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

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...

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Bibliographic Details
Published in:Advances in materials science and engineering 2017-01, Vol.2017 (2017), p.1-11
Main Authors: Amjad, Muhammad Kamal, Ayaz, Yasar, Zhang, Faping, Ahmed, Riaz, Mushtaq, Umar, Asgher, Umer, Butt, Shahid Ikramullah, Jamil, Mohsin
Format: Article
Language:English
Subjects:
Algorithms
Automation
Cameras
Controllers
Inspection
Machine vision
Manufacturing
Mathematical models
Molds
Position (location)
Pouring
R&D
Research & development
Sand casting
Scale models
Vision systems
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Summary: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.
ISSN:1687-8434
1687-8442
DOI:10.1155/2017/3192672