Presales and Business Consultant with 3+ years of industry experience, currently working as a Consultant for the Product & Platform Engineering division of Brillio. Expertise spans from handling digital transformation projects in multiple verticals to client-focused delivery across the Globe. Passionate about digital & strategy consulting, new age technology, building POVs, and exploring emerging tech use cases.
In recent years, we have witnessed the emergence of new technologies that have played a vital role in the advancement of smart manufacturing. These include advanced analytics, robotics, artificial intelligence, and machine learning to name a few. One such technology that has been instrumental in having the most immediate and significant impact on smart manufacturing is the Digital Twin technology. It is estimated that the Digital Twin global market will grow at a 31.7% CAGR to reach $54.6 billion by 2027.
A Digital Twin – also known as a digital replica – is an exact virtual copy of a real-world object or even a complete business ecosystem. In manufacturing, the digital twin is a virtual representation of the as-built and as-maintained physical object that is supplemented by real-time data and inputs from a real-world component. It is created by using the data derived from sensors that are embedded in real-world components or objects. The sensor continuously feeds data into a cloud which then allows for both operational and structural views of what is happening to the component in real-time, thus allowing the staff to effectively monitor the system dynamics. Adjustments can be made to the Digital Twin, before being implemented in real-time, to see how the system would react.
In the manufacturing sector, understanding what is happening now on the production line, and predicting what will happen in the future, is vital for maximizing productivity, and improving profitability. This can be achieved with the help of digital twin technologies.
In manufacturing, the Digital Twins technology can be used at various levels. At a component level, the focus can be on a single component that is critical to the manufacturing process. At a system level, the entire production line can be replicated to drive monitoring efficiency. At a process level, the entire manufacturing process life cycle, ranging from – design to production and distribution to product consumption can be replicated.
Product Development: With the help of Digital Twins, manufacturers can test the feasibility of any product configuration. The results of the test data can be used to identify and rectify any product defects before launching them. This simulation of scenarios is much faster and easier than physical testing.
Asset Lifecycle Management: Digital Twin visualization pairs well with Augmented Reality programs to help manage assets. AR glasses can help maintenance technicians to view up-to-date information about the models of machines in front of them and ensure access to the specifications as needed.
Design Customization: With the help of Digital Twins, manufacturers can test and design different permutations of a product while lowering the risks of costly miscalculations. This enables manufacturers to offer personalized products tailored to the end-user needs at a faster pace.
Preventive Maintenance: With the help of IoT-connected devices and Digital Twins, manufacturers can collect vital information about their machinery, such as motion, vibration, etc., which can then be used to get a comprehensive view of the system. This provides an opportunity to identify any outliers and unexpected behaviors early on and halt the production before it becomes a hazard.
Remote Troubleshooting: Just like home working is becoming a norm across industries, thanks to COVID-19, digital twins are setting a context for manufacturers to work remotely. Manufacturers can now set up “remote teams” to deal with product and machinery inspections and troubleshoot problems without the need to physically check equipment. When combined with edge computing, this can help manufacturers manage machinery in offshore locations that have limited network infrastructure.
A surge in the adoption of cloud-based technologies, the rise of 5G, and the growing propensity towards IoT solutions are accelerating the adoption of digital twins across industries. Thanks to cloud technology and edge, the computing power to run simulations and forecasts using high data volumes is now more widely available.
The falling price of IoT-based sensors and the growing sophistication of 5G networks are now making it easier to create and monitor real-time digital reflections of large and complex systems at a granular level. It can be observed that 13% of organizations that are implementing IoT projects already use Digital Twins, while 62% are either in the process of establishing its use or plan to do so.
It can be established that the Digital Twin technology will play a vital role in Industrial IoT deployments. All aspects of manufacturing and production will benefit from Digital Twins – especially monitoring and maintenance. It will help answer questions in real-time that were previously unanswerable and thus provide meaningful insights that may be pivotal to manufacturers. Thanks to new technologies – companies will now be able to create a digital twin with lower capital investments and at a faster pace. Manufacturers need efficient tools and technologies to compete and be a part of the smart-manufacturing world, and Digital Twins are a part of that future.