MASTER OF TECHNOLOGY (M.TECH.)

IN

QUALITY, RELIABILITY AND OPERATIONS RESEARCH

 

 

 

PREMABLE

The Indian Statistical Institute initiated the use of Statistical Quality Control and Operations Research in India in the early fifties and started developing these fields through theoretical and applied research, practical training in industry and consultation work. Recognising the need for trained manpower by the industry for conserving the scarce resources in the country through the application of scientific techniques, the Institute started a full-time advanced one-year course in SQC and OR at the post-graduate level in 1964. Later on, this course was converted to a Post Graduate Diploma in SQC and OR of fifteen months’ duration. The Institute also introduced SQC and OR as a field of specialisation in the M.Stat programme in late 1960s, and since then offered the specialisation to meet the growing needs and demands for such specialists from the industry. Meanwhile, significant changes were brought about in our economy with import libaralisation, export thrust and restructuring since late eighties. These changes coupled with the advent of up-to-date quality management and assurance system standards (such as ISO 9000 series) worldover gave an unprecedented thrust for quality improvement of products and services in our country. The demand for trained quality professionals grew. To meet this demand, the Institute started a two-year full-time M.Tech programme in Quality, Reliability and Operations Research in Calcutta, in 1989, in place of the earlier P.G. Diploma in SQC and OR. Besides the above programme, Institute also offers a two year part-time Post-graduate Diploma course in SQC and OR at Chennai and Mumbai and a six month evening certificate course in SQC & OR at Bangalore and Hyderabad for supervisory staff sponsored by their organisations

The course structure, the curriculum and the method of instruction have been continually reviewed and updated taking into consideration the feedback from our students, faculty and the respresentatives from industries in keeping with the changing needs and emphasis of the industry on using most up-to-date quality assurance and management systems (such as, ISO 9000, QS 9000, ISO 14000, TQM etc.) and computers (online and offline)

 

 

CONTENTS

  1. Scope

  2. Duration

  3. Eligibility

  4. Method of Selection

  5. Sponsoring

  6. Course Structure

  1. Semester - I

  2. Semester - II

  3. Semester - III

  4. Semester - IV

  1. General Rules, Method of Examination and Award of Degree

  2. Tuition Fee, Stipend and Caution Deposit

  3. Faculty

  4. Library Rules

  5. Syllabi of Subjects

  1. Semester - I

  2. Semester - II

  3. Semester - III

  1. Back to Main Page

 

 

SCOPE

The Master of Technology in Quality, Reliability and Operations Research is a full time programme and is offered at Kolkata. This programme is intended to produce specialists in Quality Management with emphasis on Statistical Quality Control, Reliability, Operations Research, Computer Software and Management Systems. The programme is designed to offer adequate instruction in the theory and practice of the above disciplines. The objective is to equip students with the basic practical skills with sufficient theory to understand the principles involved in the application and to develop in them the power of systematic thinking and reasoning, practical approach and exposition. Every student, besides undergoing classroom instruction, shall do practical work by way of case studies,dissertation and project work on live problems in factory under the guidance of the expert faculty of ISI. On successful completion of this programme, the students may take up either

  1. a professional career in the field of quality engineering and management in departments of government, semi-government, public/private sector undertakings, industrial organisations, consultancy agencies, or

  2. an academic career for further study and research in theoretical and applied aspects of Quality, Reliability and Operations research in organisations of higher learning and research institutions.

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DURATION

The duration of the course is two years, inclusive of the period of factory training at the end of the first year during the summer and a period of project and dissertation work in the semester IV the second year of the programme. The practical training for the project will be offered at different centres of the SQC and OR Division. During the practical training, the candidates are required to work on live plant problems and to submit project reports which form a part of the curriculum. The field trainings are, as far as possible, arranged in industrial establishments which are clients of the different SQC and OR Units of the Institute. However, where the Institute is not able to arrange training in such plants, the sponsoring organisations should provide training facilities for their nominees either in their own plants or in other plants approved by the Institute. The deputation of a candidate to any plant is at the sole discretion of the Institute.

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ELIGIBILITY

A candidate seeking admission to this course should

    1. be conversant with the following topics :

      2. Mathematics (at graduate level) and knowledge of Physics and Chemistry (at the higher secondary level) ;

    2. possesses any one of the following minimum qualifications :

    1. Master degree in Statistics

    2. Master degree in Mathematics with Probability and Statistics as major subjects.

    3. Bachelor degree in Engineering or Technology, or, any other qualification considered equivalent.

    4. Post-Graduate Diploma/part time Post Graduate Diploma in SQC and OR from the Indian Statistical Institute.

The programme is offered in two streams: Statistics stream and Engineering stream. The candidates with qualifications as in (a), (b) or (d) above are administered admission test in Statistics and Probability, whereas, the candidates with Bachelor’s/equivalent degree in Engineering as in (c) above are administered admission test in Mathematics and Engineering for their admission, (if selected, to the first year of the course in Statistics and Engineering streams respectively). However, the exact nature of the admission test will be decided by an appropriate selection committee.

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METHOD OF SELECTION

 

Admission is based strictly on merit assessed through academic record and performance in the written/oral admission tests and interviews. There is however a provision for admitting a few eligible candidates sponsored by their employers. Advertisements announcing the commencement of the programme and inviting applications for admission are issued around January/February every year in nationally circulated newspapers. Eligible candidates, including sponsored candidates, are required to appear at written/oral selection tests and interviews during May/June. However, sponsored candidates may be admitted on the basis of their suitability alone and not on a competitive basis as may be decided by the Selection Committee at its sole discretion.

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SPONSORING

 

Industrial organisations can sponsor candidates from their establishments for this programme provided they satisfy the eligibility requirements.

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COURSE STRUCTURE

 

The Master of Technology in Quality, Reliability and Operations Research is conducted in four semesters, two semesters each in the first and second years. The courses for study and examinations in each semester are as follows.

 

 

SUBJECTS (COURSES) FOR INSTRUCTION AND GRADES

 

SEMESTER I

Engineering Stream

 

 

 

16 weeks

classes

Statistics Stream

Probability – I

Electrical & Electronics Engineering

Statistical Methods – I

Workshop - I

SQC – I

SQC - I

Operations Research – I

Operations Research - I

Programming Techniques and Data

Structure

Programming Techniques and Data Structure

Quality Management & Systems

Quality Management & Systems

 

 

 

 

 

 

 

 

 

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SEMESTER II

Engineering Stream

 

 

16 weeks

classes

Statistics Stream

Probability – II

Mechanical Engineering

Statistical Methods – II

Workshop - II

SQC – II

SQC - II

Reliability – I

Reliability – I

Instrumentation & Computer Engineering

Instrumentation & Computer Engineering

Industrial Engineering & Management

Industrial Engineering & Management

 

 

 

 

 

 

 

  

* Project I starts from 1 May after Semestral examinations and continues till 31 July. This is included in Semester IV

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SEMESTER III

Engineering and Statistics Stream

Operations Research – II

 

 

 

16 weeks classes

Elective Subjects **

Industrial Experimentation

1.Applied Stochastic Process

Reliability - II

2.Advanced Statistical Methods

Elective - I

3.Advanced Optimisation

Elective - II

4. Software Engineering

Elective - III

5.Data Base Management System

 

6.Advance Reliability

7.Game Theory & Decisions

8.Other selected Subjects as suggested by the Faculty

 

 

 

 

 

 

 

 

 

 

 ** From the above list of elective subjects, the teachers’ committee will decide on the subjects to be offered to the students in a particular semester and also the combination a student may take up.

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SEMESTER IV

Engineering and Statistics Stream

Project - I (Summer, at factory) – 12 weeks

Starting on first working day of May

Dissertation

2 Jan.- Last day of February

Project - II (at factory) - 20 weeks

Starting on first Monday of March

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GENERAL RULES, METHOD OF EXAMINATIONS AND AWARD OF DEGREE

For each course there are two examinations, mid-semestral and semestral (final), except for the courses Dissertation, Project - I and Project - II. The composite score in a course is a weighted average of the scores in the mid-semestral and semestral examinations, home-assignments, practical record-book, etc. (announced at the beginning of the semester). For courses other than Dissertation, Project - I, Project – II, Workshop - I and Workshop - II, the minimum weight given to the semestral examination is 50%.

The attendance requirement is 75% for each course in a semester. If a student fails to attend classes in any course continuously for one week or more, he/she will be required to furnish explanation to the Dean of Studies or the Head, SQC-OR (T&P) Unit or the Class Teacher for such absence. If such explanation is found to be satisfactory by the Teachers’ Committee, then the percentage of attendance is determined disregarding the period for which explanation has been provided by the student and accepted by the Teachers’ Committee.

A student is also required to maintain satisfactory conduct as a necessary condition for taking semestral examination, for promotion and award of degree. Unsatisfactory conduct will include copying in examination, rowdyism, other breach of discipline of the Institute, unlawful / unethical behaviour and the like.

