Hands-On System Simulation

Master the essentials of system simulation, probability, Python, and Rockwell Arena to solve real-world challenges.

What you'll learn

Understand the Fundamentals of System Simulation: Define key simulation concepts, differentiate between modeling and simulation, and classify simulation models.

Use probability theory, statistical distributions, and random number generation methods to support simulation stu

Develop and analyze simulations with Rockwell Arena and Python, Julia, Java leveraging modules like SimPy for advanced problem-solving.

Verify and validate simulation models while interpreting the results to make informed decisions in real-world scenarios.

Requirements

Basic knowledge of mathematics and statistics.

Familiarity with basic programming concepts (optional but helpful).

A computer with internet access for installing required software like Python, Jupyter, or Rockwell Arena.

Description

Are you ready to explore the exciting world of system simulation? This comprehensive course is designed to provide you with a strong foundation in simulation modeling, probability, and practical tools to analyze and optimize real-world systems. Whether you are a student, engineer, or professional, this course will equip you with the skills needed to tackle complex decision-making problems using simulation techniques.The course begins with an introduction to system simulation, including terminology, model classification, and data collection techniques. You will learn how to set up, verify, and validate simulation models while exploring popular tools in the industry.Next, you’ll dive into the mathematical foundations of simulation, covering probability theory, statistical distributions, and random number generation. These concepts are essential for building accurate and reliable simulation models.The course also features practical applications, including modules on Rockwell Arena, Julia programming, Python programming, and the SimPy library. You’ll learn how to use these tools to create simulations for real-world scenarios like bank teller systems and car wash operations.By the end of this course, you’ll have a clear understanding of system simulation and the confidence to apply it in your projects. Join us today and take the first step towards mastering this valuable skill set!

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Introduction to System Simulation

Lecture 2 Introduction to System Simulation

Lecture 3 Decision-Making Workflow in Simulation

Lecture 4 Simulation Modeling Terminology

Lecture 5 Comparing Modeling and Simulation

Lecture 6 Classifying Simulation Models

Lecture 7 Data Collection for Simulation

Lecture 8 Setting Up the Simulation Model

Lecture 9 Verification of the Software Solution

Lecture 10 Popular Simulation Software

Lecture 11 Exploring Discrete Event Simulation (DES)

Section 3: Rockwell Arena Modules

Lecture 12 Create

Lecture 13 Dispose

Lecture 14 Process

Lecture 15 Decide

Lecture 16 Batch

Lecture 17 Seperate

Lecture 18 Assign

Lecture 19 Record

Lecture 20 Attribute

Lecture 21 Set

Section 4: Python Programming (Optional)

Lecture 22 What is Python?

Lecture 23 Anaconda & Jupyter & Visual Studio Code

Lecture 24 Google Colab

Lecture 25 Environment Setup

Lecture 26 Python Syntax & Basic Operations

Lecture 27 Data Structures: Lists, Tuples, Sets

Lecture 28 Control Structures & Looping

Lecture 29 Functions & Basic Functional Programming

Lecture 30 Intermediate Functions

Lecture 31 Dictionaries and Advanced Data Structures

Lecture 32 Exception Handling & Robust Code

Lecture 33 Modules, Packages & Importing Libraries

Lecture 34 File Handling

Lecture 35 OOP

Section 5: Closure

Lecture 36 The End

Students and professionals interested in learning the fundamentals of system simulation,Beginner to intermediate learners looking to explore discrete event simulation and Python-based simulation tools.,Engineers, data analysts, and decision-makers seeking practical knowledge to implement simulation in real-world scenarios.