scheme of teaching and examination & syllabus · scheme of teaching and examination &...

M.Tech.: Industrial Automation & Robotics (2014 - 15)

Scheme of Teaching and Examination & Syllabus

Department of Mechanical Engineering The National Institute of Engineering, Mysore

M.Tech - Industrial Automation & Robotics

BLUEPRINT OF SYLLABUS STRUCTURE AND QUESTION PAPER PATTERN

(To be effective from the odd semester of the academic year 2014-15 for all semester students)

Blue Print of Syllabus Structure

1. Complete syllabus is prescribed in SIX units as Unit 1, Unit 2, etc. 2. In each unit there is one topic under the heading “Self Learning Exercises” (SLE).

These are the topics to be learnt by the student on their own under the guidance of the course instructors. Course instructors will inform the students about the depth to which SLE components are to be studied. Thus there will be six topics in the complete syllabus which will carry questions with a weightage of 10% in SEE only. No questions will be asked on SLE components in CIE.

Blue Print of Question Paper

1. Question paper will have seven full questions. 2. One full question each of 15 marks (Question No 1, 2, 3, 4, 5 and 6) will be set from

each unit of the syllabus. Out of these six questions, two questions will have internal choice from the same unit. The unit in which choice is to be given is left to the discretion of the course instructor.

3. Question No 7 will be set for 10 marks only on those topics prescribed as “Self Learning Exercises”.

Dr. B. K. Sridhara July 2014 Dean (Academic Affairs)

Department of Mechanical Engineering, NIE Page 1


M.Tech: Industrial Automation and Robotics

Course Structure: I Semester

Sl. No. Subject Code Subject

Contact Hrs. / Week Credits

L T P 1 APM0401 Applied Mathematics 4 0 0 4 2 IAR0501 Industrial Automation 4 2 0 5 3 IAR0502 Robotics for Industrial Automation 4 2 0 5 4 IAR0503 Computer Aided Engineering 4 0 2 5 5 IAR05XX Elective–I 4 2 0 5 6 IAR05XX Elective –II 4 0 0 4 7 IAR0101 Seminar–1 0 0 0 1

Total number of Credits 29

Elective – I Elective – II

IAR0508 Modeling, Simulation and Analysis of

Manufacturing Systems. IAR0403 Knowledge Based Design

IAR0509 Finite Element Analysis IAR0404 Dynamics and Mechanisms Design

IAR0520 Automatic Control Systems IAR0405 Product Design & Development



Course Structure: II Semester Sl. No.

Subject Code

Subject Contact Hrs. / Week

Credits L T P

1 IAR0521 Computer Concepts for Automation 4 2 0 5

2 IAR0505 Drives and Control systems for Automation

4 2 0 5

3 IAR0506 Microprocessors and Micro Controllers

4 0 2 5

4 IAR0406 Sensors Applications in Manufacturing

4 0 0 4

5 IAR05XX Elective - III 4 2 0 5 6 IAR04XX Elective - IV 4 0 0 4 7 IAR0102 Seminar-2 0 0 2 1

Total number of Credits 29

Elective - III Elective - IV

IAR0522 Computer Aided Production and Operation Management

IAR0407 ANN & Genetic Algorithms

IAR0523 Rapid-Prototyping IAR0408 Computer Vision and Image Processing

IAR0516 Mathematical Approach to Robotic Manipulators

IAR0409 Artificial Intelligence and Expert Systems in Automation



Course Structure: III Semester

Sl. No.

Subject Code

Subject L T P Credits

1

IAR0401

Industrial Training for 8 Weeks duration (At the end of the training, students are required to submit a report and present a seminar)

-

-

-

4

2

IAR0801

Project Work (preliminary) (Students have to initiate the project work and at the end of the semester should present a progress seminar)

-

-

-

8

3 IAR0201 Seminar 0 0 4 2 Total number of credits 14

Course Structure: IV Semester Sl. No.

Subject Code

Subject

L

T

P

Credits

1

IAR2801

Project-Work (Students have to submit the final project report at the end of the semester which will evaluated followed by a seminar presentation and viva-voce examination)

-

-

-

28

Total number of credits 28

Credit Structure

Core Courses 38 Elective Courses 20 Seminars/Ind Training/preliminary project 14 Major Project 28 TOTAL 100

Legend:

1) L – Lecturers Hrs/ Week 2) T – Tutorials Hrs/ Week 3) P – Practical Hrs/ Week 4) SLE – Self Learning Exercise

Department of Mechanical Engineering, NIE

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(Common to IAR, Machine Design, PEST, Nanotechnology) APPLIED MATHEMATICS (4-0-0)

Sub Code: APM0401 CIE : 50% Marks Hrs/Week: 04 SEE : 50% Marks SEE Hrs: 3Hrs Max :100 Marks

Course Outcome: 1.Obtain roots of algebraic and transcendental equations using various numerical

methods. 2.Obtain complex roots of quadratic factors of the given polynomial using iterative

methods. 3.Apply quadrature formulae to solve application problems. 4.Solve linear algebraic equations using direct and iterative methods. 5.Obtain Eigen values and Eigen vectors using iterative methods 6.Establish the homomorphism between vector spaces using Linear transform and obtain orthonormal basis and solve some application problems using the definition of inner product space

PART-A: Numerical Analysis

Unit I Approximation & Errors. Significant figures, Accuracy & precision. Round off & truncation errors. Numerical solution of equations – Fixed point iteration method false position method, Secant method, Newton - Raphson method, multiple roots. (SLE: Bisection, Graphical methods). 9 Hrs

Unit II Polynomials in Engineering & Science, Birge- Vieta method, Muller’s method, Horner’s method, Graeffe’s roots squaring method. Numerical differentiation (SLE: Applications to Engineering problems). 9 Hrs Unit III Numerical Integration – Newton cote’s quadrature formula. Trapezoidal rule (SLE: Simpson’s one third and three eighth’s rule), Boole’s rule, Weddle’s rule. Romberg integration.Numerical double integration.Gauss quadrature formulae -Gauss Legendre.Numerical solution of ODE – Taylor series method, Adam-Bashforth- Moulton method. (SLE: Runge-Kutta method of order IV). 8 Hrs


M.Tech - Industrial Automation & Robotics PART-B: Linear Algebra

Unit IV

Solution of system of linear algebraic equations, Triangularization method, Cholesky’s method, Partition method, Gauss Seidel iterative method. (SLE: Gauss elimination method). 9 Hrs

Unit V

Eigen values & Eigen vectors,Bounds on eigen values. Given’s method, Jacobi’s method for diagonalisation of symmetric matrices ,Rutishauser method for arbitrary matrices, Power method , Inverse power method. (SLE: Analytical method to obtain eigen values and eigen vectors) 9 Hrs Unit VI

Vectors & vector spaces, Linear Transformations - Kernel, Range.Matrix of linear transformation.Inverse linear transformation, Inner product, Length / Norm.Orthogonality, orthogonal projections.Orthonormalbases.Gram-Schmidt process.Least square problems. (SLE: Applications) 8 Hrs Books for Reference:

1.Introductory Methods of Numerical Analysis – S.S. Sastry, 5th edition. 2.Numerical Methods in engineering and science – B.S.Grewal ,Khanna Publications 8th

edition, 2009. 3.Higher Engineering Mathematics – Dr. B.V. Ramana,5th edition, Tata McGraw – Hil

publications. 4.Linear Algebra – Larson &Falvo (Cengage learning) 5.Numerical Methods – M.K. Jain S.R.K. Iyengar R.K. Jain, 2nd edition, New Age

International Pvt Ltd Publishers.