A student will be allowed to take a semestral examination in any course if he / she attends at least 75% of all classes of that course and his / her conduct is satisfactory.

For any semestral examination a student is declared to have passed the examination if he / she

  1. maintains a satisfactory conduct;

  2. does not obtain a score of less than 35% in any course;

  3. does not obtain a score of less than 45% in more than one credit course;

  4. does not obtain a score of less than 45% in OR – I, SQC – I, Workshop – I, Workshop – II, Dissertation, Project – I and Project – II;

  5. secures an average score of at least 45% in all credit courses of that semester.

NOTE: The term ‘score’ mentioned in the preceeding criteria for passing a semester will mean composite score or post backpaper score, as may be applicable.

A student is declared have failed the examination if he / she fails to pass the same.

There is a provision of backpaper examinations in all the courses, except Dissertation, Project - I and Project - II. If the composite score of a student falls short of 45% in a credit course, or 35% in a non-credit course, the student may take a backpaper examination to improve the score. A student is required to take a backpaper examination if the composite score is less than the pass-mark. At most one backpaper examination is allowed in a given course. The post-backpaper score in a course is equal to the maximum of backpaper examination score and composite score, subject to a maximum of 45% .

A student can take a maximum of 2 (two) backpaper examinations in any of the four semesters of the M.Tech.(QROR) programme subject to a ceiling of a maximum of 2 (two) in the first year and 2 (two) in the second year. However, a student may take more than the alloted quota of backpaper examinations in a given academic year and decide at the end of that academic year which of the backpaper examination score / scores should be disregarded for computation of the post-backpaper score / scores. Such communication must reach the Class Teacher, in writing.

If a student misses the mid-semestral or semestral examination due to medical or family emergency he/she may be allowed to take supplementary examination/ at the discretion of the Teachers’ Committee, on the basis of an adequately documented request from the student. The maximum a student can score in any supplementary examination is 60%.

A student admitted to the first year of the programme is allowed to attend the second semester of the programme if he / she passes the first semestral examinations, otherwise he / she has to discontinue the programme.

A student, who takes all the second semestral examinations, will be allowed to go for field training (Project work) otherwise he/she has to discontinue the programme.

A student who passes the second semestral examination and completes the field training (Project work) satisfactorily as certified by the supervisor is promoted to the third semester of the programme, otherwise, he/she has to discontinue the programme.

A student promoted to the third semester of the programme will be allowed to attend the fourth semester of the programme if he / she passes the third semestral examinations.

A student who submits his / her dissertation and project report within the prescribed time limit and passes the fourth semestral examinations and does not obtain less than 45% in dissertation and projects will be declared to have completed the fourth semester of the programme.

If even after the backpaper and supplementary examinations referred to in the preceeding paragraphs the student fails in the first or the second semesteral examinations, he/she has to discontinue the course. However, if he / she fails in the third or the fourth semestral examination even after the backpaper and supplementary examinations, then he / she may be allowed to repeat the second year of the course without stipend. The scores obtained during the repetition of the final year are taken as final scores in the final year. A student is given only one chance to repeat a programme. A student will be asked to discontinue if he / she fails in third or fourth semester of the repeating year.

A student who is asked to discontinue the programme is not eligible for readmission to this programme even through the admission test.

A student gets a degree if his/her conduct is satisfactory and he/she passes all the four semesters and is placed in the

  1. First division with distinction if he/she secures an overall percentage score of at least 75% in all four semesters put together and at most 2 (two) scores less than 45%

  2. First division (with no distinction) if the student secures an overall average percentage of at least 60% and at most 4 (four) scores less than 45%.

  3. Second division if the student passes all four semesters but fails to secure first division with distinction or first division

A student passing the M.Tech.(QROR) degree examination is given a certificate of the degree and a mark-sheet mentioning.

  1. all the credit courses taken and the composite percentage score or the post-backpaper score in each course.

  2. the non-credit courses taken and the composite percentage score or post-backpaper percentage score in each, and

  3. the division in which placed.

The stipend rules for second, third and fourth semesters following the declaration of results of the preceeding semester is as follows:

  1. full stipend and contingency grant will be given to a student if he/she gets an overall percent score of at least 60%,

  2. 50% of the full stipend and 50% of the contingency grant will be given to a student who passes the preceeding semester but fails to secure an overall percent score of at least 60%.

  3. No stipend is awarded to
    1. A repeating student,
    2. A student whose attendance falls short of 75%, overall, in the preceeding semester.

Stipend can be restored because of improved performance and/or attendance, but no stipend is restored with retrospective effect.

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TUITION FEE, STIPEND AND CAUTION DEPOSIT

 

All students other than those sponsored by the employers are awarded full stipend at the time of admission initially for the first semester only. The present rate of stipend is Rs.2500/- (Rupees two thousand five hundred only) per month. The students (other than those sponsored by the employers) are also eligible to receive a contingency grant of Rs.1500/- (Rupees one thousand five hundred only) per semester in reimbursement of cost of text books and supplementary text books, photostat copies of required academic materials, a scientific calculator and other required accessories for the practical classes. All such expenditure should first be approved by the respective class teachers. The payment of stipend and the reimbursement of contingency grant will, however, be governed by the following terms and conditions :

The contingency grant sanctioned will be treated as a limit and the student concerned will be reimbursed the actual expenditure incurred by him on the admissible items within the limit. The grant is not to be paid as an outright payment.

The books and nonconsumable items purchased or acquired out of the contingency grant allowed will be the property of the Institute and the student will have to return them at the end of the course.

The following terms and conditions will govern the grant of the stipend :

  1. It will be obligatory for every student concerned to undertake 8 to 10 hours (per week) of work related to teaching and research activities as assigned to him/her by the Institute. This could include tutorials, laboratory classes, development activities undertaken by faculty members, maintenance and operation of computers and other facilities, assistance in Library etc.

  2. Wherever Government of India/University Grants Commission/Council of Scientific and Industrial Research/Industry sponsored projects are undertaken, the services of the student may be used for providing assistance in projects founded by these agencies. In that event, a portion of stipend amount i.e., Rs.800/- per month, for the time being may be charged to the project founds for the duration the student is engaged on these projects.

  3. The Institute will work out specific programmes of work and maintain the record of each student.

  4. If a student fails to secure at least 60% marks in any semestral examination, his/her stipend and contingency grant will be reduced to Rs.1250/- and Rs.750/- respectively for the following semester.

  5. A student shall be required to give an undertaking to the effect that he would not leave the course midway or appear in any competitive examinations, etc., not related to engineering and technology, statistics and related fields in order to be eligible to receive this stipend.

  6. During the course of studies, the student shall not receive any emoluments, salary, stipend, etc. from any other source.

  7. Suitable hostel type accommodation may be provided wherever available.

  8. No House Rent Allowance (HRA) is admissible to the M.Tech. students.

For sponsored candidates : Sponsored candidates, if admitted to the course, will not receive any stipend or contingency grant. Their sponsors will have to pay a tuition fee of Rs.20,000/- only per candidate per year as course fee and provide facilities for carrying out project work on practical problems during normal working hours under the guidance of the faculty of the Institute. In addition to the course fee, the sponsoring organisations will have to reimburse the travelling expenses of the members of the faculty to guide the project work of their nominees.

Each student, whether sponsored or not, will have to make a refundable deposit of Rs.1,000/- only as caution money for use of department equipment and facilities.

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FACULTY

 

The Institute has many experienced and highly qualified personnel in SQC and OR. In addition to their research work, they actively participate in the teaching programmes of the Institute. Moreover, experts in the field are invited from professional and industrial organisations to deliver lectures on different topics of quality reliability and opetations research. Most of the faculty members also actively engage themselves in externally funded consultancy/project works on live problems of quality.

 

 

CLASS TEACHER

 

One of the faculty in a class is designated as the class-teacher. All students are required to meet their respective class-teacher periodically to get their academic performance reviewed and to discuss any academic problems if any.

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ISI LIBRARY RULES

Students are allowed to use the reading-room facilities in the library and are allowed access to the stacks. They have to pay Rs.250/- as security deposit in order to avail of the borrowing facility. At most four books can be borrowed at a time. Any book from the Text Book Library (TBL) may be issued to a student only for overnight or week-end provided at least two copies of that book are present in the TBL; only one book will be issued at a time to a student. Fine will be charged if any book is not returned by the due date stamped on the issue-slip. The library rules and otherdetails are posted in the library.

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SYLLABI OF SUBJECTS ---SEMESTER I

 

PROBABILITY -I

  1. Concept of probability (10)

    2. Historical introduction and citation of examples for application of probability. Definition of probability - classical, relative frequency and subjective approaches, their drawbacks, practical exercises on relative frequency approach. Sample space and events; calculus of events, examples of sample space. Concept of random experiment with examples. Axiomatic development of probability- discrete and general probability space, properties of probability. Conditional probability, Bayes theorem, independence of events, pairwise and mutual independence.

