Many phenomena are difficult to visualize. They may be remote from the observer, or simply too complex to understand. Some processes may be cost prohibitive to simply build for the purpose of observation or experimentation. This is why people develop process simulations. Process simulation software can help visualize changes, small and large. For example, an industrial engineer might need to know how increasing the flow rate in a heat exchanger will affect production. A process simulation can demonstrate this change on cloud-based software through a web interface, giving the engineer confidence that the adjustments will be beneficial.
There are many different ways to create a process simulation. First, the properties of the process being simulated should be known. Second, the behavior of the various parts of the process need to be articulated. Finally, the starting conditions must be provided as input, and each step of the process is methodically worked through.
The underlying mathematics can be done by hand using mathematical operations, as when a physics student calculates the trajectory of a cannonball. The MONIAC, for instance, was a system that used the flow of water to simulate the movement of money in the United Kingdom. Even a simple block diagram combined with a pocket calculator to perform the mathematics can serve as a process simulation.
Process simulations can also be built on computers, and with the wide range of powerful, specialized process simulation software available, this is often the most effective route. A simulation can be built using software wizards that ask the user for information about the process being simulated. This information should include anything germane to the simulation, such as the materials the equipment is made of. The software wizards are designed to help the user identify relevant information and ensure that extraneous data is not included.
In industrial settings, process simulations will always be run in specialized software. There are simply too many variables to contend with to make any practical use of other methods such as hand calculations. The software may be run on a local machine, or remotely in the cloud.
Inputs and starting conditions are provided to the software running the simulation. Modern process simulator software can fed this information by actual sensor data, either prerecorded or even streamed live. One major advantage that comes with industrial digitalization and plant digitalization is that by wiring a facility with networked sensors, a valuable supply of data is created. This trove of historical data can be accessed again and again, to be used in future simulations or to help create a digital twin or model.
The software will then perform the mathematical operations that correspond to different parts of the process. As the computer works its way through the various equations that represent the components of the process simulation, new conditions will arise. For example, the ambient temperature of the facility may start at one value, but once the process simulator software begins calculating the effects of turning on a boiler, that ambient temperature value will be increased. The new values are processed again, and the resulting values processed again, over and over. This builds up a frame by frame picture of the simulated process.
The results of the process simulation should be compared to the real world results of similar conditions. This allows for adjustments to increase the fidelity of the simulation for future simulator runs.
There are numerous reasons why an enterprise would want to spend time and effort on a process simulation. In terms of planning, being able to create a digital model of the proposed asset before you break ground means that any surprises will happen in the safety of a software environment.
For existing processes, a process simulation can help a company optimize production by providing an inexpensive way to explore different production configurations and parameters. Instead of spending money trying out a new, expensive piece of equipment—even an upgrade that may promise increased efficiency—a process simulation can visualize and spell out what kind of an effect the new piece of equipment will have on the operations of the firm as a whole.
How is a process simulation different from a digital twin?
Digital twin technology seeks to replicate every aspect, from the smallest physical details of a process all the way to the resulting phenomena. Thus, it can be considered a type of process simulation. A digital twin will also be connected to live sensor data using specialized digital twin software so that it remains up to date, whereas in general process simulations do not have this as a requirement.
Is process simulation software expensive?
Although the upfront costs of purchasing and installing process simulation technology may be significant, it will likely save the company money in the long run. The advantages of being able to explore and experiment with different options for production, equipment, and supply chains are numerous, and are likely to pay for themselves in the long run.
The Digital Twin and the Smart Enterprise