karnatak law society’s gogte institute of technology

Karnatak Law Society’s

GOGTE INSTITUTE OF TECHNOLOGY

DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

M.Tech. (Computer Science and Engineering)

ELECTIVE – I

First Semester

S.No.

Course Code

Course Credits Total

credits Contact Hrs/wk

Marks

L - T - P CIE SEE TOTAL

1. 16SCS11 Big Data Management PC1 3 - 1 - 0 4 5 50 50 100

2. 16SCS12 Cloud Computing PC2 3 - 1 - 0 4 5 50 50 100

3. 16SCS13 Advanced Algorithm PC3 4 - 0 - 0 4 4 50 50 100

4. 16SCS14 Digital Image Processing PC4 3 - 1 - 0 4 5 50 50 100

5. 16SCS16X Elective – I PE- A 4 - 0 - 0 4 4 50 50 100

6. 16SCS16 Advanced Algorithms Lab 0 - 0 - 2 2 4 25 25 50

7. 16SCS17 Seminar-I 0 - 1 - 0 1 - 25 - 25

8. 16PTA18 Mini Project-I Mandatory 0 - 0 - 2 2 4 25 - 25

Total 25 31 325 275 600

16SCS161 Analysis of Computer Networks

16SCS162 Multi Core Architecture and Programming

16SCS163 Data Mining & Warehousing

16SCS164 Programming with Python

First Semester

Big Data Management

Subject Code 16SCS11 Credits 4

Course Type PC1 CIE Marks 50

Hours/Week: L-T-P 3-1-0 SEE Marks 50

Total Hours 40 SEE Duration 3 Hours for 100 marks

Course Objectives:

1. To understand big data dimensions and its applications. 2. To understand NoSQL big data management. 3. To become aware of the Map Reduce paradigm and the Hadoop framework. 4. To explore various Big Data Tools and Technologies.

Prerequisite:

1. Database Management System

2. Basic Commands of UNIX Operating System

Detailed Syllabus:

Unit I 08 Hours

Understanding Big Data: What is big data? : Characteristics of Big Data, Data in the Warehouse and Data in Hadoop; Why is Big Data Important? : When to consider a Big Data solution? Big Data Use Cases: IT log analytics, Fraud detection, Social Media, Risk Management and Energy Sector. Patterns for Big Data Deployment. Big Data Frameworks: Hadoop, Spark, Flink , Storm. Big Data Challenges.

Unit II 08 Hours

NoSQL Data Management: Introduction to NoSQL – aggregate data models – aggregates –

key-value and document data models – relationships – graph databases – schema less

databases – materialized views – distribution models – sharding – master-slave replication –

peer-peer replication – sharding and replication – consistency – relaxing consistency – version

stamps.

Self-Study: Map-reduce partitions and combining-composing map-reduce calculation.(2hours)

Unit III 08 Hours

Basics of Hadoop: The History of Hadoop, Components of Hadoop, Application

Development in Hadoop, Getting your data into Hadoop, Other Hadoop Components

Data format – analyzing data with Hadoop – scaling out – Hadoop streaming –

Hadoop pipes. Design of HDFS

Self-Study: HDFS concepts-Java interface. (2hours) 02 Hours

Unit IV 08 Hours

Mapreduce Applications: MapReduce workflows – unit tests with MRUnit – test data and local tests – anatomy of MapReduce job run – classic Map-reduce – YARN – failures in classic Map-reduce and YARN – job scheduling – shuffle and sort – task execution – MapReduce types – input formats – output formats.

Unit V 08 Hours

Hadoop Related Tools Pig – Grunt – pig data model – Pig Latin – developing and testing Pig

Latin scripts. Hive – data types and file formats – HiveQL data definition –HiveQL data

manipulation – HiveQL queries.

Self-Study: Hbase –data model and implementations- Hbase clients –Hbase examples,

Cassandra –Cassandra data model –Cassandra examples-Cassandra clients-Hadoop

integration. (2hours)

Course Outcomes (COs):

The students should be able to:

1. Describe big data and use cases from selected business domains [L1].

2. Justify use of data model in Big-Data[L5].

3. Install, Configure, and run Hadoop and DFS[L3].

4. Demonstrate working of map-reduce using Hadoop map [L3].

5. Demonstrate Hadoop related tools such as Pig and Hive for big data

analytics[L3]

Programme Outcomes (POs):

1. Graduates will demonstrate the knowledge of mathematics, logical reasoning

and engineering [PO1].

2. Graduates will demonstrate the ability to identify, formulate and solve

computer systems engineering problems [PO2].

3. Graduate will be capable of pursuing research in their field of interest [PO11].

Text Books:

1. Paul C. Zikopoulos, Chris Eaton, Dirk deRoos, Thomas Deutsch, George Lapis, Understanding Big Data – Analytics for Enterprise Class Hadoop and Streaming Data, McGraw Hill, 2012

2. P. J. Sadalage and M. Fowler, "NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence", Addison-Wesley Professional, 2012.

3. Tom White, "Hadoop: The Definitive Guide", Third Edition, O'Reilly, 2012.

4. Eric Sammer, "Hadoop Operations", O'Reilly, 2012.

References:

1.Vignesh Prajapati, Big data analytics with R and Hadoop, SPD 2013.

2. E. Capriolo, D. Wampler, and J. Rutherglen, "Programming Hive", O'Reilly, 2012.

3. Lars George, "HBase: The Definitive Guide", O'Reilly, 2011.

4. Alan Gates, "Programming Pig", O'Reilly, 2011.

Scheme of Continuous Internal Evaluation (CIE):

The Total marks of CIE shall be 50 (three tests of 30 marks each, two Assignments of 10 marks each

and quiz/course seminar/course project of 10 marks each). The weight-age of CIE is as shown in the

table below.

Component Average of

best 2 Tests

Test-2

Average of 2

Assignments

Quiz/Seminar/

Project

Total

Marks

Maximum marks

30 10 10 50

Scheme of Semester End Examination (SEE):

1. It will be conducted for 100 marks of 3 hours duration. It will be reduced to 50 marks for the calculation of SGPA and CGPA.

2. Question paper contains 08 questions each carrying 20 marks. Students have to answer FIVE full questions. SEE question paper will have two compulsory questions (any 2 units) and choice will be given in the remaining three units. ( Kindly incorporate / mention the changes in the pattern of SEE question paper, if required, based on the content of course)

First Semester

Cloud Computing





COURSE OBJECTIVES

1. To learn how to use Cloud Services. 2. Apply Map-Reduce concept to applications. 3. To understand role of Virtualization in enabling Cloud Computing. 4. To implement Task Scheduling algorithms. 5. To build Private Cloud.

Prerequisite:

1. Operating system

2. Computer Networks.

3. Multi core Architecture.

Detailed Syllabus:

Unit I 8 Hours

Evolution of Computing, Cloud Computing Basics

Introduction to Mainframe architecture; Client-server architecture; Cluster Computing; Grid

Computing; Parallel Computing and Distributed Computing; Evolution of sharing on the Internet;

Utility Computing; Autonomic Computing; Cloud Computing; Introduction of Cloud Computing;

Service Models; Deployment Models; Reference Architectures; Understanding Distributed

Application Design, Virtualized Computing Environments, High-Performance Computing Models;

Role of virtualization in enabling the cloud; Anatomy of Cloud

Unit II 8 Hours

Cloud Computing: Application Paradigms.

Challenges of cloud computing, Architectural styles of cloud computing, Workflows: Coordination of multiple activities, Coordination based on a state machine model: The Zookeeper, The Map Reduce programming model, A case study: The Grep The Web application, Cloud for science and engineering, High-performance computing on a cloud, Cloud computing for Biology research, Social computing, digital content and cloud computing.

Self-Study: The grep the web application 2 Hours

Unit III 8 Hours

Cloud Architecture and Programming Model

Cloud Storage and Standards; Three Layered Architectural Requirement; Service Centric Issues: Interoperability and QoS; Fault Tolerance; Data Management Storage and Processing; Understanding Model View Controller (MVC); Mobile application development – Android, iOS; integration with third party API; Parallel and Distributed Programming Paradigms: Map Reduce ,Twister and Iterative; MapReduce.Mapping Applications and Programming Support: Google App Engine, Amazon AWS - Cloud Software Environments -Eucalyptus, Open Nebula, OpenStack, Aneka, CloudSim.

Self-Study: Cloud software environments eucalyptus open stack. 2 Hours

Unit IV 8 Hours

Virtualization and Data Center: Backbone of Cloud Computing

Basics and Types of Virtualization; Evolution of Data Centers:Types of Storage; distributed file systems ; Object Storage; Benefits and types of Storage Virtualization; Networking and Storage in Enterprise Virtualized Environments; Virtual machine monitors,Virtual Machines, Performance and Security Isolation, Full virtualization and paravirtualization, Hardware support for virtualization, Case Study:Xen a VMM based paravirtualization, Optimization of network virtualization, vBlades, Performance comparison of virtual machines. The dark side of virtualization, Exercises and problems.

Self-Study: Case study of optimization of network virtualization & VBlades performance comparison of virtual machines. 2 Hours

Unit V 8 Hours

Cloud Resource Management and Scheduling.

Policies and mechanisms for resource management, Application of control theory to task scheduling on a cloud, Stability of a two level resource allocation architecture, Feedback control based on dynamic thresholds, Coordination of specialized autonomic performance managers, A utility based model for cloud based Web services, Resourcing bundling: Combinatorial auctions for cloud resources, Scheduling algorithms for computing clouds, Fair queuing, Start-time fair queuing, Borrowed virtual time, Cloud; scheduling subject to deadlines, Scheduling Map Reduce applications subject to deadlines, Resource management and dynamic scaling, Exercise sand problems.

Self-Study: Performance analysis of various resource scheduling algorithms using CloudSim simulator. 2 Hours



1. Demonstrate and experiment simple Cloud Applications. [L3]

2. Apply Map-Reduce concept. [L3]

3. Analyze resource allocation and scheduling algorithms in cloud computing. [L3]

4. Create virtual machines from available physical resources. - Setup a private cloud. [L6]

Programme Outcomes (POs)

1. Graduates will demonstrate the knowledge of mathematics, logical reasoning and engineering

[PO1].

2. Graduates will demonstrate the ability to identify, formulate and solve computer systems

engineering problems [PO2].


Text Books: 1. Dan C Marinescu: Cloud Computing Theory and Practice. Elsevier (MK) 2013.

Reference Books:

1. Rajkumar Buyya, James Broberg, Andrzej Goscinski: Cloud Computing Principles and Paradigms, Willey 2014.

2. John W Rittinghouse, James FRansome: Cloud Computing Implementation, Management and Security, CRC Press 2013.




table below.


best 2 Tests

Average of 2

Assignments

Quiz/Seminar/

Project

Total

Marks

Maximum marks

Marks

30 10 10 50




First Semester

Advanced Algorithms





Course Objectives 1. To review various techniques for analysis of algorithms. 2. To study graph search algorithms. 3. To gain an understanding of Number Theoretic Algorithms 4. To learn algorithms for matching strings 5. To get an awareness of polynomial algorithms and study probabilistic and

randomized algorithms

Prerequisite: 1. Design and Analysis of Algorithms

Detailed Syllabus: Unit I 10 Hours

Review of Analysis Techniques: Growth of Functions: Asymptotic notations; standard notations and common functions; Recurrences and Solution of Recurrence equations- The substitution method, The recurrence – tree method, The master method; Amortized Analysis:

Aggregate, Accounting and Potential Methods.

Unit II 10 Hours

Graph Algorithms: Bellman - Ford Algorithm; Single source shortest paths in a DAG; Johnson’s Algorithm for sparse graphs; Flow networks and Ford-Fulkerson method; Maximum bipartite matching.

Unit III 10 Hours

Number -Theoretic Algorithms: Elementary notions; GCD; Modular Arithmetic; Solving modular linear equations; The Chinese remainder theorem; Powers of an element; RSA cryptosystem; Primality testing; Integer factorization.

Unit IV 10 Hours

String-Matching Algorithms: Naïve string Matching; Rabin - Karp algorithm; String matching

with finite automata; Knuth-Morris-Pratt algorithm; Boyer – Moore algorithms.

Unit V 10 Hours

Probabilistic and Randomized Algorithms: Probabilistic algorithms; Randomizing deterministic

algorithms, Monte Carlo and Las Vegas algorithms; Probabilistic numeric algorithms.


Upon completion of the course, the students will be able to

1. Analyze the complexity of a given algorithm by applying algorithm analysis technique.[L4] 2. Demonstrate the working of shortest path algorithms on directed graphs. [L3] 3. Compute modulo inverse of a given number using extended Euclid technique. [L3] 4. Design & demonstrate an algorithm to test the primality with lowest probability of error.

[L6] 5. Design an efficient string search algorithm & demonstrate its working. [L6]


1. Graduates will demonstrate the knowledge of mathematics, logical reasoning and

engineering[PO1]

2. Graduates will demonstrate the ability to identify, formulate and solve computer systems

engineering problems[PO2]

3. Graduates will demonstrate an ability to analyze the given problems and design solutions, as

per the needs and specifications[PO4]

Text Books:

1. T. H Cormen, C E Leiserson, R L Rivest and C Stein: Introduction to Algorithms, 3rd Edition, Prentice-Hall of India, 2010.

2. Kenneth A. Berman, Jerome L. Paul: Algorithms, Cengage Learning, 2002.

Reference Books:

1. Ellis Horowitz, Sartaj Sahni, S.Rajasekharan: Fundamentals of Computer Algorithms, 2nd Edition, Universities press, 2007.

2. Anany Levitin, Introduction to the Design & Analysis Of Algorithms 2nd Edition, Pearson, 2009




table below.


best 2 Tests

Test-2

Average of 2

Assignments

Quiz/Seminar/

Project

Total

Marks

Maximum marks

30 10 10 50



Question paper contains 08 questions each carrying 20 marks. Students have to answer FIVE full

questions. SEE question paper will have two compulsory questions (any 2 units) and choice will be

given in the remaining three units. ( Kindly incorporate / mention the changes in the pattern of SEE

question paper, if required, based on the content of course)

First Semester

Digital Image Processing


Course Type PC CIE Marks 50


Total Hours 40+6 SEE Duration 3 Hours for 100 marks

Course objectives:

1. To understand the importance and applications of Digital Image Processing. 2. To understand the image representation and image formation in Gray and Color. 3. To understand the image fundamentals and mathematical transforms necessary for image

processing and study the image enhancement techniques. 4. To introduce the various image processing techniques in spatial and frequency domains 5. To introduce the techniques of transforms, morphological processing and image

segmentation. Prerequisites:

1. Basics of Mathematical Analysis, Vectors, Matrices 2. Probability & Statistics 3. Computer Programming.

Detailed Syllabus:

Unit I 8 Hours

Introduction: What is Digital Image Processing, origins of digital image processing, examples of fields that use DIP., fundamental steps in digital image processing, components of a digital processing system. Digital Image Fundamentals: Elements of visual perception, a simple image formation model, basic steps in image Sampling and Quantization, representing digital images, zooming and shrinking of digital images, some basic relationships between Pixels, Linear and Non-linear operations.

