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    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Mechanical Engineering

    Ramchandra Chandravansi University Palamu
    Duration
    4 Years
    Mechanical Engineering UG OFFLINE

    Duration

    4 Years

    Mechanical Engineering

    Ramchandra Chandravansi University Palamu
    Duration
    Apply

    Fees

    ₹8,00,000

    Placement

    92.5%

    Avg Package

    ₹6,00,000

    Highest Package

    ₹12,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Mechanical Engineering
    UG
    OFFLINE

    Fees

    ₹8,00,000

    Placement

    92.5%

    Avg Package

    ₹6,00,000

    Highest Package

    ₹12,00,000

    Seats

    120

    Students

    1,200

    ApplyCollege

    Seats

    120

    Students

    1,200

    Curriculum

    Curriculum Overview

    The mechanical engineering curriculum at Ramchandra Chandravansi University Palamu is designed to provide students with a comprehensive understanding of mechanical systems and their applications. The program is structured over eight semesters, with a balanced mix of core subjects, departmental electives, science electives, and laboratory sessions.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    1MAT101Engineering Mathematics I3-1-0-4None
    1PHY101Physics for Engineers3-1-0-4None
    1CHM101Chemistry for Engineers3-1-0-4None
    1ENG101English for Engineers3-0-0-3None
    1ME101Introduction to Engineering Design2-0-2-3None
    1ME102Engineering Graphics2-0-2-3None
    2MAT201Engineering Mathematics II3-1-0-4MAT101
    2PHY201Thermodynamics3-1-0-4PHY101
    2ME201Strength of Materials3-1-0-4ME101
    2ME202Manufacturing Processes3-1-0-4ME101
    2ME203Fluid Mechanics3-1-0-4PHY201
    2ME204Computer Programming2-0-2-3None
    3MAT301Engineering Mathematics III3-1-0-4MAT201
    3ME301Heat Transfer3-1-0-4PHY201
    3ME302Machine Design3-1-0-4ME201
    3ME303Control Systems3-1-0-4MAT301
    3ME304Materials Science3-1-0-4CHM101
    3ME305Engineering Economics3-0-0-3MAT201
    4MAT401Engineering Mathematics IV3-1-0-4MAT301
    4ME401Advanced Thermodynamics3-1-0-4ME301
    4ME402Computational Fluid Dynamics3-1-0-4ME303
    4ME403Renewable Energy Technologies3-1-0-4ME301
    4ME404Advanced Manufacturing Processes3-1-0-4ME202
    4ME405Project Management3-0-0-3ME305
    5ME501Robotics and Automation3-1-0-4ME303
    5ME502Biomechanics3-1-0-4ME301
    5ME503Advanced Materials3-1-0-4ME304
    5ME504Finite Element Analysis3-1-0-4MAT401
    5ME505Environmental Impact Assessment3-1-0-4ME301
    6ME601Industry 4.03-1-0-4ME501
    6ME602Smart Manufacturing Systems3-1-0-4ME404
    6ME603Energy Storage Systems3-1-0-4ME401
    6ME604Advanced Turbomachinery3-1-0-4ME303
    6ME605Machine Learning for Engineers3-1-0-4MAT401
    7ME701Capstone Project I4-0-0-4ME501
    7ME702Advanced Project Management3-1-0-4ME505
    7ME703Research Methodology2-0-2-3ME501
    7ME704Special Topics in Mechanical Engineering3-1-0-4ME601
    8ME801Final Year Thesis6-0-0-6ME701
    8ME802Internship2-0-0-2ME701
    8ME803Professional Ethics2-0-0-2ME701

    Advanced Departmental Elective Courses

    Advanced departmental elective courses in mechanical engineering at Ramchandra Chandravansi University Palamu are designed to provide students with in-depth knowledge in specialized areas. These courses are offered in the fifth and sixth semesters and are led by faculty members who are experts in their respective fields.

    Robotics and Automation: This course introduces students to the principles and applications of robotics and automation. Students learn about robot kinematics, dynamics, control systems, and sensor integration. The course includes hands-on laboratory sessions where students build and program robots.

    Biomechanics: This course explores the application of mechanical engineering principles to biological systems. Students study the mechanics of human movement, biomechanical modeling, and medical device design. The course includes laboratory sessions involving motion analysis and biomechanical testing.

    Advanced Materials: This course provides an in-depth study of advanced materials used in engineering applications. Students explore the properties, processing, and applications of composites, ceramics, and smart materials. The course includes laboratory sessions involving materials characterization and testing.

    Finite Element Analysis: This course introduces students to the finite element method for engineering analysis. Students learn to use computational tools to model and analyze complex engineering problems. The course includes hands-on sessions with industry-standard software.

    Environmental Impact Assessment: This course focuses on assessing the environmental impact of engineering projects. Students learn about environmental regulations, impact assessment methodologies, and sustainable engineering practices. The course includes case studies and field visits.

    Industry 4.0: This course explores the principles and applications of Industry 4.0 technologies. Students study the integration of IoT, AI, and automation in manufacturing processes. The course includes laboratory sessions involving smart manufacturing systems.

    Smart Manufacturing Systems: This course focuses on the design and implementation of smart manufacturing systems. Students learn about digital twins, predictive maintenance, and real-time monitoring systems. The course includes hands-on sessions with industrial automation tools.

    Energy Storage Systems: This course explores the principles and applications of energy storage technologies. Students study batteries, supercapacitors, and other energy storage systems. The course includes laboratory sessions involving energy storage testing and characterization.

    Advanced Turbomachinery: This course provides an in-depth study of turbomachinery design and analysis. Students learn about turbine and pump design, performance analysis, and optimization techniques. The course includes laboratory sessions involving turbomachinery testing.

    Machine Learning for Engineers: This course introduces students to machine learning techniques for engineering applications. Students learn about data preprocessing, model selection, and implementation of machine learning algorithms. The course includes hands-on sessions with machine learning software.

    Project-Based Learning Philosophy

    The department's philosophy on project-based learning emphasizes the integration of theoretical knowledge with practical application. Students are encouraged to work on real-world engineering problems from their early semesters, with increasing complexity and scope as they progress through the program.

    Mini-projects are mandatory in the third and fourth semesters. These projects are designed to reinforce concepts learned in core courses and provide students with hands-on experience in engineering design and analysis. Projects are typically completed in teams, with each team member contributing to specific aspects of the project.

    The final-year thesis or capstone project is a comprehensive endeavor that allows students to integrate knowledge from multiple disciplines and apply it to a complex engineering challenge. Students select their projects in consultation with faculty mentors, ensuring alignment with their interests and career goals.

    Project evaluation criteria include design quality, technical execution, innovation, teamwork, and presentation skills. Students are assessed on their ability to solve engineering problems, communicate their solutions effectively, and demonstrate critical thinking and creativity.