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Course Detail

Course Name Modeling and Simulation of Manufacturing Systems
Course Code 24MU653
Program M.Tech. Manufacturing and Automation​
Credits 3
Campus Coimbatore

Syllabus

Unit 1

Concept of System and environment, Continuous and discrete systems, Linear and non-linear systems, Stochastic processes, Static and Dynamic models, Principles of modelling, Basic Simulation modelling, Role of simulation in model evaluation and studies, Steps in a simulation study, Verification, validation and credibility of simulation models, Advantages, disadvantages and pitfalls of simulation, Review of probability distributions and basic statistics.

Unit 2

Definition, Classifications and characteristics of production systems; measures of manufacturing systems performance, modelling elements in manufacturing systems; processes, resources, single and multi-server queues, arrival processes, service times, downtime, manufacturing costs, resources selection rules, different manufacturing flexibilities. Input data modelling – Basic DES Modelling, Manufacturing Performance Metrics in DE, Modelling basic and detailed operations: part arrivals, sequencing, and scheduling, resources/processes, transporters, material handling, inventory management, inspection

Unit 3

Simulation output analysis – Bottleneck analysis – Sensitivity Analysis – Simulation Optimization – Exercise / Case problems: Modelling and analysis of Flow shops, Job shops, Flexible Manufacturing Systems, Push / Pull manufacturing systems, Supply Chains using discrete event simulation package.

Objectives and Outcomes

Course Objectives

  • To make the students proficient in the use of discrete event simulation software for modeling and simulation of the manufacturing system.
  • Expose students to model real-world manufacturing systems
  • Analyze any manufacturing system for improvement using a discrete event simulation

 

Course Outcomes

CO

CO Description

CO1

Appreciate the role of discrete-event simulation and modeling and their application in the manufacturing

environment.

CO2

Analysis of simulation input data using statistical tools and fit the input data into a suitable probability

distribution for developing simulation models of manufacturing systems.

CO2

Model and analyze complex manufacturing systems using discrete event simulation software package.

CO4

Interpret and analyze the simulation results of a real-world problem, identify bottlenecks, and provide

suggestions for performance improvement.

 

CO-PO Mapping:

 

PO1

PO2

PO3

PO4

PO5

PO6

CO1

2

 

2

1

 

 

CO2

2

3

2

2

 

 

CO3

2

3

2

2

 

 

CO4

2

3

2

2

 

1

 

Skills Acquired

Performance Modelling of Manufacturing Systems using Discrete Event Simulation Software; Bottleneck analysis

 

Text Books / References

  1. Kelton, David. “Simulation with ARENA”. McGraw-Hill, 2015.
  2. Altiok, Tayfur, and Benjamin “Simulation modeling and analysis with Arena”. Elsevier, 2010.
  3. Rossetti, Manuel “Simulation modeling and Arena”. John Wiley & Sons, 2015.
  4. Lab Manual

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