Unit II 8 Hours Image Enhancement in the Spatial Domain: Some Basic Gray Level Transformations, Histogram Processing, Enhancement Using Arithmetic/Logic Operations, Basics of Spatial Filtering, Smoothing Spatial Filters, Sharpening Spatial Filters. Image Enhancement in the Frequency Domain: Introduction to the Fourier Transform and the Frequency Domain, Smoothing Frequency-Domain Filters, Sharpening Frequency-Domain Filters. Unit III 8 Hours Image Restoration: A Model of the Image degradation/Restoration process, Noise Models, Restoration in the Presence of Noise Only–Spatial Filtering. Self Study: Component: Estimating the degradation function 2 Hours

Unit IV 8 Hours Image Transforms: Introduction, Need for transforms, Classification of Image transforms, 2D DCT, Walsh transform, Hadamard Transform, HAAR transform. Unit V 8 Hours Morphological Image Processing: Preliminaries, Dilation and Erosion, Opening and Closing, Hit-or-Miss Transformation, Some Basic Morphological Algorithms, namely Boundary Extraction, Region Filling . Self Study: Component: Image Segmentation: Detection of Discontinuities, Edge Linking and Boundary Detection 2 Hours

Course Outcomes (COs): The students will be able to:

1. Explain the importance of DIP and its applications [L1]. 2. Explain the image formation and representation of digital images [L1]. 3. Apply the spatial and frequency domain image processing techniques [L3]. 4. Implement noise reduction and morphological techniques [L3]. 5. Explain the image segmentation methods [L1].


1. Graduates will demonstrate the knowledge of mathematics, logical reasoning and engineering[PO1]

2. Graduates will demonstrate the ability to identify, formulate and solve computer systems engineering problems[PO2]

3. Graduate will be capable of pursuing research in their field of interest.[PO11]

Text Books: 1. Rafael C. Gonzalez and Richard E. Woods: Digital Image Processing PHI 2nd Edition 2005. 2. S. Jayaraman S. Esakkirajan, T.Veerakumar: Digital Image Processing, McGraw Hill Ed.

(India) Pvt. Ltd. 2013.

References: 1. A.K.Jain: Fundamentals of Digital Image Processing Pearson, 2004.

2. Scott E. Umbaugh: Digital Image Processing and Analysis, CRC Press, 2014. Scheme of Continuous Internal Evaluation (CIE):



table below.


best 2 Tests

Test-2

Average of 2

Assignments

Quiz/Seminar/ Project

Total Marks

Maximum marks

Marks

30 10 10 50



First Semester

Advanced Algorithms Lab


Course Type PC CIE Marks 50


Total Hours 50 SEE Duration 3

Course Objectives:

1. To Implement the graph search algorithms

2. To Implement the string matching algorithms

3. To implement the modular linear equation algorithms.

LABORATORY WORK

1. Design & implement Euclid and Extended Euclid algorithm to find GCD of 2 numbers.

2. Implement the Bellman-ford algorithm and determine its performance. Give its

application.

3. Implement a Monte Carlo algorithm to test the primality of a given integer and

determine its performance.

4. To solve string matching problem using naïve approach and the KMP algorithm.

Compare their performance.

5. Design and implement Finite State Machine based String search algorithm and

compare its performance with Naïve Search technique.

6. To solve string matching problem using Robin Karp algorithm and determine its performance.


At the end of the course, students will be able to,

1. Design and demonstrate working of graph search algorithm. [L6]

2. Design and implement string matching algorithms. [L6]

3. Design modular linear and equation algorithms. [L6]

4. Demonstrate the application RSA algorithm. [L6]

Programme Outcomes (POs)

1. Graduates will demonstrate the knowledge of mathematics, logical reasoning and engineering[PO1]

2. Graduates will demonstrate the ability to identify, formulate and solve computer systems engineering problems[PO2]

3. Graduates will demonstrate an ability to analyze the given problems and design solutions, as per the needs and specifications[PO4]


The total marks of CIE shall be 25. The weight-age of CIE is as shown in the table below.

Component Lab Attendance Lab Journal Internal Lab test Total Marks

Max. Marks 5 10 10 25

Scheme of semester-end Examination (SEE):

Semester end examination will be conducted for 50 marks which will be converted to into 25

marks.

First Semester

Analysis of Computer Networks


Course Type PE-A CIE Marks 50



Course Objectives:

1. To learn the different ways of analyzing the computer networks 2. To learn the quantitative modeling of telecommunication networks. 3. To understand the network performance and measure the various network parameters.

Prerequisite:

1. Concepts of Computer Networks & it’s Protocols

Detailed Syllabus:

Unit I 10 Hours

Introduction: Two examples of analysis: Efficient transport of packet voice calls, Achievable

throughput in an input-queuing packet switch; The importance of quantitative modeling in the

Engineering of Telecommunication Networks.

Unit II 10 Hours

Multiplexing: Network performance and source characterization; Stream sessions in a packet

network: Delay guarantees; Elastic transfers in a packet network; Packet multiplexing over Wireless

networks.

Unit III 10 Hours

Stream Sessions: Deterministic Network Analysis: Events and processes in packet multiplexer

models: Universal concepts; Deterministic traffic models and Network Calculus; Scheduling;

Application to a packet voice example; Connection setup: The RSVP approach; Scheduling

(continued).

Unit IV 10 Hours

Stream Sessions: Stochastic Analysis: Deterministic analysis can yield loose bounds; Stochastic traffic

models; Additional notation; Performance measures; Little’s theorem, Brumelle’s theorem, and

applications; Multiplexer analysis with stationary and ergodic traffic; The effective bandwidth

approach for admission control; Application to the packet voice example; Stochastic analysis with

shaped traffic; Multi-hop networks; Long-Range-Dependent traffic.

Unit V 10 Hours

Adaptive Bandwidth Sharing for Elastic Traffic: Elastic transfers in a Network; Network parameters

and performance objectives; Sharing a single link; Rate-Based Control; Window-Based Control:

General Principles; TCP: The Internet’s Adaptive Window Protocol; Bandwidth sharing in a Network.


The students will be able to:

1. Analyze the different types of networks considering the parameters such as throughput, bandwidth utilization, packet loss etc [L3].

2. Design network analysis tool for given network [L6]. 3. Experiment with networks using network simulation tools [L3].


1. Graduates will demonstrate the knowledge of mathematics, logical reasoning and engineering [PO1].

2. Graduates will demonstrate the ability to identify, formulate and solve computer systems engineering problems [PO2].


Text Books:

1. Anurag Kumar, D. Manjunath, Joy Kuri: Communication Networking An Analytical Approach,

Elsevier, 2004.

References:

1. M. Schwartz: Broadband Integrated Networks, Prentice Hall PTR, 1996. 2. J. Walrand, P. Varaiya: High Performance Communication Networks, 2nd Edition, Morgan

Kaufmann, 1999.




table below.


best 2 Tests

Test-2

Average of 2

Assignments

Quiz/Seminar/ Project

Total Marks

Maximum marks

Marks

30 10 10 50





First Semester

Multi-Core Architecture and Programming





Course Objectives:

1. To understand the recent trends in the field of computer architecture and identify performance related parameters.

2. To study the concepts of parallel programming. 3. To understand the concepts of multi threading and OPENMP. 4. To analyze the solutions to Common Parallel Programming Problems.

Prerequisite:

1. Computer Organization

2. Operating System

3. Advanced computer Architecture

Detailed Syllabus:

Unit I 10 Hours

Introduction to Multi-core Architecture: Motivation for Concurrency in software,

Parallel Computing Platforms, Parallel Computing in Microprocessors, Differentiating

Multi-core Architectures from Hyper- Threading Technology, Multi-threading on Single-

Core versus Multi-Core Platforms Understanding Performance, Amdahl’s Law,

Growing Returns: Gustafson’s Law. System Overview of Threading: Defining Threads,

System View of Threads, Threading above the Operating System, Threads inside the OS,

Threads inside the Hardware, What Happens When a Thread Is Created, Application

Programming Models and Threading, Virtual Environment: VMs and Platforms,

Runtime Virtualization, System Virtualization.

Unit II 10 Hours

Fundamental Concepts of Parallel Programming: Designing for Threads, Task

Decomposition, Data Decomposition, Data Flow Decomposition, Implications of

Different Decompositions, Challenges You’ll Face, Parallel Programming Patterns, A

Motivating Problem: Error Diffusion, Analysis of the Error Diffusion Algorithm, An

Alternate Approach: Parallel Error Diffusion, Other Alternatives.

Unit III 10 Hours

Threading and Parallel Programming Constructs: Synchronization, Critical Sections,

Deadlock, Synchronization Primitives, Semaphores, Locks, Condition Variables,

Messages, Flow Control- based Concepts, Fence, Barrier, Implementation-dependent

Threading Features. Threading APIs, Threading APls for Microsoft Windows, Win32/MFC

Thread APIs, Threading APIs for Microsoft. NET Framework, Creating Threads,

Managing Threads, Thread Pools, Thread Synchronization, POSIX Threads, Creating

Threads, Managing Threads, Thread Synchronization, Signaling, Compilation and Linking.

Unit IV 10 Hours

OpenMP: A Portable Solution for Threading: Challenges in Threading a Loop, Loop-

carried Dependence, Data-race Conditions, Managing Shared and Private Data, Loop

Scheduling and Portioning, Effective Use of Reductions, Minimizing Threading

Overhead, Work-sharing Sections, Performance-oriented Programming, Using Barrier

and No wait, Interleaving Single-thread and Multi-thread Execution, Data Copy-in and

Copy-out, Protecting Updates of Shared Variables, Intel Task queuing Extension to

OpenMP, OpenMP Library Functions, OpenMP Environment Variables, Compilation,

Debugging, performance.

Unit V 10 Hours

Solutions to Common Parallel Programming Problems: Too Many Threads, Data Races,

Deadlocks, and Live Locks, Deadlock, Heavily Contended Locks, Priority Inversion,

Solutions for Heavily Contended Locks, Non-blocking Algorithms, ABA Problem, Cache

Line Ping-ponging, Memory Reclamation Problem, Recommendations, Thread-safe

Functions and Libraries, Memory Issues, Bandwidth, Working in the Cache, Memory

Contention.

A Case Study: Threading on Intel Multi-core Processors.



1. Identify the limitations of ILP and the need for multi-core architectures. [L1] 2. Analyze the issues related to multiprocessing. [L4] 3. Develop the solutions using parallel programming. [L3] 4. Demonstrate the use of synchronization technique in threads. [L3] Program outcomes (Pos):

1. Graduates will demonstrate the ability to identify, formulate and solve computer

systems engineering problems.[PO 2]

2. Graduates will demonstrate an ability to analyze the given problems and design solutions, as per the needs and specifications.[PO 4]

3. Graduates will develop confidence for self education and ability for lifelong

learning[PO 10]

Text Book

1. Shameem Akhther and Jason Roberts, “Multicore Programming, Increasing

Performance through Software Multi-threading”, Intel Press, 2006.

2. Michael J Quinn, “Parallel programming in C with MPI and OpenMP”, Tata McGraw Hill, 2003.

Reference Book

1. Rohit Chandra, Leonardo Dagum, Dave Kohr etc. “Parallel Programming in Openmp”, 2000.

2. John L. Hennessey and David A. Patterson, “Computer architecture – A quantitative approach”, Morgan Kaufmann/Elsevier Publishers, 5th. Edition, 2011.


The Total marks of CIE shall be 50 (three tests of 30 marks each, two Assignments of 10

marks each and quiz/course seminar/course project of 10 marks each). The weight-age of

CIE is as shown in the table below.


best 2 Tests

Test-2

Average of 2

Assignments

Quiz/Seminar/

Project

Total

Marks

Maximum marks

30 10 10 50




First Semester

Data Mining & Warehousing





Course Objectives:

1. To introduce the basic concepts and techniques of data mining and data warehousing 2. To develop the skills using recent data mining software for solving practical problems. 3. To assess the strengths and weaknesses of various data mining methods and

algorithms

Prerequisite:

1. Database Management System 2. Information Management

Detailed Syllabus:

Unit I 10 Hours

Introduction:

What is a Data Warehouse?, A Multidimensional Data Model, Data Warehouse Architecture, Data Warehouse Implementation, Data cube Technology, From Data warehousing to Data Mining, Data Mining Functionalities, Data cleaning, Data Integration and Transformation, Data Reduction.

Unit II 10 Hours

Data Mining primitives, Languages and System Architecture: Data Mining primitives, Presentation and Visualization of Discovered patterns, A Data Mining Query Language. Association Rule Mining Single–dimensional Boolean Association Rules From Transactional Databases, Mining Multilevel Association Rules from Transactional Databases.

Unit III 10 Hours

Classification and Prediction: Issues regarding Classification and Prediction, classification by Decision tree induction, Bayesian classification, Classification by back propagation, Classification Based on the concepts from association rule mining. Other classification methods, prediction.

Unit IV 10 Hours

Cluster Analysis: What is Cluster Analysis? Types of data in cluster Analysis: a Categorization of Major Clustering Methods, Partitioning Methods, Hierarchical methods, Density-Based

Methods, Model-Based Clustering Methods: Statistical Approach, Neural Network Approach Outliner Analysis.

Unit V 10 Hours

Application and Trends in Data Mining: Data mining application, Data mining system Products research Prototypes, Additional Themes on Data Mining, Data Mining and Intelligent Query Answering, Trends in Data Mining.

