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

Authors: Alaa F. Sheta; Peter Rausch; Alaa S. Al-Afeef

Addresses: Computer Science Department, Faculty of Information Technology, The World Islamic Science and Education (WISE) University, P.O. Box 1101, Amman 11947, Jordan. ' Computer Science Department, Georg Simon Ohm University of Applied Sciences, Kesslerplatz 12, 90489, Nuremberg, Germany. ' School of Computing Science, University of Glasgow, Room G102, Sir Alwyn Williams Building, Lilybank Gardens, Glasgow, G12 8QQ, Scotland

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.

Keywords: electrical capacitance tomography; ECT; process tomography; image reconstruction; genetic programming; quality management; lost foam casting; process monitoring; process control; manufacturing industry; production activity control; PAC; enterprise resource planning; ERP; business intelligence.

DOI: 10.1504/IJBIC.2012.047182

International Journal of Bio-Inspired Computation, 2012 Vol.4 No.2, pp.111 - 118

Received: 25 Aug 2011
Accepted: 01 Apr 2012
Published online: 22 Sep 2014 *

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