1. Simulation - Introduction

2. Simulation?
Simulation: “… imitation of a dynamic system using a computer model in order to evaluate and improve system performance.”
By studying the behavior of a model one can gain insights about the behavior of the actual system
Focus will be on discrete-event simulation
Models the effects of the events in a system as they occur over time
Employs statistical methods for generating random behavior and estimating model performance

3. Why simulate?
Provides a way to validate whether or not the best decisions are being made
It is a powerful planning and decision-making tool
Simulation promotes a try-it-and-see attitude that stimulates innovation and encourages thinking “outside-the-box”

4. What makes simulation such a powerful planning and decision-making tool?
Captures system interdependencies
Accounts for variability in the system
Is versatile enough to model any system
Shows behavior over time
Is less costly, time consuming, and disruptive than experimenting on the actual system: “… if at first you don’t succeed, you probably should have simulated it.”
Provides information on multiple performance measures
Is visually appealing and engages people’s interest
Provides results that are easy to understand and communicate
Runs in compressed, real, or even delayed time
Forces attention to detail in a design: developing a model is, in itself, beneficial in that it forces one to think through the operational details of the process

5. Process of simulation experimentation
Formulate a hypothesis about what design or operating policies work best
Set up simulation model
Conduct multiple replications of the experiment/simulation
Analyze simulation results and draw conclusions about hypothesis
Simulation itself is not a solution tool, but rather an evaluation tool: it describes how a defined system will behave; it does not prescribe how it should be designed

6. Typical applications of simulation
Simulation has been used to help plan and make improvements in many areas of both manufacturing and service industries:
work-flow planning
throughput analysis
capacity planning
productivity improvement
cycle time reduction
layout analysis
staff and resource planning
line balancing
work prioritization
batch size optimization
bottleneck analysis
production scheduling
quality improvement
resource scheduling
cost reduction
maintenance scheduling
inventory reduction
control system design

7. Simulation is appropriate if the following criteria hold true
An operational (logical or quantitative) decision is being made
The process being analyzed is well defined and repetitive
Activities and events exhibit some interdependency and variability
The cost impact of the decision is greater than the cost of doing the simulation
The cost to experiment on the actual system is greater than the cost to do a simulation

8. Decision maker involvement in simulation
Decision maker should be heavily involved in, if not actually conducting, the simulation project
Often improvements suggest themselves in the very activity of building the model