Course Outcomes (COs): Upon the completion of the course the students will be able to 1. Identify the key processes of data mining, data warehousing and knowledge discovery

process. [L1] 2. Describe the basic principles and algorithms used in practical data mining and

understand their strengths and weaknesses. [L1] 3. Apply data mining techniques to solve problems in interdisciplinary domains. [L3] 4. Demonstrate the classification, Regression & clustering technique. [L3]

Program outcomes (POs): 1. Graduates will demonstrate an ability to analyze the given problems and design solutions, as

per the needs and specifications. [PO4]

2. Graduate will demonstrate skills to use modern engineering tools, software’s and equipment to analyze and provide solutions to problems [PO6]

3. Graduate will be capable of pursuing research in their field of interest. [PO11]

Text Books: 1. Jiawei Han, Michelin Kamber, "Data Mining Concepts and Techniques", Morgan

KaufMann Publishers, 3rd edition, July 2011

References: 1. Alex Berson and Stephen J Smith, “Data Warehousing, Data Mining and OLAP” (Data

Warehousing/Data Management). New Delhi : Tata Mcgraw- Hill, 2004 2. Arun K Pujari, “Data Mining Techniques”, Universities Press, Oct 2013


The Total marks of CIE shall be 50 (three tests of 30 marks each, two Assignments of 10 marks each and

quiz/course seminar/course project of 10 marks each). The weight-age of CIE is as shown in the table

below.


best 2 Tests

Test-2

Average of 2

Assignments

Quiz/Seminar/

Project

Total

Marks

Maximum marks

Marks

30 10 10 50

http://www.amazon.in/Arun-K-Pujari/e/B0034PZ2GK/ref=dp_byline_cont_book_1




questions. SEE question paper will have two compulsory questions (any 2 units) and choice will be given

in the remaining three units. ( Kindly incorporate / mention the changes in the pattern of SEE question

paper, if required, based on the content of course)

First Semester

Programming with Python





Course Objectives:

1. To acquire programming skills in core Python 2. To write programs in Python for simple problems. 3. To develop the skill of writing GUIs. 4. To develop an ability to write simple graphics animations with sound.

Prerequisite:

1. Knowledge of Programming Concepts

Detailed Syllabus:

Unit I 10 Hours

Getting started:

The Game over program, Examining the game over program, introducing python, setting up python on windows and other operating systems, introducing IDLE, back to the game over program. Types, variables and simple I/O, introducing the useless trivia program, using quotes with strings, using escape sequences with strings, concatenating and repeating strings, working with numbers, user input, string methods, right types, converting values, back to the trivia program. Branching, while loops and program planning, using the if, else, elif statements, creating while loops, infinite loops, values as conditions, compound conditions, planning your programs, guess my number game.

Unit II 10 Hours

FOR loops, strings and tuples:

Using for loops, using sequence operators and functions with strings, indexing strings, string immutability, building a new string, slicing strings, tuples, jumble game. Lists and dictionaries – using Lists, list methods, understanding when to use tuples and lists, nested sequences, shared references, dictionaries, hangman game. Functions, creating functions, parameters and return values, keyword arguments, default parameters, global variables, tic tac toe game.

Unit III 10 Hours

Files and Exceptions:

Reading and writing to text files, storing complex data, handling exceptions, trivia Challenge

game. Software objects, caretaker program, object oriented basics, creating Classes, methods

and objects, constructors, attributes, class attributes and static methods, object encapsulation,

private attributes and methods, attribute access, critter caretaker program. Object oriented

programming – sending and receiving messages, combining objects, inheritance, extending a

class through inheritance, altering behavior of inherited methods, understanding polymorphism,

creating Units, blackjack game.

Unit IV 10 Hours GUI development:

Examining GUI, understanding event driven programming, root window, labels, buttons,

creating a GUI using a class, binding widgets and event handlers, text and entry widgets and Grid

layout manager, check buttons, radio buttons, adlib program. Graphics – Pizza panic game,

creating a graphics window, setting background image, understanding the graphics coordinate

system, displaying sprite, text, message, moving sprites, dealing with screen boundaries,

mouse input, collisions.

Unit V 10 Hours Sound, animation and program development:

Reading keyboard, rotating a sprite, creating an animation, working with sound and music, astrocrash game, asteroids, rotating the ship, moving the ship, firing missiles, controlling the missile rate, collisions and explosions, adding levels, store keeping and theme music. Course Outcomes (COs):

At the end of the course, students will be able to

1. Write and execute programs for simple problems using Python. [L6] 2. Design and develop GUIs. [L6] 3. Design and develop graphical animations with sound. [L6] 4. Demonstrate use of python in text analysis. [L3] Program Outcomes(Pos):

1. Graduates will demonstrate an ability to analyze the given problems and design solutions, as per the needs and specifications.[PO4]

2. Graduate will demonstrate skills to use modern engineering tools, software’s and equipment to analyze and provide solutions to problems[PO6]

3. Graduates will develop confidence for self education and ability for lifelong learning.[PO10] 4. Graduates will demonstrate Research skill to identify research issues and propose novel

techniques.[PO12] Text Book:

1. Python Programming, Michael Dawson, 3rd Edition, Course technology PTR, 2010

Reference Books:

1. Programming Python by Mark Lutz, O'Really, 4th Edition, 2011. 2. Head First Python by Paul Barry, O'Reilly Shroff Publishers, 2010.


The Total marks of CIE shall be 50 (three tests of 30 marks each, two Assignments of 10 marks

each and quiz/course seminar/course project of 10 marks each). The weight-age of CIE is as

shown in the table below.


best 2 Tests

Test-2

Average of 2

Assignments

Quiz/Seminar/

Project

Total

Marks Maximum marks

Marks

30 10 10 50




KLS Gogte Institute of Technology Department of Mechanical Engineering “Jnana Ganga”,Udyambag, Belagavi - 590008 Karnataka, India

Scheme of Teaching for

M.Tech.

in

Computer Integrated Manufacturing

For the Academic year 2016-17

Curriculum frame work Distribution of credits

Semester Credits1 252 253 264 18

Total 94

S.No. Subject Area Credits1 Professional Core ( Theory & Practical's) PC 362 Professional Elective PE 163 Lab PC 44 Seminar PC 25 Internship SS 106 Project PR 227 Term Assignment 4

Total 94

Lecture (L): One Hour /week – 1 credit Practical (P): Three hours /week – 2 credits

First Semester

S.No. Code CourseCredits Total

creditsContact

Hours/weekMarks

L – T - P CIE SEE TOTAL

1. 16CIM11Computer Control of Manufacturing

SystemsPC 4 – 0 - 0 4 4 50 50 100

2. 16CIM12 Rapid Prototyping and Tooling PC 4 – 0 - 0 4 4 50 50 1003. 16CIM13 Design for Manufacture PC 4 – 0 - 0 4 4 50 50 1004. 16CIM14 Automation in Manufacturing Systems PC 4 – 0 - 0 4 4 50 50 1005. 16CIM15X Elective- A PE 4 – 0 - 0 4 4 50 50 1006. 16CIM16 CNC and Robot programming Lab PC 0 – 0 - 2 2 3 25 25 507. 16CIM17 Seminar-1 PC 0 – 0 - 1 1 25 258. 16PTA18 Term Assignment-1 Mandatory 0 – 0 - 2 2 4 25 25

Total 25 27 325 275 600* SEE: SEE (Theory exam) will be conducted for 100 marks of 3 hours duration. It is reduced to 50 marks for the calculation of SGPA and CGPATerm Assignment: The performance is continuously evaluated by the faculty member and Grade isgiven.

ELECTIVE- A

16CIM151 Computer Aided Design 16CIM153 Finite Element Method16CIM152 Management Information System 16CIM154 Mechatronics System Design

Second Semester


creditsContact

Hours/weekMarks

L – T - P CIE SEE TOTAL1. 16CIM21 Advanced Foundry Technology PC 4 – 0 - 0 4 4 50 50 1002. 16CIM22 Industrial Robotics PC 4 – 0 - 0 4 4 50 50 1003. 16CIM23 Non Traditional Machining PC 4 – 0 - 0 4 4 50 50 1004. 16CIM24 Flexible Manufacturing Systems PC 4 – 0 - 0 4 4 50 50 1005. 16CIM25X Elective- B PE 4 – 0 - 0 4 4 50 50 100

6. 16CIM26Rapid Prototyping and Casting Analysis Lab

PC 0 – 0 - 2 2 3 25 25 50

7. 16CIM27 Seminar-2 PC 0 – 0 - 1 1 25 258. 16PTA28 Term Assignment-2 Mandatory 0 – 0 - 2 2 4 25 25

Total 25 27 325 275 600* SEE: SEE (Theory exam) will be conducted for 100 marks of 3 hours duration. It is reduced to 50 marks for the calculation of SGPA and CGPATerm Assignment: The performance is continuously evaluated by the faculty member and Grade is given.

ELECTIVE- B

16CIM251 Advanced Tool Engineering Design 16CIM253 Artificial Intelligence and Expert Systems

16CIM252 Non Destructive Testing 16CIM254 Advanced Control Engineering

Third Semester


creditsContact

Hours/weekMarks

L – T - P CIE SEE TOTAL1. 16CIM31 Design of Experiments PC 4 – 0 - 0 4 4 50 50 1002. 16CIM32X Elective- C PE 4 – 0 - 0 4 4 50 50 1003. 16CIM33X Elective- D PE 4 – 0 - 0 4 4 50 50 1004. 16CIM34 #Internship SS 10 50 50 1005. 16CIM35 *Project Phase-1 PR 4 25 25

Total 26 12 225 200 425

* SEE: SEE (Theory exam) will be conducted for 100marks of 3 hours duration. It is reduced to 50 marks for the calculationof SGPA and CGPA# Internship report and presentation to be submitted at the end of semester* Selection of topic and Literature Review

ELECTIVE- C

16CIM321 Advanced Materials Technology 16CIM323 Micro Electro Mechanical Systems16CIM322 Reverse Engineering 16CIM324 Concurrent Engineering

ELECTIVE- D

16CIM331 Integrated Production Control Systems 16CIM333 Agile Manufacturing16CIM332 Product Life Cycle Management 16CIM334 Industrial Tribology

Fourth Semester


creditsContact

Hours/weekMarks

L – T - P CIE SEE TOTAL1. 16CIM41 Project Phase -2 PR 4 25 252. 16CIM42 Project Phase -3 PR 4 25 253. 16CIM43 Viva-voce PR 10 100 100

Total 18 24 50 100 150

First SemesterCOMPUTER CONTROL OF MANUFACTURING SYSTEMS

Course Code 16CIM11 Credits 4Course type PC CIE Marks 50 marksHours/week: L-T-P 4 – 0 – 0 SEE Marks 50 marksTotal Hours: 50 SEE Duration 3 Hours

Course learning objectives:

1. To impart the basic concepts in manufacturing systems and fundamentals of CIMS.2. Enhancement of knowledge in the use of computers for control and planning in the field of

manufacturing, machining centers, tooling and programming of CNC machines3. To enhance student’s awareness in Inspection principles and methods.

Pre-requisites: Basic knowledge of CNC, computers in manufacturing etc.

Detailed Syllabus:

Unit I10 Hours

Introduction to Computer integrated Manufacturing Systems: Manufacturing Systems, Types ofManufacturing Systems, , Machine Tools and related equipment’s, Material Handling Systems,Computer monitoring and control, Manufacturing support systems, Functions of computers in CIMS:CIMS Data Files, System Reports, Benefits of Computer integrated Manufacturing Systems.Self Learning Topics: The Product Cycle and CAD/ CAM

Unit II10 Hours

CNC Machine Tools: General architecture of CNC Machine, Components of the CNC Systems, Types ofCNC, Functions of CNC Control in Machine Tools, Direct Numerical Control (DNC Systems): Configurationof DNC system, Functions of DNC, Communication between DNC computer & MCU, Adaptive controlmachining systems. Adaptive control optimization system, adaptive control constraint system,applications to machining processes.Self Learning Topics: Advantages of CNC, Advantages of DNC, Benefits of Adaptive control machining

Unit III10 Hours

CNC part programming: Introduction, CNC programming methods: Manual part programming forturning and milling centers, G codes, M codes, canned cycles, Programming with CAD/CAM integration,Practical Exercises on CNC part programming for generating toolpath for contour, holes, pockets,subroutine programming, facing, step and multiple turning.

Unit IV10 Hours

Group technology: Introduction, Part classification and coding, Methods of Grouping part families,Opitz system, Problems in GT.Computerized Manufacturing Planning and Control Systems: Computer aided process planning,Variant and Generative approaches, Computer integrated production planning and control systems.Self Learning Topics: MICLASS system, Benefits of GT.

Unit V 10 HoursInspection Principles and Practices: Inspection fundamentals, Sampling vs. 100% inspection,Automated Inspection, Off-line and On-line inspection, Product Inspection vs. Process Monitoring.Computer Aided Quality Control: Introduction, Terminology in quality control, The computers in qualitycontrol, Contact Inspection methods, Coordinate Measuring Machines: construction and operation, Noncontact inspection methods: Optical and Non-Optical.Self Learning Topics: Distributed Inspection vs. Final Inspection, Computer Aided testing.

Text Books:1. Groover M P, Automation, Production Systems and Computer Integrated Manufacturing, Prentice

Hall India (P) Ltd, 1989.2. Mikell P. Groover and Emory W. Zimmer, Jr., CAD/CAM Computer Aided Design and Manufacturing,

Prentice Hall India (P) Ltd, 1992.3. M.Koren ―Computer Controls of Manufacturing Systems, McGraw Hill, 1983

Reference Books:1. P. Radhakrishna, CAD/CAM/CIM, New Age International, 20082. P.N. Rao – CAD/CAM Principles and Applications, McGraw hill 2002.3. B.S. Pabla, CNC Machines, New Age International, 2005.4. Y. Koren & J.Benuri -“Numerical control of machine tools, Khanna, 1992.5. Suk-Hwan Suh, Seong-Kyoon Kang, Dea-Hyuk Chung and Ian Stroud, Theory and Design of CNC

Systems, Springer, 2008.

Course Outcome (COs):Students will get

1. Understand the NC/CNC machines, elements of CNC machines and its uses [L2].2. Knowledge of CNC programming and its implementation [L3].3. Insight into the inspection and QC methods [L2].

Program Outcomes(POs) of the course:1. Graduates shall acquire in-depth knowledge in manufacturing and update the same, integrating

existing and updated knowledge in global perspective [PO1]2. Graduates shall conceptualise through lateral thinking and obtain feasible and optimal solutions for

engineering problems considering societal and environmental requirements [PO3]3. Graduates shall be able to adopt modern techniques, analytical tools and softwares for complex

engineering solutions [PO5]

Self Study topics shall be evaluated during CIE (Assignments and IA tests) and 10% weightage shall begiven in SEE question paper.


ComponentsAverage of best two

tests out of threeAverage of two

assignments/ activitySeminar/ Mini

ProjectTotal Marks

Maximum Marks 30 10 10 50

Scheme of Semester End Examination (SEE):1. It will be conducted for 100 marks of 3 hours duration. It will be reduced to 50 marks for the

calculation of SGPA and CGPA.2. Question paper contains 08 questions each carrying 20 marks. Students have to answer FIVE full

questions. SEE question paper will have two compulsory questions (any 2 units) and choice will begiven in the remaining three units.

