Automation and machine learning are becoming more prevalent than ever in the manufacturing industry, as companies recognize the benefit of strategic technology trends. Whether it’s the manufacturing process or breaking down analytics to determine business strategy, data management is at the core of the innovations and strides being made in this line of industry. This includes the implementation of digital twin technology.
What is a digital twin?
A digital twin is when every process or physical product gets a dynamic digital form or representation. This allows a physical product to then be evaluated based on an analysis of its digital replication. These digital twin concepts bring the physical and digital world together, making use of real-world data to create simulations via computer programs that predict how a process will fare. These programs are then easily integrated into the Internet of Things, also known as IoT, as well as artificial intelligence to enhance output.
The concept of digital twins has brought unlimited possibles. The traditional approach of building something is now obsolete, thanks to virtual-based design systems. There’s no longer a need to manufacture a prototype, as well as its numerous follow-ups after changes.
Smart manufacturing now allows for changes to be made before the deployment phase without spending significant amounts of money thanks to a digital footprint. These digital twins are essentially actionable information, providing businesses with the opportunity to better analyze and predict possible challenges, and embrace future scenarios.
Application of Digital Twins
Digital twin technology helps to create an accurate prediction of the current and future state of physical assets simply through the analysis of digital counterparts. Organizations are able to gain more accurate insights into those physical objects with the help of historical data and analytics, leading to quicker decisions and enhanced customer service.
In the manufacturing process, digital twins have changed the foundation of this line of industry, creating efficient design models and improving upgrades. This has also led to reduced time on the supply chain from invention to arrival.
For example, the auto industry is now relying on virtual models of a connected vehicle to capture behavioral and operational data. Data scientists analyze the overall function and performance levels of a car and all its connected features, leading technicians to develop a more personalized experience for car owners.
In the meantime, industrial firms adopt digital twins to monitor, track and control the physical aspects of their inner workings digitally. This provides businesses with the ability to capture environmental data, with analytics putting on a spotlight on configuration and financial models. This helps in future predictions in operations and points out any deviations that could create issues in the long run.
Benefits of Digital Twins
The concept of a digital twin is quickly changing how manufacturing can leap through different hurdles without ever having to actually create a physical product. Smart manufacturing is cost-friendly, sparring the hours of labor that go into creating prototypes and subsequent models, and avoiding regulatory hurdles that come with that process. This also allows businesses to reduce any existing or potential defects during production, giving engineers the chance to test and simulate the product or service in the digital world.
Manufacturers are able to eliminate all possible risks in the output and ensure that the physical product functions as intended. Digital twins allow companies to also cut down on the amount of time it takes to go from the drawing board to the marketplace, helping them beat out their competitors.
The entire lifecycle of the product can be simulated in a digital environment, with digital twins allowing businesses to anticipate problems and provide solutions through predictive maintenance. These real-time analytics allow businesses to address any difficulties immediately.