  2. Combinatorial probability (6)

    3. Probability of occurrence of at least one and exactly m events, Birth day, Matching and. Occupancy etc. problems, exercises.

  3. Concept of random variables and probability distribution (4)

    4. Definition of random variable, cumulative distribution function. Discrete random variables and their p.m.f. and d.f. with some general examples. Continuous random variables and their p.d.f. and d.f. with some general examples

  4. Discrete random variable and its distribution (10)

Bernoulli trials, binomial, poisson, geometric, negative binomial, hyper geometric distributions, their properties, relationship and simple approximations (Hypergeometric to binomial and binomial to poisson). Numerical examples and statistical tables for individual and cumulative probabilities. Discrete random vector and bivariate cases – marginal and conditional density functions, independence of discrete random variables. Distribution of the sum of two or more discrete independent random variables. Probability generating function (p.g.f.), properties and exercise.
  1. Continuous random variable and its distribution (10)

    2. Uniform, normal, gamma, beta, exponential, weibull, cauchy, lognormal distribution, Relationship between gamma and poisson, beta and binomial. Cumulative probabilities. Bivariate distribution - marginal and conditional density, bivariate normal, independence of continuous random variables. Distribution of sum, product and ratio of two independent random variables. Some derived distributions such as c 2, t, F. Order statistics and distribution of range.

  2. Expected values and moments (6)

    3. Mathematical expectation and its properties; Moments, their properties and interpretation; moments through p.g.f.; variance of sum of independent random variables, conditional expectation, conditional variance. Correlation coefficient and its properties.

  3. Moment generating and characteristic function (4)

    4. Definition, properties and relationship. Statement of uniqueness theorem of characteristic function and its applications.

  4. Limit Theorems (6)

Chebyshev’s lemma, Chebyshev's inequality, weak law of large numbers(WLLN), Central limit theorem (Lindbergh & Levy) Demoivre’s theorem, examples for application these limit theorems in Statistical Quality Control.

References:

  1. Introduction of Probability Models, S.M. Ross, Academic Press, N.Y.

2) A first course in Probability, S.M. Ross.

3) An introduction of Probability, P.G. Hoel, S.C. Port, C.J. Stone, Universal, N.Delhi

  1. An Introduction to Probability Theory and its application (Vol.I & II), W.Feller.

  2. Probability Theory and Mathematical Statistics, M. Fisz.

  3. Modern Probability Theory and its applications, E. Parzen, F.A.Graybill, D.C.Boes,

  4. Introduction to the Theory of Statistics, A.M. Mood, F.A.Graybill, D.C. Bose. McGraw-Hill

  5. Mathematical Methods of Statistics, Harlod Cramav.

  6. Elementary Probability Theory with Stochastic Processes, Kai Lai Chung

 

STATISTICAL METHODS-I

  1. Introduction (2)

    2. Definition of ‘Statistics’. Basic objectives. Applications in various branches of science with examples.

  2. Collection of Data (3)

Internal and external data, Primary and secondary Data. Population and sample, ‘Representative’ sample.

  1. Descriptive Statistics (20)

Classification and tabulation of univariate data, graphical representation, Frequency curves. Descriptive measures - central tendency and dispersion.

Bivariate data. Summarisation, marginal and conditional frequency distribution. Scatter diagram. Linear regression and correlation. Least squares method. Rank correlation.

Multivariate data. Multiple linear regression, Multiple and partial correlation.

  1. Simulation of Probability models (8)

    2. Random Numbers, Simulation techniques.

  2. Sampling Techniques (10)

    3. Random sampling. Sampling from finite and infinite populations. Estimates and standard error (sampling with replacement and sampling without replacement).

    Sampling distribution of sample mean, Stratified random sampling.

  3. Sampling distribution (10)

Sampling distribution related to standard univariate probability models-Binomial, Poisson, Normal, Uniform, Exponential, Gamma, Beta etc.

References: Vide references given for Statistical Methods II under Semester-II

 

SQC-I

  1. Introduction to SQC (2)
  2. SPC Techniques (33)

Definition of quality, meaning of control, chance and assignable causes of variation, statistical process control (SPC), basis of SPC, expected benefits of SPC. Tools of SPC - Process capability Analysis, process capability and machine capability indices (Cp, Cpk, Cm, Cmk), Control charts- Classical (Shewhart) control chart for variables and attributes- X_bar - R, X_bar - s, np. p, c, u charts. Sloping control chart, Median chart. Modified control (Shewhart) charts, Control charts with memory – CUSUM chart, Moving sum/Moving average chart, EWMA chart, Pre control, Softwares for SPC.

  1. Acceptance Sampling (20)

Introduction to acceptance sampling. Rejection and Rectification types. Sampling risks and parameters- consumer’s risk, producer’s risk. Operating characteristic curve, average sample number (ASN) curve, AQL, AOQL, ATI, LTPD, Single, Double, Multiple and Sequential sampling plans. Published sampling plans- Attribute (Dodge-Romig, Mil std, IS-2500) and variable (AQL, LTPD stipulated plans, MIL std.414) type plans.

 

References :

  1. Statistical Quality Control- 5th edition, E.L. Grant & R.S. Leavenworth, McGraw- Hill, N.Y.

  2. Quality Control and Industrial Statistics - 5th edition. A.J. Duncan, Irwin, Homewood, Ill.

  3. Quality Control and Statistical Methods – Edward M. Schrock, Asia Publishing House.

  4. Statistical Process Control, Theory and Practice, -G.B. Wetherill & D.W. Brown, Chapmann & Hall, N.Y.

  5. Introduction to Statistical Quality Control-D.C.Montgomery, Wiley, N.Y.
  6. Acceptance sampling in Quality Control, E.G. Shilling, Marcel Dekker, Inc. N.Y.

 

 

OPERATIONS RESEARCH-I

  1. Introduction to OR : (2)

    2. Origin of OR and its definitons- Operational Research with special emphasis on interdisciplinary and system approach, Orientation-iconic, Analogue and Mathematical models, Stages of an OR project: Formulation of the problem, Developing a model, Testing the adequacy of the model, Deriving a Solution and Evaluation of the solution and implementation.

  2. Linear Programming : (32)

Linear programming Modeling and Examples. Geometric solution, Vector spaces, Basis, Linear transformations. Matrices, Partitioned matrices, Quadratic form. Convex sets, extreme points and convex polyhedral sets, Simplex Algorithm-its theory and computational details, resolution of degeneracy. Duality theory, dual-simplex and primal-dual algorithms. Transportation, Assignment problems, Sensitivity Analysis.

Bounded variables algorithm and decomposition principle. Flows in network, max flow-min cut theorem and its application to transportation problems. Industrial applications of linear programming like product mix problems, blending problems, optimal allocation of resources etc.

  1. Replacement and Maintenance Models : (6)

Replacement of items that deteriorate, Equipments that suddenly fail, chain of improving equipments, assuming (i) same life for each member in the chain and (ii) increasing life, equal to that of deterioration only at infinity. Replacement of items that fail stochastically- individual and common preventive replacements, Investment decision models.
  1. Inventory Control : (10)

    2. Inventory control problem ; Concept of inventory and various costs, EOQ formula.

    Single period models: Single period models, newspaper boy problems-provisioning of spares with or without salvage value.

    Multi-period Models: Different models, Comparison of different models-evaluation of system consequences.

    Inventory Control Project: Carrying out an inventory control study-relevant costs to be considered, estimation of costs by imputation or otherwise, ABC analysis and Selective inventory management, Decaying inventory.

  2. Queuing Theory : (10)

Introduction to waiting line models – steady state behavior of M/M/1 and M/M/C queues-the problem of machine interference and use of finite queuing tables-introduction to M/G/1, and G/M/1.

 

References:

  1. Principles of OR with Application to Managerial Decisions –H.M. Wagner, Prentice Hall.
  2. Introduction to Operations Research – F.S. Hiller and G.J. Lieberman, Addison Wesley.
  3. Linear Programming – G. Hadley, Addison Wesley.
  4. Linear Programming & Network flows - M.S. Bazaraa, J J Jarvis and H D Sherali, John Wiley.
  5. Linear Programming and Extensions – G.Dantzig, Princeton, N.J.
  6. Linear Programming – K.G. Murthy, John Wiley
  7. Modern Inventory Management – J.W. Prichard and R.H. Eagle, John Wiley.
  8. Material Management in Inventory Systems – M.K. Starr and R.J. Tersine, North Holland.
  9. Renewal Theory - D.R. Cox
  10. Queues – D.R. Cox and W.L. Smith
  11. Analysis of Queuing Systems – J.A. White, J.W. Schmidt and G.K. Bennet, Academic Press.
  12. Elements of Queuing Theory – Thomas L. Saaty, McGraw Hill.
  13. Introduction to Queuing Theory-B.V. Gnedenko and I.N. Kovalenko.
  14. Operations Research – An Introduction- H.A. Taha, Macmillan, N.Y.