INDUSTRIAL AUTOMATION (4-2-0)

Sub Code: IAR0501 CIE: 50% Hrs/Week: 06 SEE: 50% SEEHrs:3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able:

1.To identify potential areas for automation and justify need for automation 2.To select suitable major control components required to automate a process or an

activity 3.To translate and simulate a real time activity using modern tools and discuss the

benefits of automation. 4.To identify suitable automation hardware for the given application. 5.To recommend appropriate modeling and simulation tool for the given manufacturing

application. Unit I Introduction: Automation in Production System, Principles and Strategies of Automation, BasicElements of an Automated System, Advanced Automation Functions, Levels of Automations. Flow lines & Transfer Mechanisms, Fundamentals of Transfer Lines. (SLE: Analysis of Transfer Lines) 8 Hrs Unit II Material handling and Identification Technologies: Overview of Material Handling Systems,Principles and Design Consideration, Material Transport Systems, Storage Systems, Overview of Automatic Identification Methods. (SLE: Material Identification Methods) 8 Hrs Unit III Automated Manufacturing Systems: Components, Classification and Overview ofManufacturing Systems, Manufacturing Cells, GT and Cellular Manufacturing, FMS, FMS and its Planning and Implementation.Quality Control Systems: Traditional and Modern Quality Control Methods, SPC Tools,Inspection Principles and Practices, Inspection Technologies. (SLE: Usage of SPC tools using excel or Minitab). 10 Hrs Unit IV Control Technologies in Automation: Industrial Control Systems, Process Industries VersusDiscrete-Manufacturing Industries, Continuous Versus Discrete Control, Computer Process and its Forms. (SLE: Sensors, Actuators and other Control System Components). 8 Hrs



Unit V Computer Based Industrial Control: Introduction & Automatic Process Control, Building Blocks of Automation Systems: LAN, Analog & Digital I/O Modules, SCADASystems& RTU. Distributed Control System: Functional Requirements, Configurations & some popularDistributed Control Systems. (SLE: Display Systems in Process Control Environment.) 8 Hrs

Unit VI Modeling and Simulation for Plant Automation: Introduction, need for system Modeling,Building Mathematical Model of a Plant, Modern Tools & Future Perspective. Industrial Control Applications: Cement, Thermal, Water Treatment & Steel Plants. (SLE: Cases Studies minimum one for Cement, Thermal, Water Treatment & Steel Plants applications) 10 Hrs

Text Books:

1. Automation, Production Systems and Computer Integrated Manufacturing- M.P.Groover, Pearson Education.5th edition, 2009.

References:

1. Computer Based Industrial Control- Krishna Kant, EEE-PHI,2nd edition,2010 2. An Introduction to Automated Process Planning Systems- Tiess Chiu Chang & Richard A. Wysk 3. Performance Modeling of Automated Manufacturing Systems,-Viswanandham, PHI, 1st edition,2009.



ROBOTICS FOR INDUSTRIAL AUTOMATION (4-2-0) Sub Code: IAR0502 CIE: 50% Hrs/Week:06 SEE: 50% SEEHrs:3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able:

1.To explain the basic principles of Robotic technology, configurations, control and programming of Robots.

2.Design an industrial robot which can meet kinematic and dynamic constraints. 3.To describe the concept of Robot kinematics and dynamics, latest algorithms &

analytical approaches 4.To discuss and apply the concepts of dynamics for a typical Pick and Place robot. 5.To choose the appropriate Sensor and Machine vision system for a given application. 6.To explain the basic principles of programming and apply it for typical Pick & place,

loading & unloading and palletizing applications.

Unit I Introduction: Automation and Robotics, Historical Development, Definitions, Basic Structureof Robots, Robot Anatomy, Complete Classification of Robots, Fundamentals about Robot Technology, Factors related to use Robot Performance, Basic Robot Configurations and their Relative Merits and Demerits, the Wrist & Gripper Subassemblies. Concepts about Basic Control System, ,Control Loops of Robotic Systems, Different Types of Controllers-Proportional, Integral, Differential, PID controllers. (SLE: Types of Drive Systems and their Relative Merits) 8 Hrs Unit II Kinematics of Robot Manipulator: Introduction, General Mathematical Preliminaries onVectors& Matrices, Direct Kinematics problem, Geometry Based Direct kinematics problem, Co-ordinate and vector transformation using matrices, Rotation matrix, Inverse Transformations, Problems, Composite Rotation matrix, Homogenous Transformations,, Robotic Manipulator Joint Co-Ordinate System, Euler Angle & Euler Transformations, Roll-Pitch-Yaw(RPY) Transformation. D H Representation & Displacement Matrices for Standard Configurations, Jacobian Transformation in Robotic Manipulation. (SLE: Geometrical Approach to Inverse Kinematics.) 10 Hrs Unit III Trajectory Planning: – Introduction, Trajectory Interpolators, Basic Structure of TrajectoryInterpolators, Cubic Joint Trajectories. General Design Consideration on Trajectories:- 4-3-4 & 3-5-3 Trajectories. (SLE: Admissible Motion Trajectories) 8 Hrs Department of Mechanical Engineering, NIE

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M.Tech - Industrial Automation & Robotics Unit IV Dynamics of Robotic Manipulators: Introduction,. Preliminary Definitions, GeneralizedRobotic Coordinates, Jacobian for a Two link Manipulator, Euler Equations, TheLagrangian Equations of motion. Application of Lagrange–Euler (LE) Dynamic Modeling of Robotic Manipulators: - Velocity of Joints, Kinetic Energy T of Arm, Potential Energy V of Robotic Arm, The Lagrange L, Two Link Robotic Dynamics with Distributed Mass. (SLE: Dynamic Equations of Motion for A General Six Axis Manipulator) 10 Hrs Unit V Robot Teaching: Introduction, Various Teaching Methods, Task Programming, Survey ofRobot Level Programming Languages, A Robot Program as a Path in Space, Motion Interpolation, WAIT, SIGNAL & DELAY Commands, Branching, Robot Language Structure, various Textual Robot Languages Such as VAL II, RAIL and their Features, Typical Programming Examples such as Palletizing, Loading a Machine Etc. (SLE: Survey of Robot level programming Languages ) 7 Hrs

Unit VI Robot Sensing & Vision: Various Sensors and their Classification, Use of Sensors and SensorBased System in Robotics, Machine Vision System, Description, Sensing, Digitizing, Image Processing and Analysis and Application of Machine Vision System, Robotic Assembly Sensors and Intelligent Sensors. Industrial Applications: Objectives, Automation in Manufacturing, Robot Application inIndustry, Task Programming,, Robot Intelligence and Task Planning, Modern Robots, Future Application and Challenges and Case Studies. (SLE: Goals of AI Research, AI Techniques) 9 Hrs Text Books:

1.Robotics, control vision and intelligence-Fu, Lee and Gonzalez. McGraw Hill International, 2nd edition, 2007. 2.Introduction to Robotics- John J. Craig, Addison Wesley Publishing, 3rd edition, 2010.

References:

1.Robotics for Engineers -YoramKoren, McGraw Hill International, 1st edition, 1985. 2.Industrial Robotics-Groover, Weiss, Nagel, McGraw Hill International, 2nd edition, 2012. 3.Robotic Engineering - An Integrated approach, Klafter, Chmielewski and Negin, PHI, 1st edition, 2009.



COMPUTER AIDED ENGINEERING (4-0-2)

SubCode: IAR0503 CIE: 50% Hrs/Week:06 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcomes: After the successful completion of this course, the student will be able:

1.To design and do manufacturing planning of mechanical system using state of the art CAD/ CAM and CAE tools and integrated database.

2.To create and manipulate 2D and 3D objects on graphic work station 3.To explain surface modeling and solid modeling and the use of application software

in designing mechanical systems 4.To use FEM in the design of mechanical system 5.To integrate technical skill with business activities of a company.

Unit I Computer Aided Design: Introduction, Conventional Approach to Design, Description of theDesign Process, Parametric and Variation Designs, Engineering Analysis and CAD, Compute Aided Engineering, Integrated Database Management System in CAE, CAE product Development, CAE implementation. (SLE: Simulation Based Design.) 8 Hrs Unit II Transformation and Manipulation of Objects: Introduction, Homogeneous Co-ordinatesystem, 2DTransformation-Translation, Scaling,Rotation,Mirroring,Reflection,Concatenation, , Manipulation of Simple Geometrical objects, Algorithms. (SLE: 3D Transformations) 8 Hrs

Unit III Curves and Surfaces: - Conic sections, Involutes, Cycloids, Spirals and other curves, Parametricequations- algorithms. Line Fitting, Non Linear Curve Fitting with a Power Function, Curve Fitting with a High Order Polynomial, Chebyshev Polynomial Fit. Cubic Splines, , Bezier Curves, B-Spline Curve, Surface creation, Plane Surface, Ruled Surface, Rectangular Surface, Surface of Revolution,. Solid Modeling: Introduction, Construction Techniques, Representation Schemes. (SLE: Application Software, Application of Solid Modeling.) 10 Hrs


M.Tech - Industrial Automation & Robotics Unit IV Finite Element Modeling and Analysis: Introduction, Basic Concepts in FEM, PotentialEnergy Formulation and Closed form Solution, Galerkin Method, Bar element: Introduction, FE formulation, Proprieties of the Local Stiffness Matrix, Global Stiffness Matrix, Solution of the Truss Problem (SLE: Weighted Residual Method.) 10 Hrs Unit V One Dimensional Heat Transfer: Introduction, Modes of Heat transfer, Governing equations,Finite element formulation, Conduction & Convection matrices & heat rate vectors. Heat transfer through Composite wall, Analysis of Fins. (SLE: Galerkin method) 9 Hrs Unit VI Advances in CAD/CAM: CIM, Architecture, Objectives, CIM Implementation, AgileManufacturing, Reverse Engineering, Concurrent Engineering, Rapid Prototyping, Virtual Manufacturing & Prototyping and Factory of the Future. (SLE: The Enterprise and Product Modeling) 7 Hrs

Note: Laboratory classes are conducted for duration of 2 hours per week

Text Books:

1. Principles of Computer Aided Design and Manufacturing- Farid Amirouche,2nd Edition, Pearson Prentice Hall, 2003 2. CAD/CAM Theory and Practice- Ibrahim-Zeid, TATA McGraw Hill, 2nd edition, 2009. 3. Introduction to Finite elements in Engineering – ChandruPatla&Belagundu, 3rd edition, 2009.

