Chandra Nath
Engineering · Purdue University West Lafayette
Publications
57
Citations
2,182
Est. group size
~4
Recurring co-author estimate
Active years
49
Publishing since 1978
Chandra Nath's research focuses on manufacturing engineering, particularly machining processes such as drilling, turning, and milling of metals like stainless steel, titanium, and Inconel. Work includes monitoring tool wear and condition using sensor data and neural networks, improving cutting fluid delivery methods, and developing computational path-planning techniques for subtractive 3D printing (machining material away to create shapes). The publication record also includes at least one item outside this core area related to military leadership challenges in AI.
Publication output was intermittent in the middle of the decade but has increased in recent years, with the highest yearly count in 2024.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Challenge Taxonomy Military Leadership Challenges in the AI World Military Leadership Challenges in the Artificial Intelligence World A Challenge Taxonomy A. Strategic and Geopolitical Leadership Challenges
2026
- Advanced MQL methods for machining processes
Elsevier eBooks · 2024
- Integrated Tool Condition Monitoring Systems and Their Applications: A Comprehensive Review
Procedia Manufacturing · 2020
- Effect of In-Built Anisotropic and Heterogeneous Material Properties on Machinability in Drilling of AISI 304 Stainless Steel
Journal of Manufacturing Processes · 2020
- Study of spindle power data with neural network for predicting real-time tool wear/breakage during inconel drilling
Journal of Manufacturing Systems · 2017
- Finish turning of Ti-6Al-4V with the atomization-based cutting fluid (ACF) spray system
Journal of Manufacturing Processes · 2017
- A Graphics Processor Unit-Accelerated Freeform Surface Offsetting Method for High-Resolution Subtractive Three-Dimensional Printing (Machining)
Journal of Manufacturing Science and Engineering · 2017
- Tool life predictions in milling using spindle power with the neural network technique
Journal of Manufacturing Processes · 2016
- Enhancing Spindle Power Data Application with Neural Network for Real-time Tool Wear/Breakage Prediction During Inconel Drilling
Procedia Manufacturing · 2016
- Obstruction-type Chip Breakers for Controllable Chips and Improved Cooling/Lubrication During Drilling – A Feasibility Study
Procedia Manufacturing · 2016
- Investigating surface metrology of curved wall surface during milling of SS304 with different tool path strategies
The International Journal of Advanced Manufacturing Technology · 2016
- Step Ring-Based Three-Dimensional Path Planning Via Graphics Processing Unit Simulation for Subtractive Three-Dimensional Printing
Journal of Manufacturing Science and Engineering · 2016
- A Graphical Approach for Freeform Surface Offsetting With GPU Acceleration for Subtractive 3D Printing
Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing · 2016
- Step Ring Based 3D Path Planning via GPU Simulation for Subtractive 3D Printing
Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing · 2016
- Journal of Manufacturing Processes×4
- Procedia Manufacturing×3
- Journal of Manufacturing Science and Engineering×3
- The International Journal of Advanced Manufacturing Technology×2
- Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing×2
- Martin Byung‐Guk Jun
Engineering · Purdue University West Lafayette
- Xiangyu Zhang
Engineering · Purdue University West Lafayette
- Yung C. Shin
Engineering · Purdue University West Lafayette
- Juan Camilo Osorio
Engineering · Purdue University West Lafayette
- E. Lenz
Engineering · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile