control of manufacturing processes is
                 an essential part of any industry. Being able to
                 collect sensor measurements, analyse the measurements
                 in an intelligent way, select appropriate actions and
                 validate the desired results of these actions is a
                 tremendous goal to be achieved. In this paper, we
                 propose a monitoring and control framework of a
                 multi-tier closed-loop controlling lost foam casting
                 (LFC) system. The proposed system consists of several
                 subsystems like production activity control (PAC),
                 enterprise resource planning (ERP), and business
                 intelligence (BI). Another essential part of the system
                 is the electrical capacitance tomography (ECT)
                 subsystem. This subsystem is in charge of collecting
                 measurements from the LFC process, develops an
                 evolutionary model-based genetic programming (GP) of
                 the process and reconstructs an image of the casting
                 process. The proposed framework can be used to improve
                 the quality of manufacturing processes and to enhance
                 process reliability which, as a result, will increase
                 companies' profit. The proposed framework can be
                 extended to a variety of applications.",
  notes =        "Computer Science Department, Faculty of Information
                 Technology, The World Islamic Science and Education
                 (WISE) University, P.O. Box 1101, Amman 11947,
                 Jordan.",
  bibdate =      "2012-06-11",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/journals/ijbic/ijbic4.html#ShetaRA12",
}

Genetic Programming entries for Alaa Sheta Peter Rausch Alaa Al-Afeef

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