 

PROGRAMMING TECHNIQUES AND DATA STRUCTURES

  1. Programming Techniques and Structures
  1. C-language and structural programming concepts.

  1. Data Structures

Formal definitions, operations, implementations and applications of basic data structures; array, stack, queue, dequeue, priority queue, doubly linked list, orthogonal list, binary tree-traversal algorithms, threaded binary tree, generalized list.

  1. Search Techniques

Binary search, Fibonacci search, binary search tree, height balanced tree, heap, B-tree, B*-tree, digital search tree, tree, hashing techniques.

Three lectures and one two-hour tutorial per week.

60% for theory and 40% for programming assignments.

References:
  1. Data Structures using C, -A.M. Tanenbaum and M.J. Augesestein, Y. Langsan
  2. The Art of Computer programming, Vol. I - D.E. Kunth
  3. Data structure techniques -T.A. Standish:
  4. Fundamentals of Data Structures -E. Horowitz and S. Sahni :
  5. Data Structure and Program Design.- R.J. Kruse :
  6. Data Structures and Algorithm. -A. Aho, J. Hopcroft, and J. Ullman :

 

QUALITY MANAGEMENT SYSTEMS

  1. Strategic quality Management : (5)

    2. Basic concepts. Elements of strategic Management, Quality and Management cycles, Quality policies and Goals, Resources for Quality activities, Training, Obstacles to SQM.

  2. Organising for Quality : (5)

    3. Evolution of organisation for quality, co-ordination of quality activities, role of upper management, middle management, work force and teams. Self managing teams quality circles.

  3. Developing quality culture :(5)

    4. Culture, Motivation, Creating and maintaining quality awareness, Providing evidence of management leadership, Providing for self-development and Empowerment. Providing recognition and Rewards, time to change culture. Achieving total commitment to quality-various approaches.

  4. Quality Management & Assurance systems : (20)

    5. Developing and establishing quality management and assurance system. Basics of ISO 9000, QS 9000, ISO 14000 systems, Quality Audit, Accreditation systems.

  5. Quality costs - Foundations of Quality Systems Economics : (5)

  6. TQM and allied concepts : (10)

(i) TQM implementation process –Deming’s 14 point

(ii) Six Sigma Process.

(iii) Kaizen.

References:

  1. ISO 9000 : Quality Management and Quality systems element standards

  2. ISO 8403 : Quality Management and Quality Assurance – Vocabulary

  3. ISO 9001: Quality systems- Models for Quality assurance in design/development, production, installation and servicing.

  4. Strategic Management, -A.A. Thompson and A.J. Stricklard, R.D. Irwin, Illinois.

  5. Quality planning and Analysis - J.M. Juran and F.M. Gryna, Tata McGraw Hill.

  6. Total quality Control – A.V. Feigenbaum, McGraw Hill

  7. Quality Handbook - J.M. Juran (Ed.), McGraw Hill.

  8. Total Quality Management- A practical approach -H. All, Wiley Eastern.

  9. Handbook of Quality Management.-D.Lock (Ed.), Jaico

  10. QS 9000 Quality Assurance System Standard

  11. ISO 14001 Environmental Management systems- specifications with guidance for use.

 

 

ELECTRICAL AND ELETRONICS ENGINEERING

  1. Basic Electrical Systems & Control: (25)

    2. D.C. and A.C. circuits (including three phase circuits), Electromagnetic induction, Principles of D.C. motors and generators, Transformers, Alternators and A.C. motors. Feedback and feed forward control, Stability of control systems.

  2. Electronics: (25)

Kirchoff’s law, analysis of RLC circuits, Network theorems.

Principles of semiconductor diodes and transistors, Transistor biasing and RC-coupled amplifiers, Operational amplifiers, Feedback amplifiers, Oscillators, Pulse and digital Circuits.

References:

  1. Fundamentals of Electrical engineering and electronics - B.L. Theraja.
  2. Electrical Technology – B.L. Theraja, A.K. Theraja
  3. Network, lines and Fields –J.D. Ryder, Asia publishing.
  4. Electronics Engineering Principle – J.D. Ryder, McGraw Hill.
  5. Integrated Electronics : Analog and Digital Circuits and systems – S. Millman and C.C. Halkias, McGraw Hill
  6. Analysis and Design of feedback control systems – G.J. Thaler and R.G. Brown, McGraw Hill.
  7. Operational Amplifiers, design and applications- J.G. Graeme and T.E. Tobey, McGraw Hill.
  8. Transistor Engineering – A.B. Phillips, McGraw Hill.
  9. Digital Electronics with engineering applications- T.P. Sifferlen & V. Vartanian, Prentice Hall, N. Jercy

 

WORKSHOP - I

  1. Engineering Drawing (25)

    2. Basic concept of orthogonal projection, third angle and first angle projections, scale of drawing and dimensioning, theory of section and conventional sectional view, offset section, revolved section, auxiliary view.

    Convention of representing screw threads in a drawing, diametral clearance in bolt holes and their spacing, standard bolt diameters, bolt circle diameter and flange diameter.

    Concept of fitting boss and alignment, standard key, key ways and spline, dimensioning parts before assembly and after assembly, Duplication of dimensions and cumulative errors, representing gears by pitch circles in a drawings.

    Computer aided graphics, sketch-pad concept, features drawing and simple topographical representation of product (practical demonstration with OMC drafting machine).

  2. Basic workshop practices (15)

  3. Exercises on Electrical and Electronics Engg. (30)

s BACK

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SYLLABI OF SUBJECTS -- SEMESTER II

 

PROBABILITY – II

  1. Concept of a stochastic process: (4)

    2. State space and parameter space. Various types of Stochastic processes. Examples.

  2. Markov processes and Markov chains: (5)

Definition and Examples

3. Discrete Time Parameter, Time Homogeneous Markov Processes: (36)

  1. Transition probabilities, Chapman-Kolmogorov equations, First passage time (8)

  2. Communication among states. Classification of states. Definition of recurrence, transience, positive and null recurrence, periodicity- (10)

  3. Stability of Markov chain. Limiting probabilities. (3)

  4. Absorption probabilities. (3)

  5. Examples of Markov chains-Birth and Death chain, Random walk, Ehrenfest chain, Gambler’s ruin chain etc. (2)

  6. Modeling of common industrial and real life systems as Markov chains – Examples of waiting line and inventory models (10)

4. Poisson process: (10)

Postulates for Poisson process. Properties of Poisson process.

Poisson process and related distributions. Examples.

References:

  1. Elements of Applied Stochastic Process, 2nd ed., U.N. Bhatt, Wiley, N.Y.
  2. An Introduction to Probability Theory and Its Applications, Vol.1, 3rd ed., W. Feller, Wiley N.Y.
  3. Introduction to Stochastic Processes, P.G. Hoel, S.C. Port and C.J. Stone, Haughton Miffin, Boston
  4. Markov Chains-Theory and Applications, D.L. Isaacson and R.W. Madson, Wiley, N.Y
  5. A First course in Stochastic Processes 2nd ed., S. Karlin and H.M. Taylor, Academic Press, N.Y
  6. Stochastic Processes, J.Medhi ,Wiley eastern, N. Delhi
  7. An Introduction to Probability Models, 2nd ed., S.M. Ross, Academic Press, N.Y.
  8. Stochastic Processes, S.M. Ross, Wiley, N.Y.

 

STATISTICAL METHODS – II

  1. Introduction (2)

    2. Principles of Statistical Inference. Formulation of the problems with examples.

  2. Estimation (8)

    3. Point estimation. Estimator and estimate criteria for good estimates-unbiasedness, consistency, efficiency and sufficiency, Illustrations. Methods of estimation of Parameters of standard distributions. Interval estimation by examples- Confidence internals of the parameters of the standard distributions, one-sided confidence interval.

  3. Testing hypothesis (20)

    4. Formulation of the problem and concepts for evaluation of tests, Illustrations.

    Statistics Sampling distribution of statistic and its standard error.

    Small sample tests associated with standard univariate probability distributions and corresponding sampling distributions (without derivations)

    Large sample tests in one and two-sample problems of standard probability distributions, Statement of central limit theorem, Determination of sample size.

    Small sample tests connected with Bivariate Normal population, Simple linear regression and correlation and corresponding confidence intervals. Transformation of statistics to stabilize the residual plots. Assessment of the model. Fitting of non-linear regression using transformation.

    Analysis of categorical data. Pearsonian chi-square and its applications.

  4. Linear Statistical Models (5)

    5. Definition of linear model, interactions with illustrations. One way and two way analysis of variance.

  5. Non-parametric Inference (10)

    6. Comparison with parametric inference, Use of order statistics. Confidence interval for fractile. Sign test, Wilcoxon signed rank test, Mann-Whitney test, Run test, Kolmogorov-Smirnov test. Spearman’s and Kendall’s test. Tolerance region.

