Balaram Dey

Papers

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About

Balaram Dey is a researcher specializing in intelligent decision-making systems, robotics, and manufacturing automation, with a particular focus on applying fuzzy logic and multi-criteria decision-making (MCDM) methodologies to complex industrial selection problems. His work addresses one of the most pressing challenges in modern manufacturing: systematically evaluating and selecting robotic systems for specialized applications where both quantifiable and intangible factors must be considered simultaneously. Dey's most influential contribution, "Selection of robot for automated foundry operations using fuzzy multi-criteria decision making approaches" (2014), has garnered 33 citations and demonstrates his expertise in integrating Fuzzy Analytical Hierarchy Process (FAHP) with complementary FMCDM techniques to deliver robust, real-world decision frameworks. His subsequent work on TOPSIS-based fuzzy MCDM approaches further refined methods for handling the inherent uncertainty in robotic system selection, while his earlier multiplicative model (2012) helped lay the conceptual groundwork in this domain. With a cumulative citation count reflecting steady recognition across the research community, Dey's contributions provide valuable, practical tools for engineers and decision-makers navigating the increasingly complex landscape of industrial automation. His research remains particularly relevant for students exploring the intersection of fuzzy mathematics, operational research, and smart manufacturing systems.