What is Simulation?
There are many different definitions of simulation, SIMUL8 software specializes in discrete event simulation described below.
Discrete Event Simulation
A simulation is a computer model that mimics the operation of a real or proposed system, such as the day-to-day operation of a bank, or the running of an assembly line in a factory, or the staff assignment of a hospital or call center.
The model is time based, and takes into account all the resources and constraints involved, and the way these things interact with each other as time passes. Simulation also builds in the randomness you would see in real life. For example it doesn't always take exactly 5 minutes for a customer to be served and a customer doesn't always arrive every 15 minutes. This means that the model really can match reality - so something you try in the model will behave the same way as it would in real life.
With simulation you can quickly try out your ideas at a fraction of the cost of trying them in the real organization. And, because you can try ideas quickly, you can have many more ideas, and gain many insights, into how to run the organization more effectively.
How Does Simulation Work?
When you click the run button in a simulation model you see the work you do (products, patients, paper work etc.) move around the organization. The clock in the corner of the screen tells you what the equivalent time would be in the real system.
Simulation is animated. This enables visualization of a new facility and a greater ability to visualize the impact of experiments in an existing facility. You can see key bottlenecks, over-utilized resources and under resourced elements of a system.
The software automatically collects performance measures as the model runs so that you can not only see visually what will happen, you can also get accurate numerical results to prove your case.
Typical outputs include:
- Inventory
- Throughput
- Bottleneck utilization
- Productivity
Typical inputs include:
- Cycle time
- Staff levels
- Arrival/order rates
- Average order size
What Can Be Simulated?
There are many scenarios that can be simulated. As a general rule systems that involve a process flow with discrete events can be simulated. So any process you can draw a flowchart of you should be able to simulate.
The processes you'll gain most benefit from simulating are those that involve change over time and randomness. For example a gas station. Nobody can guess at exactly which time the next car will arrive at the station, whether they'll decide to purchase gas only etc. Modeling complex dynamic systems like this effectively in any other way isn't possible.
Why Simulate?
There are many process improvements you can make using simulation: higher quality and efficiency from capital assets, better management of inventory, higher return on assets this list is endless. But some of these improvements could be made without simulation, so the real question is 'Why use simulation instead of another method?'
Simulation vs Real Life Experimentation
Cost:
Experimenting in real life is costly. Its not only the capital expenditure of hiring new staff or purchasing new equipment its the cost of the ramifications of these decisions. What if you fire 3 staff and then find you can't cope with the workload and you loose customers? The only cost with simulation is the software and the man hours to build the simulation.
Repeatability:
In real life its really difficult to repeat the exact circumstances again so you only get 1 chance to collect the results and you can't test different ideas under the exact same circumstances. So how do you know which idea is really the best. With simulation you can test the same system again and again with different inputs.
Time:
If you want to know whether hiring another 3 doctors will reduce patient waiting lists over the next 2 years you'll actually have to wait 2 years. With simulation you can run 2, 10 or even 100 years into the future in seconds. So you get the answer now instead of when its too late to do anything about it.
Simulation vs Other Mathematical Modeling Techniques
Interaction of Random Events:
Some other mathematical tools can mange to effectively model a steady state scenario but only simulation lets you build in random occurrences like a machine breaking down and see the effects of this further down the line. The more complex the scenario is the more these tools fall down and simulation is the only answer.
Non Standard Distributions:
Many mathematical techniques force the model builder to describe a situation as an approximation, it takes and average of 5 minutes to serve each customer. In real life this isn't the case. It takes 3 minutes to serve the customer if they have 4 items, it takes 7 minutes if they have 20 items. Approximating means results such as resource utilization time, customer waiting time are all inaccurate. Only simulation gives you the flexibility to describe events and timings as they actually are in real life.
Makes you think:
Simulation provides a vehicle for a discussion about all aspects of a process. The rule and data collection forces you to consider why elements work in a certain way, if they could work better. It also brings to the surface inconsistencies and inefficiencies especially between different sections of a process who work independently. Sometimes the simulation doesn't even have to be finished the framework it has provided to think through the issues reveals the solution.
Communication:
Because simulation is visual and animated it lets you clearly describe your proposal to others. Its more convincing that just displaying the end results as people can't see where these came from. Simulation is so effective at communicating ideas that many companies now use it as a sales tool to sell their products.
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