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<p>Over the recent years, the manufacturing sector has been rapidly changing the operational mechanism using advanced technologies such as Artificial Intelligence, Computer Vision, etc. The availability of various categories of sensors like IoT, IMU, obstacle detecting sensors, actuators embedded in the system helps to visually monitor the manufacturing process. However, there are many challenges that are yet to be addressed in Cyber-Physical Systems (CPS) and industry 4.0. This includes reliability, precision, adaptability and multi-sensor information fusion and analysis. Hence, this work proposes an advanced and integrated framework Digital Twin Manipulator Arm (DTMA) that establishes the primary base for industrial level analysis of Digital Twins, including the required concepts of anomaly detection. The main objective of the proposed DTMA framework is three-fold. The first objective is to design a digital twin of robotic arm. The second is to design the visual inspection module for object inspection in manufacturing process. The third objective is to integrate both the modules with automated correction using robotic arm in to the entire process. The application of DTMA framework is gauged from two different use-cases discussing the heuristic based block level functioning of the proposed framework. The proposed framework will enable the development of mechanisms for key advantages such as predictive maintenance, reduced operation cost, visual inspection with higher processing rates and improved productivity.</p>

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DTMA: visual object inspection and mechanism for digital twin with robotic arm

  • 期刊论文

  • 发表日期：

    2025年7月8日

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  • Hrishikesh Venkataraman,
  • Jaswanth Nidamanuri,
  • Aditya Dittakavi,
  • Y Raja Vara Prasad,
  • Ramona Trestian,
  • Huan Nguyen

摘要

Over the recent years, the manufacturing sector has been rapidly changing the operational mechanism using advanced technologies such as Artificial Intelligence, Computer Vision, etc. The availability of various categories of sensors like IoT, IMU, obstacle detecting sensors, actuators embedded in the system helps to visually monitor the manufacturing process. However, there are many challenges that are yet to be addressed in Cyber-Physical Systems (CPS) and industry 4.0. This includes reliability, precision, adaptability and multi-sensor information fusion and analysis. Hence, this work proposes an advanced and integrated framework Digital Twin Manipulator Arm (DTMA) that establishes the primary base for industrial level analysis of Digital Twins, including the required concepts of anomaly detection. The main objective of the proposed DTMA framework is three-fold. The first objective is to design a digital twin of robotic arm. The second is to design the visual inspection module for object inspection in manufacturing process. The third objective is to integrate both the modules with automated correction using robotic arm in to the entire process. The application of DTMA framework is gauged from two different use-cases discussing the heuristic based block level functioning of the proposed framework. The proposed framework will enable the development of mechanisms for key advantages such as predictive maintenance, reduced operation cost, visual inspection with higher processing rates and improved productivity.