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M-TECH in Production Engineering at Jawaharlal Nehru Technological University Kakinada
Kakinada, Andhra Pradesh
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About the Specialization
What is Production Engineering at Jawaharlal Nehru Technological University Kakinada Kakinada?
This M.Tech Production Engineering program at Jawaharlal Nehru Technological University Kakinada focuses on advanced manufacturing processes, industrial automation, quality management, and systems optimization. It addresses the growing need for skilled professionals in India''''s rapidly expanding manufacturing sector, emphasizing efficiency, quality, and innovation in production systems and technologies.
Who Should Apply?
This program is ideal for mechanical, production, or industrial engineering graduates seeking to specialize in advanced manufacturing techniques, as well as working professionals aiming to upgrade their skills in areas like lean manufacturing, supply chain, and industrial robotics. It caters to those aspiring for leadership roles in various manufacturing industries across India.
Why Choose This Course?
Graduates of this program can expect promising career paths in Indian manufacturing giants, automotive, aerospace, and defense sectors. Typical roles include Production Engineer, Quality Assurance Manager, Process Improvement Engineer, or R&D Specialist, with starting salaries often ranging from INR 4-8 LPA, progressing to 10-20+ LPA with experience in leading companies.
Student Success Practices
Foundation Stage
Master Core Production Principles- (Semester 1-2)
Focus on building a strong foundation in Industrial Robotics, Metal Forming, Metal Cutting, and Advanced Materials. Utilize textbooks, online lectures from NPTEL, and practical lab sessions diligently to grasp theoretical concepts and their applications thoroughly.
Tools & Resources
NPTEL videos, J-Gate for research papers, Department laboratories
Career Connection
A strong grasp of fundamentals is crucial for excelling in technical interviews and for effectively tackling initial roles in manufacturing and process design.
Engage in Mini-Projects and Technical Seminars- (Semester 2)
Actively participate in the Mini Project and Technical Seminar to develop research skills, problem-solving abilities, and presentation techniques. Identify a real-world manufacturing challenge and propose innovative solutions, seeking regular guidance from faculty mentors.
Tools & Resources
MATLAB, SolidWorks, Ansys, IEEE Xplore for research
Career Connection
Showcasing practical project experience and strong communication skills significantly enhances employability and prepares for advanced dissertation work.
Network and Explore Elective Specializations- (Semester 1-2)
Attend departmental workshops, guest lectures, and industry interaction events to network with faculty, alumni, and industry professionals. Carefully evaluate elective options like Additive Manufacturing or Industrial Automation to align with career interests and future industry demands.
Tools & Resources
LinkedIn, Professional societies (e.g., Institution of Engineers, SAE India)
Career Connection
Early networking opens doors to internships and mentorship, while focused elective choices lead to specialized and in-demand career paths.
Intermediate Stage
Initiate and Progress Dissertation Research- (Semester 3)
Dedicate significant effort to ''''Dissertation Phase – I'''' by thoroughly formulating a research problem, conducting an extensive literature survey, and defining clear objectives. Regularly consult with your supervisor for feedback and refine your research methodology.
Tools & Resources
Mendeley/Zotero for referencing, Python/R for data analysis, Relevant simulation software
Career Connection
A well-executed dissertation showcases independent research capability, a highly valued trait in R&D roles, academic pursuits, and advanced problem-solving positions.
Seek Industry Internships or Live Projects- (Semester 3 onwards)
Actively pursue internships or live industry projects during semester breaks or alongside your studies. Apply theoretical knowledge to solve practical manufacturing issues within a company, gaining invaluable hands-on experience and crucial industry exposure.
Tools & Resources
College placement cell, Internship portals (e.g., Internshala, LinkedIn), Company career pages
Career Connection
Internships are critical for building a professional network, gaining practical skills, and often lead to pre-placement offers in leading industrial firms.
Develop Advanced Software Proficiency- (Semester 3)
Beyond academic requirements, proactively learn and gain proficiency in advanced simulation, design, and analysis software widely used in the production engineering industry (e.g., ABAQUS, CATIA, Arena Simulation, SAP ERP modules for production planning).
Tools & Resources
Online courses (e.g., Coursera, Udemy), Software tutorials, University-provided licenses
Career Connection
Demonstrating advanced software skills makes you a more competitive candidate for specialized engineering, analytical, and automation roles.
Advanced Stage
Finalize and Present High-Impact Dissertation- (Semester 4)
Conclude ''''Dissertation Phase – II'''' with meticulous data analysis, accurate interpretation of results, and clear, concise thesis writing. Prepare thoroughly for the final viva voce by practicing presentations and anticipating potential questions from external examiners and faculty.
Tools & Resources
LaTeX for thesis writing, Academic presentation tools, Mock viva sessions with faculty
Career Connection
A strong final dissertation is a powerful portfolio piece, demonstrating expertise and research acumen for future employers or for pursuing a Ph.D. in related fields.
