Object Sorting Conveyor using Delta PLC

Abstract

The automated object sorting and counting system integrates a Delta PLC, sensors, and actuators to streamline industrial sorting processes. By leveraging sensor-based decision-making, the system detects objects, categorizes them based on predefined criteria, and directs them to appropriate bins using stepper motor or pneumatic pushers. This automation significantly enhances efficiency in production lines by reducing human intervention, minimizing sorting errors, and optimizing workflow speed. Industries that require precise classification—such as manufacturing, packaging, and logistics—benefit from improved productivity and accuracy. The Delta PLC acts as the central controller, processing sensor inputs and executing sorting commands, making the entire system reliable, scalable, and adaptable to various industrial applications.

Introduction

The text presents a PLC-based automated object sorting conveyor system designed to improve efficiency, accuracy, and productivity in industrial environments such as manufacturing, packaging, and logistics. Manual sorting methods are slow, error-prone, and costly, making automation essential for large-scale operations. The proposed system uses a Delta PLC as the central controller to process real-time sensor data and execute precise sorting decisions with minimal human intervention.

The system architecture consists of a conveyor belt, multiple sensors (proximity, photoelectric, and inductive), actuators (DC motors, stepper motors, relays), and a power supply. Objects are transported along the conveyor, detected by sensors, classified based on criteria such as material type, size, or count, and then diverted into designated bins using PLC-controlled actuators. Real-time counting and monitoring functions support quality control and inventory management.

Sorting logic is implemented using ladder logic programming in Delta’s WPL Soft software. The PLC continuously scans sensor inputs, determines object characteristics, activates actuators with precise timing, and updates counters. The system operates in a fast PLC scan cycle, ensuring real-time responsiveness and synchronized motion control.

Experimental results demonstrate high sorting accuracy (over 98%), improved operational speed, and consistent performance during continuous operation. Compared to traditional manual systems and earlier pneumatic-only designs, the use of stepper motors enables smoother and more precise object handling. Delta PLCs are highlighted for their compact design, reliability, integrated I/O, and cost-effectiveness.

While effective, the system has limitations, as it relies on predefined sorting criteria and requires reprogramming to accommodate new object types. Future improvements may include the integration of artificial intelligence and machine learning to enable adaptive and intelligent sorting.

Conclusion

The PLC-based object sorting conveyor system successfully addresses the challenges of manual sorting in industrial environments by automating the sorting and counting process using Delta PLC, sensors, and actuators. The sensor-based decision-making architecture ensures precise object classification, significantly reducing the errors inherent in manual sorting operations. The integration of stepper motors and pneumatic actuators allows smooth and controlled movement of objects into their respective bins, substantially enhancing productivity. This automated system eliminates human intervention while ensuring speed, accuracy, and scalability, making it highly suitable for manufacturing, packaging, and logistics industries. The implementation of real-time counting mechanisms provides reliable data tracking essential for quality control and inventory management. The system\'s modular design allows for easy adaptation to various industrial applications and sorting criteria. The successful implementation demonstrates that PLC-based automation is a cost-effective and reliable solution for industrial sorting challenges. Future enhancements incorporating artificial intelligence and advanced vision systems will further improve the system\'s adaptability and intelligence, enabling even more sophisticated sorting capabilities for next-generation industrial automation.

References

[1] Kumar, A., & Singh, R. (2022). Design and implementation of PLC-based conveyor control systems. International Journal of Industrial Automation, 18(4), 234–248. [2] Chen, L., Wang, Y., & Zhang, H. (2023). Sensor integration in automated sorting systems: A comprehensive review. Journal of Manufacturing Systems, 45(2), 156–172. [3] Delta Electronics Inc. (2023). DVP Series PLC Programming Manual (Version 3.0). Delta Electronics. [4] Patel, M., & Sharma, K. (2022). Pneumatic actuator control using PLC for industrial applications. In Proceedings of the IEEE International Conference on Automation Science and Engineering (pp. 789–796). IEEE. [5] Johnson, R. T., Brown, A. M., & Davis, P. L. (2023). Real-time object detection and classification using photoelectric sensors. Sensors and Actuators A: Physical, 312, 112089. [6] Lee, S. H., & Kim, J. W. (2021). Ladder logic optimization techniques for industrial PLC applications. Control Engineering Practice, 28(3), 445–459. [7] International Electrotechnical Commission. (2020). IEC 61131-3: Programmable controllers - Part 3: Programming languages (3rd ed.). IEC Standards. [8] Garcia, M., Rodriguez, F., & Martinez, L. (2023). Comparative analysis of PLC brands for industrial automation. Industrial Electronics Magazine, 17(1), 45–58. [9] Automated Systems Research Group. (2022). Guidelines for sensor selection in conveyor-based sorting systems. Technical Report TR-2022-15, Industrial Automation Research Institute.

Copyright

Copyright © 2025 Prof. Ramya R, Likith P, Mani Deepak S, Punith Kumar G, Sandeep B M. 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.