International Conference on Mechanical Engineering Processes and Blockchain (ICMEPB - 27)

This track explores the integration of blockchain technology within mechanical engineering practices. It aims to highlight innovative applications that enhance transparency and traceability in manufacturing processes.

This session focuses on the development and application of predictive modeling techniques to optimize manufacturing processes. Participants will discuss methodologies that leverage data analytics for improved decision-making.

This track delves into the use of supervised and unsupervised learning algorithms for process optimization in mechanical engineering. It emphasizes the role of machine learning in enhancing efficiency and reducing waste.

This session examines the application of deep learning techniques for anomaly detection in manufacturing systems. Researchers will present findings on how these methods can identify deviations and improve quality assurance.

This track focuses on feature extraction techniques and data analytics methodologies in the context of Industrial IoT. It aims to showcase how these approaches can enhance system monitoring and resource allocation.

This session explores the intersection of predictive maintenance and blockchain technology in mechanical engineering. Discussions will center on how blockchain can facilitate real-time data sharing and enhance maintenance strategies.