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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