Andreas Ch. Yiannopoulos
Papers
1
Total Citations
5
H-Index
1
About
Dr. Andreas Ch. Yiannopoulos is a distinguished researcher at the intersection of industrial engineering, fuzzy logic, and manufacturing optimization. His work is primarily concerned with addressing the inherent uncertainties—or "fuzziness"—that plague modern production systems, and his most-cited study, "Genetic-Based Optimization of the Manufacturing Process of a Robotic Arm under Fuzziness" (2018), exemplifies this focus. In this pivotal contribution, Dr. Yiannopoulos tackled the complex Simple Assembly Line Balancing Problem of type 2 (SALBP-2) by integrating genetic algorithms with fuzzy set theory. This innovative approach allows for more realistic and robust optimization of robotic arm manufacturing, directly addressing a high-practical-need area for industrial audiences. While his citation count of 5 reflects a specialized, emerging field, the scientific contribution is significant: he provides a methodological framework that moves beyond deterministic models to embrace the ambiguity of real-world factory floors. His work is essential reading for engineers and researchers seeking to enhance efficiency and adaptability in automated production environments.
Research Focus
Key Achievements
Top Papers
- 1