References:

1. CAD/CAM/CIM – P. Radhakrishnan, New age international, 3rd edition, 2007. 2. Finite Element procedure- Bathe, Eastern Economy Edition. PHI, 2009 3. Interactive Computer Graphics- Principles & Practice- Foley &Vandam, 2nd Edition, 2006 4. CAD/CAM - P.N.Rao, 3rd edition, 2010. 5. Computer graphics- Hearn Donald & Beaker, M.Pauline, PHI, 3rd edition, 2009.


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MODELING, SIMULATION AND ANALYSIS OF MANUFACTURING SYSTEMS (4-2-0)

Sub Code: IAR0508 CIE: 50% Hrs/Week: 06 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able to: 1. Describe a model and document a problem in preparation for the application of simulation solution techniques 2. Recognize, model, and analyze typical queueing scenarios 3. Develop and apply appropriate random number and random variable generation techniques 4. Analyze, model, and select appropriate input distributions and to explain simulation time advance mechanisms 5. Apply appropriate simulation statistical output techniques 6. Use the Arena simulation language to model and analyze problems found in industrial engineering practice and to design and analyze a simulation experiment Unit I Principles of Modeling & Simulation: Basic Simulation Modeling, When simulation is appropriate, When simulation is not appropriate, Advantages and disadvantages and pit falls of Simulation, Monte - Carlo Simulation, Areas of Applications, Discrete and Continuous Systems, Modeling of a system, Types of Models, Discrete event simulation. (SLE: Steps in simulation study) 10 Hrs

Unit II Modeling Approaches: Modeling Complex Systems, List processing in simulation, Simple simulation language, Single server queuing systems, Time shared computer model, Multiteller banking with jockeying, Job shop model. (SLE: Simulation Software) 8 Hrs Unit III Random Number Generation : Basic Probability and Statistics-Random variables and their properties, Properties of random numbers, generation of Pseudo random numbers, techniques for generating random numbers, Various tests for random numbers-frequency test, and test for Autocorrelation. (SLE: General procedure for hypothesis testing) 8Hrs


M.Tech - Industrial Automation & Robotics Unit IV Random Variate Generation: Introduction, different techniques to generate random variate: Inverse transform technique,-exponential, Normal, uniform, Weibull, direct transformation technique for normal and log normal distribution, convolution method and acceptance rejection techniques-Poisson distribution. Output Data Analysis for a single system: Types of simulation with respect to output analysis, transient and steady state behavior of a stochastic process. (SLE: statistical analysis for terminating simulation) 10 Hrs Unit V Statistical Techniques: Comparison of two system design, Comparison of several system design – Bonferroni approaches to multiple comparisons for selecting best fit, for screening, Variance reduction Techniques such as simple linear regression, multiple linear regression. (SLE: Optimization via simulation) 8 Hrs Unit VI Simulation Studies: Simulation of Inventory Problems,Discrete Event Simulation problems, Experimental Design and Optimization, 2k factorial designs, Simulation of Manufacturing Systems. (SLE:Case Studies) 8 Hrs Text Books:

1. Simulation, Modeling and Analysis –Averill Law & David M.Kelton, TMH, 4th Edition, 2007.

2. Discrete event and Simulation Systems – Banks & Carson, Prentice Hall Inc, 4th edition, 2011.

Reference Books:

1. System Simulation- Gordon, PHI, 2nd edition, 2009 2. Probability and statistics for engineers – Richard A. Johnson, Prentice hall, 7th edition,

2006.


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FINITE ELEMENT ANALYSIS (4-2-0) Sub Code: IAR0509 CIE: 50% Hrs/Week: 06 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able to: 1. Explain the concepts of Finite element analysis, matrix algebra and theory of elasticity. 2. Apply variational methods and solve problems in one dimensional and two dimensional analysis. 3. Apply various analytical methods such as Rayleigh-Ritz method, Galerkin method for solving cantilever beam problem and other structural problems. 4. Derive element stiffness matrix and apply the concept of numerical integration to solve different problems. 5. Solve problems in structural elements such as Trusses and Beams. 6. Undertake a project, create a mathematical model, analyze and address various issues pertaining to structures.

Unit I Calculus Of Variation: Introduction to Calculus of Variations, Introduction to EquilibriumEquations in Elasticity, Euler’s Langrange’s Equations, Principal of Virtual Work, Virtual Displacements, Principles of Minimum Potential Energy, Boundary Value, Initial Value Problems, Flexibility Approach, Different Problems in Structural Analysis. (SLE: Displacement Approach) 9 Hrs Unit II FEM Procedure: Derivation of FEM Equations by Variation Principle Polynomials, Concept ofShape Functions, and Derivation for Linear Simplex Element, Interpolation Polynomials in Global and Local Coordinates. (SLE: Need for Integral Forms) 7 Hrs Unit III Weighted Residual Methods: Concept of Weighted Residual Method, Derivation of FEMEquations by Galerkin’s Method, Solving Cantilever Beam Problem by Galerkin’s Approach, Derivation of Shape Functions for CST Triangular Elements, Shape Functions for Rectangular Elements, Shape Functions for Quadrilateral Elements. Higher Order Elements: Concept of Iso-Parametric Elements, Concept of Sub- Parametric andSuper –Parametric Elements. (SLE: Concept of Jacobian Matrix.) 10 Hrs


M.Tech - Industrial Automation & Robotics Unit IV Numerical Integration: Numerical Integration, One Point Formula and Two Point Formula for2D,Different Problems of Numerical Integration Evaluation of Element Stiffness Matrix, (SLE: Automatic Mesh Generation Schemes) 8 Hrs Unit V Pascal’s Triangle Law For 2D Shape Functions Polynomial, Pascal’s Triangle Law for 3DShape Function Polynomials, Shape Function for Beam Elements, Hermitian Shape Functions. Convergence: Convergence Criteria, Compatibility Requirements, Geometric IsotropyInvariance, Shape Functions for Iso-Parametric Elements, , Direct Method for Deriving Shape Functions using Langrage’s Formula, Plane Stress Problems.(SLE: Special Characteristics of Stiffness Matrix) 10 Hrs

Unit VI Analysis of Structures: Truss Elements, Analysis of Truss Problems by Direct StiffnessMethods, Analysis of Frames and Different Problems. (SLE: Different Axi-Symmetric Truss Problems.) 8 Hrs Text Books: 1.Finite Element Procedure- Bathe, PHI (EEE), 1st edition, 2009. 2.Finite Elements in Engineering – Chandrupatla, and Belagundu, Prentice Hall of India Pvt.

Ltd., New Delhi, 3rd edition, 2009.

References: 1. The Finite Element Method – O. C. Zienkiewicz, R. L. Taylor. , TMHl, New Delhi, 5th

edition, 2009 2. Concepts and Applications of Finite Element Analysis:- Cook.D Robert, Malus.S.David,

Plesha E. Michel , John Wilely& sons 3rdEdn., New York, 2000 3. Finite Element Analysis – C.S.Krishnamoorthy, TMH, New Delhi, 1995.



