Large enterprises have relied on digital solutions for decades now. Whether it’s business intelligence software, inventory management solutions, or customer relationship management software, a business that refuses to adapt digitally is one that’s set up to fail. Of course, these days, it’s not enough to rely on legacy systems or the traditional ways of doing things. Even in the digital realm, things have changed, and a modern digital transformation means that you’ll need to rely on more advanced systems than ever before.
Automation has been used to improve business processes since the First Industrial Revolution, and the Third Revolution introduced computers and software solutions. There’s something that separates modern digital technology from the options of the past, however. Thanks to advanced data analytics, integrations, machine learning, and the Internet of Things (IoT), digital solutions are now capable of performing their functions with little to no human intervention. This is what makes The Fourth Industrial Revolution, often called Industry 4.0, unique. One of the most impressive capabilities this modern age has brought enterprises is the ability to create digital twins. Here’s everything you need to know about digital twins in Industry 4.0.
Digital Twins Defined
A digital twin is, essentially, a dynamic digital representation of a product, service, or an entire process. In other words, it’s a simulation of a real object or event. This is made possible thanks to data virtualization, as well as integrations with software analytics, IoT technology, and artificial intelligence. Industry 4.0 is built around automated processes and the rapid collection, transfer, and analysis of big data. Digital twin technology is seen by many as the future of manufacturing. Here are the basic types of digital twins and some of their use cases.
Product Twins
Gone are the days when you’d have to fully develop a new product based on the first product design and then spend time and money tweaking it until it actually lived up to expectations. Now, you can fully design, model, and test a new product in real-time using a simulation. You can use predictive analytics to anticipate problems in the physical design phase and work with the virtual models to overcome them.
This eliminates downtime that would be present if the product had already gone through the manufacturing process, not to mention the money it saves on wasted manufacturing costs. Digital twins allow for better quality control, and once the product is ready, it can be sped to release.
Process Twins
Digital twin technology has also been instrumental in business process management. Many industries in the manufacturing sector, such as the automotive industry, use digital twins to simulate new business processes or to evaluate proposed tweaks to existing ones. With the digital twin approach, it’s easy to analyze an existing process for bottlenecks, design a new process to eliminate them, and even model and test the new process in a simulated environment that mimics the real manufacturing process.
Now, a new physical process on the manufacturing floor can be fully tested before implementation. It’s even possible to simulate a process long enough to make predictions for when parts are likely to break down. Predictive maintenance like this makes it easy to assign schedules for routine checks and repairs.
System Twins
It’s also possible to create a digital twin of an entire organization or factory. This type of digital twin can collect vast amounts of data from all operational processes at once and use it to optimize all processes simultaneously. Some enterprises are already trying to use this approach to replace the need for human workers to diagnose equipment failures and other manufacturing concerns.
Digital twins are cost-effective solutions for practically any business need, and taking advantage of them is sure to boost your productivity and result in better products and services.
