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About

Partha Protim Das is a researcher whose work sits at the intersection of advanced manufacturing and intelligent decision-making. His primary research areas include the parametric optimization of machining processes and the application of multi-criteria decision-making (MCDM) models for industrial automation. Das has made significant contributions by developing and applying novel integrated frameworks—such as the grey-fuzzy logic approach for optimizing CNC turning on glass-fibre-reinforced plastic (GFRP) pipes, and the PIPRECIA-TOPSIS model for selecting industrial arc welding robots. His recent work on cobot selection using the LOPCOW-OPTBIAS approach addresses the growing need for systematic evaluation of collaborative robots in assembly operations. With over 17 citations across his most-cited papers, Das’s research is gaining traction for its practical relevance in manufacturing. Notably, his 2018 study on GFRP pipe optimization remains a foundational reference, while his 2023–2024 publications demonstrate a clear trajectory toward modern automation challenges. Through his methodological innovations, Das is helping engineers and decision-makers navigate complex trade-offs in material processing and robotic system selection.