Qualification: 
M.Tech
cs_sumesh@cb.amrita.edu

Sumesh C. S. currently serves as Assistant Professor (Sr. Gr) at Department of Mechanical Engineering, School of Engineering, Coimbatore Campus. His areas of research include Mechanics of Solids, Theory of Mechanisms and FEM.

Education

  • Pursuing Ph. D.
    Amrita Vishwa Vidyapeetham, Coimbatore
  • 2003 - 2006 : M.Tech.
    Govt. Engineering College, Thrissur
  • 1998 - 2002 : B.Tech.
    Govt. Engineering College, Thrissur

Experience

  • August 8, 2011 - Present :

Assistant Professor
School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore

  • February 2006 - August 2011 :

Assistant Professor
Vidya Academy of Science & Technology, Thalakkottukara, Thrissur

Subjects and the Classes Taught in Both the Semesters

Academic Year Semester Name of the Subject Taught
Theory Practical
2019-20 ODD Mechanics of Solids Engg. Drawing Material Testing Lab
EVEN Engg. Mechanics Workshop, FEM Lab, Measurements Lab
2018-19 ODD Engg. Drawing (2 batches Material Testing Lab, Workshop
EVEN Engg. Mechanics, Engg. Drawing Workshop, FEM Lab, Project Review
2017-18 ODD Engg. Drawing (2 batches) Engg. Drawing, Material Testing Lab
EVEN Engg. Mechanics, Mechanics of Solids Measurements Lab
2016-17 ODD Computer Aided Graphics (CAG) (2 batches) CAG Asst.,CAE/CAM Lab
EVEN Engg. Mechanics Fluid Machinery Lab, Engg. Drawing, Workshop
2015-16 ODD Computer Aided Graphics (CAG) (2 batches) CAE/CAM Lab
EVEN Engg. Mechanics Material Testing Lab (1 Main, 1 Asst.)
2014-15 ODD Engg. Mechanics Engg. Drawing Engg. Drawing, CAE/CAM Lab
EVEN Engg. Mechanics CAD, Material Testing Lab, UG project review
2013 - 14 ODD Engg. Mechanics Engg. Drawing Engg. Drawing, Workshop
EVEN Engg. Mechanics CAD, Material Testing Lab

Projects Guided

Year (5 years) Title of the Project/Thesis Number of Students/group Industry Project / In-house Outcome
PG Level
2019-20 Finite Element Modeling And Optimization for Milling of TI6Al4V Alloy 1 In-house Ongoing
2018-19 Numerical Modelling and Optimisation of Cold Rolling Process 1 In-house Completed
2017-18 Finite element modelling to investigate the influence of process parameters on surface integrated properties during face milling of AISI 304 steel 1 In-house Completed
2016-17 Finite element modelling to investigate the influence of process parameters on laser assisted machining of Ti6Al4V alloy 1 In-house Completed
2015-16 Finite element modelling to investigate the influence of process parameters on Surface finish of Ti6Al4V (Co-guide) 1 In-house Completed
2014-15 Failure prediction of Single Edged Notched Tension Al-8011 alloy specimens 1 In-house Completed
Finite Element Modelling of Orthogonal cutting of hard to machine materials under thermal assisted conditions (Co-guide) 1 In-house Completed
UG Level
2019-20 Influence of notch parameters on failure properties of SENT specimen Multi parameter optimisation of Machining Parameters in orthogonal turning of AISI 4340 Steel using TLBO 1 1 In-house Ongoing
2017-18 Effect of grinding parameters on surface properties of Spheroidal Graphite Cast Iron. Multi objective optimisation of Machining Parameters in turning of AISI 4340 Steel using RSM 1 1 In-house Completed
2016-17 Optimisation of Surface finish during up-milling of AISI 4340 steel using RSM Optimisation of Surface Roughness during Orthogonal Turning of Aluminium 6061 T6 alloy 1 1 In-house Completed
2015-16 Analysis of Casting defects and Identification of remedial measures – A study in a pump industry 3 In-house Completed
2013-14 Effect of tool geometry on cutting forces in turning process 4 In-house Completed
Effect of tool geometry on tool chip interface temperature in turning process 4 In-house Completed
2012-13 Optimisation of feed force using Taguchi method 5 In-house Completed