First SemesterRAPID PROTOTYPING & TOOLING

Subject Code: 16CIM12 Credits: 4

Course Type: PC CIE Marks: 50

Hours/week: L – T – P 4-0-0 SEE Marks: 50

Total Hours: 50 SEE Duration: 3 Hours


1. The course enables students to conceive, design, and implement products quickly andeffectively, using the latest rapid prototyping methods and CAD/CAM technology.

2. The students learn to differentiate various process parameters associated with RapidManufacturing technique

3. Students will learn about the applications of RP in various industries like automotive,aerospace, jewelry, coin, medical and dental applications.

Pre-requisites: Manufacturing Process 1 (Foundry Technology), CAD / CAM basics

Detailed Syllabus:

UNIT –I 10 Hours

Introduction: Prototype fundamentals, historical development, fundamentals of RP, commonly usedterms, classification of RP systems.RP Processes: Processes involving liquid, Stereo Lithography, liquid thermal polymerization, etc.,Processes Involving Discrete Particles, Processes Involving Solid Sheets.

UNIT –II 10 Hours

Technical Characteristics and Technological Capabilities of Rapid Prototyping Systems: StereoLithography Apparatus (3D Systems), Solid Ground Curing systems (Cubital Ltd.), Fused DepositionModelling Systems, Selective Laser Sintering Systems, Laminated Object Manufacturing SystemsTechnical Characteristics and Technological Capabilities of Concept Modelers: 3D Systems Thermo-Jet Printer, Sanders Model Maker II (Inkjet Modeling Technology), Z- Corporation Z402 3D Printer,Stratasys Genisys Xs 3D Printer, JP System 5, Object Quadra System.

UNIT –III 10 Hours

Rapid Prototyping Data Formats: STL format, STL file problems, Consequences of building valid andinvalid Tessellated Models, STL file repair, newly proposed formatsRapid Prototyping Process Optimization: Factors influencing accuracy, data preparation, part building,part finishing and selection of part build orientation

UNIT –IV 10 Hours

Indirect Methods for Rapid Tool Production: Role of indirect methods in tool production, metaldeposition tools, RTV tools, Epoxy tools, Ceramic tools, Cast metal tools, Investment casing, Fusiblemetallic core, Sand castingSelf-Learning Topics:Direct Methods for Rapid Tool Production: Classification of direct tool methods, Direct ACES InjectionMolds, Laminated Object Manufactured (LOM) tools, DTM Rapid tool process, Sand form, EOS DirectTool.

UNIT –V 10 Hours

Applications of Rapid Prototyping Technology: Functional Models, Pattern for Investment andVacuum CastingSelf-Learning Topics: Medical Models, Art Models, Engineering Analysis Models

Text Books:

1. Chua C.K., K.F.Leong, Lim C.S., Rapid Prototyping: Principles and Applications, World Scientific, 3rd

Ed, 2010.2. Pham D.T., Dimov S.S., Rapid Manufacturing: The Technologies and Applications of Rapid

Prototyping and Rapid Tooling, Springer-Verlog London, 2001

Reference Books:

1. Paul F. Jacobs, Stereo Lithography and other RP & M Technologies, SME NY, 1996

Course Outcomes (CO's):On completion of the course the student will be able to :

1. Understand fundamentals of Rapid Prototyping and be able to compare it with otherapproaches. [L2, L4]

2. Understand various types of Rapid Prototyping and RP machines[L2]3. Understand Rapid Tooling and RP Formats[L2]4. Understand the various applications of RP technology [L2]

Program Outcomes(POs) of the course:

Usage of modern tools: Graduates shall be able to adopt modern techniques, analytical tools andsoftware for complex engineering solutions. [PO-5]

Communication: Graduates shall possess communication skills to comprehend, document and presenteffectively to the engineering community and society at large. [PO-8]

Life-long Learning :Graduates shall engage in lifelong learning with motivation and commitment forprofessional advancement. [PO-9]

Ethical Practices and Social Responsibility: Graduates shall imbibe the professional ethics and integrity forsustainable development of society. [PO-10]

Independent and Reflective Learning: Graduate shall be able to introspect and apply corrections.[PO-11]



ComponentsAverage of besttwo tests out of

three

Average of twoassignments/

activity

Seminar/Mini Project

TotalMarks



1. It will be conducted for 100 marks of 3 hours duration. It will be reduced to 50 marks for thecalculation of SGPA and CGPA.

2. Question paper contains 08 questions each carrying 20 marks. Students have to answer FIVE fullquestions. SEE question paper will have two compulsory questions (any 2 units) and choice will begiven in the remaining

First SemesterDESIGN FOR MANUFACTURE

Subject Code 16CIM13 Credits 4Course Type PC CIE Marks 50Hours/Weak: L-T-P 4-0-0 SEE Marks 50Total Hours 50 SEE Duration 3Hours

Course learning Objectives (CLO’s):

1. To educate students a clear understanding of factors to be considered in designing parts andcomponents with focus on manufacturability.

2. To enable the student to fully understand the importance of manufacturing principles indesigning parts of a component.

3. To teach the students how to use the theoretical principles of manufacturing and assembly indesigning parts of a components.

4. To teach the students the importance of material selection, tolerances, datum in the designof components.

5. To introduce students the concepts of parting line, cored holes and machined holes inmanufacturing.

Pre-requisites: Basic Knowledge of Manufacturing and design stream.

Detailed Syllabus:

UNIT-I 10 Hours

Effect of Materials and Manufacturing Process On Design: Major phases of design. Effect of materialproperties on design Effect of manufacturing processes on design. Material selection process- costper unit property, weighted properties and limits on properties methods.Engineering Design and Datum features: Dimensioning, Tolerances, General Tolerance, GeometricTolerances, Assembly limits, achieving larger machining tolerances. Screw threads, Ground surfaces,holes. Examples Functional datum, machining sequence, manufacturing datum, changing the datum.Examples.

UNIT-II 10 Hours

Component design: Machining Considerations Drills, Milling cutters, Drilling, Keyways, Dowels,Screws, Reduction in machining areas, Simplification by separation and amalgamation, work pieceholding, surface grinding, ExamplesComponent design: Casting Considerations Pattern, Mould, parting line, cast holes, machined holes,identifying parting line, special sand cores, designing to obviate sand cores. Examples

UNIT-III 10 Hours

Geometric Tolerance and Analysis: Process capability ,mean, variances, skewness, kurtosis, processcapability metrics, Cp ,Ck Cost aspects, Feature tolerance. Examples.Design of Gauges: Design of gauges for checking components in assemble with emphasis on varioustypes of limit gauges for both holes and shaft

Self-Learning Topics: Tolerance – Symbols three datum concept of dimensioning, Straightness,concentricity, Run-out, Location Tolerance, Assembly of parts having concentric cylinders, Control of

feature location by true position, Body of revolution, Roundness, Profile dimensioning, Tapers, Shaft oftwo diameters.

UNIT-IV 10 Hours

Design for Injection molding and Sheet metal working : Design guidelines, Introduction to sheetmetalworking, Dedicated Dies and Press working, Press selections, Design Rules.

Self-Learning Topics: Injection molding materials, Molding cycle, Systems, molds, machine size, cycle time,Cost estimation, Insert molding.

UNIT-V 10 HoursDesign for Die casting and Powder metal processing: Die casting alloys, cycle, machines, dies, finishing,Assembly techniques, Design principles.

Self-Learning Topics: Powder metallurgy processing, stages, compaction characteristics, Tooling, Sintering,Design guidelines.

Text Books:1. H. Peck, Designing for Manufacturing, Pitman Publications,1983.2. Dieter, Machine Design, McGraw-Hill Higher Education, 20083. R. K. Jain, Engineering Metrology, Khanna Publishers,1986

4. W.Knight, M.Dekker, Product design for manufacture and assembly, Inc.CRCPress, Third Edition.5. Material selection and Design, Vol. 20, ASM Handbook.

Course Outcomes(CO’s):At the end of the course, the student will be able to:

1. Include manufacturability in mechanical engineering design of parts and their assemblies [L3].

2. Understand the importance of manufacturing principles in designing a particular product andincorporating the same in its design[L2].

3. Identify a parting line in the design of casting[L3].4. Design the components by considering all machining operations[L4].5. Design gauges by giving emphasis on various types of limit gauges[L4].

Program Outcomes (POs) of the course:1. Graduates shall acquire in-depth knowledge and update the same, integrating existing and

updated knowledge in global perspective. [PO1]

2. Graduates shall possess ability for independent judgment based on critical analysis and also forsynthesis of information for extensive research in the area of specialization. [PO2]

3. Graduates shall conceptualize through lateral thinking and obtain feasible and optimal solutionsfor engineering problems considering societal and environmental requirements. [PO3]



ComponentsAverage of best two tests

out of threeAverage of two

assignments/ activitySeminar/

Mini ProjectTotal

Marks

MaximumMarks

30 10 10 50



2. Question paper contains 08 questions each carrying 20 marks. Students have to answer FIVE fullquestions. SEE question paper will have two compulsory questions (any 2 units) and choice will begiven in the remaining three units.

First SemesterAUTOMATION IN MANUFACTURING SYSTEMS

Subject Code 16CIM14 Credits 4

Course Type PC CIE Marks 50 marks

Hours/Week: L-T-P 4-0-0 SEE Marks 50 marks

Total Hours 50 SEE Duration 3 Hours

Course Learning Objectives (CLO's):

1. To impart the basic concepts in manufacturing systems and fundamentals of Automation.2. Students will get an exposure to various aspects of automation in manufacturing, modeling

techniques, drives and controls used in manufacturing applications.3. Enhancement of knowledge in use of PLC and its applications.4. Understand the concepts features & parameters governing the Hydraulic and Pneumatic

circuits and their applications.

Prerequisite: Basic knowledge of manufacturing processes and types of manufacturing systems.

Detailed Syllabus:

UNIT –I 10 HoursFundamentals of Manufacturing: Production System Facilities, Different types of manufacturing systems,Automation in production systems, Automation Principles & Strategies, Manufacturing Operations,Product, Production Relationship.Mathematical Concepts & Models: Production Concepts & Mathematical Models, Costs ofManufacturing Operations, Numerical.

UNIT –II 10 HoursIntroduction to Automation: Basic elements of Automated system, Advanced Automation Functions,Levels of Automation.Hardware components for Automation and Process ControlManufacturing Support System: Concurrent Engineering & Design for Manufacturing, AdvancedManufacturing Planning, Just-in Time Production System, Basic concepts of Lean and Agilemanufacturing.Self learning topics: Sensors, Actuators, Analog-to- Digital converters, Digital-to-Analog converters, Input/ Output devices for discrete data.


Detroit type of Automation: Flow lines, Configurations of automated flow line, Work patterntransfer, Different methods, Different Transfer mechanisms, Numerical, Control functions, Buffer storage.The Future Automated Factory: Introduction, Trends in manufacturing, The Future Automated Factory: TheInformation System in the Automated Factory, Processing and Assembly, Material handling, Inspectionsystems, Social Impact of Automation of Factories.

UNIT –IV 10 Hours

Programmable Logic Controllers: Introduction, Hardware, Internal Architecture, Input and Output devices,Ladder diagrams, Logic functions, Function blocks, PLC processors, PLC instructors, Documenting a PLC system,Timers & Counters , Comparison & Data Handling instructions, Sequencing instructions, Mask Datarepresentation, Simple programs.

UNIT –V 10 Hours

Power Hydraulics & Pneumatics: Concepts features & parameters governing the selection of variouscomponents necessary for building the elements, Circuit Design & Analysis.

Self learning topics: Industrial applications of fluid power & pneumatic systems, Electro-Hydraulic Servosystem, Fluid logic control, MPL, Fluidics logic control.

Text Books:1. Viswanandham, Performance Modeling of automated Manufacturing Systems, PHI. 142. Goodwin, Fluid Power System, McGraw Hill Press Limited, 1976.3. Web , Principles & Applications, PLC McMillan 1992.4. W. Bolton , Programmable Logic Controllers, Elsevier, Fourth edition,2006

Reference Books:1. Vajpayee, Principles of CIM, PHI.2. Mikell P. Grover, Automation Production Systems & CIM, Pearson Education Asia, Third edition, 2008.3. Anthony Esposito, Fluid Power with Applications, Prentice Hall, 1997.

Course Outcomes (CO's):On completion of the course the student will be able to:

1. Obtain an understanding of the fundamentals of automation in manufacturing. [L2]2. Will be able to demonstrate knowledge of their understanding of drives, controls and modeling in

automation.[L3]3. Clear understanding of PLCs circuits and their applications.[L2]4. Design and Analyze the hydraulic and pneumatic circuits.[L4,L6]5. Clear understanding of applications of hydraulic and pneumatic circuits.[L2]

Program Outcomes (POs) of the course:

PO-1: [Scholarship of Knowledge]Graduates shall acquire in-depth knowledge in manufacturing and update the same, integrating existing and updated

knowledge in global perspective.

PO-4: [Research Skill]Graduates shall review relevant literature, apply appropriate research methodologies, working individually or as a teamcontributing to the advancement of domain knowledge.

PO-5: [Usage of modern tools]Graduates shall be able to adopt modern techniques, analytical tools and softwares for complex engineering solutions.

Self Study topics shall be evaluated during CIE (Assignments and IA tests) and 10% weightage shall be given in SEEquestion paper.



tests out of three


activity


TotalMarks

MaximumMarks

30 10 10 50


1. It will be conducted for 100 marks of 3 hours duration. It will be reduced to 50 marks for the calculation of SGPAand CGPA.

2. Question paper contains 08 questions each carrying 20 marks. Students have to answer FIVE full questions. SEEquestion paper will have two compulsory questions (any 2 units) and choice will be given in the remaining threeunits

First SemesterCOMPUTER AIDED DESIGN

Course Code 16CIM151 Credits 4Course type PE CIE Marks 50 marksHours/week: L-T-P 4-0-0 SEE Marks 50 marksTotal Hours: 50 SEE Duration 3 Hours


1. To impart the basic Fundamentals of CAD, The Design Process, Computers Applications in Design, Knowledgeenhancement in areas like computer graphics, database structure and software configuration in CAD systems

2. Understand the engineering design process and its role in graphic communication process.3. To understand the process of transformations during geometrical modeling.4. Generate and interpret engineering technical drawings of parts and assemblies according to engineering

design standards.

Pre-requisites: Knowledge of Computer Aided Engineering Drawing, Computer Aided Machine Drawing and Matrices.

Detailed Syllabus:

Unit I 10 HoursIntroduction to CAD: Graphics standard, functional areas of CAD, Modeling and viewing, software documentation, TheDesign Process, Computers Applications in Design, Manufacturing Database, Benefits of CAD.Computer graphics software and database: Software configuration of a Graphic system, Functions of a Graphicspackage, Constructing the Geometry, Database Structure and Content.

