Email: chalam@iitm.ac.in

Tel (O): +91 44 2257 4722

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Dr. N. Arunachalam
Associate Professor, IIT Madras

Publications

    DIAGNOSTICS, PROGNOSTICS AND HEALTH MANAGEMENT

  1. Shanbhag, V.V., Rolfe, F.B., N.Arunachalam, and Pereira, P.M., Investigation of stamping tool wear initiation at microscopic level using acoustic emission sensors. 2019, December, AEPA conference. Key Engineering Materials. (In-production, Paper ID: AEPA 142).

  2. K.Ramasubramanian, N.Arunachalam, M.S. Ramachandra Rao, A Study on CVD Diamond Coated Cutting Tools Wear Performance using Vibration and Acoustic Emission Signals, Procedia CIRP, Volume 72, 2018, Pages 1415-1420-(IF- 0.982).

  3. Shanbhag, V.V., Rolfe, B.F., N.Arunachalam and Pereira, M.P., 2018, September. Understanding the source of acoustic emission signals during the wear of stamping tools. In IOP Conference Series: Materials Science and Engineering (Vol. 418, No. 1, p. 012098). IOP Publishing.

  4. Shanbhag, V.V., Pereira, P.M., Rolfe, F.B. and Arunachalam, N., 2017, September. Time series analysis of tool wear in sheet metal stamping using acoustic emission. In Journal of Physics: Conference Series (Vol. 896, No. 1, p. 012030). IOP Publishing.

  5. Vignesh. V. Shanbhag, Michael. P. Pereira, N.Arunachalam, Bernard F. Rolfe, Nov 2017. Towards active monitoring of sheet metal stamping. Institute for Frontier Materials 2017 Annual conference.

  6. N.Arunachalam, L.Vijayaraghavan, Evaluation of the Working Surface of the Grinding Wheel Using Speckle Image Analysis, ASME 2015 International Manufacturing Science and Engineering ConferenceVolume 1: Processing Charlotte, North Carolina, USA, June 8–12, 2015.

  7. N.Arunachalam, Vijayaraghavan L. Assessment of grinding wheel conditioning process using machine vision. IEEE conference on Prognostics and Health Management (PHM) , 2014;221(3):419-430.

  8. K. T. Kumar, N.Arunachalam, L. Vijayaraghavan, Prognostics model for tool life prediction in milling using texture features of surface image data. IEEE Conference on Prognostics and Health Management (PHM) IEEE, (2014) 1-5.

  9. W.Adithiyakumar, N.Arunachalam, A.Venkatasami, Jayalakshmi chandle, Sensitivity check of Internal UHF sensor for PD detection in Power transformer , Trafotech-2010.

  10. N.Arunachalam, B.Rajapagalavan, A.Venkatasami, R.Udhayakumar, Localization of partial discharge in model transformer tank using Acoustic Emission sensor, CMD-2010,CHINA.

  11. N.Arunachalam, A. Venkatasami, Anilkumar B. Bhatia, A Review on the Monitoring Methods for Condition Based Maintenance of on Load Tap Changer, CMD 2010, CHINA.

  12. N.Arunachalam, B.Ramamoorthy, Fourier transform based texture measures for grinding wheel wear assessment using machine vision, Proceedings of All India Machine Tool Design and Research Conference, AIMTDR-2006,IITRoorkee,Dec.22-25,pp.659-664.

    13. INDUSTRY 4.0 IMPLEMENTATION, DIGITAL TWINS AND CYBER PHYSICAL SYSTEMS

  13. Kalpana Kannan, N.Arunachalam, Aakash Chawla, Sundararajan Natarajan, Multi-Sensor Data Analytics for Grinding Wheel Redress Life Estimation- An Approach towards Industry 4.0, Procedia Manufacturing, Volume 26, 2018, Pages 1230-1241. (46th SME North American Manufacturing Research Conference, NAMRC 46, Texas, USA). (IF- 0.798).

  14. KalpanaKannan, N.Arunachalam, Grinding wheel redress life estimation using force and surface texture analysis, Procedia CIRP, Volume 72, 2018, Pages 1439-1444-(IF- 0.982).