  6. Elements of Sequential Test and its Uses. (5)

Tests for Binomial and Normal population parameters.

References:

  1. Probability and Statistics for Engineers (4th Edition) –by I.R. Miller, J.E. Freund and R. Johnson.

  2. Fundamentals of Statistics (vol. I and vol. II)-by A. Goon, M. Gupta and B. Dasgupta.

  3. Statistical Theory with Engineering Application-by A. Hald.

  4. Statistical Methods-by G.W. Snedicor and W.G. Cochran.

  5. Statistical Concepts & Methods – by G.K. Bhattacharyya and R.A. Johnson.

  6. Introduction to Linear Regression Analysis –by D.C. Montgomery & E.Peck

  7. Introduction to the Theory of Statistics – by A.M. Mood, F.A. Graybill & D.C. Boes.

  8. Practical Non-Parametric Statistics –by W.J. Conover

  9. Applied Regression Analysis – by N. Draper & H. Smith

 

SQC-II

  1. Advanced SPC Techniques (20)

    2. Group control chart for multiple stream processes, Multivariate control chart. Control chart of process mean vector and process variability matrix, Control chart based on Run lengths. Control chart for short run process.

    Process capability analysis under non-normal situation.

    SPC with correlated quality characteristic. Interface and integration between SPC and EPC (Engineering process control). Selecting optimum target for a production process.

    Economic design of control charts – economic models of X-R control chart. Economic design of p chart.

  2. Taguchi’s on-line QC Techniques (15)

    3. Taguchi’s loss function and quality level. Taguchi’s on-line feedback quality control (variable and attribute characteristics), On-line process parameter control (variable and attribute types), On-line quality control and methods for process improvement.

  3. Further topics in Acceptance Sampling (15)

Continuous sampling plans (CSP-1, CSP-2, CSP-3), Multilevel plans.

Special purpose plans – Chain sampling and Skip lot sampling plans.

Economic design of acceptance sampling plans.

References:

    1. Introduction to statistical quality control, D.C. Montgomery 3rd Edition,

    1. Multivariate QC" in Encyclopedia of statistical sciences, Vol. 6, edited by W.L. Johnson, S, Kotz, John Wiley, N.Y.

    2. Quality Control and Industrial Statistics -A.J. Duncan .5th edition, Irwin, Homewood, Ille.

    3. Principle of Quality Control, Jerry Banks, John Wiley.

 

RELIABILITY – I

  1. Concept of Reliability (5)

    2. Importance of reliability, definition of reliability and its measures, concept of failure. General provision of a reliability specification, Methods of achieving reliability, Broad functions of reliability.

  2. Failure patterns (8)

    3. Bath tub curve, causes of early failure and methods to avoid them, failure distributions: exponential, Weibull, truncated normal, log normal, gamma, inverse Gaussian, their properties and uses.

  3. Combinatorial reliability (12)

    4. Series, parallel and r-out of n configurations; their block diagram, reliability graph and determination of reliability through combinatorial methods of inspection, events space, cut set and tie set. Multistate models.

  4. System reliability redundancy (15)

    5. System reliability with exponential components in series, parallel and r-out-of-n system. Usefulness of redundancy and improvement factor. MTTF, MTBF, Equivalents MTBF of series and parallel system. Cold and hot redundancy, reliability of stand-by system. Weakest link model, chain model, stress-strength model, non-parametric estimation of reliability.

  5. Reliability testing demonstration and acceptance (15)

Problem of life testing, estimation of parameters and reliability using standard probability models using complete and censored (type I, II and III) samples, properties of these estimators. Probability plotting and graphical procedures for estimating the parameter and testing validity of model by some standard statistical tests. Life test acceptance sampling plans in exponential case. Sequential life test in exponential case, accelerated life tests.

Reference:

  1. Methods for Statistical Analysis of Reliability and Life Data, Mann, N.R. Schofer R.E. & Singpurwalla, N.D., Wiley, New York

  2. Statistical Analysis of Reliability and Life- Testing Models, Bain, L.J, Dekker, New York,

  3. Statistical Models and Methods for Lifetime Data, Lawless, J.F., Wiley, New York

  4. Bayesian Reliability Analysis, Martz, H.E. & Weller, A., Willey New York,

  5. Statistical Theory of Reliability and Life Testing Probability Models, Barlow R.E. & Proschan, F., Holt, Rinehart and Winston, New York.

  6. Statistical Reliability Theory, Gertsbakh , I.B., Marcel Dekker Inc.

  7. Reliability and Life Testing, Sinha, S.K., Wiley Eastern Limited.

  8. Reliability Theory and Practice, Bazvosky, I., Prentice Hall, New Jersey

  9. Fundamentals of Reliability Theory, Polvko, A.M., Academic press, New York.

  10. Mathematical Theory of Reliability, Barlow, R.E. and Proschan, F, John Wiley, New York.

  11. Mathematical Methods of Reliability Theory, Gnedenko, Yu, Belyayev K and Solovyev, A.D., Academic Press, New York.

  12. Repairable system Reliability-Modeling, Inference, Misconception and their Causes, Ascher Harold and Feingold Harry, Marcel Dekker, Inc., New York,

  13. Life Testing and Reliability Estimation, Sinha, S.K. and Kale, B.K., Wiley Eastern, New Delhi.

  14. Software Engineering: Design, Reliability and Management, Shooman, M.L., McGraw - Hill, New York.

  15. Reliability in Engineering Design, Kapur, K.C. and Lamberson, L.R., John Wiley, New York.

  16. The Statistical Analysis of failure time data, Kalb Feisch, J.D. and Prentice, R.L., John Wiley, New York.

  17. Reliability and Maintainability of Electronic System (edited), Arsenault and Roberts, J.A., PITMAN.

 

INSTRUMENTATION AND COMPUTER ENGINEERING

  1. Instrumentation (25)

    2. Primary sensing elements, Transducers, Signal conditioning and conversion, Telemetry, Process control.

  2. Computer Engineering (30)

Boolean algebra, Switching functions and their minimization, Circuit realization.

Logic gates, Combinatorial and sequential circuits.

Number representation, Binary arithmetic, Fixed point and floating point arithmetic, Processor organisation, Memory organisation, Input-Output organisation, Process management, memory management, Input-Output management.

References:

  1. Measurement Systems – Application and Design. E.O. Doebelin, McGraw Hill, Int.

  2. Instrumentation Fundamentals and Applications, R. Marrison, John Willey

  3. Electronics Measurement and Instrumentation, M.Oliver and J.M. cage, McGraw Hill

  4. Instrumentation, Measurement and Feedback, B.E. Jones, McGraw Hill

  5. Digital Computer Fundamentals, T.C. Bartee,

  6. Computer Systems Architecture, M.M. Mano, Prentice Hall

  7. Operating systems, J.J.Donovan and S.E. Madnick McGraw Hill.

INDUSTRIAL ENGINEERING AND MANAGEMENT

INDUSTRIAL ENGINEERING AND MANAGEM

  1. Industrial Engineering (30)

    2. (a) Operations Management: (10)

    Method:

    Methods study: Recording techniques, critical examination, and development of alternative and implementation, Examples:

    Estimation of task times by past data approach, direct time study approach, predetermined time standards approach, work sampling approach.

    Machine:

    Equipment selection, techniques and replacement strategies, Examples

    Break- down, preventive and predictive maintenance, distribution of breakdown time, distribution of repair time, determination of crew sizes, Scheduling.

    (b) Man Management: (5)

    Incentive schemes, job specification, job evaluation, work & job design.

    (c) Material & Management: (5)

    Choice of materials, standardisation, value engineering and analysis.

    (d) Plant Management: (5)

    Plant location, plant layout, and materials handling.

    (e) Ergonomics and Human engineering: (5)

    Introduction, application in product and job design, Safety.

  2. Industrial Management (15)

    3. (a) Introduction to management and Systems (5)

    Functions of management, Planning, Co-ordination, Motivation and Control, Decision making, Roles and role conflict, Organisation structure, Communication and information subsystem, Administration & management of change , Case studies.

    (b) Management Accounting and Financial Management (10)

    Introduction to financial Management, Scope & functions, structure & components of balance sheet, income statement, funding flow and cash flow, Ratio analysis, and interpretation of financial statements, Budgeting, standard budgeting and control, control and accounting of materials, control and accounting of labour, control and accounting of overhead, system of cost accounting with reference to historical predetermined cost, process cost and uniform cost accounting, cost accumulation systems, variance analysis, financial evaluation of alternatives, cost of capital and capital budgeting.

  3. Marketing : (10)

Consumer, Demand, Marketing strategy (Segmentation, Pricing, Distribution channel), Product life cycle & product development, Market research (techniques of data collection & information processing), Brand Management, Advertising & Promotional activity.

