Simulation and Optimization of Material Handling Systems Using Factory I/O for Industrial Automation

Ms. Priyanka Chemudugunta, Madhan. E, Pranav Anandkumar, Ashvath. K, Guru akash. C, Yogasanthiya. R and Dhanabalan. T
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Ms. Priyanka Chemudugunta: Department of Robotics and Automation Engineering, Karpaga Vinayaga College of Engineering and Technology, Chengalpattu district, Tamilnadu, India.
Madhan. E: Department of Robotics and Automation Engineering, Karpaga Vinayaga College of Engineering and Technology, Chengalpattu district, Tamilnadu, India.
Pranav Anandkumar: Department of Robotics and Automation Engineering, Karpaga Vinayaga College of Engineering and Technology, Chengalpattu district, Tamilnadu, India.
Ashvath. K: Department of Robotics and Automation Engineering, Karpaga Vinayaga College of Engineering and Technology, Chengalpattu district, Tamilnadu, India.
Guru akash. C: Department of Robotics and Automation Engineering, Karpaga Vinayaga College of Engineering and Technology, Chengalpattu district, Tamilnadu, India.
Yogasanthiya. R: Department of Robotics and Automation Engineering, Karpaga Vinayaga College of Engineering and Technology, Chengalpattu district, Tamilnadu, India.
Dhanabalan. T: Department of Robotics and Automation Engineering, Karpaga Vinayaga College of Engineering and Technology, Chengalpattu district, Tamilnadu, India.

International Journal of Research and Scientific Innovation, 2025, vol. 12, issue 5, 2195-2204

Abstract: The advancement of automation technology has revolutionized manufacturing industries by enhancing productivity, accuracy, and efficiency. This study focuses on developing and simulating an intelligent material handling system using Factory I/O, aiming to replicate real world industrial automation scenarios. The objective of this project is to design a smart conveyor based system integrated with sensor technology and robotic manipulation to streamline the transfer and assembly processes. By employing precise object detection through diffusion sensors and timing control via encoders, the simulation ensures accurate handling and positioning of components. A manipulator equipped with a vacuum suction gripper automates the transfer of objects between conveyors, emulating real world assembly line operations. This simulation offers significant benefits, including reduced manual intervention, minimized errors, and optimized production flow, aligning with Industry 4.0 standards. The results demonstrate the effectiveness of integrating advanced sensors and automated handling systems in improving operational efficiency. Comparative analysis with existing studies validates the simulation’s relevance and applicability to modern manufacturing environments. The project thus provides valuable insights into the potential of simulation based training and testing to drive future innovations in smart factories and industrial robotics.

Date: 2025
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