Participation / Paper Presentation / Session Chair / Key Note or Invited Address

Sl. No. Name of the Programme and Organiser Duration Purpose of attending (Participation / Paper Presentation / Session Chair / Key Note or Invited Address) Financial Support availed from the University towards TA, DA, Reg., etc. (Rs.)
From To
1. Summer School in Tribology 24th June 2013 28th June 2013 Participation 12000/-
2. ISTE workshop on Engg. Mechanics 26th Nov 2013 06th Dec 2013 Participation NIL
3. Workshop on Advanced Finite Element Analysis 22nd Dec 2013 24th Dec 2013 Participation 16750/-
4 Sri Chandrasekharaendra Saraswathi Vishwa Maha Vidyalaya , Kanchipuram University 02nd April 2015 03rd April 2015 Paper Presentation 8750/-

Seminars, Workshops and Conferences Attended

Sl. No. Name of the International Seminar/Workshop/Conference Date Name of Organizing Institution & Venue
1 International Conference on Mechanical & Manufacturing Engineering 02&03 April 2015 Sri Chandrasekharaendra Saraswathi Vishwa Maha Vidyalaya , Kanchipuram University
Sl. No. Name of the National Seminar/Workshop/Conference Date Name of Organizing Institution &Venue
1. Summer School in Tribology 24 – 28 June 2013 Indian Oil Institute of Petroleum Management, Gurgaon
2. ISTE workshop on Engg. Mechanics 26th Nov – 06th Dec 2013 Amrita Vishwa VIdyapeetham
3. Workshop on Advanced Finite Element Analysis 22 – 24 Dec 2013 IIT Madras

Papers Presented in Conferences, Seminars, Workshops, or Symposia

Title of the Paper Name & Location of the International Conference/ Seminar/ Workshop/ Symposium Names of Co-authors if any Date and or Month, and Year of Presentation
Effect of cutting parameters on feed force in machining AISI 1018 steel International Conference on Mechanical & Manufacturing Engineering, Kanchipuram University Mr. K Sriram 02 April 2015

Publications

Publication Type: Journal Article

Year of Publication Title

2019

K. K., Sumesh C.S., and Dr. Ajith Ramesh, “Numerical modeling and multi objective optimization of face milling of AISI 304 steel”, Journal of Applied and Computational Mechanics, vol. 5, pp. 749-762, 2019.[Abstract]


There is a requirement to find accurate parameters to accomplish precise dimensional accuracy, excellent surface integrity and maximum MRR. This work studies the influence of various cutting parameters on output parameters like Cutting force, Surface roughness, Flatness, and Material removal rate while face milling. A detailed finite element model was developed to simulate the face milling process. The material constitutive behavior is described by Johnson-Cook material model and the damage criteria is established by Johnson-Cook damage model. The result indicate significant effects of all three cutting parameters on MRR and both feed rate and depth of cut have significant effect on cutting force. Also, feed rate has significant effect on PEEQ and none of the parameters have effect on flatness. © 2019 by the authors.

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2018

P. Gopikrishnan, Akbar, A., Asokan, A., Bhaskar, B., and Sumesh C.S., “Numerical Modelling and Optimization of Surface Finish during Peripheral Milling of AISI 4340 Steel using RSM”, Materials Today: Proceedings, vol. 5, pp. 24612-24621, 2018.[Abstract]


The effect of machining parameters, Cutting Speed, Feed Rate, and Depth of cut, on surface finish during peripheral milling of AISI 4340 steel, studied using response surface methodology. This paper suggests a distinctive way to calculate the surface finish, using the variance of effective plastic strain values obtained from the numerical model. The Johnson-Cook damage and material models are used in the numerical model along with the ALE. The variance of PEEQ was optimized using ANOVA, which shows that cutting speed was the most dominant factor. The optimal settings of the machining parameters was obtained for better surface finish.

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2018

Sumesh C.S. and Dr. Ajith Ramesh, “Numerical Modelling and Optimization of dry Orthogonal Turning of Al6061 T6 alloy”, Periodica Polytechnica Mechanical Engineering, vol. 62, pp. 196-202, 2018.[Abstract]