AUTOMATIC CONTROL SYSTEMS (4-2-0)

Sub Code: IAR0520 CIE: 50% Hrs/Week: 06 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able to: 1. An ability to apply knowledge of mathematics, science and engineering. 2. An ability to use the analysis and design tools of classical linear control. 3. An ability to use modern computer tools such as MatLab tools to solve control problems. 4. An ability to use appropriate method in various applications of control engineering aspects 5. An ability to understand various applications of control charts. Unit I Motivation for control. Review of differential equations, impulse response and Laplace transformations, Introduction to state equations and transfer functions. (SLE-linear systems, Definition of stability) 8 Hrs Unit II Interpretation of poles and zeros of transfer functions. Time domain response of second order system.Command tracking and system type.Rough/Hurwitz test. (SLE- Stability and performance specifications) 8 Hrs Unit III Frequency response and frequency domain methods.Nyquist stability test. Bode plots. Phase and gain margins. Bode phase formula. (SLE- Lead/lag compensation) 8 Hrs



Unit IV Robustness.Uncertainty and performance weights.Robust stability test.Robust performance test. Loop shaping necessary and sufficient conditions. Bode integral formula. (SLE- PID controllers) 8 Hrs Unit V Applications of Root locus, Sensitivity of roots of characteristics equation, Tool for design and analysis of control systems, Case studies using mat lab on Bode ,Nyquist and Root locus. (SLE- Applications of root locus) 6 Hrs Unit VI State variable analysis and design, Introduction, Concepts of state variables for linear discrete time systems, Diagonalization solutions of state equations, Concepts of controllability and observability, Pole placement by state feedback, Observer systems, problems. (SLE-Introduction to multivariable control) 6 Hrs Text Books:

1. Feedback Control of Dynamical Systems, 5th

Edition, Franklin, Powell, and Enami-Naeini, Addison-Wesley, 2006

2. Control Systems Engineering – I.J .Nagrath, M.Gopal, 5th Edition; New age International (P) Ltd, Publishers.

Syllabus taken from the reference link: http://www.aem.umn.edu/teaching/curriculum/syllabi/UGrad/AEM_4321_syllabus.shtml



KNOWLEDGE BASED DESIGN (4-0-0)

Sub Code: IAR0403 CIE: 50% Hrs/Week: 04 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100

Course Outcome: After the successful completion of this course, the student will be able: 1.To explain the concept of Artificial intelligence in CAD. 2.To apply the concept of knowledge representation and programming in an expert system. 3.To discuss the basic knowledge of decision support systems. 4.To apply the knowledge based design in a typical manufacturing system. 5.To develop problem solving skills through perceptron learning, competitive learning and

to generate genetic algorithms through artificial life and society based learning. 6.To design an expert system through Fuzzy logic and neural networks.

Unit I Introduction: Artificial Intelligence in Cad, Applications of Artificial Intelligence in Design.Scope and History of AI.Structure of an Expert System, Building an Expert System.Strategies for Knowledge Acquisition, Components of Knowledge. Knowledge Representation, Production Systems, Decision Tables, Frame Systems. (SLE -Graphs and Semantic Networks) 8 Hrs

Unit II Knowledge Representations: Knowledge Representations Process, Purposes, Contexts andAgents, Knowledge Soup, Knowledge Acquisition and Sharing. Knowledge Representation Languages, Issues in Knowledge Representation.A Network Representation Language. LISP: Introduction to LISP. Search Strategies in LISP, A Recursive Unification Function.Interpreters and Embedded Languages.Logic Programming in LISP.An Expert System Shell in LISP. (SLE-Streams and Delayed Evaluation) 10 Hrs Unit III Decision Support Systems: Introduction. Basis of Decision Making.TypicalProgressiveModels. Intelligent Models, Life-Cycle Values. Total Life-Cycle Cost. Compatibility Analysis.SensitivityAnalysis.Life-Cycle Ranking or Rating Scheme. (SLE -Smart Regenerative System) 8 Hrs Department of Mechanical Engineering, NIE

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M.Tech - Industrial Automation & Robotics Unit IV Learning Processes and AI Algorithms: The General Problem Solver and Difference Tables.Resolution Theorem Proving.Machine Learning, Perceptron Learning, Back Propagation Learning, Competitive Learning. The Genetic Algorithm: The Genetic Programming. Artificial Life and Society BasedLearning.Methods of Inference, Inexact Reasoning. (SLE -Reasoning under Uncertainty) 10 Hrs Unit V Knowledge Based Design Aids: Inference Process, Backward Chaining, Forward Chaining,Hybrid Chaining. Expert System Shells, Feature Based Modeling, Feature Recognition, Design by Features, Application of Feature Based Models. (SLE - Role of AI in Manufacturing) 8 Hrs Unit VI Design of Expert Systems and Applications: Benefits and Examples of Expert Systems.Design of Expert Systems, Introduction to CLIPS, Pattern Matching, Modular Design and Execution Control Fuzzy Logic , Typical Expert System MYCIN, DENDRAL, PROSPECTOR. (SLE - Neural Networks) 8 Hrs Text Books:

1. A guide to Expert Systems – Donald A Waterman, Addison Wesley, 1st edition, 2002. 2. Principles of Artificial Intelligence – Springer-Verlag, Berlin, paper back edition, 1982.

References: 1. Understanding Decision Support System and Expert Systems – McGraw Hill, 2nd edition, 1993. 2. Artificial Intelligence – Elain Rich, McGraw Hill, 3rd edition, 2010.



DYNAMICS AND MECHANISM DESIGN (4-0-0)

Sub Code: IAR0404 CIE:50% Hrs/Week: 04 SEE:50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able: 1.To explain the basics of mechanisms related to velocity and acceleration. 2.To apply the fundamental laws of motion to analyze the response of linear systems. 3.To explain the ‘D’Alemberts principle and apply lagrange equations for conservative and Non conservative systems.

4.To address the problems related to Holonomic and Non-Holonomic constraints. 5.To develop a mathematical program for intermittent rotary motion block synthesis and couplar curve synthesis using knowledge of complex algebra.

6.To discuss the special mechanisms applied to linkages. Unit I Geometry of Motion: Introduction, Analysis and Synthesis, Mechanism Terminology, Plane,Spherical and Spatial Mechanism, Mobility, Kinematic Inversion, Grashof’s Law, Mechanical Advantage, Couplar Curves, Velocity and Acceleration Analysis using Auxiliary Point Method, (SLE: Goodman Analysis) 8 Hrs Unit II Generalised Principles of Dynamics: Fundamental Laws of Motion Generalised Co-Ordinates,Holonomic& Non-Holonomic Constraints, Euler’s Equation of Motion. System Dynamics: Motion of Gyroscopes, Mechanical Transients, Response of Linear Systems to Transient Forcing Functions Phase Plane Methods (SLE: Phase PlaneRepresentation) 10 Hrs Unit III Lagrange’s Equation: Lagrange’s Equation ‘From D’ Alembert’s Principles, HamiltonPrinciples, Lagrange’s Equation from Hamilton Principle, Application of Lagrange Equation for Conservative. (SLE: Non Conservative system) 8 Hrs


M.Tech - Industrial Automation & Robotics Unit IV Autonomous Systems: Systems with Holonomic and Non Holonomic Constraints, Application to systems with very small displacements and to impulsive motion. Synthesis of linkages; Types, Numbers & Dimensional Synthesis Function Generation, Path.Generation and Body Guidance, Precision Point, Chebychev Spacing, Position Synthesis of General Slider – Crank Mechanism with Optimum Transmission Angle. Three Position Synthesis, Point Position Reduction. (SLE: Four Precision Points) 10 Hrs Unit V The Overlay Method: Couplar Curve Synthesis using Complex Algebra, Freudenstein’sEquation, Synthesis of Dwell Mechanism Intermittent Rotary Motion Block Synthesis. (SLE: Synthesis of Mechanical Error through Mathematical Programming.) 8 Hrs Unit VI Synthesis of Spatial Linkages: Introduction to Spatial Linkage, Special Mechanisms, ThePosition Problem, Position Analysis of the Rggr Mechanism, the Eulerian Angles, A Theorem on Angular Velocities and Acceleration. (SLE:Hook’s Universal Joint.) 8 Hrs Text Books:

1. Theory of Machines and Mechanisms-J.E. Shigley& J. J. Uicker, Internal student Edition McGraw Hill Co, 2009. 2. Kinematics and Dynamics of Plane mechanisms- J. Hirschior, McGraw Hill Co, 1st edition, 2012.

References:

1. Principles of Dynamics-Greenwood, Prentice Hall, 2nd edition, 1987. 2. Dynamics of Machinery-A. R. Holowenko, John Wiley and Sons, paper back edition. 3. Kinematics and Linkages Design-Hall.A.S., Prentice Hall, paper back edition.



PRODUCT DESIGN AND DEVELOPMENT (4-0-0)

Sub Code: IAR0405 CIE: 50% Hrs/Week: 04 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able:

1.To explain the design procedures involved in product development process. 2.To discuss the various methodologies involved in development of a product. 3.To implement the principles of product planning, Identify the customer needs and to formulate a procedure to fulfill the customer specifications.