References:

  1. Industrial Engineering and Management Science, P.R. Banga, S.C. Sharma and N.K. Agrawal

  2. Industrial Engineering and Operation research,D.M. Miller, J.W. Schmidt, John Wiley, N.Y.

  3. Motion & Time study, W.N. Benjamin, Irwin, Homewood, IL.

  4. Industrial Engineering Handbook, H.B. Maynard (Ed.) Mc Graw Hill. N.Y.

  5. Job evaluation Methods, C.W. Lytle Ronald Press N.Y.

  6. Industrial Engineering, R.B. Gupta, Satya Prakashan, N. Delhi

  7. Introduction to Work Study (3rd edition), ILO, Geneva ,Universal Book Corporation.

  8. Industrial Engineering & Management, O.P. Khanna

  9. Management: a system and contingency analysis of managerial functions-H. Koontz and C.O. Donnell.

  10. Market Research , D.J. Luck and R.S. Rubin, Prentice Hall

  11. Market research-Text and cases, H.W. Blyd, R. Westfall, S.F. Stasch, Richard Allwyn Inc, Illinois

  12. Marketing Management, Analysis, Planning, Implementation and Control, Philip Kotler, Prentice Hall (India).

  13. Financial Management & Policy (Ninth edition), J.C. Van Horne, Prentice Hall (India)

  14. Financial Management-theory & practice (2nd edn), P. Chandra, Tata McGrew Hill (India)

  15. Accounting Theory and Management Accountancy, S.P. Jain and K.L. Narang, Kalyani Publishers.

 

MECHANICAL ENGINEERING

  1. Mechanical Properties of Materials. (15)

    2. Brittleness, ductility, toughness, Engineering and true stress strain curves, Instability in tension, yielding criteria for ductile materials, tensile properties, anisotropy, Torsional properties, Hardness, Impact strength, Fatigue and Creep behaviors at low and elevated temperature.

  2. Metrology (15)

    3. Objectives of Metrology, Characteristics of measuring instruments, Functional elements of instruments, classification of methods of measurement.

    Standards for measurement and standardising organisations

    International system (SI) of units.

    Measurement uncertainty/error, types of error, methods of estimating total uncertainty in a measurement process.

    Linear measurement-steel rule, calipers, surface plates, straight edges, gauges, vernier calipers.

    Limits, Fits and Tolerances.

    Straightness, flatness, squareness, parallelism, roundness, circularity, runout.

    Surface roughness measurement.

  3. Machining (15)

    4. Various machining methods and machine tools for metal cutting. Influence of various factors like speed, feed and depth of cut on tool life. Economic tool life, various angles and geometry of single point cutting tools (ISO standard). Design of single point cutting tool. Forces of turning, drilling and milling operations.

    Non conventional machining.

    NC/CNC Machines.

  4. Mechanical working of Metals:(15)

Plastic deformation of metals – Hot and cold working, Forging, Rolling, Extrusion, Wire drawing, Deep drawing, Stretch forming, Blanking, Piercing, Bending. Hydroforming and explosive forming.

References:

  1. Production Technology by HMT, Tata McGraw Hill

  2. Manufacturing and Machine tool operation, H.W. Pollack, Prentice Hall, N.Y.

  3. Manufacturing Analysis, N.H. Cook, Addison- Wesley

  4. Structure and Properties of Engineering Materials, R.M. Brick, A.W. Pouse, R.B. Gorden, Mc Graw Hill

  5. Mechanical Metallurgy, E.M. Dieter, McGraw Hill

  6. Workshop Technology, Parts 1,2,3, W.A.J. Chapman, ELBS

  7. Numerical Control of Machines, S.J. Martin, ELBS.

  8. Principles of Machine tools, G.C. Sen and A. Bhattacharya.

  9. Fundamental of Tool design, ASTME, Prentice Hall,

  10. Fundamentals of Rolling, Z. Wusatowski, Pergamon Press, Oxford.

  11. Nontraditional Machining Process, R.K. Springborn (Ed.), ASTM

  12. Principles of Numerical Control, J.J. Childs, Ind. Press Inc, N.Y.

  13. Engineering Metrology, R.K. Jain, Khanna, N.Delhi

  14. Measurement Systems- Application & Design, E.O. Doebelin, McGraw Hill

  15. Handbook of Industrial Metrology, ASTME, Prentine Hall

  16. Engineering Metrology, K.J. Hume, Mc Donald

  17. Engineering Dimensional Metrology, L. Miller, Arnold.

 

WORKSHOP - II

  1. Instrumentation/ Digital Electronics (25)

  2. Material Testing (20)

  3. Metrology and Machining Practices (30)

s BACK

 

 

 

 

 

 

 

 

SYLLABI OF SUBJECTS—SEMESTER III

 

OPERATIONS RESEARCH – II

  1. Integer Programming: (12)

    2. Formulation of various industrial problems as integer and mixed integer programming Problems. Branch and bound algorithm. Cutting plane methods for pure and mixed Integer programming problems. Knap-sack, travelling salesman and shortest route problems.

  2. Non-linear Programming : (25)

    3. Constraint qualification and Kuhn-Tucker necessary conditions. Sufficiency of Kuhn-Tucker necessary conditions and convex programs. Linear Complementarity Problem (LCP) and Lemke’s complementary pivot algorithm. Copositive plus matrices and Lemke’s algorithm. Quadratic programming and use of LCP for solving quadratic programming problems. Separable Programming. Linear fractional Programming.

  3. Dynamic Programming : (6)

    4. Bellman’s principle of optimality and recursive relationship of dynamic programming for various optimization problems.

  4. Sequencing Models : (7)

    5. Two machine and n jobs (no passing) problem and three machine and n jobs (no passing) problems: different routing, 2 jobs and m machines, n jobs and m machines; branch and bound algorithms. Line balancing models.

  5. PERT/CPM : (10)

Introduction to Network analysis, definition of a project, job and events, drawing of arrow diagrams, determination of critical paths and calculation o floats. Resource allocation and least cost planning. Use of network flows for least cost planning. Uncertain duration and PERT. PERT COST system and installation of Network system.

References:

  1. Integer Programming – R.S. Garfinkel and G.L. Nemhauser, John Wiley.

  2. Integer Programming: Theory, applications and Computations – H.M. Taha, Academic Press.

  3. Non Linear Programming: Theory and Algorithms – M.S. Bazara and C.M. Shetty, John Wiley.

  4. Non-linear Programming- W.I. Zangwill, Prentice Hall.

  5. Practical Methods of constrained optimization – R. Fletcher, John Wiley.

  6. The Art and Theory of Dynamic Programming – S.E. Dreyfus, Academic Press.

  7. Theory of Scheduling – R. Convey, Addison Wesley.

  8. Network based Management Systems –R.D. Archibald, John Wiley,

  9. Network Analysis for Planning and Scheduling – A. Battersby, Macmillan.

10. Applied Dynamic Programming – R. Bellman and S. Dreyfus, Princeton, N.J.

 

INDUSTRIAL EXPERIMENTATION

  1. Introduction : (2)

    2. Role of experimental designs. Basic principles, use of statistical technique in experimentation.

  2. Randomised Block, Latin Squares and Related Designs : (6)

    3. Randomised complete block design, Latin square design, Graeco-Latin square design, Incomplete block designs-statistical analysis, Model adequacy checking, Problems.

  3. Factorial Designs : (4)

    4. 2K and 3K factorial designs, Statistical Analysis, Model adequacy checking, Confounding - 2K in two blocks, four blocks and in 2P blocks, 3K in 3, 9 and 3P blocks. Partial confounding problems.

  4. Nested/Hierarchical Designs : (4)

    5. Two stage nested design, –Statistical analysis, estimation of model parameters, diagnostic checking. General m-stage nested designs. Design with nested and crossed factors. Problems.

  5. Multifactor Experiments with Radomisation Restrictions : (4)

    6. Randomised block and Latin squares as multifactor designs, Split-plot design, Split-split plot design, Problems.

  6. Orthogonal Arrays : (8)

    7. Linear graphs and their applications, Different types of Orthogonal Arrays, Split unit design, Multilevel arrangement, Pseudo-factor designs, Statistical analysis, Problems.

  7. Response Surface Methodology : (80)

    8. Introduction, Method of steepest ascent, Analysis of quadratic models, Response surface designs for first order and second order models, rotatable and orthogonal -designs-Equiradial, simplex, central composite, Box Behnken designs, Problems.

  8. Taguchi’s Robust Designs : (6)

Taguchi’s philosophy of quality engineering, Loss function, Three steps approach to robust design, Parameter designs, Inner array and outer array, Signal to noise ratios, Tolerance designs, Statistical analysis, Problems.

9. Mixture Designs: (8)

Introduction, Simplex lattice designs (Scheffe). Simplex centroid designs, Extreme vertices designs, Response surface designs with mixtures–first order and second order model for constrained mixture spaces, Problems.

