Modeling and simulation technology has been utilized for decades, and has been applied to answer a wide range of manufacturing and distribution questions. Whether designing a completely new greenfield facility, or making changes to an existing operation, the costs can be in the 10s and possibly 100s of millions of dollars. In today’s competitive business environment, companies cannot afford to “learn at real time” with the existing operation. Experimenting with an existing facility can be costly and potentially disastrous. Simulation models, or “digital twins”, can show you results from a day, week, or month of operation in minutes. In today’s distribution environment led by companies like Amazon, customers expect more from their suppliers, and customers have alternatives if your company can’t ship the product to them on time. Additionally, a facility that is running below its potential can be a financial drain on the company. If your company is preparing to make a large capital outlay for new equipment and facilities, or your current operation is creating pain for the facility stakeholders, it may be time to explore the questions you can answer using simulation.
Here are a few thoughts on why simulation is an improvement over other methods of analysis:
It’s random
The real world is a random place. A picking operator might be able to make 200 picks an hour on average, which equates to 18 seconds a pick, but when something “random” happens, an individual pick could take 60 seconds. A few slower picks in a row, and the queue in front of the picker could build to the point where boxes won’t fit in the queue. Static analysis tools can help determine how many pickers are required with an average pick time. Simulation can show us when and where the system might gridlock because of a few “random” events, or a surge in orders hits the pick areas at the “wrong time”. The more randomness one has in an operation, the greater the advantages simulation can provide. While automation has been applied to many processes, reducing some random behavior, humans are still required in many areas. Automation can also behave in random ways, like conveyor jams because of improper box alignment.
It’s big
The larger a facility, the more difficult the facility is to design using a spreadsheet. Multiple areas all interacting with each other create an environment well suited for simulation. Additionally, the larger the system, the more costly, generating a greater need for assurance that the system will operate efficiently. For a large system that is currently operating, it is difficult to get the “big picture” about what is actually happening, and impossible to “replay” a day to see “what happened?”. When millions of dollars are on the line, a digital twin can pay for itself.
It’s risky
New technologies are being introduced constantly in the material handling world. One recent example is Autonomous Mobile Robots, or AMRs. Most managers don’t want to be the first to “try” a new technology in their operation. But someone has to be an early adopter, which introduces risk. Simulation can help companies see how a new technology is going to work in their operation. Equipment details like velocity, acceleration, and congestion can be represented with a high degree of accuracy, which helps reduce the risk of adopting new technology.
Simulation modeling has created value in manufacturing and distribution, helping facilities run more efficiently and reducing the risk introduced by change. Making a decision on whether to use simulation can be tough. Contact me at