Paper Contents
Abstract
Collaborative robots (cobots) are transforming defect inspection processes in micro-manufacturing under the Industry 4.0 paradigm. This study evaluates the role of cobots in improving inspection accuracy, reducing inspection times, and enhancing operational consistency through simulation modeling and real-world case studies. Results reveal that cobots equipped with advanced sensors and machine learning algorithms achieve defect detection accuracies above 95% and reduce inspection times by up to 60%. Additionally, cobots improve operator ergonomics by minimizing cognitive and physical workloads while ensuring economic feasibility with a return on investment (ROI) within 12 years. The study highlights integration challenges, including interoperability and training, and proposes a framework for effective human-cobot collaboration leveraging IoT, AI, and predictive analytics. These findings establish cobots as key enablers of zero-defect manufacturing, enhancing precision, efficiency, and safety in quality control processes. Future research should focus on addressing integration barriers and advancing task allocation strategies for optimal deployment.
Copyright
Copyright © 2024 B Sudha. This is an open access article distributed under the Creative Commons Attribution License.