Self Learning Topics: Definition of CAD, CAD Tools, Types of system, CAD/CAM system evaluation criteria, Brieftreatment of input and output devices, Wire-Frame Features & CAD/CAM Integration.

Unit II 10 HoursGeometric Modeling: Requirements of Geometric Modeling, Geometric Models, Geometric Construction Methods,Constraint- Based Modeling, Other Modeling Methods- Cell Decomposition, Variant Method, Symbolic Programming,form Features. Wireframe Modeling- Definitions of Point lines, Circles, Arcs, etc., Wireframe Data Representation.Graphic Standards: Standardization in Graphics, Graphical Kernel System (GKS), Other Graphic Standards-GKS 3D,PHIGS, NAPLPS, Exchange of Modeling Data-IGES, STEP, Drawing Exchange Format (DXF), Dimension MeasurementInterface Specification (DMIS).

Self Learning Topics: Graphics Standards

Unit III 08 HoursTransformations: Translation, Scaling, Reflection or Mirror, Rotation, Concatenations, Homogeneous Transformation,3D Transformations-Translation, Scaling, Rotation about, X, Y and Z axes. Mathematics of Projections- Orthographic andIsometric Projections.

Self Learning Topics: Clipping, Hidden Line or Surface removal, Color and Shading.

Unit IV 12 HoursModeling curves & surfaces: Curve Representation-Line, Circle, Parabola, Hyperbola, Curve Fitting- InterpolationTechniques-Lagrangian Polynomial, B-Splines, Approximate Methods- Method of Least Squares, Polynomial Curve

Fitting, Synthetic Curves-Hermite Cubic Spline, Bermestine Polynomials, Bezier Curve, Rational Curves, NURBS.Surface representation: Methods-Analytic Surfaces, Surfaces of Revolution, Ruled Surfaces, Synthetic Surfaces- HermiteCubic Surface, Bezier Surface, B-Spline Surface, Coons Surface Patch, Tabulated Cylinder, Sculptured Surfaces, Surfacesof Manipulation-Surface Display, Segmentation.

Unit V 10 HoursModeling of solids: Solid Representation- Concepts, Boundary Representations (B-Rep), Constructive Solid Geometry(CSG), Half Space Method.Mechanical assembly: Introduction, Assembly Modeling, Parts Modeling and Representation, HierarchicalRelationships, Mating Conditions, Inference of Position from Mating Conditions, Representation Schemes, GraphStructure, Location Graph, Virtual Link, Generation of Assembling Sequences, Precedence Diagram, Liaison-SequenceAnalysis, Precedence Graph, Assembly Analysis.

Books:Text Books

1. P.N. Rao, CAD/CAM Principles and Applications, McGraw Hill, Education Pvt. Ltd., New Delhi, 3rd Ed, 20122. Ibrahim Zeid & R. Shivasubramanian, CAD/CAM Theory & Practice, TMH Education Pvt. Ltd., New Delhi, 2nd

Ed, 2009

Reference Books1. M.P. Groover and E W Zimmers, CAD/CAM Computer aided Design and Manufacture, Prentice hall, 19842. C.B. Besant and E.W.K. Lui, Computer Aided design and Manufacture, Affiliated East West, press India,

19883. David F. Rogers and J Alan Adams, Mathematical Elements for Computer Graphics, McGraw-Hill

Science/Engineering/Math, 2 edition, 1989

Course Outcome (COs):At the end of the course, students will be able to

1. Explain the complete design process. [L2]2. Understand the geometric modeling, Construction of various geometries. [L2]3. Apply methods of utilization of appropriate features in CAD application enhancing productivity in design. [L3]4. Construct CAD models related to mechanical assembly leading to minimum lead time. [L3]

Program Outcomes (POs) of the course:1. Graduates shall acquire in-depth knowledge in CAD and update the same, integrating existing and updated

knowledge in global perspective. [PO1]2. Graduates shall possess ability for independent judgement based on critical analysis and also for synthesis of

information for extensive research in the area of specialization. [PO2]3. Graduates shall conceptualise through lateral thinking and obtain feasible and optimal solutions for engineering

problems considering societal and environmental requirements. [PO3]4. Graduates shall be able to adopt modern techniques, analytical tools and softwares for complex engineering

solutions. [PO5]5. Graduate shall be able to introspect and apply corrections. [PO11]




three


activity


TotalMarks

MaximumMarks

30 10 10 50



2. Question paper contains 08 questions each carrying 20 marks. Students have to answer FIVE full questions. SEEquestion paper will have two compulsory questions (any 2 units) and choice will be given in the remaining threeunits.

First Semester

MANAGEMENT INFORMATION SYSTEM


Course Type: PE CIE Marks: 50

Hours/week: L – T – P 4 SEE Marks: 100


Course Learning Objectives (CLOs):1. Introduce various aspects of MIS as applied to engineering problems in a systematic manner.2. Impart the knowledge of data base fundamentals.3. Apply MIS for business applications.

Pre-requisites: Engineering Management, Database, Information System

Detailed Syllabus:

UNIT –I 10 Hours

Introduction: MIS: Definition, Importance of MIS, Evolution of MIS, Computers and MIS, Organizational Structure,Logical Foundations of MIS, Typical MIS Systems, and Future of MIS.Information Systems and Organizations: Structure, Data and Information, Management and Decision Making,Classification of MIS, Information support for functional areas of Management, Impact of business on InformationSystems, Absorption of MIS in Organizations.

UNIT –II 10 Hours

Database Technology: Introduction, Database and Enterprise Management, File Processing Systems and DatabaseSystems, Data Independence, Database Approach, Database Architecture. Relational Database ManagementSystems (RDBMS): DBMS: Introduction, Structured Query Language (SQL), Data Administration, CurrentDevelopments in Databases.


Decision Support Systems: Introduction, Definition, Evolution of DSS, Characteristics, Model Management, DSSGenerators, Multi-criteria Modelling, Using DSS; What-if analysis, Sensitivity Analysis, Goal-seeking Analysis, DataMining.Expert Systems and Artificial Intelligence: Introduction, AI - Definition, Evolution of AI, Components of AI,Expert Systems, Benefits and Limitations, Applications.

UNIT –IV 10 Hours

Systems Analysis and Design: Introduction, Organizational Context of Systems Analysis, Role of Systems Analyst,Systems Development Life Cycle (SDLC), Requirement Analysis, Requirement Specifications, Feasibility Analysis,Feasibility Report, Case Studies.

Self-Learning Topic:Development, Implementation and Management of MIS Resources: Developing and Implementing ApplicationSystems, Quality Assurance and Evaluation of Information Systems.

UNIT –V 10 HoursOrganization and Management: Organization and Management of the Information Resources, Change from MISto IRM (Information Resource), Organization of the Information Resources Function, Allocating ScarceInformation Resources, MIS Personnel.

Self-Learning Topic:Developing a Long-Range Information System Plan: Master Plan, The Nolan Stage Model, Strategic Planning Stage,Analysis of Organizational Information Requirement.

Text Books:1. W.S Jawadekar , Management Information systems, TMH, 4th Ed, 2002.2. Davis G.B., Management Information Systems-Conceptual foundations, Structure and development,

McGraw Hill Intl. Book Co., 6th Ed, 2001.

Reference Books:1. S.Sadagopan, Management Information Systems, PHI, 2005.2. James A O’Brien, George M.Markas, Ramesh Behl, Management Information Systems,

Tata McGraw Hill, 9th Ed, 2008.

Course Outcomes (COs):At the end of this course, the students will be able to :

1. Understand fundamentals of MIS and be able to compare it with other approaches. [L2, L4]2. Identify and discuss the fundamentals of data base management as applied to respective tasks. [L2]3. Demonstrate the ability to define and state the properties and characteristics of data base management

by any engineer. [L1, L3]

Program Outcomes(POs) of the course:Usage of modern tools: Graduates shall be able to adopt modern techniques, analytical tools and software forcomplex engineering solutions. [PO-5]Communication: Graduates shall possess communication skills to comprehend, document and present effectively tothe engineering community and society at large. [PO-8]Life-long Learning : Graduates shall engage in lifelong learning with motivation and commitment for professionaladvancement. [PO-9]Ethical Practices and Social Responsibility: Graduates shall imbibe the professional ethics and integrity for sustainabledevelopment of society. [PO-10]Independent and Reflective Learning: Graduate shall be able to introspect and apply corrections. [PO-11]

Self Study topics shall be evaluated during CIE (Assignments and IA tests) and 10% weightage shall be given in SEEquestion paper.Scheme of Continuous Internal Evaluation (CIE):

Components Average of best twotests out of three

Average of twoassignments/ activity


TotalMarks


Scheme of Semester End Examination (SEE):1. It will be conducted for 100 marks of 3 hours duration. It will be reduced to 50 marks for the calculation of

SGPA and CGPA.2. Question paper contains 08 questions each carrying 20 marks. Students have to answer FIVE full questions. SEE

question paper will have two compulsory questions (any 2 units) and choice will be given in the remainingthree units.

First SemesterFINITE ELEMENT METHOD

Subject Code 16CIM153 Credits 4Course Type PE CIE Marks 50Hours/Week: L-T-P 3-0-1 SEE Marks 50Total Hours 50 SEE Duration 3 Hours

Course Learning Objectives (CLO’s)1. To present the Finite element method (FEM) as a numerical method for engineering analysis of structures.2. To acquire the knowledge of Finite elements for the analysis of bars & trusses, beams & frame problems.3. To acquire the knowledge of Finite elements for the analysis of plane stress and 3-D problems.4. To acquire the knowledge of finite element to solve statically indeterminate problems in structural mechanics.5. To acquire the knowledge of Finite element theory and formulation for dynamic analysis of mechanical

structures.

Pre-requisites: Basics of Machine Design and Strength of Materials.

Detailed Syllabus:

UNIT-I 10 Hours

Introduction to Finite Element Method: Basic Steps in Finite Element Method to solve mechanical engineering(Structural and Heat Transfer) problems: Functional approach and Galerkin approach, Displacement Approach:Admissible Functions, Convergence Criteria: Conforming and Non Conforming elements, Co C1 and Cn ContinuityElements. Basic equations, element characteristic equations, assembly procedure, boundary and constraint conditions.

Self Learning Topics: Basics of matrix algebra, concepts about energy methods

UNIT-II 10 Hours

Solid Mechanics: One-Dimensional Finite Element Formulations and Analysis Bars- uniform, varying and stepped crosssection- Basic (Linear) and Higher Order Elements Formulations for Axial and Temperature Loads with problems. Beams-Basic (Linear) Element Formulation-for uniform, varying and stepped cross section- for different loading and boundaryconditions with problems. Trusses, Plane Frames and Space Frame Basic (Linear) Elements Formulations for differentboundary condition -Axial, Bending, and Temperature Loads with problems.UNIT-III 10 Hours

Two Dimensional Finite Element Formulations for Solid Mechanics Problems: Triangular Membrane (TRIA 3, TRIA 6,TRIA 10) Element, Four-Noded Quadrilateral Membrane (QUAD 4, QUAD 8) Element Formulations for in-plane loadingwith sample problems. Triangular and higher order Elements formulation for axi-symmetric loading only with sampleproblems.Three Dimensional Finite Element Formulations for Solid Mechanics Problems: Finite Element Formulation ofTetrahedral Element (TET 4, TET 10), Hexahedral Element (HEXA 8, HEXA 20), for different loading conditions.

UNIT-IV 10 Hours

Finite Element Formulations for Structural Mechanics Problems: Introduction, thin and thick plates – Kirchhoff theory,Mindlin plate element, triangular and rectangular plates, introduction to shells.

UNIT-V 10 Hours

Dynamic Analysis: Finite Element Formulation for point/lumped mass and distributed masses system, Finite ElementFormulation of one dimensional dynamic analysis: bar, truss, frame and beam element. Evaluation of Eigen values andEigen vectors applicable to bars, shaft, beams.Self Learning Topics: Fundamentals about eigen values, vectors and mode shapes.

Text Books:1. T. R. Chandrupatla and A. D. Belegundu, Introduction to Finite Elements in Engineering, Prentice Hall, 3rd Edition,

2002.2. H. V. Lakshminarayana, Finite Elements Analysis– Procedures in Engineering, Universities Press, 2004.

Reference Books:1. S. S. Rao, Finite Elements Method in Engineering- 4th Edition, Elsevier, 2006.2. P. Seshu, Textbook of Finite Element Analysis, PHI, 2004.3. K. J. Bathe, Finite Element Procedures, Prentice-Hall, 2006.4. R. D. Cook, Finite Element Modeling for Stress Analysis, Wiley, 1995.

Course Outcome (CO’s):On completion of the course the student will be able to,

1. Obtain an understanding of the fundamental theory of the FEA method [L3].2. Develop the ability to generate the governing FE equations for systems governed by partial differential

equations [L5].3. Understand the use of the basic finite elements for structural applications using truss, beam frame, and plane

elements [L2].4. Understand the application and use of the FE method for Dynamic Problems [L2].

Program Outcomes (POs) of the course:PO-2: [Critical Thinking]Graduates shall possess ability for independent judgement based on critical analysis and also for synthesis ofinformation for extensive research in the area of specialization.PO-3: [Problem Solving]Graduates shall conceptualise through lateral thinking and obtain feasible and optimal solutions for engineeringproblems considering societal and environmental requirements.PO-5: [Usage of modern tools]Graduates shall be able to adopt modern techniques, analytical tools and softwares for complex engineering solutions.

Self Study topics shall be evaluated during CIE (Assignments and IA tests) and 10% weightage shall be given in SEEquestion paper.Scheme of Continuous Internal Evaluation (CIE):


three


activity


TotalMarks


Scheme of Semester End Examination (SEE):1. It will be conducted for 100 marks of 3 hours duration. It will be reduced to 50 marks for the calculation of SGPA

and CGPA.2. Question paper contains 08 questions each carrying 20 marks. Students have to answer FIVE full questions. SEE

question paper will have two compulsory questions (any 2 units) and choice will be given in the remaining threeunits.

First SemesterMECHATRONICS SYSTEM DESIGN

Course Code 16CIM154 Credits 4Course type PE CIE Marks 50 marksHours/week: L-T-P 4-0-0 SEE Marks 50 marksTotal Hours: 50 SEE Duration 3 Hours


1. The course gives exposure to mechatronics system design and knowledge of MEMS and Microsystems2. To educate the student regarding integration of mechanical, electronic, electrical and computer

systems in the design of CNC machine tools, Robots etc.

Pre-requisites: Should have in-depth knowledge of Sensors, Actuators, Transducers and Control Systems.

