Digital twin-assisted intelligent fault diagnostics of industrial robots

Digital twin architecture of autonomous industrial robots with joint deviation compensation toward realization of a smart factory

A comprehensive cloud-enabled Digital Twin architecture for IRs that enables remote task allocation, autonomous ROS-based execution, near real-time monitoring, and synchronized operation with physical manufacturing assets through a unified Cloud–Edge framework is presented.

Edge-AI based Real-Time Bearing Fault Diagnosis for Industrial Actuators using Lightweight Machine Learning Framework

Digital twin–driven optimization of manufacturing operations using real-time sensor data

A digital twin-inspired optimization model, which combines real-time sensor measurements with smart decisions to improve operational efficiency, is introduced, which provides a high-scaled and realistic approach to intelligent, data-driven manufacturing systems that align with the Industry 4.0 paradigms.

PRECISION MANUFACTURING IN AEROSPACE ENGINEERING USING ADVANCED ROBOTIC SYSTEMS

Automated inspection and robotic process control of the manufacturing process are becoming more integral to the precision aerospace manufacturing process to ensure product quality and assembly consistency. In this study, a complementary framework based on two modules, a robotic fastener-process characterization module...

Control Technology for Soft Robots: From Traditional Methods to Intelligent Control Methods

This paper systematically sorts out the latest research progress of soft robot control technology, elaborates on the optimized application of traditional PID control and its improved algorithms, details the practical application effect of pneumatic drive technology in complex working conditions, and deeply explores the...

Data-driven fault detection and diagnosis in automated manufacturing systems

Data-driven methods, in contrast to traditional reactive ones, make use of continuous sensor data streams to anticipate anomalies before they can result in critical failures using advanced analytics, thereby improving responsiveness and efficiency in the system.