Seksan Chaijit
Papers
3
Total Citations
7
H-Index
2
About
Seksan Chaijit is a researcher specializing in industrial automation, manufacturing systems optimization, and the application of simulation tools for process improvement. His work focuses on bridging the gap between theoretical modeling and real-world industrial efficiency, particularly through the use of robot simulation and digital factory concepts. In his most cited paper, "Modeling, analysis and effective improvement of aluminum bowl embossing process through robot simulation tools" (2019, 3 citations), Chaijit developed an automated loading and unloading system to replace manual operations in a power press process, demonstrating significant gains in safety and productivity. He further advanced this methodology in "Improvement of an automated CAN packaging system based on modeling and analysis approach through robot simulation tools" (2020, 2 citations), where he optimized a palletizing cell for aerosol cans. His research also incorporates engineering economics, as seen in "A Simulation Model to Improve the Efficiency of Painting Robots and Applied an Engineering Economic for Project Selection" (2019, 2 citations), providing a framework for selecting cost-effective automation investments. While his citation counts reflect a focused, early-career impact, Chaijit’s contributions offer practical, data-driven solutions for modernizing manual manufacturing processes—a critical step toward Industry 4.0 adoption in small-to-medium enterprises.
Research Focus
Key Achievements
Top Papers
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