4.To identify the problem, develop a new concept to understand the various steps involved in concept testing such as Survey population, measure customer response etc.

5.To define Product architecture, analyze the implication of the architecture, identify the need for Industrial design and discuss its implications.

6.To suggest the cost effective method for the estimation of manufacture cost, reduce the cost of components and also to create a prototype which meets the customer requirements.

Unit I Introduction: Characteristics of successful product development, Design and development ofproducts, duration and cost of product development, the challenges of product development. Development Processes and Organizations: A generic development process, conceptdevelopment: the front-end process, adopting the generic product development process, the AMF development process, product development organizations, the AMF organization. (SLE: Product Development Practices followed by different companies.) 8 Hrs Unit II Product Planning: The product planning process, identify opportunities. Evaluate and prioritizeprojects, allocate resources and plan timing, complete pre project planning, reflect all the results and the process. Identifying Customer Needs: Gather raw data from customers, interpret raw data in terms ofcustomer needs, organize the needs into a hierarchy, establish the relative importance of the needs and reflect on the results and the process. Product Specifications: What are specifications, when are specifications established,establishing target specifications, setting the final specifications. (SLE: Survey of FMCG products through questionnaire ) 10 Hrs Unit III Concept Generation: The activity of concept generation clarify the problem, search externally,search internally, explore systematically, reflect on the results and the process. Concept Selection: Overview of methodology, concept screening, and concept scoring,


M.Tech - Industrial Automation & Robotics Concept Testing: Define the purpose of concept test, choose a survey population, choose asurvey format, communicate the concept, measure customer response, interpret the result, reflect on the results and the process. (SLE: Pugh Selection for one problem solution) 8 Hrs Unit IV Product Architecture: What is product architecture, implications of the architecture,establishing the architecture, variety and supply chain considerations, platform planning, related system level design issues. Industrial design: Assessing the need for industrial design, the impact of industrial design, industrial design, process, managing the industrial design process, assessing the quality of industrial design. (SLE: Hand sketching / CAD model creation of the concept.) 10 Hrs Unit V Design for Manufacturing: Definition, estimation of manufacturing cost, reducing the cost ofcomponents, assembly, supporting production, impact of DFM on other factors. Prototyping: Prototyping basics, principles of prototyping, technologies, planning forprototypes. (SLE: Group exercise of one FDM prototype, Advantages & Limitations of rapid prototyping) 8 Hrs Unit VI Product Development Economics: Elements of economic analysis, base case financial mode,.Sensitive analysis, project trade-offs, influence of qualitative factors on project success, qualitative analysis. Managing Projects: Understanding and representing task, baseline project planning,accelerating projects, project execution, postmortem project evaluation. (SLE: Exercise of project planning and identification of critical path.) 8 Hrs Text books:

1. Product Design and Development- Karl.T.Ulrich, Steven D Eppinger, Irwin McGrawHill, 5th edition, 2011.

References:

1. Product Design and Manufacturing- A C Chitale and R C Gupta, PHI 3rd Edition, 2003.

2. New Product Development- Timjones. Butterworth Heinmann, Oxford. UCI. 1997 3. Product Design for Manufacture and Assembly-GeofferyBoothroyd, Peter Dewhurst

and Winston Knight, 3rd edition, 2010.


M.Tech - Industrial Automation & Robotics COMPUTER CONCEPTS FOR AUTOMATION (4-2-0)

Sub Code: IAR0521 CIE: 50% Hrs/Week: 06 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able to:

1.Analyze several key technologies used in manipulating, storing, and analyzing big data. 2.Acquire clear understanding of processing data 3.Acquire clear understanding of Hadoopmap reduce. 4.Categorize and Summarize Big Data and its importance. 5.Manage Big Data and analyze Big Data. 6.Apply tools and techniques to analyze Big Data.

Unit I Introduction to big data: Big Data and its Importance – Four V’s of Big Data – Drivers for Big Data –Introduction to Big Data Analytics – Big Data Analytics applications. Hadoop’s Parallel World – Data discovery – Open source technology for Big Data Analytics – cloud and Big Data –Predictive Analytics – Mobile Business Intelligence and Big Data – Crowd Sourcing Analytics – Inter- and Trans-Firewall, Analytics - Information Management. (SLE: Predictive Analytics) 9 hrs Unit II Processing big data: Integrating disparate data stores - Mapping data to the programming framework Connecting and extracting data from storage - Transforming data for processing - Subdividing data in preparation for Hadoop Map Reduce. (SLE: Data Preparation for Map Reduce) 9 hrs Unit III Hadoopmapreduce: Employing Hadoop Map Reduce - Creating the components of Hadoop Map Reduce jobs - Distributing data processing across server farms -Executing Hadoop Map Reduce jobs - Monitoring the progress of job flows - The Building Blocks of Hadoop Map Reduce - Distinguishing Hadoop daemons - Investigating the Hadoop Distributed File System Selecting appropriate execution modes: local, pseudo-distributed, fully distributed.


M.Tech - Industrial Automation & Robotics (SLE: Applications of HadoopMapreduce) 8hrs Unit IV Database Management System: Comparison of File System, Database Management System, Characteristic Features of Database Management Systems, Relational Databases. (SLE: Logical Database Design) 8 Hrs Unit V Data Base Models: DBMS Languages and Interfaces. Data Base Security and Authorization. (SLE: Data Ware House) 8 Hrs Unit VI Big data tools and techniques: Installing and Running Pig – Comparison with Databases – Pig Latin – User-Define Functions – Data Processing Operators – Installing and Running Hive – Hive QL – Tables – Querying Data – User-Defined Functions – Oracle Big Data. (SLE: Installing and Running Hive) 10 Hrs Text Books:

1. Fundamentals of DBMS – RamezElmasri and Navathe, Addison Wesley, 5th edition, 2009. 2. Michael Minelli, Michehe Chambers, “Big Data, Big Analytics: Emerging Business

Intelligence and Analytic Trends for Today’s Business”, 1st Edition, AmbigaDhiraj, Wiely CIO Series, 2013.

3. ArvindSathi, “Big Data Analytics: Disruptive Technologies for Changing theGame”, 1st Edition, IBM Corporation, 2012.

4. Bill Franks, “Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics”, 1st Edition, Wiley and SAS BusinessSeries, 2012.

5. Tom White, “Hadoop: The Definitive Guide”, 3rd Edition, O’reilly, 2012. References:

1. Introduction to DBMS – Date C.J, Addison Wesley, 3rd edition, 1981.



DRIVES AND CONTROL SYSTEMS FOR AUTOMATION (4-2-0)

Sub Code: IAR0505 CIE: 50% Hrs/Week:06 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able:

1. To understand working principles of various types of motors, differences, characteristics and selection criteria. 2. To apply the knowledge in selection of motors, heating effects and braking concepts in various industrial applications 3. To explain control methods of special drives 4. To elucidate various linear and rotary motion principles and methods and use the same to application areas 5. To carry out programming using PLC and use of various PLCs to Automation problems in industries. 6. To discuss supervisory control and data acquisition method and use the same in complex automation areas. 7. To understand and use logical elements and use of Human Machine Interfacing devices to enhance control & communication aspects of Automation.

