MEV443: Discrete-Event System Simulation

Course feature and Objective

Business decisions are made mostly in uncertain and dynamic environment where input variables keep changing. A model helps the analyst to predict the effect of changes to the system. A model should be a close approximation to the real system and incorporate most of its salient features but should be less complex. Simulation is the imitation of the operation of a real-world process or system over time that will help in drawing inferences concerning the operating characteristics of the real system. This course helps the students to build an expertise to develop a model and simulate using the software like ARENA or Microsoft Excel. It is expected that this course will immensely benefit the students.

Course Meeting Times: G slot (Mon: 1.00 p.m. – 2.00 p.m.; Tue: 9.00 a.m. – 10.00 p.m.; Thurs: 10.15 p.m. – 11.15 p.m.)

Text Book:

  1. Banks, J., Carson, J.S., Nelson, B.L., and Nicol, D.M., Discrete-Event System Simulation, 4th Edn. Pearson Education, Inc., 2007.

References

  1. Law, A.W. and Kelton, W.D., Simulation Modelling and Analysis, McGraw Hill International, 2000.
  2. Gordon, G., System Simulation, Second Edition, Prentice Hall of India, 1995.
  3. Ross, S.M., Simulation, Third Edition, Academic Press, 2002.
  4. Fishman, G.S., Concepts and Methods in discete Event Digital Simulations, Wiley, New York, 1973.
  5. Les Oakshott., Business Modelling and Simulation, Pitman Publishing, 1997.
  6. Carrie, A., Simulation of Manufacturing Systems, John Wiley & Sons Ltd., 1988.
  7. Rossetti, M. D., Simulation Modeling and ARENA, John Wiley, 2009
  8. Hessam S. S and, Cellier, F.E., Discrete event modelling and Simulation technologies, Springer-Verlag 2001

Course Syllabus

Module 1 (10 Hours)

  1. System concepts - Components of a system - Discrete and continuous systems - System modeling - Types of models - System simulation - Steps in a simulation study.
  2. Monte Carlo simulation
  3. Examples of simulation of single server, single queue systems
  4. Examples of Simple inventory systems
  5. Exercises (Both Class work and Home work)
  6. All above exercises must be tried in spreadsheets.
  7. Concepts in discrete event system simulation - Event scheduling/time advance algorithm.

Module 2 (11 Hours)

  1. Random number generation: Techniques for generating random numbers
  2. Linear congruential method
  3. Multiplicative congruential method
  4. Exercises
  5. Tests for random numbers
  6. Frequency tests
  7. Auto correlation tests
  8. Exercises.
  9. Random variate generation: Inverse transformation method
  10. Exponential
  11. Uniform
  12. Empirical discrete
  13. Empirical continuous distributions.
  1. Input modelling for simulation
  2. Data collection
  3. Identifying the distribution using histograms - Parameter estimation
  4. Goodness of fit test.
  5. Exercises

Module 3 (12 Hours)

  1. Verification and validation of simulation models:
  2. Concepts of verification,validation concepts
  3. Face validity
  4. Validation of model assumptions and
  5. Validating input-output transformations.
  6. Output analysis for a single model: Types of simulations with respect to output analysis
  7. Measures of performance and their estimation
  8. Output analysis for terminating simulations
  9. Confidence interval estimation for a fixed number of replication
  10. Confidence intervals with specified precision –
  11. Output analysis for steady state simulations
  12. Initialization bias
  13. Replication method
  14. Sample size determination for a specified precision - Batch means method.

Module 4 (9 Hours)

  1. Simulation modeling and analysis of manufacturing systems: Objectives and performance measures
  2. Issues in simulation of manufacturing systems - Modelling downtimes and failures.
  3. Introduction to simulation software for manufacturing applications: Salient features of ARENA.
  4. Exercises- Model building using ARENA and Microsoft excel – Exercise problem in Sl.No.2 must be tried in ARENA.

Grading Policy

Marks distribution / Remarks
Test 1 / 15% / Portions will be from Sl. Number 1 to Sl. Number 5
Test 2 / 15% / Portions will be from Sl. Number 6 to Sl. Number 11
Assignments / 10% / Exercises shown in the syllabus
Course project / 10% / A model which they build in ARENA or spreadsheet for any real time case.
End Exam / 50%

Homeworks/Assignments

About 5 home-works/Assignments (Exercises) will be assigned throughout the term at approximately two-week intervals.

Course Project

  • Students will be required to submit a course project.
  • This should involve modeling in ARENA or Spreadsheet for any real time case.
  • A brief interim progress report will be required before March 14, 2011 (3 Marks)
  • Course projects must be completed by the April 6, 2011, at which time a final report will be due.(7 Marks)

Ethics Policy

  • Collaboration and discussion of homeworks/assignments is encouraged but eachstudent must submit an individual solution.
  • Collaboration on course project is encouraged provided that there must be individual contributions.