Targeted Placement Preparation- (Semester 4)
Engage in rigorous placement preparation, focusing on technical aptitude tests, group discussions, and personal interviews. Tailor your resume and cover letters to specific job descriptions in manufacturing, operations, and R&D roles within Indian companies and PSUs.
Tools & Resources
JNTUK placement cell, Online aptitude platforms (e.g., Face Prep), Company-specific interview guides
Career Connection
Structured and targeted preparation is paramount to securing coveted positions in top manufacturing firms and public sector undertakings across India.
Continuous Learning and Certification Pursuit- (Throughout and Post-Graduation)
Identify and pursue relevant professional certifications that complement your specialization, such as Lean Six Sigma, Certified Supply Chain Professional (CSCP), or certifications in specific CAD/CAM/CAE software packages to enhance your skillset.
Tools & Resources
Certification bodies (e.g., ASQ, APICS), Industry training providers, Online professional development platforms
Career Connection
These certifications validate specialized skills, enhance your market value, and demonstrate a commitment to lifelong learning in a dynamic industrial environment.
Program Structure and Curriculum
Eligibility:
- B.E./B.Tech. in Mechanical/Production Engineering or equivalent, with valid GATE score or PGECET rank, as per JNTUK M.Tech admission norms.
Duration: 2 years (4 semesters)
Credits: 80 Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| R20MPED1101 | Industrial Robotics | Core | 3 | Robot Anatomy and Configuration, Forward and Inverse Kinematics, Differential Kinematics, Dynamics of Manipulators, Trajectory Generation |
| R20MPED1102 | Theory of Metal Forming | Core | 3 | Metal Forming Processes, Stress-Strain Relationships, Yield Criteria, Friction and Lubrication, Bulk Forming, Sheet Metal Forming |
| R20MPED1103 | Theory of Metal Cutting | Core | 3 | Mechanics of Machining, Tool Materials, Tool Wear and Tool Life, Machinability, Unconventional Machining Processes |
| R20MPED1104 | Advanced Materials | Core | 3 | Composites, Ceramics, Polymers, Smart Materials, Biomaterials, Nanomaterials |
| R20MPED1105 | Elective – I (Additive Manufacturing) | Elective | 3 | Fundamentals of AM, Liquid-Based Systems, Solid-Based Systems, Powder-Based Systems, Post-Processing |
| R20MPED1106 | Elective – II (Industrial Automation) | Elective | 3 | Automation Fundamentals, Sensors and Transducers, PLC Programming, Industrial Control Systems, SCADA and DCS |
| R20MPED1107 | Production Engineering Lab | Lab | 2 | Metal Forming Experiments, Metal Cutting Experiments, Material Characterization, Robotics Programming, Automation System Experiments |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| R20MPED1201 | Quality Control and Reliability Engineering | Core | 3 | Quality Concepts, Statistical Process Control, Acceptance Sampling, Reliability Engineering, Design for Reliability |
| R20MPED1202 | Advanced Optimization Techniques | Core | 3 | Linear Programming, Non-Linear Programming, Dynamic Programming, Genetic Algorithms, Simulated Annealing |
| R20MPED1203 | Computer Integrated Manufacturing | Core | 3 | CAD/CAM Integration, CIM Architectures, Manufacturing Databases, Group Technology, Flexible Manufacturing Systems (FMS) |
| R20MPED1204 | Elective – III (Advanced Metrology and Instrumentation) | Elective | 3 | Measurement Principles, Sensors, Transducers, Coordinate Measuring Machines (CMM), Surface Metrology |
| R20MPED1205 | Elective – IV (Research Methodology and IPR) | Elective | 3 | Research Problem Formulation, Data Collection, Statistical Analysis, Report Writing, Intellectual Property Rights |
| R20MPED1206 | Mini Project | Project | 2 | Problem Identification, Literature Review, Methodology Design, Data Analysis, Report Preparation |
| R20MPED1207 | Technical Seminar | Seminar | 3 | Literature Survey, Presentation Skills, Technical Report Writing, Recent Advances in Production Engineering |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| R20MPED2101 | Elective – V (Flexible Manufacturing Systems) | Elective | 3 | FMS Components, FMS Layouts, Tool Management, Material Handling Systems, FMS Planning and Control |
| R20MPED2102 | Elective – VI (Business Analytics - Open Elective) | Open Elective | 3 | Data Mining, Predictive Modeling, Business Intelligence, Data Visualization, Decision Making |
| R20MPED2103 | Dissertation Phase – I | Project | 10 | Problem Formulation, Extensive Literature Survey, Objective Definition, Research Methodology, Preliminary Design/Experimentation |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| R20MPED2201 | Dissertation Phase – II | Project | 24 | Detailed Research Work, Data Collection and Analysis, Result Interpretation, Thesis Writing, Viva Voce Examination |
