Swagat Nayak

Papers

Total Citations

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About

Swagat Nayak is a researcher whose work sits at the intersection of industrial automation and intelligent decision-making. His primary research areas include robotics selection, fuzzy logic systems, and multi-criteria decision analysis. Nayak is best known for his pioneering application of fuzzy logic to the complex problem of industrial robot selection, a critical task in manufacturing where multiple conflicting criteria—such as cost, payload, and precision—must be balanced. His most cited paper, "Selection of Industrial Robot Using Fuzzy Logic Approach" (2019), has garnered 5 citations and demonstrates how fuzzy set theory can handle the inherent uncertainty and subjectivity in evaluating robotic systems. This work provides a systematic, transparent framework for engineers and managers, moving beyond traditional trial-and-error methods. While his citation count is modest, the paper’s relevance to Industry 4.0 and smart manufacturing positions it as a foundational reference for those seeking to integrate AI-driven tools into production line decisions. Nayak’s contributions are particularly valuable for students and practitioners exploring how soft computing techniques can solve real-world engineering problems, offering a clear, replicable methodology that bridges theory and application.