Journal Publications

  1. A.S. Kumar, A. Agarwal, V.G. Jansari, K.A. Desai, C. Chattopadhyay, L. Mears, 'Robust on-machine tool wear monitoring through integration of machine vision system and pre-trained convolutional neural network', Journal of Manufacturing Systems, 78, 283-293, 2025. (Link)

  2. A. Agarwal, A. S. Kumar, V. G. Jansari, K. A. Desai, L. Mears, “Improving vision-based tool wear state identification under varying lighting conditions using human guided-eXplainable AI approach”, Manufacturing Letters, 44, 709-717, 2025. (Link)

  3. S. BJ, S. A. Singh, A. Agarwal, K. A. Desai, L. Mears, “Identifying tool wear stages in turning process through machined surface image analysis using convolutional neural network”, Manufacturing Letters, 44, 678-686, 2025. (Link)

  4. A.S. Kumar, A. Agarwal, V.G. Jansari, K.A. Desai, C. Chattopadhyay, L. Mears, 'HG-XAI: Human-guided tool wear identification approach through augmentation of explainable artificial intelligence with machine vision', Journal of Intelligent Manufacturing, 2024. (Link)

  5. A. Agarwal, K. Bhuta, T. Grimm, L. Mears, 'Investigating the effect of nanobubble-based cutting fluid on tool wear and cutting forces in milling of Inconel 718', Manufacturing Letters, 41, 1676-1682, 2024. (Link)

  6. N.A. Kharat, A. Agarwal, T. Grimm, L. Mears, 'Investigation of stochastic toolpath strategy in 3-axis ball-end milling of 2D and free-form surfaces', Proceeding of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 238(11), 1709-1723, 2024.(Link)

  7. N. Potthoff, A. Agarwal, F. Woste, P. Wiederkehr, L. Mears, 'Evaluation of contrived wear methodology in end milling of Inconel 718', ASME Journal of Manufacturing Science and Engineering, 145(10), 101002, 2023. (Link)

  8. A. Agarwal, P.C. Sorathiya, S. Vaishnav, K.A. Desai, L. Mears, 'Design-as-a-service framework for enabling innovations in small and medium-size enterprises', ASME Journal of Mechanical Design, 145(4), 044501, 2023. (Link)

  9. A. M. Shah, A. Agarwal, L. Mears, 'Tool wear area estimation through in-process edge force coefficient in trochoidal milling of Inconel 718', Manufacturing Letters, 35, 391-398, 2023. (Link)

  10. A. Agarwal, N. Potthoff, A.M. Shah, L. Mears, P. Wiederkehr, 'Analyzing the evolution of tool wear area in trochoidal milling of Inconel 718 using image processing methodology', Manufacturing Letters, 33, 373-379, 2022. (Link)

  11. N. Potthoff, A. Agarwal, F. Woste, L. Jan, L. Mears, P. Wiederkehr, 'Experimental and simulative analysis of an adapted methodology for decoupling tool wear in end milling', Manufacturing Letters, 33, 380-387, 2022. (Link)

  12. A. Agarwal, K.A. Desai, 'Effect of component configuration on geometric tolerances during end milling of thin-walled parts', The International Journal of Advanced Manufacturing Technology, 118, 3617-3630, 2022. (Link)

  13. A. Agarwal, K.A. Desai, 'Rigidity regulation approach for geometric tolerance optimization in end milling of thin-walled components', ASME Journal of Manufacturing Science and Engineering, 143(11), 111006, 2021. (Link)

  14. A. Agarwal, K.A. Desai, 'Modeling of flatness error in end milling of thin-walled components', Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 235(3), 543-554, 2021. (Link)

  15. A. Agarwal, K.A. Desai, 'Predictive framework for cutting force induced cylindricity error estimation in end milling of thin-walled components', Precision Engineering, 66, 209-219, 2020. (Link)

  16. A. Agarwal, K.A. Desai, 'Importance of bottom and flank edges in cutting force models for end milling operation', The International Journal of Advanced Manufacturing Technology, 107(3), 1437-1449, 2020. (Link)

  17. S. Vaishnav, A. Agarwal, K.A. Desai, 'Machine learning based instantaneous cutting force model for end milling operation', Journal of Intelligent Manufacturing, 31(6), 1353-1366, 2020. (Link)

  18. N. Arora, A. Agarwal, K.A. Desai, 'Modeling of static surface error in end milling of thin-walled geometries', International Journal of Precision Technology, 8(2-4), 107-123, 2019. (Link)

Conference Publications

  1. V. Tummala, A. Agarwal, A. Gill, S.J. Lee, L. Mears, “Evaluating the impact of cyberattacks on AI-based machine vision systems: A case study of threaded fasteners” ASME International Mechanical Engineering Congress & Exposition (IMECE) 2025.

  2. V. Tummala, A. Agarwal, A. Gill, Kevin Bottomley, “AI and cybersecurity literacy course for mechanical engineers” ASME International Mechanical Engineering Congress & Exposition (IMECE) 2025.

  3. T. Grimm, A. Agarwal, L. Mears, “Brief Paper: Electric pulse assisted milling”, ASME Manufacturing Science and Engineering Conference, Greenville, USA, June 2025.

  4. A. Gill, A. Agarwal, V. Tummala, S.J. Lee, L. Mears, ‘Comparison of explainable AI for image classification to human perception: A case study of threaded fasteners’, ASME International Mechanical Engineering Congress & Exposition (IMECE), Portland, USA, November 2024, V002T03A094. (Best Paper Award) (Link)

  5. S. Vaishnav, A. Agarwal, P.C. Sorathiya, K.A. Desai, L. Mears, 'Research2market Connect: Cloud-based platform to connect academic research with SMEs for accelerated innovations', ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE), Washington, USA, August 2024, V02AT02A047. (Link)

  6. A.S. Kumar, A. Agarwal, V.G. Jansari, K.A. Desai, C. Chattopadhyay, L. Mears, 'Vision-based tool wear classification during end-milling of Inconel 718 using a pre-trained convolutional neural network', ASME International Mechanical Engineering Congress & Exposition (IMECE), New Orleans, Louisiana, USA, October-November 2023, V003T03A016. (Link)

  7. A. Agarwal, K.A. Desai, 'Amalgamation of physics-based cutting force model and machine learning approach for end milling operation', 53rd CIRP Conference on Manufacturing Systems (CMS), Chicago, USA, Procedia CIRP, 93, 1405-1410, July 2020. (Link)

  8. A. Agarwal, K.A. Desai, 'Tool and workpiece deflection induced flatness errors in milling of thin-walled components', 53rd CIRP Conference on Manufacturing Systems (CMS), Chicago, USA, Procedia CIRP, 93, 1411-1416, July 2020. (Link)

  9. A. Agarwal, K.A. Desai, 'Effect of workpiece curvature on axial surface error profile in flat end milling of thin-walled components', 48th SME North American Manufacturing Research Conference (NAMRC), Cincinnati, USA, Procedia Manufacturing, 48, 498-507, June 2020. (Link)

  10. N. Arora, A. Agarwal, K.A. Desai, 'Modeling of static surface error in end milling of thin-walled geometries', 10th International Conference on Precision, Meso, Micro and Nano Engineering 2017 (COPEN), Indian Institute of Technology Madras, India, December 2017. (Link)