Nuntiya Kruethi
Papers
1
Total Citations
2
H-Index
1
About
Nuntiya Kruethi is a researcher whose work bridges industrial automation, engineering economics, and data-driven decision-making. Her most-cited paper, "A Simulation Model to Improve the Efficiency of Painting Robots and Applied an Engineering Economic for Project Selection" (2019), exemplifies her focus on optimizing manufacturing processes through simulation and economic analysis. This study integrates robotic efficiency improvements with cost-benefit evaluation, offering a practical framework for project selection in industrial settings. Though her citation count is modest, her research touches on critical intersections of data mining, artificial intelligence, and pattern classification, with applications ranging from investment analysis to social network behavior. Kruethi’s work is particularly notable for its interdisciplinary approach—combining engineering economics with machine learning techniques like support vector machines and neural networks. Her contributions are valuable for students and practitioners seeking to apply computational methods to real-world industrial and economic challenges, demonstrating how simulation and AI can enhance both operational efficiency and strategic decision-making.
Research Focus
Key Achievements
Top Papers
- 1