Simulation - Introduction

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

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”

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

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

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

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

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