Unit I Introduction: Working principle of synchronous, Asynchronous & stepper motors, Difference between Induction and servo motors, Torque v/s speed characteristics, Power v/s. Speed characteristics, Vector duty induction motors, Concepts of linear and frameless motors, Selection of feedback system, Duty cycle, , V/F control, Flux Vector control. (SLE: Current control (sensor less vector control) ) 8 Hrs Unit II Industrials Drives: DC and AC motors operation and selection, method of control and application of brushless DC motor, PMSM, stepper motor, A.C servomotor, selection criteria for servo motor and servo amplifier, universal motor, electric drive, types of industrial drives, the characteristics of drive, advantages of drives over other prime movers, motor rating, heating effects, electric braking, rheostatic and regenerative braking principles in power converters. (SLE: The Hydraulic Motor) 10 Hrs


M.Tech - Industrial Automation & Robotics Unit III Motion laws for rotary and linear systems: converting rotary to linear system, concepts and principles of ball screws, rack and pinion, belt and pulley, chain drives, gear drives, Selection of converting systems, Dynamic response gearing, and control approaches of Robots, Control loops using Current amplifier. (SLE:control loops Using Voltage Amplifier.) 8 Hrs Unit IV Introduction to Programmable Logic Controllers: Definitions of PLC, basic structure of PLC, working principles, data storage methods, inputs / outputs flag processing’s, types of variables, definition of firmware, software, programming software tool and interfacing with PC (RS232 & TCP-IP), methods of PLC programming (LD, ST, FBD & SFC), function blocks logical / mathematical operators & data types, array & data structure, PID, types of tasks and configuration, difference between relay logic and PLC, selection of PLC controller (case study) Centralized concept. (SLE: types of field bus systems) 8 Hrs Unit V Logic, instructions & Application of PLC: What is logic, Conventional Ladder v/s PLC ladder, series and parallel function of OR, AND, NOT logic, Ex Or logic, Analysis of rung. Timer and Counter Instructions; on delay and Off delay and retentive timer instructions, PLC counter up and down instructions, combining counters and timers, Comparison and data handling instructions, Sequencer instruction, Visualization Systems, Types of visualization system, PC based Controller, Applications of HMI’s, and Interfacing of HMI with controllers. (SLE: Programming of HMI and its implementation) 10 Hrs Unit VI Supervisory control & data Acquisitions: Introduction to Supervisory control & data Acquisitions, distributed Control System (DCS): computer networks and communication in DCS. different BUS configurations used for industrial automation – GPIB, HART and OLE protocol, Industrial field bus – FIP (Factory Instrumentation Protocol), PROFIBUS (Process field bus), Bit bus. Interfacing of SCADA with controllers, Basic programming of SCADA, SCADA in PC based Controller / HMI, (SLE: Case study & implementation for different examples.) 8 Hrs


M.Tech - Industrial Automation & Robotics Lab Exercises: PLC Programming exercises on PLC/ Drives & Control/ SCADA

1. Star-Delta - starting up 2. Road works traffic lights 3. Automatic tablet filler 4. Changing floor 5. Drilling tool 6. Pressing unit 7. Testing unit 8. Development &reliazation of SCADA programs

Text Books: 1.Process Control Instrumentation Technology, Johnson Curties, Prentice hall of India, 8th edition 2.Andrew Parr, Industrial drives, Butterworth – Heineamann 3.G.K.Dubey.Fundamentals of electrical drives 4.Programmable Logic Controllers by W.Bolton

References:

1.Introduction to Programmable Logic Controllers by Garry Dunning, 2nd edition, Thomson, ISBN:981-240-625-5 2.Instrumentation Engineers Hand Book - Process Control, Bela G Liptak, Chilton book company, Pennsylvania 3.A.E. Fitzerald ,C.Kingsley and S.D Umans, Electric Machinery - McGraw Hill Int. Student edition 4.S.K.Pillai. A First course on electric drives –Wiley Eastern 1990 5.Programmable Logic Controllers by Hugh Jack.



MICROPROCESSORS AND MICRO CONTROLLERS (4-0-2)

Sub Code: IAR0506 CIE: 50% Hrs/Week: 06 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able: 1. To explain the internal organization of some popular microprocessors/microcontrollers. 2. To analyze the instruction set of microprocessors/microcontrollers 3. To discuss hardware and software interaction and integration. 4. To explain the design of microprocessors/microcontrollers-based systems for industrial automation systems. 5. To demonstrate interfacing examples using 8051 microcontroller 6. To develop assembly language source code for applications that use I/O ports, timer and Single/multiple interrupts Unit I Introduction to Microprocessors: Introduction to Microprocessors, Microprocessor basedComputer Systems, Architecture of 8085, 8086 and Segmentation. (SLE: Memory Addressing.) 7 Hrs Unit II Microprocessors Assembly Language Programming: Addressing Modes of 8086, DataMovement Instructions. Instruction Encoding, Arithmetic and Logic Instructions.ProgrammingExamples.Machine Control and Miscellaneous Instructions. Hardware Feature Of 8086: Pin Outs and Pin Functions. Clock Generator, Bus Buffering,Latching and Timing Diagrams. (SLE: Ready and Wait State.) 11Hrs Unit III Interrupt Systems, Memory and I/O Interfacing In Microprocessors: Introduction toInterrupts, Interrupt related Instructions, Interrupt Processing, Memory Devices, Address Decoding, 8/16-Bit Memory Interfacing, DRAM Memory Systems. Introduction to I/O Interfacing.Memory Mapped and I/O Mapped I/O; Application examples related to Stepper Motor. (SLE: Temperature Control and Robot Control) 8 Hrs


M.Tech - Industrial Automation & Robotics Unit IV Introduction to Micro Controllers: Introduction, Comparing Microprocessors and MicroControllers, Z-80, 8051, PIC Micro Controllers, PIC Development Tools. The Micro Controller Survey, 4Bit, 8Bit, 16Bit And 32 Bit Micro Controllers. Develop Systems for Micro Controllers. Micro Controllers Architecture: 8051 Architecture, PIC Architecture, 8051 Micro ControllerHardware, Input/Output Pins, Ports and Circuits, External Memory, Counter and Timers, Serial Data Input/Output, (SLE:Interrupts ) 11 Hrs Unit V Basic Assembly Language Programming Concepts In Micro Controllers: The Mechanics OfProgramming, The Assembly Language Programming Process, PAL Instructions, Programming Tools and Techniques. Addressing Modes, Data Exchanges, Code Memory Read-Only Data Moves, Push Pop Op Codes, Logical Operators, Arithmetic Operators, Jump and Call Instructions. (SLE: Programming Concepts for 8051 and PIC.) 8 Hrs Unit VI Micro Controller Applications: Introduction, Key Boards, Displays, Pulse Measurement, D/A and A/D Conversions, Multiple Interrupts. (SLE: Programming the 8255) 7 Hrs Note: Laboratory classes are conducted for duration of 2 hours per week Text Books:

1.Advanced Microprocessors and IBM PC- K. Udaya Kumar & B.S. Umashankar , TMH, 1st edition, 1996.

2.Design with PIC and Micro controllers- John B Peatman, Pearson Education, 1st edition, 2001.

References:

1. The Intel Microprocessors-Barry .B.Brey, PHI, 8th Edition, 2008. 2. Microprocessors and Interfacing- Douglas V.Hall, McGraw Hill, 3rd edition, 2012. 3. Essentials of Assembly Language Programming -Rajaraman, Radhakrishna, PHI, 1st

edition, 2003.


Page 31


SENSORS APPLICATIONS IN MANUFACTURING (4-0-0)

Sub Code: IAR0406 CIE: 50% Hrs/Week: 04 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course outcome: After the successful completion of this course, the student will be able to: 1. To explain various signal condition devices used in electronic devises and use of appropriate method in signal conditions in various applications 2. Analyse and choose appropriate sensors in different industrial applications. 3. To describe the impact of an RFID system on manufacturing, defense, distribution, retail and health sectors 4. To describe the methods to abstract (“filter”) information in RFID and other sensor networks 5. To integrate various sensors in developing Flexible Manufacturing Systems. 6. To describe the future advances to the quality and integrity of Manufacturing and related sectors resulting from the use of RFID and other sensor technologies

Unit I Fundamentals of Sensors and Transducers: Performance terminology, static and dynamic characteristics of transducers, classification of sensors and transducers, signal processing and signal conditioning. Operational amplifiers, filters, protection devices, analog to digital converter, digital to anolog converter. (SLE: multiplexers and data acquisition systems) 8 Hrs

Unit II Sensors and their applications: Inductive, capacitive, magnetic, various types of photo sensors, detection methods, through-beam detection, reflex detection & proximity detection, ultrasonic and microwave sensors. Applications and understanding of the above sensors. (SLE: limit switches) 8 Hrs Unit III Advanced Sensor Technologies: Laser production, characteristics of lasers, types of laser sensors, bar code sensors, benefits of bar coding, transponder, RFID (Radio Frequency Identification), electro-magnetic identifier, optical encoders ,.color sensors, sensing principles, color theory, unit color measurement, colour comparator, color sensing algorithm, fuzzy logic color sensor. fuzzy logic for opt-electronic colour sensor in manufacturing. (SLE: advantages and disadvantages of optical encoders) 10 Hrs


M.Tech - Industrial Automation & Robotics Unit IV Sensors in Flexible Manufacturing Systems: Vision sensors, image transformations, robot visual sensing tasks, detecting partially visible objects, sensors in flexible manufacturing system cell. (SLE: edge detection and extraction.) 8 Hrs Unit V Sensors for Special Applications: A multi objective approach for selection of sensors in manufacturing, cryogenic manufacturing applications, semiconductor absorption sensors, semiconductor temperature detector using photoluminescence temperature detectors using point-contact, sensors in process manufacturing plants, measurement of high temperature, robot control through sensors, other sensors, collection and generation of process signals in decentralized manufacturing system. (SLE: noncontact Sensors (pyrometers) multi sensor applications) 10 Hrs

