The latest industrial revolution dubbed Industry 4.0 focuses on utilizing digital technologies to improve business processes and product design. The core of the revolution revolves around artificial intelligence and machine learning. These technologies work together to provide businesses with useful information that can help improve their operations.
Digital twins and simulations are a big part of the digitization process. These seemingly identical technologies offer different benefits, but they both focus on improving business practices by running simulations. This article will tell you more about the similarities between these two modern business practices.
Simulation Technology Explained
Simulations have been around for decades. Every simulation is a process of imitating real-world products, services, or processes in a digital environment. Businesses and manufacturing companies use 2D and 3D simulations to test products, systems, and processes.
Generally speaking, simulations are an excellent choice for testing and implementing new ideas. Most simulations run using CAD-based rendering software. These simulations test designs for stress analysis and material quality. These tests can tell designers how a product or design will behave in the real-world environment.
There are a few different types of simulations, such as stochastic simulations, deterministic simulations, etc. The difference between them is the variables they use to extract information. All simulations run in a digital environment, so companies can perfect their products, or processes without actually making changes in the real world.
Digital Twin Technology in More Detail
A digital twin is a complete representation of a product, system, or process in a digital environment. Unlike a simulation that depends on manually input variables, a digital twin uses real-world data generated by IoT sensors and computers to recreate a process or a product in a digital environment.
All changes and tweaks in the digital twin simulation are made automatically in real-time, as the data feeding the model changes. Most digital twin systems use the Internet of Things devices, HMIs, sensors, and other embedded devices to generate data and copy the behavior in the digital environment.
There is no doubt that the digital twin is far more versatile than a simple simulation. It allows you to create any type of test, environment, or test duration. For example, you can see how your production line will behave after working non-stop for months. You can also see which parts will break first and test your products and systems in crazy situations.
The Difference Between Simulations and Digital Twins
As mentioned above, even though these two technologies look similar at first, there are some major differences between them. Here are some areas where digital twins and simulations provide very different results.
Static Vs. Active Models
All simulations run using some CAD-based software. Product designers have to input parameters manually to recreate the product or design in a virtual environment. Simulations can test various design elements, materials, operating conditions, etc. Every new simulation requires the designer to input new parameters to change the outcome. In other words, all simulations are static and offer results based on given parameters.
Digital twin technology, on the other hand, is far more flexible than a simulation because it uses real-world data to recreate products, systems, or services in a digital environment. All digital twin simulations are active, as the model changes according to the data it's fed. That makes digital twin the ideal product simulation technology, as it can simulate the entire product lifecycle accurately. These simulations can provide valuable information that leads to better business decisions.
Could Be Vs. What Is
All simulations only show what could happen in the real world if the product goes through specific changes. Simulations can still tell designers more about product quality, but only if they know which parameters to use to create the simulation. If the designer doesn't know how to provide these parameters, the simulation won't show any useful information.
Digital twin technology uses IoT sensors and embedded devices to learn how a product, service, or system behaves in the real world. All simulations run using real-world data, allowing designers to see if the product works as it should. That's why this approach generates more accurate insights that can help improve the product design. The process is managed by AI software, so your designers don't have to input any parameters or creative ideas.
The result is a far more flexible and agile platform that uses real-time data to test products and improve their quality. Digital twin technology allows you to create products according to your customer's needs. All the guesswork is taken out of the equation, leaving you with pure, hard facts you can actually apply to your operation.
Product-Focused VS. Business-Focused
CAD-based simulations can only simulate how a product will behave and look. It allows designers to test products in various scenarios to improve their design. A simulation can't tell you anything about the effects of the product on your business operation.
Digital twins use data from all stages of a product's lifecycle. That allows your designers to test various solutions and see how they will affect your business workflow. Moreover, digital twins can also tell you which processes need improvements and what steps to take to improve business decisions. In other words, digital twins offer way more useful information that can help you improve your product quality and operation.
Pros and Cons
It's clear that the digital twin is far more versatile and offers a deeper simulation than a CAD-based simulation. Its ability to gather real-time data and simulate the entire product lifecycle leads to better product quality as your designers can address real issues and make improvements.
Furthermore, digital twins share data between multiple systems to create a clear picture of performances in different settings. The best thing is that your designers only work with results, instead of preparing the simulation.
CAD-based simulations are less capable of finding solutions, but they are much more affordable than digital twins. You need to install IoT sensors and integrate AI into your operation to run digital twin simulations. Of course, that takes a lot of money, which often makes this approach too expensive. Digital twins are not the best approach if you're running a small business, as the costs outweigh the benefits.
Transforming Your Business For The Future
The goal of every digital transformation is to improve existing business practices using advanced simulations. The transformation process requires a lot of planning, system overhauls, and placement of IoT sensors and smart devices.
Digital twin technology is extremely flexible and versatile. It can run simulations that offer some incredible data that helps designers improve product quality. But if you're a small business, the costs of implementing digital twins into your operation might be too high to be justified. However, if you're still keen on implementing this technology, it will help you bring your business to a whole new level.