In this paper, the influence of machining parameters, Cutting Speed, Feed Rate, and Depth of cut, on surface finish during dry orthogonal turning of Al 6061 - T6 alloy, is studied using the response surface methodology (RSM). This paper proposes a unique way to predict the surface finish in turning, using the effective plastic strain (PEEQ) values obtained from the simulations. A comprehensive finite element model was proposed to predict the surface finish accurately, by correlating the variance of the PEEQ. The Johnson-Cook damage model is used to define the damage criteria and Johnson-Cook material model is used to explain the material constitutive behavior. A dynamic, explicit method is used along with the Adaptive Lagrangian-Eulerian (ALE) method to predict material flow accurately. The influence of machining parameters was studied by assuming Central Composite Design (CCD). The output response, PEEQ, was fitted into analytical quadratic polynomial models using regression analysis, which shows that feed rate was the most dominant factor for PEEQ than the other parameters considered in this study. Using the individual desirability function method, the objective, optimal setting of the machining parameters was obtained for better surface finish. © 2018 Budapest University of Technology and Economics. All rights reserved.

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2018

Sumesh C.S. and Narayanan, P. J. Arun, “Influence of Notch Depth-to-Width Ratios on J-Integral and Critical Failure Load of Single-Edge Notched Tensile Aluminium 8011 Alloy Specimens”, Journal of Solid Mechanics, vol. 10, pp. 86-97, 2018.[Abstract]


In this paper, the influence of notch depth-to-width ratios on J-integral and critical load of Aluminium 8011 alloy specimens with U-notch under Mode I loading are studied. Using experiments, for a set of specimens having different notch depth–to–width ratios, J-integral was found and the same was verified using analytical methods. Further, using the results obtained from the experiments, failure assessment diagrams (FAD) were plotted for the same ratios, to determine the safe or critical load and the type of failure mechanism was also studied. The results show that, for both shallow and deep notch depths, the J-integral values obtained from the experimental method, are in very close agreement with the analytical values. J-integral values decrease with increase in notch depth and increase with increase in applied load. Furthermore, from FAD, the safe load decreases when the notch depth-to-width ratio increases and it was found that, all the tested specimens failed due to elastic plastic deformation mechanism.

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2015

Sumesh C.S. and Sriram, K., “Effect of Cutting Parameters on Feed Force in Machining AISI 1018 Steel”, Advances in Mechanical Engineering, 2015.[Abstract]


In this present work, influence of cutting parameters on feed force is studied and optimized using Taguchi approach. AISI 1018 steel alloy is selected and machined using tungsten carbide tool. Eighty-One specimens were thus turned and cutting force was measured using lathe tool dynamometer. L27 orthogonal array in Taguchi approach selected for optimization. From ANOVA, the results showed that out of the parameters selected feed rate has major effect on feed force. In addition, the combination of cutting speed and feed rate has major effect on feed force

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2015

Dr. Ajith Ramesh, Sumesh C.S., Abhilash, P. M., and Rakesh, S., “Finite Element Modelling of Orthogonal Machining of Hard to Machine Materials”, International Journal of Machining and Machinability of Materials, vol. 17, pp. 543-568, 2015.[Abstract]


This paper presents a detailed finite element model to predict deformation and other machining characteristics involved in high-speed orthogonal machining (cutting speed > 54 m/min) of hard-to-deform materials like Ti6Al4V. The influence of various cutting parameters like feed rate, spindle speed, and rake angle, on the output parameters like cutting force and surface finish, was analysed. The paper tries to relate the degree of surface finish with the variance of the effective plastic strain. The Johnson-Cook material model is used to describe the material constitutive behaviour, and the Johnson-Cook damage model is used to establish the damage criteria. Due to the high machining costs associated with the titanium alloy, the model is first validated using aluminium alloy (Al2024-T351), and the same model is then extended to predict the results for titanium alloy. The matrix for the design of experiments (DOE) considers a full factorial approach, with about 48 simulations, for a proper understanding on the influence of the major machining parameters. A dynamic, explicit integration scheme is used along with the arbitrary Lagrangian-Eulerian (ALE) technique to accurately predict material flow. This paper also presents a unique method to tackle the commonly encountered numerical issues involved in modelling self-contact.

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Publication Type: Conference Proceedings

Year of Publication Title

2015

Sumesh C.S. and Sriram, K., “Effect of Cutting Parameters on Feed Force in Machining AISI 1018 Steel”, International Conference on Mechanical & Manufacturing Engineering. Trans Tech Publications, Sri Chandrasekharaendra Saraswathi Vishwa Maha Vidyalaya , Kanchipuram University, 2015.

Membership of Professional Bodies, Societies

Sl.No. Name of the Professional Body / Society Membership Number
1. ISTE LM54561
2. TSI LM#5217