  15. Kunal Tiwari, Ameer Shaik, N.Arunachalam, Tool wear prediction in end milling of Ti-6Al-4V through Kalman filter based fusion of texture features and cutting forces, Procedia Manufacturing, Volume 26, 2018, Pages 1459-1470. (46th SME North American Manufacturing Research Conference, NAMRC 46, Texas, USA)-(IF- 0.798).

  16. R.Dwaraka and N.Arunachalam, Investigation on non-invasive process monitoring of Die Sinking EDM using Acoustic Emission signals, Procedia Manufacturing, Volume 26, 2018, Pages 1471-1482- (IF- 0.798).

  17. T.K.Balasaravanan, R.Bhattacharyya, J.Siegel, N.Arunachalam and Sanjay E. Sarma, Development of an Internet of Things enabled Manufacturing system for tool wear characterization, IEEE ROMA, 2017.

    18. MACHINE VISION / METROLOGY IN PRODUCTION LINES

  18. Sudhanva Bhat, Sreedath Panat, and N.Arunachalam Classification of rice grain varieties arranged in scattered and heap fashion using image processing", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034126 (17 March 2017).

  19. Jibin G John, N.Arunachalam, Improved surface roughness evaluation of ground components using illumination compensated image- A machine vision approach” , IMECE 2016, ASME, held on November 11-17 2016 at Phoenix Convention center, Arizona, USA.

  20. Jibin G John, N.Arunachalam, Surface roughness inspection of ground components using statistical texture parameters of images – A machine vision approach” . AIMTDR 2016, held on Dec 16-18 2016 at College of engineering Pune, India.

  21. N.Arunachalam, B.Ramamoorthy, Vision based Surface Roughness Evaluation of Ground Components using Wavelet Transform and Neural Network, XVIII Imeko World Congress Metrology for a Sustainable Development, September, 17 – 22, 2006, Rio de Janeiro, Brazil.

  22. N.Arunachalam, B.Ramamoorthy, Characterisation of ground components quality using Machine vision for Grinding wheel condition monitoring, Proceedings of International Conference on Global Manufacturing and Innovation, organized by CIT and University of Massachusetts-Dartmouth,USA,pp.19,2006.

    23. HIGH PERFORMANCE MACHINING

  23. K.Ramasubramanian, N.Arunachalam, M.S. Ramachandra Rao, A Study on CVD Diamond Coated Cutting Tools Wear Performance using Vibration and Acoustic Emission Signals, Procedia CIRP, Volume 72, 2018, Pages 1415-1420-(IF- 0.982).

  24. J.Rajaguru, N.Arunachalam, Coated tool Performance in Dry Turning of Super Duplex Stainless Steel, Procedia Manufacturing, Volume 10, 2017, Pages 601-611.

  25. E.L.Chidambaram, N.Arunachalam, L.Vijayaraghavan, Analytical Model to Predict Sauter Mean Diameter in Air Assisted Atomizers for MQL in Machining Application, Procedia CIRP, Volume 37, 2015, Pages 117-12.

  26. K.Ramasubramanian, N.Arunachalam, M.S.R.Rao, Nanocrystalline Diamond Coated Tool Performance In Machining Of Lm6.Aluminium Alloy/Alumina Mmc, Proceedings of the 10th ASME 2015 Manufacturing Science and Engineering Conference MSEC2015, USA.

  27. Monith Biswojyothi, A.S.S.Balan, N.Arunachalam, L.Vijayaraghavan, A Study On The Minimum Quantity Lubrication In Grinding Of Titanium Alloy (Ti-6Al-4V), International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014) December 12 –14, , 2014, IIT, Guwahati, Assam, India.

    28. HIGH PERFORMANCE GRINDING

  28. D. Selvakumaran, N.Arunachalam, L. Vijayaraghavan, A.S.S. Balan. Performance Comparison of Sol-gel with White Alumina Abrasives for Grinding of Super Duplex Stainless Steel (SDSS) . Procedia Manufacturing, 26 (2018) 1448–1458.

  29. D. Selvakumaran, L. Vijayaraghavan, N.Arunachalam, A. Xavier Kennedy. Grinding Efficiency of Sol-gel Alumina based Grinding Wheels Sintered at Two Different Temperatures. Proceedings of the 19th International Symposium on Advances in Abrasive Technology 2-5 October 2016, Stockholm, Sweden, pp. 141-147.