Abstract This study proposes a PLC-controlled omni wheel conveyor sorting system designed to address limitations in traditional sorting mechanisms by integrating barcode-based classification with high-speed and adaptable sorting capabilities. The system utilizes a Siemens S7-1200 PLC, omni wheels, a barcode scanner, and a conveyor motor to achieve precise, flexible, and efficient material handling. Mathematical analysis validated the system’s structural integrity, with deflections under 0. 009 \, mm, and operational efficiency, including a roller speed of 35. 46 \, RPM to support a throughput of 2000 objects per hour at a conveyor speed of 0. 167 \, m/s. Simulations conducted in Factory IO achieved a sorting accuracy of 98\%, demonstrating the seamless synchronization of barcode scanning and sorting operations through deterministic ladder logic. The omni wheels provided multidirectional flexibility, reducing energy losses and enabling rapid redirection of objects. Compared to reinforcement learning-based approaches, the proposed system offers simplicity, cost-effectiveness, and ease of implementation without compromising accuracy or scalability. However, the simulations assumed ideal conditions, and limitations such as environmental factors, dynamic loading, and real-world scalability remain unaddressed. Future research could explore integrating IoT-enabled monitoring, hybrid control strategies, and dynamic adaptability to enhance performance in complex industrial environments. The results highlight the potential of this system to revolutionize material handling across manufacturing, logistics, and e-commerce sectors.
Bhat et al. (Wed,) studied this question.
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