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

Author:

Butt Shahid Ikramullah1ORCID,Asgher Umer1ORCID,Mushtaq Umar1,Ahmed Riaz2,Zhang Faping3ORCID,Ayaz Yasar1ORCID,Jamil Mohsin1,Amjad Muhammad Kamal1

Affiliation:

1. School of Mechanical & Manufacturing Engineering, National University of Sciences and Technology (NUST), Islamabad, Pakistan

2. Directorate of Quality Assurance, National University of Sciences and Technology (NUST), Islamabad, Pakistan

3. School of Mechanical Engineering, Beijing Institution of Technology, Beijing, China

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.

Publisher

Hindawi Limited

Subject

General Engineering,General Materials Science

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Automation Inspection in Metal Fabrication: Enhancing Sheet Metal Forming Processes with Automation, Machine Vision and Image Correlation for Quality Assurance;Journal of Advanced Manufacturing Systems;2024-07-09

2. A Survey on Detection of Various Casting Defects Using Deep Learning Techniques;2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT);2024-01-04

3. Advanced Procedures for Series Production with 3D-Printed Core Packages;International Journal of Metalcasting;2023-04-29

4. A Review on Machine Learning Models in Injection Molding Machines;Advances in Materials Science and Engineering;2022-01-05

5. A critical review for machining positioning based on computer vision;Measurement;2021-11

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