Detailed Syllabus:

Unit I 08 Hours

Introduction: Definition and Introduction to Mechatronic Systems, Measurement Systems, Control Systems,Microprocessor Based Controllers and Applications.Study of Actuation Systems: Pneumatic and Hydraulic Systems, Mechanical Actuation System, Electrical ActuationSystems

Self Learning Topics: Study of Actuation Systems

Unit II 12 Hours

Modeling for mechatronics system design: Introduction, System, Hydraulic circuits, hydraulic servo motor dashpots.Mathematical modeling of thermal systems: Thermal resistance and thermal capacitance mathematical modeling ofthermal systems. Electrical Systems: RLC Circuits, active and passive electrical circuits, PMDC Motor, Stepper motor,three phase squirrel cage induction motor, three phase permanent magnet synchronous motor, servo-motor.

Self Learning Topics: Mechanical Systems: rotational systems, spring mass damper system. Mathematical modeling of apneumatic systems, Mathematical modeling of hydraulic systems:

Unit III 12 Hours

Signal Conditioning: Signal conditioning, the operational amplifier, Protection, Filtering, Wheatstone Bridge, Digitalsignals , Multiplexers, Data Acquisition, Introduction to digital system processing, pulse-modulation.MEMS and Microsystems: Introduction, Working Principle, Materials for MEMS and Microsystems, Micro Systemfabrication process, Overview of Micro Manufacturing, Micro system Design, and Micro system Packaging.

Self Learning Topics: Signal conditioning.

Unit IV 10 Hours

Micro System Fabrication Process: Photolithography, Ion Implantation, Diffusion, Oxidation, CVD, PVD, Epitaxy, Etching.Overview of Micro Manufacturing: Bulk Micro Manufacturing, Surface, Micromachining, the LIGA Process.Materials for MEMS and Microsystems: Substrate and wafers, Active substrate material, Silicon, Silicon compound,Silicon Piezo-resisters, Gallium Arsenide, Quartz, Piezoelectric crystals, Polymers

Unit V 08 Hours

Fault Finding: Fault–Detection Techniques, Watch Dog Timer, Parity and Error Coding Checks, Common HardwareFaults, Microprocessor Systems, Emulation and Simulation, PLC Systems.

Books:Text Books:

1. W. Bolton, Mechatronics, Pearson Edition, 6th Edition, 20152. Tai-Ran Hsu, MEMS and Microsystems design and manufacture, Tata McGraw-Hill Education, 20023. K. Lal Kishore, Electronic Measurements and Instrumentation, Pearson Education Publications, 2009

4. H.S. Kalsi, Electronic Instrumentation, Tata McGraw-Hill Education, 2004

Reference Books:

1. Devdas Shetty and Richard Kolk, Thomson, Mechatronics System Design, Cengage Learning, 2nd Edition, 20112. Mahalik, Mechatronics, Tata McGraw-Hill Education, 20033. HMT, Mechatronics, Tata McGraw-Hill Education Pvt. Ltd., 20004. Lawrence J. Kamm, Understanding Electro-Mechanical Engineering: An Introduction to Mechatronics, PHI,

1995

Course Outcome (COs):At the end of the course, the students will be able to

1. Explain various mechatronic components. [L2]2. Understand how mechatronics systems can be designed and developed. [L1]3. Understand the functioning of Micro Electro Mechanical System (MEMS) and their applications. [L1, L3]4. Acquaint themselves with the application of mechatronics systems in various engineering applications.[L1,

L3]


1. Graduates shall acquire in-depth knowledge in Mechatronics System Design and update the same, integratingexisting and updated knowledge in global perspective. [PO1]

2. Graduates shall conceptualise through lateral thinking and obtain feasible and optimal solutions for engineeringproblems considering societal and environmental requirements. [PO4]

3. Graduate shall be able to introspect and apply corrections. [PO11]




three


activity


TotalMarks

MaximumMarks

30 10 10 50



2. Question paper contains 08 questions each carrying 20 marks. Students have to answer FIVE full questions. SEEquestion paper will have two compulsory questions (any 2 units) and choice will be given in the remaining threeunits.

First SemesterCNC AND ROBOT PROGRAMMING LAB





Course Learning Objectives (CLOs):

1. To enable the students to write and generate toolpath for Milling programs for prismatic & cylindricalfeatures.

2. To enable the students to write and generate toolpath for Lathe programs for cylindrical features..3. To enable the students to write and simulate robot programming for simple tasks.

List of Experiments:1. Demonstrate the user interface for FANUC programming and the G/M Codes used

2. Develop a program for Drilling/ Reaming of holes

3. Develop a program for contour with linear and circular interpolation

4. Develop a program to mill a pocket using canned cycle

5. Develop a program for milling a slot and drilling/reaming holes

6. Develop a program for facing & step turning operations

7. Develop a program for facing, step turning and drilling a cylindrical component

8. Develop a program for multiple turning operation

9. Demonstrate the user interface for Robot programming

10. Develop a program for pick & place operation for a robot

Manuals and Books:1. MTAB Manual for Mill and Lathe programming, MTAB Engineers Pvt Ltd, Chennai.2. P.N. Rao, CAD/CAM Principles and Applications, McGraw Hill Education Pvt Ltd., 3rd Edition, 2010.

Course Outcomes (COs):After the completion of the course the students will be able to:1. Write & simulate toolpath for machining contours, pockets, holes and other machining features. [L3]2. Write & simulate toolpath for machining tapers, steps and other machining features. [L3]3. Write & execute programs for making the robot perform simple tasks. [L3]


PO-1: [Scholarship of Knowledge]Graduates shall acquire in-depth knowledge in manufacturing and update the same, integrating existing

and updated knowledge in global perspective.

PO-5: [Usage of modern tools]Graduates shall be able to adopt modern techniques, analytical tools and softwares for complex

engineering solutions.

Scheme of Continuous Internal Evaluation (CIE) for Lab:

CIE

Conduct of lab 10

25Journal 10

Lab test 5

Scheme of Semester End Examination (SEE) for Lab:

SEE Final examinationConduct of experiments 20

25Viva- voce 5

Second Semester

ADVANCED FOUNDRY TECHNOLOGY



Hours/week: L – T –P 4 – 0 – 0 SEE Marks: 50


Course Learning Objectives(CLO’s):

To make student understand1. Foundry metallurgy and concept of solidification of metals. Interpretation and use of cooling

curves2. Design principles of Casting, Gating and Riser system3. Advanced melting techniques and quality control of castings.4. Cast iron foundry, particular attention to grey cast iron, ductile iron and malleable iron5. Aluminum alloy foundry practice discussing principal alloys such as Al-Si, Al-Cu and Al-Zn-Mg6. Copper alloy foundry practice7. Automation and Modernization of foundry. Robotic applications

Pre-requisites: Basic Knowledge of Foundry technology and material science

Detailed Syllabus:

UNIT –I ` 10 Hours

Foundry Metallurgy: Oxidation of liquid metals, gas dissolution in liquid metals, methods of degassing,fluidity, factors affecting fluidity, fluidity tests, hot tearing, Shrinkage of liquid metals.Solidification of Casting: Concept of solidification of metals. Homogenous and heterogeneousnucleation. Growth mechanism. Solidification of pure metals and alloys. Mechanism of columnarand dendritic growth. Coring or Segregation. Solidification time and Chvorinov’s rule. Concept ofprogressive and directional solidification. Interpretation and Use of Cooling Curves(Thermal Analysis), X-Ray Imaging of Solidification Processes and Microstructure Evolution

UNIT–II 10 Hours

Casting Design: Initial considerations in design, Functional design, Simplification of foundry practices,Metallurgical design, Economic considerations.Riser Design: Types of risers and their application, Optimum riser design, Feed metal volume, Riserlocation, Progressive and directional Solidification, Feeding Distance, NRL method, Feeding aidsused in riser design, Factors in riser size, computerized method of riser design.Gating Design: Components of Gating system, Effects of gates on aspiration, turbulence and drosstrap, Pressurized versus unpressurized systems, Vertical versus horizontal gating systems.

UNIT–III 10 Hours

Furnace Technology: Cupola and its recent developments, charge calculation, Electron Beam Melting,Plasma Melting and Heating, Electro slag, Re melting.Self-Learning Topics: Casting Defects & Quality Control Casting defects: Shaping faults arising inpouring, Inclusions and sand defects, Gas defects, Shrinkage defects, Contraction defects,Dimensional errors, Compositional errors and segregation. Different inspection and testing methods toevaluate the casting. Coating of Castings, Quality control activities in a foundry

UNIT–IV 10 Hours

Grey cast iron foundry practice: Melting practice, Inoculation, grey iron alloying, pouring, Gating andfeeding systems, Foundry properties and engineering properties, Specification, Heat treatment,Applications.Ductile iron foundry practice: Melting practice, Desulfurization methods, Composition control, magnesiumtreatment, inoculation, casting and solidification, Engineering Properties, Austempered Ductileiron(ADI),Applications.Malleable iron foundry practice: Melting practice, Structure of White-heart and black-heart malleablecast iron, Pearlitic malleable iron, Properties and applications.Self-Learning Topics:Cast Iron MetallurgyClassification of cast iron, Composition and graphitization, Carbon equivalent, Graphite morphology,effect of various elements. Special casting processes Investment casting, Die casting, centrifugal casting,full mould casting, vacuum shield casting etc

UNIT–V 10 Hours

Soft Material foundry Practice: Aluminum casting-Composition, properties and application of commonaluminum alloy casting, Melting and casting of aluminum alloys, Gating and risering of Al-alloy casting,Copper alloy foundry practice- General characteristics of common cast copper alloys, Melting and casting ofcopper alloys, Gating and risering of copper alloy castings.Foundry Automation and Modernization: Introduction to modernization. Mechanization of foundry and itsadvantages. Mechanization of sand plant, moulding and core making mechanization in melting,pouring and shake out units. Material handling equipments and conveyor systems. Foundry roboticapplications.

Text Books1. R W Heine,C R Loper, and P C Rosenthal, Principles of Metal Casting, Tata McGraw Hill, 19762. P.R. Beelely, Foundry Technology, Butterworth ,20013. Titov Stepnov, Foundries practice4. M.Lal and O.P. Khanna, A Text Book of Foundry Technology, Dhanpat Rai & Sons ,2007

Reference Books:1. ASM Handbook, Casting, Vol. 15, ASM Publication, Materials Park, Ohio,2008.2. Hans Roedter, The Essential of Gating and Risering system Design, Rio Tinto Iron and Titanium

Inc.20003. P.C. Mukherjee, Fundamentals of Metal casting Technology4. P.D.Webster, Fundamentals of Foundry Technology

Course Outcomes(COs):1. At the end of course students will be able to design casting, gating and risering systems [L6].2. The students will get a clear thought on importance of solidification of advanced alloys,

interpretation of cooling curves, imaging of solidification process and microstructure evaluation [L3].

3. The student will recognize the different types of melting and molding techniques for a particularalloy[L2].

4. They will be able to appraise control casting quality, knowledge in inspection, testing methods andstatistical quality control activities[L5].

5. Ability to use the methods, skills and engineering tools to produce castings of grey cast iron, ductileiron and malleable iron[L3]

6. Develop foundry practice for advanced soft materials[L6].7. Ability to implement computer and robot technology in the foundry process to meet desired

needs and to function on multi disciplinary team[L5]8. Broad education to understand the impact of mechanization in melting, pouring and material

handling[L2].

Program Outcomes(POs) of the course:1. Graduates shall acquire in-depth knowledge and update the same, integrating existing and updated

knowledge in global perspective. [PO1]


3. Graduates shall conceptualize through lateral thinking and obtain feasible and optimal solutions forengineering problems considering societal and environmental requirements . [PO3]

Self Study topics shall be evaluated during CIE (Assignments and IA tests) and 10% weightage shall be givenin SEE question paper.





Mini ProjectTotal

Marks

MaximumMarks

30 10 10 50




Second SemesterINDUSTRIAL ROBOTICS


Course Type: PC CIE Marks: 50 marks

Hours/week: L – T – P 4-0-0 SEE Marks: 50 marks



1. To introduce the basic concepts, parts of robots and types of robots.

2. To study different robot transformations and sensors.

3. To study the kinematics and dynamics of different standard configuration ofmanipulators.

4. To make the student familiar with the various drive systems for robot, sensors and theirapplications in robots.

5. To understand various control systems and their applications in robot

Prerequisites: Basic knowledge of mathematics- matrices, control systems.

Detailed Syllabus:

UNIT –I 10 Hours

Introduction: Automation and Robotics, Historical Development, Definitions, Basic Structure of Robots,Robot Anatomy, Complete Classification of Robots, Fundamentals about Robot Technology, Factorsrelated to use Robot Performance, Basic Robot Configurations and their Relative Merits and Demerits,Types of Drive Systems and their Relative Merits, the Wrist & Gripper Subassemblies.ROBOT TRANSFORMATIONS: 2D and 3D Transformation-Scaling, Rotation, Translation- Homogeneouscoordinates, multiple transformation-Simple problems.Self learning topics: Automation and Robotics, Historical Development, Definitions, Basic Structure ofRobots, Robot Anatomy, Complete Classification of Robots, Fundamentals about Robot Technology,Factors related to use Robot Performance, Basic Robot Configurations and their Relative Merits andDemerits

UNIT –II 10Hours

Kinematics of Robot Manipulator: Introduction, General Description of Robot Manipulator,Homogenous Representation of Objects, Robotic Manipulator Joint Co-Ordinate System, Euler Angle &Euler Transformations, Roll-Pitch-Yaw(RPY) Transformation, Direct & Inverse Kinematics Solution, D HRepresentation & Displacement Matrices for Standard Configurations.

UNIT –III 10Hours

Dynamics of Robotic Manipulators: Introduction, Brief Discussion on Lagrange–Euler (LE) DynamicModeling of Robotic Manipulators: - Preliminary Definitions, Generalized Robotic Coordinates, DynamicConstraints, Newton’s Equation, Euler Equation, The Lagrangian & Lagrange’s Equations. Applications ofLagrange– Euler (LE), Dynamic Modeling of Robotic Manipulators: - Velocity of Joints, Kinetic Energy ofArm, Potential Energy of Robotic Arm, The Lagrange of two Link Robotic Dynamics with Distributed Mass.

UNIT –IV 10 Hours

Robotic Motion Trajectory Design: – Introduction, Trajectory Interpolators, Basic Structure of TrajectoryInterpolators, Cubic Joint Trajectories. General Design Consideration on Trajectories:-4-3-4 & 3-5-3trajectories.Robot Teaching: Introduction, Various Teaching Methods, Task Programming, Survey of Robot LevelProgramming Languages, WAIT, SIGNAL & DELAY Commands, various Textual Robot Languages Such as VALII, RAIL, AML and their Features, Typical Programming Examples such as Palletizing, Loading Etc.

