Manufacturing Simulation: 3 Ways to Model Your Manufacturing Process


Manufacturing simulation is a powerful tool for optimizing production processes, reducing costs, and improving overall efficiency. By simulating various scenarios, manufacturers can predict outcomes, identify bottlenecks, and test changes without disrupting the actual production line. 

In this article, we’ll explore three methods for conducting manufacturing simulations: a quick and simple approach using Excel, a more sophisticated method with Discrete Event Simulation (DES), and detailed 3D modeling using advanced software.

1. Quick and Dirty Way with Excel

One of the fastest and easiest ways to model a manufacturing process is by using spreadsheets. This method involves building a simple table that lists each process step, the number of stations, average throughput per station, total throughput, downtime, and other relevant metrics.

Although this method isn’t a true simulation and serves more as a high-level summary, it provides the basic information needed to plan resources and right-size the line.

Example Table

Process StepNumber of StationsThroughput Per Station (units/hr)Downtime (%)Total Throughput (units/hr)
Chassis Assembly2505%95
Component Installation3301.5%88
Final Assembly26010%108
Spreadsheet model of a simple production line

The table above is a simplified example of a production line modeled in Excel. It provides quick insights, such as the painting process being the main bottleneck due to its low throughput. This can be improved by adding another painting station or increasing resources. Despite high downtime in the final assembly, its throughput remains high, so reducing downtime there won’t significantly impact overall performance.

Pros and Cons of using spreadsheets to model a production line


  • Fast and easy to set up
  • Requires no specialized software or advanced skills
  • Provides a basic overview of the manufacturing process


  • Does not account for variability or standard deviations in throughput, cycle times, and downtimes.
  • No information on WIP (work in progress) build up in the system over time
  • Lack of information on wait times and total time spent in production
  • Limited in complexity and less accurate and reliable for complex processes

2. Discrete Event Simulation (DES) For Manufacturing Simulation

Discrete Event Simulation (DES) is a more advanced method that models the manufacturing process as a series of discrete events, each representing a specific action or change in the system. 

DES accounts for variability, providing a more accurate representation of the manufacturing process, including WIP at each station, wait times, and total production lead time. It also enables planning for best- and worst-case scenarios, helping to better prepare for uncertainty.

Two Ways to Conduct DES

1. Easy Way – Using Kaizoft’s Manufacturing Simulation Software

One of the simplest ways to conduct DES is by using specialized software like Kaizoft’s Manufacturing Simulator Tool. This software offers an intuitive interface and pre-built components for modeling complex processes without needing advanced programming skills. 

Within minutes, users can build the model in table form, similar to Excel but with additional variables, or use a flowchart format for a graphical view.

2. Using Python Libraries, VB Scripts on Excel, or MATLAB

For those with programming skills, conducting DES using Python libraries like SimPy, VB scripts on Excel, or MATLAB offers greater flexibility and customization.

Example in Python using SimPy:

manufacturing simulation using simpy
Source: code snippet from Simpy machine shop example:

Pros and Cons of using DES for manufacturing simulation


  • More accurate and detailed than Excel-based simulations.
  • Can account for variability and stochastic elements.
  • Flexible and customizable.


  • Requires knowledge of specialized software or programming.
  • Can be time-consuming to set up and run.
  • May require more computational resources.

The downsides mentioned here primarily apply to the coding approach and can be significantly mitigated by using DES and manufacturing simulation software like Kaizoft’s Manufacturing Simulator Tool

3. Detailed 3D Modeling and Simulation Using Advanced Software

For the most detailed and accurate simulations, advanced software that offers 3D modeling and simulation capabilities is the best choice. This software can model every aspect of the manufacturing process in great detail, providing a comprehensive view of the system.

Examples of Advanced Software

  • AnyLogic
  • FlexSim
  • Siemens Tecnomatix Plant Simulation
flexsim manufacturing simulation
Source: Flexsim

Pros and Cons of using advanced 3D modeling tools for simuation


  • Highly detailed and accurate simulations.
  • Can visualize the manufacturing process in 3D.
  • Ideal for complex and large-scale manufacturing processes.


  • Expensive and requires a significant investment.
  • Time-consuming to learn and implement.
  • Requires specialized skills and expertise.


Choosing the right method for manufacturing simulation depends on the complexity of your process, available resources, budget, and desired level of detail. For quick and simple simulations, Excel offers a fast and easy solution. For more accuracy and flexibility, Discrete Event Simulation using software like Kaizoft’s Process Simulator Tool or programming languages like Python provides a robust option. For the highest level of detail and accuracy, advanced 3D modeling and simulation software are the best, albeit more expensive and complex, choices. By leveraging these tools, manufacturers can optimize their processes, reduce costs, and improve overall efficiency.

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