This article aims to elucidate the distinctions between emulation and simulation, two essential concepts in the fields of computer science, engineering, and various other domains. Emulation and simulation are often used interchangeably, but they represent distinct approaches to replicating real-world systems and processes. In today’s blog post I will define, compare, and contrast simulation and emulation.

Emulation and simulation are two different modeling concepts

Emulation and simulation are both techniques used to model, analyze, and understand complex systems or processes. They serve different purposes and are employed in various domains, from computer science and electronics to transportation and healthcare. In supply chain management and production planning, emulations and simulations are both applied in many different domains and ways, e.g. for warehouse design and lateron warehouse operation, for process design and lateron process selection, for production planning and lateron production execution, and so on.

Emulations replicate system behaviour while simulation imitate it

Emulation involves replicating the behavior of one system using another system, typically a computer. It aims to imitate the functions and operations of the target system accurately. Emulation often focuses on hardware or software, mimicking the functionality and compatibility of the original system.

Simulation, on the other hand, refers to the imitation of a system or process over time, typically through computer-based models. It involves creating a dynamic model of the real-world system to analyze its behavior under various conditions, making it suitable for experimentation and analysis.

Key differences between emulation and simulation

The core differences between emulation vs. simulation are:

• Purpose: While emulation is used for legacy system support and operational support, simulation is employed to study system behaviour, i.e. design e.g. warehouse designs, production proceses, and production control concepts. For example, an emulation would be used to forecast the lead time of a specific customer order, currently placed in the real-world system, to be picked and shipped, a simulation would be used to compare different warehousing designs and process designs to reduce or verify lead time expectations.
• Level of abstraction: Emulations operate at low levels of abstractions, are very detailed, and replicate the real-world system in any relevant way. A simulation may be more abstract, as its objectives are of more strategic nature.
• Fidelity: Emulation aims for a high degree of fidelity to the original system, emphasizing accuracy and precision in mimicking its functions. Simulation may prioritize approximations of behavior rather than exact replication, focusing on capturing essential aspects of a system’s behavior.

Emulation and simulation are distinct concepts, each serving different purposes and having specific characteristics. Emulation focuses on precise replication of systems for compatibility, while simulation aims to model the behavior of systems for analysis, experimentation, and decision-making. Understanding these differences is crucial for choosing the right approach in various applications, leading to more effective system development, testing, and analysis.

Concrete examples of emulation and simulation

Imagine you want to play a classic video game that was originally designed for a game console, like the Super Nintendo Entertainment System (SNES), on your modern computer. To do this, you can use an emulator, such as ZSNES or SNES9x, which replicates the SNES’s hardware and software environment on your PC. The emulator mimics the SNES’s central processing unit (CPU), graphics processor, sound system, and game controller input, allowing you to run SNES games as if you were using the original console. It provides a high level of compatibility, enabling you to play the games without the need for the actual SNES hardware.

In urban planning or transportation engineering, simulating traffic flow is a common practice. Imagine a city planner wants to assess the impact of proposed changes to a city’s road network, such as adding a new highway or adjusting traffic signal timings. In this simulation, a dynamic model of the city’s road network is created, with representations of vehicles, intersections, traffic lights, and other relevant components. The software models how vehicles move through the network, considering factors like traffic density, driver behavior, and road conditions. By inputting various scenarios, such as different traffic volumes or signal timings, the planner can analyze the impact on traffic congestion, travel times, and overall efficiency. This simulation allows the planner to make informed decisions about urban development and traffic management without physically changing the city’s infrastructure.

Use cases of emulation and simulation in SCM and manufacturing

Emulation and simulation are valuable tools in supply chain management and production planning. They enable organizations to model, analyze, and optimize various aspects of their operations. Here’s how these techniques can be applied in these domains:

1. Production line emulator: Emulation can be used to replicate the behavior of a production line or manufacturing process. By emulating a production line, organizations can test changes in equipment, processes, or configurations before implementing them in the actual production environment. This helps identify potential issues, reduce downtime, and optimize the production process.
2. Emulating supply chain nodes: Emulating different nodes in the supply chain, such as warehouses or distribution centers, can help organizations assess the impact of changes in locations, capacities, or handling processes. This is useful for evaluating the efficiency of distribution networks and optimizing inventory management.
3. Emulation for inventory management: Emulators can simulate inventory systems, allowing organizations to experiment with various inventory policies, reorder points, and safety stock levels. This helps in achieving a balance between minimizing holding costs and ensuring product availability.

Simulation in SCM and production planning:

1. Demand forecasting: Simulation models can predict future demand based on historical data, market trends, and other variables. This aids in production planning and helps organizations adjust inventory levels and manufacturing schedules accordingly.
2. Lead time simulator: Simulating lead times from suppliers and transportation times in the supply chain enables organizations to assess the impact of variability in these factors. This is crucial for ensuring timely deliveries and minimizing disruptions.
3. Production capacity planning: Simulation models can help determine the optimal production capacity, taking into account factors like machine availability, labor resources, and maintenance schedules. This ensures that production lines are not over- or underutilized.
4. Optimizing order fulfillment: Simulating order fulfillment processes, including order picking, packing, and shipping, helps organizations fine-tune their operations to meet customer delivery expectations efficiently.
5. Scenario analysis: Simulation allows for scenario analysis, enabling organizations to evaluate the consequences of various decisions and disruptions. For example, it can model the impact of a sudden increase in demand, supply chain disruptions, or changes in production capacities.
6. Risk analysis: Simulation is useful for identifying and mitigating risks in the supply chain, such as supply chain disruptions, transportation delays, or demand fluctuations. By running “what-if” scenarios, organizations can develop contingency plans and risk mitigation strategies.

In both supply chain management and production planning, emulation and simulation provide decision-makers with a platform to experiment with different strategies, optimize operations, and make informed decisions. They can lead to cost savings, improved efficiency, and more resilient supply chain and production processes.

Concluding remarks on emulation vs. simulation

This article explained the differences between emulation and simulation, and how both concepts may be applied in production planning and SCM. If you are interested in learning more you might be interested in reading the following articles:

• Link: Simulation methods for SCM analysts
• Link: Open-cast mine simulation for better planning
• Link: Analytics in the steel production value chain
• Link: Parking lot simulator with simmer in R
• Link: 53% ROI: Barge transport simulation study
• Link: Job shop SimPy Python simulation

Linnart Felkl

Data scientist focusing on simulation, optimization and modeling in R, SQL, VBA and Python