simulation models
Posted by MOSIMTEC LLC
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In an earlier post, we defined simulation as “a replication of a real-world process or event in an environment that is isolated or disconnected from its real-world counterpart.”

The basic idea is to see how the real system could interact with a set of new conditions or rules. These conditions/rules could include a new implementation model (e.g., changing over to Lean Manufacturing) or issues (such as a late shipment, surge in shopping traffic, etc).

You can choose from a wide range of simulation models. Your selection depends on the nature of your real-world system, your requirements, and your intended business outcomes.

In this article, we take a look at the 4 leading types of simulation models.

The Leading Types of Simulation Models

1. Monte Carlo / Risk Analysis Simulation

In simple terms, a Monte Carlo simulation is a method of risk analysis. Businesses use it prior to implementing a major project or change in a process, such as a manufacturing assembly line.

Built on mathematical models, Monte Carlo analyses use the empirical data of the real system’s inputs and outputs (e.g., supply intake and production yield). It then identifies uncertainties and potential risks through probability distributions.

The advantage of a Monte Carlo-based simulation is that it provides awareness and a thorough understanding of potential threats to your bottom-line and time-to-market.

You can implement Monte Carlo simulations to practically any industry or field, including oil and gas, manufacturing, engineering, supply chain management, and many others.

2. Agent-Based Modeling & Simulation

An agent-based simulation is a model that examines the impact of an ‘agent’ on the ‘system’ or ‘environment.’ In simple terms, just think of the impact a new laser-cutter or some other factory equipment has on your overall manufacturing line.

The ‘agent’ in agent-based models could be people, equipment, and practically anything else. The simulation includes the agent’s ‘behavior,’ which serve as rules of how those agents must act in the system. You then look at how the system responds to those rules.

However, you must draw your rules from real-world data — otherwise, you will not generate accurate insights. In a way, it serves as a means to examine a proposed change and identify potential risks and opportunities.


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3. Discrete Event Simulation

A discrete event simulation model enables you to observe the specific events that result in your business processes. For example, the typical technical support process involves the end-user calling you, your system receiving and assigning the call, and your agent picking up the call.

You would use a discrete event simulation model to examine that technical support process. You can use discrete event simulation models to study many types of systems (e.g., healthcare, manufacturing, etc), and for a diverse range of outcomes.

For example, the Nebraska Medical Center had used discrete event simulation models to see how it could remove workflow bottlenecks, increase the utilization of its operating rooms, and lower patient/surgeon travel distance and time.

4. System Dynamics Simulation Solutions

This is a very abstract form of simulation modeling. Unlike agent-based modeling and discrete event modeling, system dynamics does not include specific details about the system. So for a manufacturing facility, this model will not factor in data about the machinery and labor.

Rather, businesses would use system dynamics models to simulate for a long-term, strategic-level view of the overall system.

In other words, the priority is to get aggregate-level insights about the entire system in response to an action — e.g., a reduction in CAPEX, ending a product line, etc.


More on How to Use Simulation to Cut Costs & Boost Profit:


As you can see, each simulation model has its advantages and, as a result, serves a specific purpose. Selecting the right model for your needs — which is a challenge for some — is only the first step, you also require a specific set of tools and expertise.

At MOSIMTEC, we help companies mitigate costly risk and achieve key business outcomes by bringing the simulation modeling expertise and tools they need to the table. Call us today.