Understanding systems through simulation
Operations of industrial sites or logistics can be complex and difficult to understand. To understand a system properly, the best way is to dive in to the system and play with it, to change things and see how the system as a whole reacts to those changes. But this can be risky, using trial and error in real-time. Wouldn’t it be great if this was easy to do? If it was quick and simple to add equipment, identify how your operations react to the change and then make the decision after the fact whether you want to buy the equipment or not? This is where simulation can be applied, as it allows you to experiment on your complex operations and find out how they react to changes without having to mess with those systems in real life!
For example, imagine a rail system that is struggling to keep up with demand. Broadly, rail systems can be split into three physical subsystems: the physical rails themselves (below rail), the rolling stock that moves across the network (above rail), and the endpoints. We can upgrade any of these, by laying more track, purchasing more consists (trains), or adding loading/unloading points. All of these upgrades are slow, difficult, and expensive and so we want to make the right decision the first time.
It can be challenging to work out where the right place is to focus without using a simulation to drill down properly. For example, looking at operations we may notice that trains are queueing up the track and not getting through the loading point fast enough and then conclude that we need more capacity at our load point. This is an expensive proposition and it makes sense to test our hypothesis that adding a load point will solve the throughput problem before investing in it.
Building a simulation will ensure that the solution will solve the problem at hand. In this instance, there are many ways the assumed solution could fail:
It may turn out that the rail cannot support a higher throughput to feed the new loaders.
We may overload the destination unloading facilities and find the bottleneck just moves to the other end of the system.
Perhaps the most powerful ability of simulating operations is testing operating policies: a more even scheduling method may ease the congestion enough to satisfy current demand without costly capex at all!
Simulations take the “guess work” out of building business cases. While calculations assuming static or steady-state conditions are useful in certain scenarios, where there are variable buffers/storages in the system, or discrete movement of product (such as on trucks or ships) a dynamic simulation is the best way to truly test changes to the system.
If you are facing a decision on what the right changes are to make to your system to drive improved performance, and you would like some help understanding your systems so you can achieve your performance goals, send an email to hello@northcardinal.com.au and let’s have a chat about how we can help you achieve your business goals.