R S Umamaheswara Raju | CNC machine tools | Best Researcher Award

 Dr. R S Umamaheswara Raju | CNC machien tools | Best Researcher Award

 Dr, R S Umamaheswara Raju,Maharaj Vijayaram Gajapthi Raj College of Engineering(A),India

Dr. R. S. Umamaheswara Raju is a distinguished academician and researcher at Maharaj Vijayaram Gajapathi Raj College of Engineering (Autonomous), India. With extensive experience in engineering education and research, Dr. Raju has made significant contributions to his field. His academic background is grounded in a robust understanding of engineering principles, and he has dedicated his career to advancing knowledge and innovation in engineering.

 

Professional Profiles:

Orcid

Education :

  • Ph.D. in Engineering
    Jawaharlal Nehru Technological University (JNTU), Kakinada
    Completed in 2017
  • M.Tech in Manufacturing Science and Engineering
    M S Ramaiah Institute of Technology, Bangalore
    Completed in 2007
  • B.Tech in Mechanical Engineering
    Jagannath Institute of Technology and Management
    Completed in 2004

Professional Experience:

  1. Maharaj Vijayaram Gajapathi Raj College of Engineering (MVGRCE)
    Associate Professor
    Vizianagaram
    2017 – Present
  2. Maharaj Vijayaram Gajapathi Raj College of Engineering (MVGRCE)
    Assistant Professor
    Vizianagaramc
    2007 – 2017

Awards and Honors:

  • Several recognitions and awards for research contributions in the field of manufacturing engineering (specific awards not listed).

Skills:

  • Lesson planning and teaching
  • Encouraging and evaluating student progress
  • Supervising and maintaining classroom discipline
  • Research and development in manufacturing engineering
  • Machine learning applications in manufacturing
  • Surface roughness assessment
  • CNC machining
  • Machine vision systems

Patents:

  1. 3D Printing of Bio-Compatible Ceramics as Scaffolds
    Inventors: Mishra, R S Umamaheswara Raju, Mandru Anil Prakash, Boddepalli Anant Ranganath, Badari Srinivas
    Published: June 24, 2022
  2. Smart System for Adaptive Surface Roughness Control of Workpiece and Method Thereof
    Inventors: Dr. P. Satish Rama Chowdary, Dr. R S Umamaheswara Raju, Dr. VVSSS. Chakravarthy
    Assignee: Raghu Institute of Technology
    Published: February 18, 2022

Publications :

  • Machine Learning Based Surface Roughness Assessment via CNC Spindle Bearing Vibration
    International Journal on Interactive Design and Manufacturing (IJIDeM), 2024
  • Precision Enhancement in CNC Face Milling Through Vibration-Aided AI Prediction of Surface Roughness
    International Journal on Interactive Design and Manufacturing (IJIDeM), 2024
  • Machine Vision Based Surface Roughness Assessment System Based on the Internet of Things and Contourlet Transforms
    International Journal on Interactive Design and Manufacturing, 2023
  • Automated Evaluation of Surface Roughness Using Machine Vision-Based Intelligent Systems
    Journal of Scientific and Industrial Research, 2023, Volume 82, Pages 11-25
  • Surface Finish Evaluation Using Curvelet Transforms Based Machine Vision System
    Materials Today: Proceedings, 2021, Volume 44, Pages 500-505
  • Flower Pollination Algorithm Based Reverse Mapping Methodology to Ascertain Operating Parameters for Desired Surface Roughness
    Evolutionary Intelligence, 2021, Volume 14, Pages 1145-1150
  • Development of Surface Texture Evaluation System for Highly Sparse Data-Driven Machining Domains
    International Journal of Computer Integrated Manufacturing, 2020, Volume 33, Pages 859-868
  • Material Removal Rate and Surface Roughness Based Cutting Parameters Optimization for Turning EN24 Steel
    International Research Journal of Engineering and Technology (IRJET), 2019, Volume 6(8), Pages 250-260
  • Wear Characteristics of Alternative, Bio-Degradable Cutting Fluids
    Materials Today: Proceedings, 2019, Volume 26, Pages 1352-1355
  • Curvelet Transforms and Flower Pollination Algorithm Based Machine Vision System for Roughness Estimation
    Journal of Optics (India), 2018, Volume 47, Pages 243-250
  • Curvelet Transform for Estimation of Machining Performance
    Optik, 2017, Volume 131, Pages 615-625
  • Effectiveness of FPA in Sparse Data Modelling and Optimization
    Lecture Notes in Networks and Systems, 2017, Volume 5, Pages 493-501
  • Intelligence Model Based Machining Process Classification and Performance Estimation
    Materials Today: Proceedings, 2017, Volume 4, Pages 982-990
  • Image and Vibration Based Mixed Variable Approach for Machining Performance Estimation
    International Journal of Applied Engineering Research, 2016, Volume 11, Pages 2646-2650
  • Machine Vision System for Predicting Surface Roughness in Surface Grinding Process
    ICMMM, 2014, Volume 1(1), Pages 353-354
  • Design Optimization in Bolt and Nut Fasteners to Reduce Stress Concentration
    International Journal Multidisciplinary Educational Research, 2013, Volume 2(3)
  • SVM-GA Based Reverse Mapping Methodology to Identify Cutting Parameter for a Given Surface Finish in End Milling
    Global Trends and Challenges in Design and Manufacturing Proc. of the 3rd Intl. & 24th AIMTDR Conf., 2010, Volume AIMTDR-2010, Pages 565-570