Smart Maintenance Solutions: AR- and VR-Enhanced Digital Twin Powered by FIWARE

Area of Science:

• Industrial Engineering
• Computer Science
• Digital Transformation

Background:

• Digitalization is transforming industries through technologies like IoT, data analytics, AR, and VR.
• Effective industrial equipment monitoring and maintenance are crucial for operational efficiency.
• Predictive maintenance strategies aim to minimize machine downtime and prevent failures.

Purpose of the Study:

• To develop an integrated system combining IoT, data analysis, AR, and VR for industrial equipment monitoring and maintenance.
• To investigate how this integration can optimize industrial maintenance processes.
• To create a foundation for advanced predictive maintenance solutions.

Main Methods:

• Developing a system that integrates Internet of Things (IoT) sensors for data collection.
• Implementing advanced data analysis techniques to identify equipment anomalies.
• Utilizing Augmented Reality (AR) and Virtual Reality (VR) for visualising data and guiding maintenance tasks.

Main Results:

• A prototype system was successfully developed and tested.
• The integrated system demonstrated potential for effective predictive maintenance.
• The system can alert operators to anomalies and provide visual maintenance instructions.

Conclusions:

• The integration of IoT, data analysis, AR, and VR offers a promising approach to optimizing industrial maintenance.
• The developed prototype shows potential for real-world application in industrial settings.
• This integrated system can significantly contribute to reducing machine downtime and operational failures.