Unit VI Networking: Networking of sensors, control of manufacturing process, tracking- the mean time between operations interventions, tracking the yield and mean process time, detection of machining faults, diagnostic systems, resonance vibration analyzer, sensing motor current for signature analysis, temperature sensing. (SLE: acoustic sensing) 8 Hrs Note: Lab Exercises on Inductive, Capacitive, Magnetic, Photo& Ultrasonic Sensors in order to understand their characteristics. Text Books: 1. Sabnesoloman, sensors & control systems in manufacturing. Mc-Graw Hill book

Company Network, 1994. 2. Mechatronics by W,Bolton, References: 1. Sensor Technology Handbook by Jon S. Wilson 2. N.L.Buck&T.G.Buckwith, Mechanical measurement. 3. Sensors and Transducers by Ian Sinclair



COMPUTER AIDED PRODUCTION AND OPERATION MANAGEMENT (4-2-0)

Sub Code: IAR0522 CIE: 50% Hrs/Week: 06 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Out comes: After the successful completion of this course, the student will be able: 1.To explain production systems and their management 2.To solve inventory related problems in a manufacturing set up and suggest on controlling costs.

3.To map various process and production and product information and formulate a Master Production schedule using Computers.

4.To identify areas of improvement and implement JIT in a Manufacturing set up. Unit I Management of production systems:Production system and its management, Classical,Behavioural& quantitative management, Introduction to CAP-OM. (SLE: Tasks of a Production Manager) 6 Hrs Unit II Linear & Dynamic programming: Introduction, Canonical form of LP problems, Standardform of LP problems, Basic feasible Solution, The Simplex method of solution, Tabular method, Dynamic optimization models and programming. (SLE: Transportation and Assignment models) 10 Hrs Unit III Forecasting and Capacity planning: Forecasting and analysis, spreadsheet models, time seriesanalysis, simple moving average, weighted moving average, simple exponential smoothing, exponential smoothing and correction, linear regression, regression analysis and Delphi method. Capacity analysis basics, introduction to capacity planning methods, linear programming for aggregate planning, basics of facility layout methods.Introduction to Line Balancing, precedence requirements of operations, methods of solution, real life problem. (SLE: accuracy of forecasting) 10 Hrs


M.Tech - Industrial Automation & Robotics Unit IV Inventory systems: Basic inventory systems, parameters of an inventory policy, costs associatedwith inventory policy, deterministic inventory models, simple EOQ model. (SLE: model for finite production rate ) 10 Hrs Unit V MRP system: Master Production Schedule, Production scheduling and sequencing, MRPSystem, Computation in a MRP system, Information provided by the MRP system, ERP system. (SLE:Modules in an ERP system ) 8 Hrs. Unit VI Just in time manufacturing: Kanban system, Dual card Kanban, Number of KanbansImplementation of a JIT system. (SLE:Purchasing under JIT.) 8 Hrs Text Books: 1. Operations Management: A Quantitative Approach, P. B. Mahapatra, Published 2010 by

PHI Learning 2. Production Planning and Inventory Control, Narasimhan, McLeavey and Billington, PHI, 2nd edition, 2009. References:

1. Production/Operations Management- Elwood S Buffa, Wiley Eastern, 8th edition, 1987 publication. 2. Production and Operations Management- Concepts, Models and Behavior, Adam & Ebert, PHI, 5th edition, 2009.



RAPID PROTOTYPING (4-2-0)

Sub Code: IAR0523 CIE: 50% Hrs/Week: 06 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able: 1.To explain the various techniques of Rapid-prototyping. 2.To elucidate all phases of prototyping including modeling, tooling and process

optimization. 3.To describe the principles of Solid ground curing & LOM for a suitable operation. 4.To automate, optimize the process and enhance the performance of the system through

Concept modelers, Rapid tooling and Optimization skills. 5.To take up a project work, analyze, and identify the proper RP technique which meets the

requirements of the problem. 6. To apply the concept of Rapid-prototyping in fast growing industrial applications such as

automobile industry, aircraft industry, etc. Unit I Introduction: Need for the compression in product development, history of RP systems, Surveyof applications, Growth of RP industry, and classification of RP systems Stereo Lithography Systems: Principle, Process parameter, Process details, Data preparation,data files and machine details, (SLE: Application.) 7 Hrs Unit II Selective Laser Sintering and Fusion Deposition Modeling: Type of machine, Principle ofoperation, process parameters, Data preparation for SLS, Applications, Principle of Fusion deposition modeling, Process parameter. (SLE: Path generation, Applications) 11 Hrs Unit III Solid Ground Curing: Principle of operation, Machine details, Applications. Laminated Object Manufacturing: Principle of operation. Process details,application. (SLE: LOM materials) 8 Hrs


M.Tech - Industrial Automation & Robotics Unit IV Concepts Modelers: Principle, Thermal jet printer, Sander's model market.GenisysXs printer HP system 5, object Quadra systems. (SLE: 3-D printer) 7 Hrs Unit V Rapid Tooling:. Indirect Rapid tooling -Silicone rubber tooling –Aluminum filled epoxy toolingSpray metal tooling, Cast kirksite, 3Q keltool, etc Direct Rapid Tooling.,AIM, Quick cast process, Copper polyamide, Rapid Tool, DMILS, Prometal, Sand casting tooling, Laminate tooling. (SLE: Soft Tooling v/s hard tooling) 11 Hrs Unit VI RP Process Optimization: Factors influencing accuracy. Data preparation errors, Partbuilding errors, Error in finishing. (SLE: Influence of build orientation.) 8 Hrs Text books:

1. Stereo lithography and other RP & M Technologie- Paul F. Jacobs, SME, NY 1996. 2. Rapid Manufacturing- Flham D.T &DinjoyS.S ,Verlog London 2001. 3. Rapid automated- Lament wood, Indus press New York, 1st edition, 1993.

References:

1. Wohler's Report 2000- Terry Wohlers ,Wohler's Association, 2000.



MATHEMATICAL APPROACH TO ROBOTIC MANIPULATORS (4-2-0)

Sub Code: IAR0516 CIE: 50% Hrs/Week: 06 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able: 1. To explain the concepts of multifingered hands and dexterous manipulation. 2. To apply the rigid body transformations and lay basics of kinematics for redundant and parallel manipulators. 3. To explain the concepts of the open chain manipulators using Lagrange’s equations. 4. To address the issues regarding grasping using grasp planning and force closure analysis. 5. To solve simple problems on redundant and non manipulable systems using Kinematics and statics of Tendon actuation. 6. To describe the structure of non holonomic systems and understand the applications of robots in Hazardous environments and in medical applications. Unit I Introduction: Brief History, Multi-fingered Hands and Dexterous Manipulation. (SLE: Applications) 6 Hrs Unit II Rigid Body Motion: Rigid Body Transformations, Rotational Motion in R3,Rigid Motion in R3,and Velocity of a Rigid Body, Wrenches and Reciprocal Screws. Manipulator Kinematics: Introduction, Forward Kinematics, Inverse Kinematics, theManipulatorJacobian. (SLE: Redundant and Parallel Manipulators.) 10 Hrs Unit III Robot Dynamics and Control: Introduction, Lagrange’s Equations, and Dynamics of Open-Chain Manipulators, Lyapunov Stability Theory, Control of Constrained Manipulators. (SLE: Position Control and Trajectory Tracking) 10 Hrs


M.Tech - Industrial Automation & Robotics Unit IV Multifingured Hand Kinematics: Introduction to Grasping, Force-Closure, Grasp Planning,Grasp Constraints. (SLE: Rolling Contact Kinematics.) 8 Hrs Unit V Hand Dynamics and Control: Lagrange’s Equations with Constraints, Robot Hand Dynamics,Redundant and Nonmanipulable Robot Systems, Kinematics and Statics of Tendon Actuation, (SLE:Control of Robot Hands.) 9 Hrs Unit VI Nonholonomic Behavior in Robotic Systems: Introduction, Controllabity and Frobenius’Theorem, Examples of Nonholonomic Systems, Structure of Nonholonomic Systems. Future Prospects: Robots in Hazardous Environments, Medical Applications for MultifingeredHands, Robots on a Small Scale: (SLE:Microrobotics) 9 Hrs Text books:

1.A Mathematical Introduction to Robotic Manipulations- Richard M. Murray, Zexiang Li, S. Shankar Sastry CRC Press.Inc. 1st edition, 1994. 2.Dynamics and Control of Robot Manipulators-M. W. Spong and M. Vidyasagar. John Wile, 1st edition, 1989.