UNIT –V 10 Hours

Robot Sensing & Vision: Various Sensors and their Classification, Use of Sensors and Sensor BasedSystem in Robotics, Machine Vision System, Description, Sensing, Digitizing, Image Processing andAnalysis and Application of Machine Vision System.Industrial Applications: Objectives, Automation in Manufacturing, Robot Application in Industry, TaskProgramming, Goals of AI Research, AI Techniques.Self learning topics: Objectives, Automation in Manufacturing, Robot Application in Industry, TaskProgramming, Goals of AI Research, AI Techniques.

Text Books:

1. Mohsen Shahinpoor, A Robot Engineering Textbook, Harper & Row publishers, New York, 1987.

2. S. B. Niku, Introduction to Robotics Analysis, Systems, Applications, Pearson Education, 2008.

3. Fu, Lee and Gonzalez, Robotics, control vision and intelligence, McGraw Hill International, 1987.

4. J. J. Craig, Introduction to Robotics: Mechanical and Control, Addison-Wesley, 2nd

edition 1989.

Reference Books:

1. R. J. Schilling, Fundamentals of Robotics, Analysis and Control, PHI, 2006

2. Yoram Koren, Robotics for Engineers, McGraw Hill International, 1985.

3. Groover, Weiss, Nagel, Industrial Robotics, McGraw Hill International, 1986.

4. Keramas, Thomson, Robot Technology Fundaments, Vikas Publication House, 1999.

5. Klafter, Chmielewski and Negin, Robotic engineering - An Integrated approach, PHI, 1989.

6. Mikell. P. Groover, Industrial Robotics Technology-Programming and Applications, McGraw Hill Co,1995

Course Outcomes (COs):At the end of the course, the student will be able to,

1. Familiarize with the history, concept development and key components of robotics technologies[L2].

2. Understand basic mathematic manipulations of spatial coordinate representation andtransformation [L2, L4].

3. Understand and able to solve basic robot forward and inverse kinematics problems [L2, L3].

4. Understand and able to solve basic robotic dynamics, path planning and control problems [L2, L3].

5. Understand and demonstrate principles of various Sensors and their applications in robots [L2].

Program Outcomes (POs) of the course:PO-2: [Critical Thinking]Graduates shall possess ability for independent judgement based on critical analysis and also for synthesis ofinformation for extensive research in the area of specialization.PO-3: [Problem Solving]Graduates shall conceptualise through lateral thinking and obtain feasible and optimal solutions forengineering problems considering societal and environmental requirements.PO-4: [Research Skill]Graduates shall review relevant literature, apply appropriate research methodologies, working individually or

as a team contributing to the advancement of domain knowledge.PO-5: [Usage of modern tools]Graduates shall be able to adopt modern techniques, analytical tools and softwares for complex engineering

solutions.




tests out of three


activity


TotalMarks

MaximumMarks

30 10 10 50




Second SemesterNON TRADITIONAL MACHINING

Course Code 16CIM23 Credits 4

Course type PC CIE Marks 50 marks

Hours/week: L-T-P 4-0-0 SEE Marks 50 marks

Total Hours: 50 SEE Duration 3 Hours


1. To introduce the concept of non-traditional machining (NTM) processes and the need/scope ofthose processes.

2. To present an overview of classification and comparison between conventional and non- conventionalmachining process.

3. To lay a firm foundation with regard to the principles, equipments and applications of NTM processeswith emphasis on the latest developments.

4. To analyze some of the NTM processes with regard to the material removal rate (mrr) and to solverelated engineering problems.

Pre-requisites: Basic knowledge of Conventional manufacturing and its concepts.

Detailed Syllabus:

Unit I 10 Hours

Introduction: History, Classification, comparison between conventional and Non- conventionalmachining, process selection.

Ultrasonic Machining (USM): Introduction, equipment, tool materials & tool size, abrasive slurry,Acoustic Head, Tool Feed Mechanisms, Mechanics of USM, Expression for MRR:- Effect of processparameters: Effect of amplitude and frequency and vibration, Effect of abrasive grain diameter,effect of applied static load, effect of slurry concentration, tool & work material, USM processcharacteristics: Material removal rate, tool wear, Accuracy, surface finish, Numerical Problems.

Self Learning Topics: applications, advantages & Disadvantages of USM, Latest Developments.

Unit II 10 Hours

Abrasive Jet Machining (AJM): Introduction, Equipment, Variables in AJM: Carrier Gas, Type ofabrasive, size of abrasive grain, velocity of the abrasive jet, mean number, abrasive particles per unitvolume of the carrier gas, work material, stand- off distance (SOD), nozzle design, shape of cut. Processcharacteristics-Material removal rate, Nozzle wear, Accuracy & surface finish. Applications, advantages &Disadvantages of AJM. Water Jet Machining (WJM): Principal, Equipment, Operation, Application.Self Learning Topics: Advantages and limitations of water Jet machining, Abrasive water Jet machining,Latest Developments in AJM, WJM

Unit III 10 Hours

Electrochemical Machining (ECM): Introduction, study of ECM machine, elements of ECM process : Cathodetool, Anode work piece, source of DC power, Electrolyte, chemistry of the process, ECM Processcharacteristics – Material removal rate, Kinematics and Dynamics of ECM, Accuracy, surface finish,

Selective Dissolution, Effect of Heat and Hydrogen Gas Bubbles, ECM Tooling: ECM tooling technique &example, Tool & insulation materials, Tool size Electrolyte flow arrangement, Handling of slug, Economicsof ECM, Applications such as Electrochemical turning, Electrochemical Grinding, Advantages, Limitations.Numerical Problems, Latest Developments.

Chemical Machining (CHM): Introduction, elements of process, chemical blanking process : Preparation ofwork piece, preparation of masters, masking with photo resists, etching for blanking, accuracy ofchemical blanking, applications of chemical blanking, chemical milling (contour machining): process steps –masking, Etching, process characteristics of CHM: material removal rate, accuracy, surface finish, advantages& application of CHM. Latest Developments.

Self Learning Topics: Electrochemical Honing, Electrochemical De-burring, Hydrogen embrittlement

Unit IV 10 Hours

Electrical Discharge Machining (EDM): Introduction, mechanism of metal removal, EDM Circuits andOperating Principles, dielectric fluid, spark generator, EDM tools (electrodes) Electrode feed control,Electrode manufacture, Electrode wear, EDM tool design, choice of machining operation, electrodematerial selection, under sizing and length of electrode, machining time. Flushing; pressure flushing,suction flushing, side flushing, pulsed flushing synchronized with electrode movement, EDM processcharacteristics: metal removal rate, accuracy, surface finish, Machining Accuracy, Heat Affected Zone.Machine tool selection, Application, EDM accessories / applications, electrical discharge grinding.Numerical Problems.Self Learning Topics: traveling wire EDM, Latest Developments

Unit V 10 Hours

Plasma Arc Machining (PAM): Introduction, equipment, non-thermal generation of plasma, selection of gas,Mechanism of metal removal, PAM parameters, process characteristics, PAM Torch, Accuracy and SurfaceFinish, Metallurgical Effects, Safety precautions, Latest Developments.

Laser Beam Machining (LBM): Introduction, equipment of LBM mechanism of metal removal, LBMparameters, Process characteristics. Numerical Problems, Latest Developments.Electron Beam Machining (EBM): Principles, Mechanics of EBM equipment, operations. NumericalProblems, Latest Developments.Self Learning Topics: applications, advantages and limitation of PAM, EBM and LBM.

Text books:1. Pandey and Shan, Modern Machining Process, Tata McGraw Hill, 2000.

2. Amitabha Ghosh and Asok Kumar Mallik, Manufacturing Science, Affiliated East-West Press Pvt. Ltd.,New Delhi, 2010.

Reference books:1. HMT, Production Technology, Tata McGraw Hill, 2001

2. P.K.Mishra, Non-Conventional Machining, The Institution of Engineers (India) Test book series,Narosa Publishing House, 2005.

3. NPTEL Notes nptel.ac.in/downloads/

Course Outcome (COs):At the end of the course, the student should be able to:

1. Explain the concept and evolution of Non -Traditional Machining (NTM) processes. [L2]2. Explain equipment, mechanism of material removal and effect of different process parameters in the

mechanical NTM processes (AJM, USM, WJM) and thermal NTM processes (EDM, PAM, LBM, EBM) [L3,L4]

3. Explain equipment, mechanism of material removal and effect of different process parameters in thechemical and electrochemical NTM processes (CHM, ECM) [L3, L4]

4. Solve numerical problems and explain latest developments related to NTM processes. [L4]


1. Graduates shall acquire in-depth knowledge in manufacturing and update the same, integrating existingand updated knowledge in global perspective. [PO1]

2. Graduates shall conceptualise through lateral thinking and obtain feasible and optimal solutions forengineering problems considering societal and environmental requirements. [PO3]

3. Graduates shall be able to adopt modern techniques, analytical tools and softwares for complexengineering solutions. [PO5]




three


activity


TotalMarks

MaximumMarks

30 10 10 50


calculation of SGPA and CGPA.


Second SemesterFLEXIBLE MANUFACTURING SYSTEMS



Hours/week: L – T – P 4 – 0 – 0 SEE Marks: 50


Course Learning Objectives (CLO’s):

1. To impart the concept & need for flexibility in manufacturing industries.2. To impart the knowledge required to develop and implement an FMS.3. To study the different types of automated material transport systems its design and analysis

for different applications both AS/RS and Carousel storage system.4. To understand the concepts of group technology and cellularmanufacturing.5. To learn the perception of aggregate production planning, master production schedule, MRPand

Inventory control.

Pre-requisites: Basics of manufacturing processes and computer integrated manufacturing.

Detailed Syllabus:

UNIT –I ` 10 Hours

Definition of an FMS: Types, configurations & concepts – Types of flexibility & performance measures.Function of FMS host computer, FMS host and area controller function distribution.Development and implementation of an FMS: Planning phase, Integration, System configuration, FMSlayouts, Simulation, FMS Project development steps.Self learning topics: Projectmanagement, Equipment development, Host system development, planning, andHardware & Software development.

UNIT –II 10 Hours

Automated Material Handling & Storages systems: Functions, Types, Analysis of material handlingequipments, Design of Conveyor & AGV systems. Benefits of Automated material handling systems.Problems. Storage system performance, AS/RS, Carousel storage system, WIP storagesystem

UNIT–III 10 Hours

Group Technology and Cellular Manufacturing: Introduction, Part families, parts classification and coding,production flow analysis, Machine cell design, Benefits of Group Technology.Quality programs for manufacturing: Quality in design and manufacturing, Traditional and Modernquality control, Process variability Process Capabilty , SPC and Sixsigma.

UNIT –IV 10 Hours

Production Planning & Control system : Aggregate production planning and master productionschedule, material requirement planning,Just-In-Time : Definition JIT, Concept, ObjectivesSelf learning topics: Capacity planning, shop floor control, Inventory control, Extension of MRP.

UNIT –V 10 Hours

Scheduling: Introduction, Scheduling of operations on a single machine, 2 machine flow shop scheduling, 2machine job shop scheduling, 3 machine flow shop scheduling, scheduling ‘n’ operations on ‘n’ machines,Scheduling rules, loading problems , Tool management of FMS, material Handling system schedule.Problems.

Text Books1. M.P. Groover, Production Systemsand Computer IntegratedManufacturing, Automation,Prentice Hall

India (P) Ltd,2008.2. D J Parrish, Butter Worth , Flexible manufacturing – Heinemann, Ltd Oxford, 1993.3. William W. Luggen, Flexible Manufacturing Cells & Systems –Prentice hall, NJ.

Reference Books:1. D M Considine, and G D Considine, Standard Handbook of Industrial Automation -

Chopman and Hall, London, 1986.

Course Outcomes (COs):1. Students will learn and understand the concepts, techniques and applications of flexible

Manufacturing System [L2].2. The students will be able to describe an FMS system in present manufacturing

scenario [L2].3. The student will understand the different types of FMS layouts, material transport and retrieval

systems [L2].4. To solve the sequencing problems for different cases and toolmanagement [L3].


PO-1: [Scholarship of Knowledge]Graduates shall acquire in-depth knowledge in manufacturing and update the same, integrating existing andupdated knowledge in global perspective.

PO-5: [Usage of modern tools]Graduates shall be able to adopt modern techniques, analytical tools and softwares for complex engineeringsolutions.

PO-8: [Communication]Graduates shall possess communication skills to comprehend, document and present effectively to theengineering community and society at large.


Scheme of Continuous Internal Evaluation(CIE):The Total marks of CIE shall be 50 (three tests of 30 marks each, two Assignments of 10 marks each andquiz/course seminar/course project of 10 marks each). The weightage of CIE is as shown in the tablebelow.

Component Average of best2 Tests

Average of 2Assignments

Quiz/Seminar/Project

TotalMarks

Maximum marks 30 10 10 50




Second Semester

ADVANCED TOOL ENGINEERING DESIGN


CourseType: PE CIE Marks: 50


Total Hours: 50 SEE Duration: 3Hours

Course Learning Objectives(CLOs):1. To impart the basic concepts and fundamentals of Tool engineering, its techniques and

applications2. To comprehend the relationship between Tool s and Machine tool3. To enhance awareness in the recent aspects of Tool engineering

Pre-requisites: Basic Knowledge of machine tools and cutting tools and also machining process.

Detailed Syllabus:

UNIT–I 10hours

Introduction to tool design of Single point Cutting ToolsIntroduction to tool design: Tooling, requirements of a tool designer, general tool design procedure.Design of Single point Cutting Tools. Design of single point lathe tool. Design of shank dimension usingstrength and rigidity considerations for rectangular, square and round cross section and selection of toolgeometry.Self Learning Topics: Solid type tool, brazed tip tool, long indexable insert, throwaway index able inserttypes and chip breakers.

UNIT–II 10hours

Design of Multi Point Cutting ToolDesign of milling cutter. Design of elements like number of teeth and height circular pitch, bodythickness, chamfer width, fillet radius and selection of tool geometry.Self Learning Topics: Drill bit design of elements like back taper, web thickness, land width, margin, flutelength and cross section and selection of tool geometry.

UNIT–III 10hours

Design of Jigs and FixturesFunctions and differences between jigs and fixtures ,advantages in mass production, design principles,economics of jigs and fixtures. Principles of location -3-2-1 and 4-1-1 types of locations, different typesof locating elements. Clamping – Principles of clamping, types of clamping including power clampingdevices. Drill jigs- Types, Drill bushes, simple exercises of designing jigs for given components. FixtureDesign turning fixtures, milling fixtures, grinding and broaching fixtures, indexing fixtures. Design offixtures for simple components.

