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Advances in Materials Science and Engineering
Volume 2017, Article ID 3192672, 11 pages
https://doi.org/10.1155/2017/3192672
Research Article

Intelligent Machine Vision Based Modeling and Positioning System in Sand Casting Process

1School of Mechanical & Manufacturing Engineering, National University of Sciences and Technology (NUST), Islamabad, Pakistan
2Directorate of Quality Assurance, National University of Sciences and Technology (NUST), Islamabad, Pakistan
3School of Mechanical Engineering, Beijing Institution of Technology, Beijing, China

Correspondence should be addressed to Shahid Ikramullah Butt; kp.ude.tsun.emms@dihahsrd

Received 21 October 2016; Revised 31 December 2016; Accepted 16 January 2017; Published 8 February 2017

Academic Editor: Charles C. Sorrell

Copyright © 2017 Shahid Ikramullah Butt et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Advanced vision solutions enable manufacturers in the technology sector to reconcile both competitive and regulatory concerns and address the need for immaculate fault detection and quality assurance. The modern manufacturing has completely shifted from the manual inspections to the machine assisted vision inspection methodology. Furthermore, the research outcomes in industrial automation have revolutionized the whole product development strategy. The purpose of this research paper is to introduce a new scheme of automation in the sand casting process by means of machine vision based technology for mold positioning. Automation has been achieved by developing a novel system in which casting molds of different sizes, having different pouring cup location and radius, position themselves in front of the induction furnace such that the center of pouring cup comes directly beneath the pouring point of furnace. The coordinates of the center of pouring cup are found by using computer vision algorithms. The output is then transferred to a microcontroller which controls the alignment mechanism on which the mold is placed at the optimum location.