Computer-based Simulation Models of Value Streams

Tomorrow's innovations will increasingly be the byproduct of how companies and their customers behave around this new generation of models, prototypes and simulations. 

While certain disciplines, like weather forecasting, are almost 100% model-based, simulation modeling in manufacturing has generally been limited to testing various options at the design stage, much like an aircraft builder will use a wind-tunnel. Once the aircraft is built, the wind-tunnel is no longer needed.

Introduction to MBM (Model-Based Management)

​​​​​​Lean practitioners are no strangers to the use of simulations and models for both training and prototyping. 

Using computer-based simulation models of  Value Streams to manage day-to-day challenges that inevitably arise in a Mixed Model Manufacturing environment is possible. 

Role and Benefits of Models in Mixed Model Value Streams

When we attempt to mix different models and options in the same Value Stream, achieving a smooth workflow is challenged by differences in work content time, changes in customer demand, normal human variability, material delivery challenges, and on and on. No matter how experienced we may be in dealing with these issues, it's beyond human capacity to understand how our Value Stream will actually perform in the face of all of these moving parts. That's where computer-based simulation tools can be very useful. Here are some of the things we can do with a well-designed discrete-event simulation model of a production line:

1. Validate your initial design, and ensure that you are not over-resourcing or under-resourcing the line.

2. Use the model for daily staffing. Even if the same number of units are built daily, the number of workers can vary depending on the product mix.

3. Fine-tune your sequencing rules in order to optimize productivity and throughput.

4. Identify potential bottlenecks ahead of time so that you can plan for them. Remember that bottlenecks can be floating and don't always happen in the same place.

5. Optimize the use of buffers in order to improve the flow. This is difficult to do just using tools like spreadsheets.

6. Nail down a flexing plan if you need to regulate the output of a line based on customer demand.

In a nutshell,  mixed model challenges and the benefits of using modeling tools to address them make simulation modeling a no-brainer.

Build Tools With (Almost) Free Resources

1. The Lean Design Simulator.  a low learning-curve tool to help you build discrete-event simulation models without needing to start a new career. 

2. Use software you already have. Visual Basic for Application (VBA) is incredibly powerful, and already built into Excel. Don't know how to write VBA code? Let ChatGPT do the work for you!

3. Want to upgrade your model-building software? Commercial simulation software is  readily available, but there are some free options as well. Check out two of them: having ChatGPT use free simulation libraries to write a Python program for you, and using Open Source software like JaamSim.

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