Melkote Advanced Manufacturing Research Group


Education

  • Ph.D., Michigan Technological University, 1993
  • M.S., Washington State University, 1989
  • B.Tech. (Hons.) IIT Kharagpur, India, 1987

Teaching Interests

Professor Melkote's teaching interests encompass manufacturing processes and mechanical engineering principles at both undergraduate and graduate levels. He focuses on advancing student understanding of the underlying science and mechanics of conventional and modern manufacturing processes, micro- and nano-manufacturing, and automated manufacturing process planning. His instruction aims to prepare students for research and industry challenges related to precision manufacturing technologies.

Research Interests

Professor Melkote's research centers on the mechanics and dynamics of manufacturing processes, including precision machining and micro-/nano-scale fabrication techniques, and hybrid manufacturing. His work in these areas investigates process modeling, surface integrity, and the interaction of tools and materials to enhance manufacturing accuracy and efficiency. Other areas of research include industrial robotics for manufacturing and bridging the automation gap between design and manufacturing though AI/ML methods. The research actively involves graduate and undergraduate students and addresses fundamental challenges in manufacturing science and engineering.

Recent Publications

  • S Park, SN Melkote, Deep unsupervised learning-based supplier selection and ranking for assembly manufacturing, Journal of Manufacturing Systems 84, 173-188, 2026
  • J Maqueda, DW Rosen, SN Melkote, DeepMS: A data-driven approach to machining process sequencing using transformers, Journal of Manufacturing Systems 82, 947-963, 2025
  • A Kota, NM Shanghavi, PM Singh, JH Jeon, SN Melkote, Enhancing the properties of a low carbon steel and SS316L bimetallic interface via mesoscale groove engineering in hybrid wire-arc directed energy deposition, Journal of Manufacturing Processes 153, 602-618, 2025
  • GY Kim, SN Melkote, JS Colton, Ensemble cure kinetics network (ECK-Net): A method to derive cure kinetics of thermosetting resin, Composites Part A: Applied Science and Manufacturing, 109453, 2025
  • Ng K, Berenji KR, Brown A, Melkote SN. Deflection-limited trajectory planning in robotic milling, Journal of Manufacturing Processes, 120:1180-91, 2024.