Design and Implementation of a Low-Cost IoT-Based Robotic Arm for Product Feeding and Sorting in Manufacturing Lines


Creative Commons License

Yılmaz S., Akay C., Kaysi F.

Electronics, cilt.14, sa.4801, ss.1-26, 2025 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 14 Sayı: 4801
  • Basım Tarihi: 2025
  • Doi Numarası: 10.3390/electronics14244801
  • Dergi Adı: Electronics
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED)
  • Sayfa Sayıları: ss.1-26
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet

Özet

The convergence of Internet of Things (IoT), embedded microcontrollers, and robotics has significantly transformed industrial and service applications under the Industry 5.0 paradigm. IoT-enabled automation not only reduces human intervention but also improves system efficiency, safety, and adaptability across multiple domains. The growing integration of automation technologies in manufacturing lines has significantly reduced human intervention while improving productivity and operational safety. Robotic arms play a crucial role in modern industrial environments, particularly for repetitive, hazardous, or precision-demanding tasks. This study presents a cost-effective robotic arm system for product selection, sorting and processing in automated production lines. The system operates in both automatic and manual modes and utilizes an ESP32-based controller, radio frequency identification (RFID) modules, and low-cost sensors to identify and transport products on a conveyor. A mobile, IoT-enabled interface provides remote real-time monitoring and control, while integrated safety mechanisms, current-voltage protections, and emergency stop circuitry enhance operational reliability. Using cost-effective components to reduce total cost, the system has been successfully validated through experiments to reduce labor dependency and operational errors, proving its scalability and economic viability for industrial automation. Compared to similar systems, this study presents an Industry 5.0 approach for low-cost IoT-based automated production lines.