• Experimental and computational work on condition and process monitoring. On-line metal cutting tool wear analysis/monitoring using image processing technique by machine vision, applications of ANNs, fuzzy logic (classification, prediction and detection) in condition monitoring, predictive maintenance and fault diagnosis.

• Principles & process understanding of cutting technologies, high performance machining ,high speed machining (micro/macro),machine tool (geometry, materials &coatings),cutting mechanics and machining process dynamics and modeling.

• Development of optimization methodologies for, models and techniques for manufacturing process, parametric design, modeling, product assessment and optimization.

1. Y D Chethan, H V Ravindra ,Y T Krishne gowda and Bharath Kumar S “Machine vision for tool status monitoring in turning Inconel 718 using blob analysis” Materials Today 2 ( 2015 ) 1841 – 1848

2. Y D Chethan, H V Ravindra ,Y T Krishne gowda and Prashanth N “Machine Vision for Correlating Tool Status and Machined Surface in Turning Nickel-base super alloy” IEEE ISBN- 978-1-4673-9563-2/15

3. Y D Chethan, H V Ravindra and Asrith “Predictive modeling of drill wear: Comparative analysis of Ann and fuzzy logic Techniques” International Journal Of Design And Manufacturing Technology (IJDMT) ISSN 0976 – 6995(Print),ISSN 0976 – 7002(Online) ,Volume 5, Issue 1, January - April (2014), pp. 23-35

4. . Y D Chethan , H V Ravindra and Y T Krishne gowda ”Parametric Optimization in Drilling EN-8 tool steel and Drill wear monitoring using Machine Vision applied with Taguchi Method” Procedia Materials Science (2014), Volume 5, 2014, Pages 1442–1449

5. Y D Chethan , H V Ravindra and Y T Krishne gowda “Drill Wear Estimation Based On Machine Vision Signals with ANOVA“ Issue3,Vol1 International Journal of Emerging Trends in Engineering and Development (IJETED) ISSN NO.:2249-6149.

6. Y D Chethan , H V Ravindra and Y T Krishne gowda “Machined Surface Monitoring in Turning Using Histogram Analysis by Machine Vision” Materials Today, Volume 5, Issue 2, Part 2, 2018, Pages 7775-7781.

7. Y D Chethan , H V Ravindra and Y T Krishne gowda “Optimization of machining parameters in turning nimonic75 using machine vision and acoustic emission signals by taghuchi technique” Measurement Journal - Elsevier vol.144,.pp144-154, 2019.

8. Y D Chethan, H V Ravindra, Y T Krishne Gowda, “Performance Monitoring in Turing Nimonic75 Using Coated Carbide Inserts by Machine Vision System”, International Journal of Engineering Sciences & Research Technology, (2017), ISSN: 2277-9655.

9. Y D Chethan, H V Ravindra, Y T Krishne Gowda, “Estimation of Machine Vision and Acoustic Emission Features in Turning Nimonic75 by ANN”, International Journal of Engineering Research in Mechanical and Civil Engineering (IJERMCE), 2, 4, (2017), ISSN (Online) 2456-1290.

10. Y D Chethan, G Ugrasen, H V Ravindra, B M Umeshgowda and G V Naveen Prakash “Estimation of Machining Performances using GMDH and ANN in Wire EDM of Cu-1Cr-0.1Zr Alloy” IOP Conference Series: Materials Science and Engineering, Vol. 376.

Conference:

11. Y D Chethan , H V Ravindra and Y T Krishne gowda “Monitoring Of Drill Wear State Using Blob Analysis Technique By Machine Vision” At International Conference On precision, Meso, Micro And Nano Engineering COPEN-8: 2013 Organized By National Institute Of Technology Calicut, Kerala India

12. Y D Chethan , H V Ravindra “Tool wear monitoring in drilling using machine vision system” at International conference on ‘recent trends in mechanical engineering, organized by MSRIT Bangalore. During july2012

13. Y D Chethan , H V Ravindra “Automatic Inspection using Blob Analysis technique by Machine vision” at National conference on ‘image processing, pattern recognition, computer vision, organized by P.E.S.C.E.Mandya.during 22^nd -25^th Aug2009

14. Y D Chethan , H V Ravindra “Parametric Optimization In Drilling Of En-8 Using Taguchi Technique And Surface Roughness Estimation Using Multiple Regression Analysis at International Conference on Innovations and Emerging Trends in Mechanical Engineering (IIETME2014) organized by Nagarjuna College of Engineering & Technology Bangalore 13th June 2014

15. Y D Chethan , H V Ravindra and Y T Krishne gowda” Application of Digital Image Processing In Parametric Optimization Of Turning Inconel 718 By Taguchi Technique With Coated Carbide Inserts.” International Conference on computational methods in engineering December 17-19 2014 organized by Directorate of Research, Manipal University

16. Y D Chethan , H V Ravindra and Y T Krishne gowda,“ Estimation of Machine Vision and Acoustic Emission Parameters for Tool Status Monitoring in Turning Using Artificial neural network”, ASME-International Mechanical Engineering Congress and Exposition (IMECE)-2015, November 13- 15, 2015, Houstan, Texas, USA

17. Y D Chethan, H V Ravindra ,Y T Krishne gowda and Tejesh gowda “Acoustic emission assisted Monitoring and Optimization of Process Parameters in turning of nickel base super alloy” International Conference on PRECISION, MESO, MICRO AND NANO ENGINEERING, COPEN-9, December 10th-12th, 2015, Indian Institute of Technology, Bombay (IIT-B)

18. Y D Chethan, H V Ravindra, Y T Krishne Gowda “Machine Vision for Performance Status Monitoring in Turning Nickel Base Super Alloy Using Image Processing” 10th International Conference on Precision, Meso, Micro and Nano Engineering COPEN-10, December 07 - 09, 2017 at Indian Institute of Technology (IIT-M)Madras.

19. Y D Chethan, H V Ravindra, Rudreshi Addamani, Ugrasen Gonchikar, “Estimation and Comparison of Welding Performances using MRA and GMDH in P- GMAW for SS 316L Material” ASME-International Mechanical Engineering Congress and Exposition (IMECE2018).

Book chapters

20. Y D Chethan R Addamani, HV Ravindra, “Assessment of Weld Bead Mechanical Properties During Destructive Testing Using Image Processing by Multivision Technique” Emerging Research in Electronics, Computer Science and Technology, 265-275

21. 21.Y D Chethan, HV Ravindra, YTK Gowda “Machine-Vision-Assisted Performance Monitoring in Turning Inconel 718 Material Using Image Processing” Emerging Research in Electronics, Computer Science and Technology, 915-925