Reference:

  1. Design and Analysis of experiments, D.C. Montgomery, J. Wiley, N.Y.

  2. Statistics for Experimenter – An Introduction to data analysis and model building, G.E.P. Box, W.G.Hunter, J. Wiley, N.Y.

  3. Design of Experiments – A-No-Name-Approach, T.J. Lorenzer and V.L. Anderson, Marcel Dekker, N.Y.

  4. Experimental Designs, W.G. Cochran and G.M. Cox, J. Wiley, N.Y.

  5. Design of Experiments _ A realistic approach, V.L. Anderson and R.A. Mcelean, Marcel Dekker, N.Y.

  6. Statistical Design and Analysis of Experiments, P.W.M. John, MacMillan.

  7. The Design of Experiments, R.A. Fisher, Hafner N.Y.

  8. Statistical Design and Analysis of Industrial Experiments, S.Ghosh, Marcel Dekker,N.Y.

  9. Design and Analysis of Experiments, M .N. Das and N.C. Giri, Wiley Eastern, N. Delhi

  10. Empirical Model Building and Response Surface, E.E.P. box and N.R. Draper, J. Wiley, N.Y.

  11. Response Surface Methodology – Process and Product Optimisation Using Designed Experiments, R.H. Myers and D.C. Montgomery

  12. Response Surface Designs and Analysis, A.I. Khuri and J.A. Cornel, Marcel Dekker, N.Y.

  13. Introduction to Quality Engineering, G. Taguchi, APO, UNIPUB, White Plains, N.Y.

  14. Introduction to Off-line Quality Control, G. Taguchi, Central Japan Quality Control Association, Nagoya, Japan.

  15. System of Experimental Designs – Engineering Methods to Optimise Quality and Minimise Cost, UNIPUB/Kraus International, White Plains, N.Y.

  16. Experiments with Mixtures -Design, Model and the Analysis of Mixture Data, J.A. Cornell, J. Wiley, N.Y.

RELIABILITY –II

  1. Optimisation of System Reliability :

    2. Optimal spare part allocation, Generalized Kette’s algorithm, Optimisation of system reliability with redundancy through dynamic programming.

  2. Bayesian life Test Acceptance Sampling Plan.

    3. Problem of optimal design of plan under Bayesian consideration, turncation of number of failure and cost model based on cost of sampling, testing and decision of acceptance and rejection, sign regular function and monotone plan, posterior risk and minimisation of expected regret.

  3. Markov Models for System Reliability:

  1. Non-Repairable System:

Single element-non repairable, two element-non-repairable system; solution through Laplace transform. Poisson process, Stand-by system.

  1. Repairable System:

Reliability and availability function of one and two components system, up-time and down-time ratio, steady state probabilities, n equipment and r repairmen (r = n and r < n). Analysis of parallel and stand-by redundant configuration. Maintainability; Maintainability increment, Methods of achieving optimum maintainability, Availability in stand-by system. Practical considerations for maintenance management.

  1. Coherent System and its Structural Properties :

    2. Components and systems with independent components, coherent system, path sets and cut sets, reliability of coherent system, bounds on system reliability, Relative importance of components, Modular decomposition of coherent system and improved bounds for system reliability. Concept of associated random variables.

  2. Fault Tree Analysis:

Event tree, simple fault tree and its construction, Mathematics of FTA, Efficiency of FTA formats, FTA, Event space method, Monte-Carlo technique, Min-cut set algorithm, FMEA, Carrying out FMEA with practical example.

 

References:

  1. Theory of Reliability & life Testing, Probability models, R.E. Barlow and F. Proschan ,Holt, Riehort and Winston, N.Y.

  2. Practical Method for Reliability Data Analysis, J.I. Ansell and M.J. Phillps, Clarendon, Oxford.

  3. Repairable System Reliability , H. Ascher and H. Feingold, Marcel Dekker, N.Y.

  4. Introduction to Reliability Analysis, S. Zacks, Springe Verlag, N.Y.

  5. Statistical Reliability Theory, I.B. Gerstbakh, Marcel Dekker, N.Y.

  6. Mathematical Methods of Reliability Theory, B.V. Gnedenko, B.V. Belyayev, K. Yu and A.D. Solovyev, Academic Press, N.Y.

  7. Reliability Engineering and Risk Assessment, E.J. Henly and H. Kumamoto, Prentice Hall, N.Y.

  8. Bayesian Reliability Analysis, H.F. Martzad, R.A. Waller, John Wiley, N.Y.

  9. Reliability and Risk Analysis, N.J. McCormick, Academic Press, N.Y.

  10. Stochastic Methods on Reliability Theory, N. Ravichandran, Wiley Eastern, N. Delhi

  11. Reliability and Life Testing, S.K. Sinha, Wiley Eastern, N. Del

 

 

APPLIED STOCHASTIC PROCESSES

  1. Introduction to ASP (2)

  2. Types of Stochastic Process

Simple random walk and some extensions like, random walk with absorbing/reflecting barriers; A review of discrete time Markov chains, continuous time Markov Chains, Branching Process, Birth and Death process with industrial orientation; Poisson Processes, waiting time distribution and applications; Renewal Process, renewal equation, renewal theorem, Delayed and equilibrium renewal process, excess life distribution

  1. Applications of SP (8)

Application to Dam, Replacement and other models

References:

  1. Stochastic Process - S.Ross

  2. First course in Stochastic Processes –S. Karlin & H. Taylor

  3. Elements of Applied stochastic process, 2nd ed., - U.N. Bhatt.

  4. Elements of Stochastic processes with applications to National Sciences –T.J. Bailey

  5. Theory of Stochastic process – D.R. Cox & H.D. Miller

  6. Stochastic process – E. Parzen

  7. Stochastic process –N.U. Prabhu

  8. Introduction to Stochastic Processes – E. Cinlar

  9. Elements of the theory of Markov Processes and their applications-A.T. Bharucha

  10. Introduction of Probability Theory and applications. Vol.I-W.Feller.

 

 

ADVANCED STATISTICAL METHODS

  1. Multivariate Normal Distribution (7)

    2. Multivariate Normal Distribution Functions, Conditional Distribution and its relation to regression model, Estimation of parameters.

     

  2. Multiple Linear Regression Model (16)

    3. Standard multiple regression models with emphasis on detection of collinearity, outliers, non-normality and autocorrelation, Validation of model assumptions.

  3. Multivariate Regression (6)

    4. Assumptions of Multivariate Regression Models, Parameter estimation, Multivariate Analysis of variance and covariance.

  4. Discriminant Analysis (10)

    5. Statistical background, Linear discriminant function analysis, Estimating linear discriminant functions and their properties.

  5. Principal Component Analysis (6)

    6. Principal components, Algorithm for conducting principal component analysis, Deciding on how many principal components to retain, H-plot.

  6. Factor Analysis (5)

    7. Factor analysis model, Extracting common factors, Determining number of factors, Transformation of factor analysis solutions, Factor scores.

  7. Cluster Analysis (5)

Introduction, Types of clustering, Correlations and distances, clustering by partitioning methods, hierarchial clustering, overlapping clustering.

References:

  1. An Introduction to Multivariate Statistical Analysis, T.W. Anderson, John Wiley, N.Y.

  2. Applied Multivariate Data Analysis, Vol I & II, J.D. Jobson, Springer-Verlag, N.Y.

  3. Statistical Tests for Multivariate Analysis, H. Kris, Springer-Verlag, Heidelberg.

  4. Regression Diagnostics , Identifying Influential Data and Sources of Collinearety, D.A. Belsey, E. Kuh and R.E. Welsch

  5. Residuals and Influence in Regression, R. Dennis Cook and S. Weisberg, Chapman & Hall. N.Y.

  6. Applied Linear Regression Models, J. Neter, W. Wasserman and M.H. Kutner, Homewood, Illinois.

  7. The Foundations of Factor Analysis, A.S. Mulaik, McGraw Hill, N.Y.

  8. Introduction to Linear Regression Analysis, D.C. Montgomery and E.A. Peck, John Wiley, N.Y.

  9. Cluster analysis for Applications, M.R. Anderberg, Academic Press, N.Y.

  10. Cluster Analysis, B. Everitt, Halsted, N.Y.

  11. Multivariate Statistical Analysis, D.F. Morrison, McGraw Hill, N.Y.

  12. Introduction to Multivariate Analysis, G.H. Dunteman, Sage, London.

 

ADVANCED OPTIMISATION

  1. Linear Programming: (15)

    2. Computational Complexity of the simplex algorithm. Khachyan’s Ellipsoid Algorithm Karmarkar’s projective algorithm.

  2. Non-Linear Programming: (20)

    3. Kuhn-Tucker Theory, Unconstrained Optimisation: Line Search, Multi dimensional search and an outline of method of Hooke and Jeeves, Method of Rosenbrock, Method of steepest descent and method of Conjugate directions.

    Methods of Feasible Direction: Method of Zoutendijk, Grandient Projection method of Rosen, Method of reduced gradient and the Convex Simplex method of Zangwill.