References:

1. Robot Analysis and Control-H. Asada and J.J.Slotine, Springer-Verlag, 1st edition, 1986. 2. Mechanism Design: Analysis and Synthesis-A.G. Erdman and G.N. Sandor, Prentice-Hall, 4th edition, 2001. 3. Fundamentals for Control of Robotic Manipulators- A.J. Koivo, Wiley, 1st edition, 1989. 4. Robotics, control vision and intelligence-Fu, Lee and Gonzalez. McGraw-Hill International, 1st edition, 2011.



ARTIFICIAL NEURAL NETWORKS & GENETIC ALGORITHMS (4-0-0)

Sub Code: IAR0407 CIE: 50% Hrs/Week: 04 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able: 1. To address the optimization issues in Image processing 2. To explain the application of computers for the generation of genetic Algorithm 3. To analyse performance of multilayer network 4. To explain how (recurrent) networks behave. 5. To Find a way to teach networks to do a certain computation (e.g. ICA) 6. To implement various application of artificial neural network and apply in desired application by computer Implantation of a generatic. Unit I Introduction: Inspiration from Neuroscience, History, Issues. Hopfield model: Associative memory problem, capacity ofstochastic n/w. (SLE: Model, stochastic networks) 8 Hrs Unit II Optimization problems: Weighted matching problem, Traveling salesman problem, Graphbipartioning, optimization problems in image processing Simple perceptrons: feed forward n/w, Threshold units, linear units, nonlinear units, stochasticunits. (SLE: capacity of simple perceptron.) 11 Hrs Unit III Multi-layer Network: Back propagation, examples & applications, performance of multilayerfeed forward Network, Cognitron&neocognitron. (SLE: Kohoanenself organizing network) 7 Hrs


M.Tech - Industrial Automation & Robotics Unit IV Recurrent Network: Boltzmann network, Recurrent Back-propagation, Learning timesequence, Reinforcement learning.– Supervised, Unsupervised (Hebbian/Competitive), Adaptive resonance theory. (SLE: Travelling salesman problem.) 11 Hrs Unit V Neural Network: Application of Artificial Neural Network. Genetic Algorithms: Mathematical Foundations. (SLE: Introduction) 8 Hrs Unit VI Computer Implentation of a Generatic Algorithm: Data Structures, Reproduction, Crossoverand Mutation, Mapping objective functions to fitness form, Codings, Discretization, Constraints. (SLE: Fitness scaling) 7 Hrs Text Books: 1. Introduction to the theory of Neural Computation - Hertz, Krogh, Palmer,1st edition,1991. 2. Artificial Neural Networks - B. Yegnanarayana (PHI),1st edition,2009. References: 1. Genetic Algorithms - David E. Goldberg ,Addison Wesley,1st edition,1989.



COMPUTER VISION & IMAGE PROCESSING (4-0-0)

Sub Code: IAR0408 CIE: 50% Hrs/Week: 04 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able:

1. Explain the applications of computer vision in automation. 2. Select the appropriate image processing technique for application. 3. Select the appropriate segmentation technique for the application. 4. Explain the importance of 3D reconstruction. 5. Explain the method of feature detection.

Unit I Introduction :What is computer vision? A brief history, Image formation , Geometric primitives and transformations , Photometric image formation , The digital camera . (SLE: Image compression) 8 Hrs Unit II Image processing: Point operators, Linear filtering, More neighborhood operators , Fourier transforms , Geometric transformations , Global optimization. (SLE: Image restoration) 8 Hrs Unit III Feature detection and matching : Points and patches , Feature detectors , Feature matching , Feature tracking , Edge detection , Edge linking , Lines, Successive approximation, Vanishing points . (SLE: Rectangle detection) 8 Hrs


M.Tech - Industrial Automation & Robotics Unit IV Segmentation :Active contours , Split and merge , Mean shift and mode finding , K-means and mixtures of Gaussians , Normalized cuts , Graph cuts and energy-based methods . (SLE: Medical image segmentation) 8 Hrs Unit V Stereo correspondence :Epipolar geometry, Sparse correspondence , Dense correspondence , Local methods , Global optimization , Multi-view stereo (SLE: Volumetric and 3D surface reconstruction) 8 Hrs Unit VI 3D reconstruction : Shape , Active rangefinding , Surface representations , Volumetric representations , Model-based reconstruction , Recovering texture maps . (SLE: 3D photography) 8 Hrs Text Books :

1.Computer Vision: Algorithms and Applications , Richard Szeliski , 2010 Springer Reference Books :

1. Computer Vision - A modern approach by D. Forsyth and J. Ponce, Prentice Hall 2. Robot Vision by B. K. P. Horn, McGraw-Hill.



ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS IN AUTOMATION (4-0-0)

Sub Code: IAR0409 CIE: 50% Hrs/Week: 04 SEE: 50% SEE Hrs: 3Hrs Max.Marks:100 Course Outcome: After the successful completion of this course, the student will be able: 1. Explain the applications of AI. 2. Select search strategies based on application requirement. 3. Explain the knowledge representation methods 4. Discuss the applications of uncertain knowledge and reasoning. 5. Discuss the architecture of expert systems

Unit I Artificial Intelligence: WhatisAI?, The Foundations of Artificial Intelligence , The History of Artificial Intelligence, Intelligent Agents: Agents and Environments, The Concept of Rationality, The Nature of Environments, The Structure of Agents. (SLE: State of the Art of AI applications) 8 Hrs Unit II Problem-solving: Problem-Solving Agents, Example Problems, Searching for Solutions, Uninformed Search Strategies, Breadth-first search, Uniform-cost search, Depth-first search, Depth-limited search, Iterative deepening depth-first search, Bidirectional search. Informed (Heuristic) Search Strategies, Greedy best-first search, A* search, Heuristic Functions, The effect of heuristic accuracy on performance. (SLE:Comparing uninformed search strategies) 8 Hrs Unit III Beyond Classical Search: : Local Search Algorithms and Optimization Problems, Hill-climbing search, Simulated annealing, Local beam search, Genetic algorithms, Local Search in Continuous Spaces, Searching with Nondeterministic Actions, Searching with Partial Observations, Online Search Agents and Unknown Environments.

(SLE: Simulated annealing) 8 Hrs


M.Tech - Industrial Automation & Robotics Unit IV

Knowledge Representation: Ontological Engineering, Categories and Objects, Events, Mental Events and Mental Objects,Reasoning Systems for Categories, Semantic networks, Description logics, Reasoning with Default Information, Truth maintenance systems.

(SLE: The Internet Shopping World) 8 Hrs Unit V Uncertain knowledge and reasoning: Quantifying Uncertainty, Acting under Uncertainty, Basic Probability Notation, Inference Using Full Joint Distributions, Bayes' Rule and Its Use, Probabilistic Reasoning, Representing Knowledge in an Uncertain Domain, The Semantics of Bayesian Networks, Exact Inference in Bayesian Networks, Approximate Inference in Bayesian Networks, Inference by Markov chain simulation, Relational and First-Order Probability Models.

(SLE: Other Approaches to Uncertain Reasoning) 8 Hrs Unit VI Probabilistic Reasoning over Time: Time and Uncertainty, Inference in Temporal Models, Hidden Markov Models, Kalman Filters, Dynamic Bayesian Networks, Keeping Track of Many Objects, Combining Beliefs and Desires under Uncertainty, The Basis of Utility Theory, Utility Functions, Multiattribute Utility Functions, Decision Networks, The Value of Information. Expert system architecture.

(SLE: Decision-Theoretic Expert Systems) 8 Hrs

Text Books:

1. Artificial Intelligence: A Modern Approach by StuartRussell and Peter Nowig, PEARSON 3rd ed. 2. A Guide to Expert Systems - Donald A Waterman, Addison Wesley,2nd edition,1986.

References:

1. Introduction to Artificial Intelligence and Expert Systems – DAN.W.Patterson, PHI, 2nd edition, 2009. 2. Artificial Intelligence- George.F.Luger, Pearson Education, Asia, 3rd Edition,2009. 3. Artificial Intelligence: An Engineering Approach- Robert J. Schalkeff, PHI, Second edition, 1990.


scheme of teaching and examination & syllabus · scheme of teaching and examination &...

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