Simulation of Operations

Recommended Prerequisites

Statistics.

Teaching Methods

In the first part of the course theoretical lectures are used to present the curricular unit subjects. In the remaining weeks, in each class a simulation problem is proposed to be solved by the students. They have to study the problem and prepare the model as homework. In the following class the students build the computer model. The lectures are tutorial where the teacher helps the students to overcome their difficulties.

During the semester a simulation problem must be solved by the students as part of the evaluation process.

Learning Outcomes

The primary objectives of this course is: (1) to aquire knowledge about queuing theory; (2) To enhance the student’s ability to apply critical thinking to the solution of complex industrial problems; (4) To develop the student’s ability of creating computer simulation models of manufacturing and service systems and analyzing their simulation results.

A simulation software (Simul8) is used to demonstrate building and executing the models. At the completion of the course the student should be able to: (1) understand the importance and solve analitically queuing problems; (2) Understand the broad applicability of discrete-event process simulation to industrial engineering problems; (3) Understand the fundamental logic, structure and components of simulation modeling; (4) Demonstrate knowledge of how to use Simul8 to build a simulation model; (5) Analyze simulation output and correctly infer performance measures.

Work Placement(s)

No

Syllabus

1. Queing theory. Little law. M/M/1 and M/M/S modelos. Queues with limited size. Queus with finite populations. Models requiring other distributions

2 Manufacturing and service system modeling by simulation.

3. Simulation software’s.

4. Models validity and credibility.

5. Selection of probability distributions for simulation data.

6. Results analysis.

Head Lecturer(s)

Samuel de Oliveira Moniz

Assessment Methods

Assessment
Project: 40.0%
Exam: 60.0%

Bibliography

Silva C. “Slides de apoio à disciplina de logística”.

Law, Averill and Kelton, W.David (2000). Simulation Modeling and Analysis (3rd ed), McGraw-Hill.

Elder, Mark. Simulation Course Handbook, University of Strathclyde, UK.