    Penalty and Barrier function methods.

  3. Goal Programming and Multicriteria Decision Making: (13)

    4. Multicriteria decision. Multicriteria decision making models, Determination of set of feasible alternatives, Solution Techniques, Multicriteria simplex method.

    Modeling Multiple objective problems, Goal programming approach. Goal programming models. Ranking and Weighting of multiple goals. Simplex method in goal programming. Post optimality analysis, Computer based goal programming. Applications.

  4. Stochastic programming: (12)

Stochastic programming with one objective function. Stochastic linear programming. Two stage programming technique. Chance constrained programming technique, Stochastic dynamic programming.

References:

  1. Linear Programming & Network flows : MS Bazaraa, J J Jervis and H D Sherali, John Wiley.

  2. Non Linear Programming; Theory and Algorithms – M.S. Bazarra and C.M. Shetty, John Wiley.

  3. Mathematical Programming Techniques – N.S. Kambo, Affiliated East-West Press.

  4. Advanced Linear Programming – B.A. Murtagh, McGraw Hill.

  5. Practical Method of Optimisation, Vol I and II, R. Fletcher, John Wiley.

  6. Conflicting objectives in Decisions- D.E. Bell, R.L. Keenev and H. Raiffa (Eds.), John Wiley.

  7. Multiple criteria Decision Making – M. Zeleny (ED.) Springer Verlag, N.Y.

  8. Goal Programming For Decision Analysis – S.M. Lee. Auerback Publishers Inc., Philadelphia. (19720.

  9. Goal programming and extensions – J.P. Ignizio, Laxington Books, Laxington, Massachusetts.

  10. Stochastic Programming With Multiple Objective Functions – I.M. Stancu-Minasian, D. Reidel Publishing Company, Boston

 

SOFTWARE ENGINEERING

  1. Software Engineering Concepts :

    2. Introduction: Software project planning (basic concepts of life cycle model, milestone, cost models, successive version model, project structure, team structures), Requirements Analysis (Specifications, Algebraic axioms, Regular expressions, Decision tables, Event tables, Transition Tables, FS mechanism, Petri Nets), Software Design- Architectural and detailed Design (Abstraction, Information hiding, Modularity, Concurrency etc., coupling and cohesion, data flow diagrams, structure charts, Pseudo code, stepwise refinement, top-down and bottom-up programming etc.); test plan, Implementation issues (structured coding, recursion, documentation guidelines), modern programming language features (type less, Strong type and pseudo strong type checking, user-defined data types, data encapsulation, generic facilities, concurrency mechanism), program verification and validation(Unit testing, integration testing , acceptance testing, formal verification), Software maintenance(Source code metrices-halstead’s effort equation, cyclomatic metric), Reliability and software assurance, software quality assurance, Software cost estimation (Delphi, COCOMO etc.)

  2. Projects -Team-based term project.

Reference:

  1. Software Engineering concepts,-R. Fairly :

  2. An Integrated Approach to Software Engineering -P. Jalote

  3. Software Engineering-A Practitioner’s Approach, R.S. Pressman

DATA BASE MANAGEMENT SYSTEMS

  1. Introduction :

    2. Purpose of Database systems, Data abstraction and Modeling, Instances and schemes, Database manager, Database users and their interactions, Data Definition and manipulation language, Data Dictionary, Overall system structure

  2. Entity relationship model :

    3. Entities and entity sets, Relationship and relationship sets, Mapping constraints, E-R diagram, Primary keys, Strong and weak entities, Reducing E-R diagram to tables, trees or graphs, Generalization and Specialization, Aggregation, E-R language.

  3. Files and Data-structure Revisited :

    4. Sequential file organization, buffer management, mapping tables, trees or graphs to files, ISAM file, Use of B-tree for indexing, Hashing and Hash functions.

  4. Relational Model

    5. Structure of relational database, operations on relation Relational Algebra, Tuple

    And Domain relational calculus, Sailent features of query language.

  5. Hierarchical Model:

    6. Information Management System (IMS), Database description and tree-structure diagram, DL/I language, data retrieval and update facility, Limitations of hierarchical systems, Virtual records.

  6. Net Work Model:

    7. Database task group (DBTG) model, Data-structure diagram, Record and Set constructs, Record retrieval and update facility, Set processing facility, Example of an actual network database implementation (DMS), Importance of network database.

  7. Normalization in Relational System:

    8. Pitfalls in RDBMs, Importance of normalization, Functional, multivalued and join dependencies, 1NF to 5NF, Limitations of RDBMS.

  8. Description of an actual RDBMS and its Query language:

    9. Involves extensive practice in computer centre to get an idea of an actual implementation.

  9. Query Optimization:

    10. Importance of query processing, Equivalence of queries, Cost estimation for processing a query, general strategies, bi-relational and multi-relational join algorithms, algebraic manipulations

  10. Failure and Crash recovery in DBMS:

    11. Failure classification, transactions, Long maintenance, check point implementation, Shadow paging, example of an actual implementation.

  11. Security and Integrity:

    12. Security and Integrity violations and constraints, Authorization and views, Encryption, Example of an actual implementation.

  12. Special Topics:

Structure of a database machine, Distributed database, Present trends in Database technology.

 

References:

  1. Database System Concepts,- H.F. Korth and S. Silberschatz :

  2. Principles of Database System -J.D. Ullman

  3. Introduction to Database System-C.L. Date

  4. Fundamentals of Database System-Elmasri & Navthe :

 

 

ADVANCED RELIABILITY

  1. Class of Life Distributions Based on Notions of Ageing :

    2. Ageing properties. Families of probability distributions based on aging properties: IFR, IFRA, NBU, NBUE, DMRl and HNBUE properties (and their duals), interrelation among them; Closure under reliability operations of formation of coherent systems, mixtures and convolutions. Reliability bounds.

  2. Dependent components and their distributions :

    3. Bivariate exponential distribution and its properties. Fatal and non-fatal shock models and Bivariate exponential distribution derived from them.

  3. Maintenance and Replacement models :

    4. Block, age and random replacement policies, class of life distributions in replacement; NBU, NWU, NBUE, NWUE and their properties and relevant shockmodels. Renewal theory for replacement models.

  4. Mixture Distribution

Mixture Distribution and Competing risk Mixtures of exponential, mixtures of Weibull, Competing risks.

  1. Reliability Growth Models

NHPP reliability growth models, Alternative models.

  1. Probabilistic Modeling of Repairable Systems :

Basic concepts for stochastic point process, Inter-arrival times between successive failures, ROCOF, Estimating Avg.ROCOF, ROCOF for stationary, transient and non-stationary point processes, Statistical analysis of part and system failure data, Trend testing, Plot of cumulative failure vs. cumulative time, Statistical tests, Homogeneous Poisson Process (HPP), Non homogeneous Poisson Process (NHPP), Renewal Process (RP), Superimposed Renewal Process (SRP) Branching Poisson Process (BPP)

References:

  1. Renewal Theory, D.R. Cox, Methuen, London

  2. Repairable System Reliability, H. Ascher and H. Feingold, Marcel Dekker, N.Y.

  3. Practical Methods for Reliability Data Analysis, J.I. Ansell and M.J. Phillips, Clarendon, Oxford

  4. Statistical Analysis of Reliability Data, M.J. Crowder, A.C. Kimber, R.L. Smith and T.J. Sweeting, Chapman and Hall, London.

  5. Reliability Analysis for Complex Repairable System (L.H. Crow) in Reliability and Biometry (eds), F. Proschams and R.J. Serfling, SIAM, Philadelphia.

 

 

GAME THEORY AND DECISIONS

  1. Games Types : (29)

    2. Games in extensive form-normal form-coalitional form (3 hours); two person zero sum games –Minimax throrem-Linear programming formulation (8 hours);Infinite games-games on unit square-duels-multistage games-stochastic games (4 hours); Bimatrix games-LCP formulation-Lemke’s algorithm for solving bimatrix (6 hours); N-person games-core shapley (8 hours).

  2. Elements of Decision Theory : (20-24)

  1. Randomization, Optimality, Bayes rules, Minimax rules Admissiable rules, Invariance and sufficiency, Complete class and essential complete class of rules.

  2. Minimax rules.

  3. Complete class theorem.

  4. Results on admissibility (16-20 hours)

  5. Elements of Multicriteria decision methods (4 hours)

References :

  1. Game Theory – Guillermo Owen, Academic Press.

  2. Games and Decisions-Introduction and Critical Survey-R.D. Luce and H. Raiffa, Chapman and Hall, London

  3. Game Theory for Economists – Jurgen Eichberger, Academic Press.

  4. Mathemetical Statistics – T.S. Ferguson, Academic Press.

  5. Statistical Decision Theory – James O. Berger, Springer Verlag.

  6. Decision with Multiple Objective – R.Keeney and H. Raiffa, John Wiley.

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