UNIT–IV 10hours

Design of Sheet MetalWorking of a power press and classification of presses. Components of a simple die, press tool operation,die accessories, shearing action in punch & die, clearance ,shear on punch and die, Centre of pressure andproblems, scrap strip layout. Simple, progressive, compound, combination and inverted dies. Designproblems on blanking and piercing dies for simple components.

Injection MoldingInjection moulding machine and its elements, general configuration of a mould. 2 plate and 3 plate mould.Introduction, to gate, runner, parting surface, ejection system. Core and cooling system. Introduction tocompression, transfer, blow moulding, extrusion, forming and calendaring.

UNIT–V 10hours

Die Casting DiesTerminology: Core, cavity, sprue, slug, fixed and movable cores, finger cams, draft, and ejector pins ejectorplates, gate, goose nozzle, over-flow, platten, plunger, runner, vent, water-line etc. Types of Dies: Singlecavity, multicavity dies, combination dies, unit dies, advantages and disadvantages of types of dies. Diecasting dies, unit dies. Advantages and disadvantages of types of dies. Die casting alloys, defects in diecasting, finishing trimming and inspection of die casting components, safety, and modern trends in diecasting dies.

TextBooks:1. C. Donaldson, G.H.LeCain ,V.C.Goold , Tool Design, Tata McGraw Hill pub.19762. M.H.A Kempster, Introduction to Jigs and Fixture Design ,Elbs Edition1974.

ReferenceBooks:1. P.N.Rao, Manufacturing Technology (Foundry, Forming and Welding) Tata Mcgraw Hill

Publication Edition1996.2. RGW Pye John, Injection Moulding Design,19983. D. V. Rosato& Donald V. Rosato Injection Moulding Handbook, CBS Publishers 1996

Course Outcomes(COs):1. Students will learn the concepts, techniques and applications of Tool Design engineering [L2]2. Students will learn the working concepts of Fixturing and various tools of engineering [L2]

Program Outcomes (POs) of the course:1. Graduates shall acquire in-depth knowledge and update the same, integrating existing and

updated knowledge in global perspective. [PO1]


3. Graduates shall conceptualize through lateral thinking and obtain feasible and optimal solutionsfor engineering problems considering societal and environmental requirements . [PO3]






Mini ProjectTotal

Marks

MaximumMarks

30 10 10 50




Second Semester

NON DESTRUCTIVE TESTING


Course type PE CIE Marks 50 marks




To make student understand1. The concept & need for inspection equipment and techniques.2. The different methods of non destructive evaluation.

Pre-requisites: Basic knowledge of Inspection techniques

Detailed Syllabus:

Unit I 10 Hours

Introduction to ND Testing: Visual Inspection, Laser Inspection, Coordinate Measuring Machine. MachineVision and Robotic Evaluation. Leak Testing.Self Learning Topics: Liquid PenetrantInspection

Unit II 10 Hours

Magnetic Particle Inspection - Methods of generating magnetic field, types of magnetic particles andsuspension liquids steps in inspection.Eddy Current Inspection- principles, operation variables, procedure, inspection coils, and detectablediscounts by themethodSelf Learning Topics: applicationandlimitations of magnetic particle inspection

Unit III 10 Hours

MicrowaveInspection: Microwaveholography,applicationsandlimitationsUltrasonic Inspection- Basic equipment characteristics of ultrasonic waves, variables inspection, inspectionmethods pulse echo A,B,C scans transmission, resonance techniques, search units, contact types andimmersion types inspection standards-standards reference books.Self Learning Topics: transducer elements couplets

Unit IV 10 Hours

Acoustic Emission Inspection- relationship to other test methods, range and applicability, acoustic emissionwaves and propagation, acoustic emission sensors and preamplifiers, instrumentation principles, acousticemission in material studies.Radiographic Inspection- principles, radiation source X-rays and gamma rays, X-ray-tube, radio graphic films,neutron radiography, Thermal inspection principles, equipment inspection methods applications.

Unit V 10 Hours

Neutron Radiography- Principles of neutron radiography, attenuation of neutron beams, applicationsOptical Holography- Basics of Holography, recording and reconstruction - Acoustical Holography: systemsand techniques applications.Self Learning Topics: neutron detection methods, IndianstandardsforNDT.

Text Books1. ASM Handbook , NonDestructiveEvaluationandQualityControl– Vol 17, 2001.2. Baldev Raj, T.Jayakumar . and M. Thavasimuthu, Practical NondestructiveTesting, Narosa

Publishing House,2002

Reference Books:1. R.K .Jain, Engineering Metrology, Khanna Publishers, 19972. Progress in Acoustic Emission’, Proceedings of 10th International Acoustic Emissionsymposium,

Japanese society forNDT,19903. Barry Hull and Vernon John, Non Destructive Testing, Macmillan, 1988

Course Outcome (COs):1. Students will understand the concepts, techniques and applications of non destructive testing [L2].2. The students will describe the importance of non destructive testing in present inspection

world [L2].3. The student will learn and explain the different types of different non destructive methods [L2].

Program Outcomes(POs) of the course:1. Graduates shall acquire in-depth knowledge in manufacturing and update the same, integrating existing

and updated knowledge in global perspective.[PO1]2. Graduates shall possess ability for independent judgement based on critical analysis and also for synthesis

of information for extensive research in the area of specialization.[PO2]3. Graduates shall be able to adopt modern techniques, analytical tools and softwares for complex

engineering solutions. [PO5]




three


activity


TotalMarks

MaximumMarks

30 10 10 50




Second SemesterARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS


Course Type: PE CIE Marks: 50 marks

Hours/week: L – T – P 4-0-0 SEE Marks: 50 marks



1. The course is aimed at providing a complete overview Artificial Intelligence and Expert System.2. The course is aimed in order to make the student aware of significance of AI & expert

System’s application in advanced manufacturing applications

Prerequisites: Basic knowledge of control systems.

Detailed Syllabus:

UNIT –I 10 Hours

Human and Machine Intelligence; Concepts of fifth generation computing, programming AIenvironment, developing artificial intelligence system, definition of Expert systems, Natural Languageprocessing, neural networks.Tools for Machine Thinking: Forward chaining, backward chaining, use of probability and fuzzylogic.

UNIT –II 10 Hours

Expert System Development: Choice of Domain, collection of knowledge base, selection ofinference mechanism, case studies of expert system development in design and manufacturing.Advanced Programming Techniques: Fundamentals of object oriented programming, creating structureand object, object operations, involving procedures, programming applications, object oriented expertsystem.


Languages in AI: Using PROLOG to design expert systems, converting Rules to PROLOG, Conceptualexample, introduction to LISP, Function evaluation, Lists, Predicates, Rule creat io n .

UNIT –IV 10 Hours

Advanced knowledge representation for smart systems: Semantic nets-structure and objects, ruledsystems for semantic nets, certainly factors, Automated learning

Expert System Tools: General structure of an expert system shell, examples of creation of an expertsystem using an expert system tool.

UNIT –V 10 Hours

Industrial Application of AI and Expert systems: Robotic vision systems, Image processing techniques,application to object recognition and inspection, automatic speech recognition.Self learning topics: Robotic vision systems, Image processing techniques, application to object

recognition and inspection, automatic speech recognition.

Text Books:1. Robert Levine et al, A Comprehensive guide to AI and Expert Systems, McGrawHill Inc, 1986.

Reference Books:1. Henry C. Mishkoff, Understanding AI, BPB Publication, New Delhi, 1986.

Course Outcomes:At the end of the course, the student shall be able to,

1. understand human and Machine Intelligence [L2].2. Understand tools for machine thinking and associated advanced programming techniques [L2, L3]3. Demonstrate the application of AI & expert systems in industry [L1, L2].

Program Outcomes (POs) of the course:PO-2: [Critical Thinking]Graduates shall possess ability for independent judgement based on critical analysis and also for synthesis ofinformation for extensive research in the area of specialization.PO-3: [Problem Solving]Graduates shall conceptualise through lateral thinking and obtain feasible and optimal solutions forengineering problems considering societal and environmental requirements.PO-4: [Research Skill]Graduates shall review relevant literature, apply appropriate research methodologies, working individually or

as a team contributing to the advancement of domain knowledge.PO-5: [Usage of modern tools]Graduates shall be able to adopt modern techniques, analytical tools and softwares for complex engineering

solutions.




three


activity


TotalMarks



calculation of SGPA and CGPA.


Second SemesterADVANCED CONTROL ENGINEERING


Course type PE CIE Marks 50 marks




1. To study various control techniques used in industrial automatic controls.2. To study various frequency response methods.3. To study various response and system compensation methods.4. To get exposure of digital control systems.

Pre-requisites: Should have knowledge of Basic Electronics and Control Engineering

Detailed Syllabus:

Unit I 10 Hours

Introduction to Automatic Controls: Steady-State Operation, Laplace Transforms.The Root-Locus Method: - Introduction, Root Locus Plots, Illustrations, General rules for Constructing RootLoci, Root Locus Analysis of Control Systems, Transport Lag and Root contour Plots.

Self Learning Topics: Representation of Control Components, Representation of Control Systems,Characteristic functions.

Unit II 10 Hours

Frequency Response Methods: - Introduction, Evaluating the Gain K, Equivalent Unity-Feedback Systems.Polar Plots, M And α Circles, Correlation between Transient and Frequency Response, Determining theGain K to Yield a Desired Mp, Relative Stability.

Self Learning Topics: Frequency Response, Logarithmic Representation

Unit III 10 Hours

System Compensation: Gain Margin and Phase Margin, Lead Compensation, Lag Compensation, Lag-LeadCompensation.

Self Learning Topics: Nyquist Stability Criterion

Unit IV 10 Hours

State-Space Methods: - Introduction, Basic materials in State-Space Analysis, Transfer Matrices,Controllability, Observability, System Representation, Signal Flow Graphs, Solution of State-SpaceEquations, Transform Functions and Multivariable Systems.

Unit V 10 Hours

Digital Control Systems: - Sampled-Data Systems, The Z Transform, Inverse Z Transforms, Block-DiagramAlgebra, Transient Response, Filters. Discrete Data Systems, Sampled-Data Control Systems, Computer-Controlled Systems.

Books:Text Books:

1. Francis H. Raven, Automatic Control Engineering, McGraw- Hill International, Third edition,1978.

2. K. Ogata, Modern Control Engineering, PHI, Fifth edition, 2010.

Reference Books:

1. B.C. Kuo, Automatic Control Systems, Prentice hall, Third edition, 1975.

2. Rao V. Dukkipati, MATLAB for Mechanical Engineers, 1st Edition, New Age InternationalPublishers, 2008

Course Outcome (COs):At the end of the course, the student will be able to:

1. Understand various control techniques used in modern engineering control system[L2, L3]2. Understand various system compensation and response methods [L2, L3].3. Explain digital control systems [L1].

Program Outcomes (POs) of the course:1. Graduates shall acquire in-depth knowledge in manufacturing and update the same, integrating

existing and updated knowledge in global perspective. [PO1]2. Graduates shall possess ability for independent judgement based on critical analysis and also for

synthesis of information for extensive research in the area of specialization. [PO4]3. Graduates shall conceptualise through lateral thinking and obtain feasible and optimal solutions for

engineering problems considering societal and environmental requirements. [PO3]4. Graduates shall be able to engage in collaborative multidisciplinary scientific research for decision

making through rational analysis. [PO6]5. Graduate shall be able to introspect and apply corrections. [PO11]




tests out of threeAverage of two


Mini ProjectTotal

Marks


Scheme of Semester End Examination (SEE):1. It will be conducted for 100 marks of 3 hours duration. It will be reduced to 50 marks for the calculation ofSGPA and CGPA.

2. Question paper contains 08 questions each carrying 20 marks. Students have to answer FIVE full questions.SEE question paper will have two compulsory questions (any 2 units) and choice will be given in the remainingthree units.

Second Semester

RAPID PROTOTYPING AND CASTING ANALYSIS LAB



Hours/week: L – T – P 3 SEE Marks: 25


Course Learning Objectives (CLOs):1. To enable the students to use CAD software for solid modeling2. To enable the students to use RP process and parameters for prototyping3. To enable the students to use Solidcast for casting analysis

List of Experiments:1. Solid modeling using modelers like CATIA/SE of casting component 12. Solid modeling using modelers like CATIA/SE of casting component 23. Solid modeling using modelers like CATIA/SE of casting component 34. Rapid Prototyping system- introduction to FDM process and parameters5. Making the RP parts for simple components6. Introduction to Casting analysis, gating and riser design7. Introduction to Solidcast- Casting parameters and process8. Casting analysis of component using Solidcast, riser design parameters to predict shrinkage.9. Designing of riser, gates in modeling software.

10. Casting analysis of component incorporating riser and gates using Solidcast and Flowcast toreduce shrinkage.

Manuals and Books:1. P.N. Rao, CAD/CAM Principles and Applications, McGraw Hill Education Pvt Ltd., 3rd Edition,

2010.2. Solidcast reference material, Finite Solutions Inc, 20153. Creatr (FDM) RP machine reference manual, Leapfrog, 2014.4. P L Jain, Principles of Foundry Technology, Tata McGraw-Hill Education, Revised edition, 2003.

Course Outcomes (COs):After the completion of the course the students will be able to:1. Apply the tools to model mechanical components. [L2]2. Demonstrate the process to manufacture prototypes using FDM process.[L2]3. Analyze the castings for shrinkage and other defects. [L4]


PO-1: [Scholarship of Knowledge]Graduates shall acquire in-depth knowledge in manufacturing and update the same, integrating existingand updated knowledge in global perspective.

PO-5: [Usage of modern tools]Graduates shall be able to adopt modern techniques, analytical tools and softwares for complexengineering solutions.

Scheme of Continuous Internal Evaluation (CIE) for Lab:

CIE

Conduct of lab 10

25Journal 10

Lab test 5

Scheme of Semester End Examination (SEE) for Lab:

SEE Final examinationConduct of experiments 20

25Viva- voce 5

First and Second SemesterSeminar

Subject Code: 16CIM17/ 16CIM27 Credits: 1


Hours/week: L – T –P 0 – 0 - 1

Total Hours:

Seminar should be based on the literature survey on any topic relevant to Computer Integrated

Manufacturing. It may be leading to selection of a suitable topic of dissertation.

• Each student has to prepare a write-up of about 25 pages. The report typed on A4 sized sheets and

bound in the necessary format should be submitted after approved by the guide and endorsement of

the Head of Department.

• The student has to deliver a seminar talk in front of the teachers of the department and his

classmates.

• The Guide based on the quality of work and preparation and understanding of the candidate

shall do an assessment of the seminar.

karnatak law society’s gogte institute of technology

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