ABOUT THE COURSE:This course is the first part of a three-part series which gives a brief introduction about basic mechanical engineering concepts. The course, due to the huge amount of content, is split into three: This course encompasses the concepts of solid mechanics and design like basic concepts of solids, machine components, linkages, mechanisms, and mechanical components of automobiles. The course also consists of basic concepts of machine learning and artificial intelligence techniques and topics like machine learning and deep learning methods like linear regression, logistic regression, clustering, classification, decision tree, random forest, SVM, and artificial neural network. The course will enable the student to have a firm grasp on these basic concepts and will serve as an introductory course which will discuss these topics and help students to develop interest and knowledge in basic and core concepts of mechanical engineering.INTENDED AUDIENCE: Students of all Engineering and Science disciplinesPREREQUISITES: The student should have completed two semesters of UG Engineering or Science program.INDUSTRY SUPPORT: HAL, NAL, SAIL, ISRO
Overview
Syllabus
Week 1:
- Units and dimensions, dimensional analysis
- Scalars and vectors, vector algebra
- Statics, kinetics and kinematics
- Laws of motion, inertia, momentum
- Friction, lubrication, moment of inertia, gravity
- Mechanical properties: stress, strain, residual stress
- Stress-strain curve, elasticity, Poisson’s ratio
- Hardness,toughness, impact, creep
- Principal stress, Castigliano’s theorem
- Static and fatigue loading, critical loads
- Brittleness, ductility
- Homogeneous materials, isotropic and anisotropic materials
- Testing for tension, compression, bending, impact, fracture etc.
- Materials: Metals, composites, glass, diamond, etc.
- Columns, slenderness
- Stress in cylinders and spheres
- Factor of safety, degree of freedom, endurance limit
- Linkages,mechanisms
- Cam follower design
- Mohr circle
- Shear force and bending moment diagram
- Stress concentration and notch sensitivity
- Spring-mass systems -1
- Spring-mass systems -2
- Failure theories
- Finite Element analysis,mesh generation
- Bearings, lubrication
- Fracture and fatigue
- Gears: basic concepts
- Contact ratio,interference
- Force analysis of gears
- Laboratory Demonstration: Types of gears, gear trains
- Shafts, keys, nuts bolts and fasteners, screws
- Chains, pulleys, belts, couplings, flexible shafts
- Design of shafts and permanent joints
- Permanent joints, stress and strength of permanent joints
- Clutches, brakes and flywheels
- Superchargers and turbochargers, camber, caster and toe
- Vibration analysis and Acoustics
- Laboratory Demonstration,Vibrations
- Basic concepts of statistics and probability
- Hypothesis testing,outliers and missing values, transformations
- Feature engineering, model validation techniques
- Basics of machine learning, regression, classification, and their performance metrics
- Regression and classification models, segmentation
- Advanced ML techniques (Decision tree, random forest etc.)
- Support vector Machine, Artificial Neural network
- ANN, CNN, RNN
Taught by
Prof. Janakranjan Ramkumar, Prof. Amandeep Singh Oberoi
