Simulation
Simulation

KEY OUTLINE
1. Definition of Simulation

2. Simulation Methodology
1. Problem Definition
2. Constructing a Simulation Model
1. Parameters Defined
2. Variables Defined
3. Decision Rules Defined
4. Distributions Defined
5. Time Incrementing Defined
3. Specifying Values of Variables and Parameters
1. Run Length (or Run Time) Defined
4. Evaluating Results
5. Validation
6. Proposing a New Experiment
7. Computerization

3. Simulating Waiting Lines
1. Example: A Two-Stage Assembly Line

5. Simulation Programs and Languages
1. Desirable Features of Simulation Software

Advanced Case: Understanding the Impact of Variability on the Capacity of a Production System

KEY POINTS

Simulation refers to using a computer to perform repeat experiments on a model of a real system. It is undertaken before the real system is operational to aid in its design and to see how the system might react to changes in its operating rules or even to evaluate the system's response to changes in its structure. It is a standard tool in business, particularly in manufacturing situations.

It is also useful as a training tool to train managers and workers in how the real system operates, in demonstrating the effects of changes in system variables, in real-time control, and in developing new ideas about how to run a business.

In problem definition, simulation entails specifying the objectives and identifying the relevant controllable and uncontrollable variables of the system to be studied. The next step is to construct a simulation model that specifies the variables and parameters, the decision rules to be used and the probability distributions - either empirical frequency distributions or standard mathematical distributions. Other variables to address in the model are the time-incrementing procedures, starting conditions, run length, and statistical tests. Results can be compared with other information in the organization including past operating data from the real system and operation data for the performance of similar systems. Even the judgment of the analyst is used. Validation assures the simulation is correct.

New experiments can be performed changing the various factors of the model. Spreadsheet simulation can also be used. Models for simulation can be classified as either continuous or discrete. Some disadvantages of simulation are the time and effort for model building and the computer time needed to run complex models. Also the techniques, while popular, lack a standardized approach.

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