Digital Twins in Manufacturing – Benefits, Examples, Use Case, and More
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Imagine being able to create an exact digital replica of a manufacturing operation, machine, or product and then use it to optimize and improve the physical counterpart in real time. Sounds like something out of a science fiction movie, right? Well, this technology exists in real, and it’s called a digital twin.
Digital twins are revolutionizing the manufacturing industry by providing immense visibility into the production process. By creating virtual replicas of physical assets, manufacturers can test different scenarios, predict failures, and make adjustments in real time. The result? Increased efficiency, reduced costs, and improved product quality.
In this blog post, we’ll explain the meaning of digital twins in manufacturing, exploring their benefits and the exciting future they offer for the industry. So, strap in and get ready to learn how this cutting-edge technology is transforming the manufacturing industry.
What are Digital Twins in Manufacturing?
Digital twins in manufacturing refer to virtual replicas of physical machines, products, or processes. It replicates the entire production process, which includes machinery, equipment, and raw materials, and provides the dynamics of how an object functions in the real world.
A digital twin can also be the design model for a future asset, which can be updated and maintained to reflect the as-built state of the asset during the construction and operational phases of its lifecycle.
“Digital twins are a dynamic software model of a physical thing or system (Gartner)”
Manufacturers use digital twins to simulate different scenarios and test potential improvements, which can help reduce costs, improve efficiency, and increase productivity in manufacturing. By analyzing data from the digital twin, manufacturers can make informed decisions about changes to the physical object or process.
For example, a digital twin of a machine tool could be used to simulate different machining strategies, allowing manufacturers to identify the most efficient approach before making changes to the physical machine. Similarly, a digital twin of a production line could be used to identify bottlenecks and optimize the flow of materials and products.
Overall, digital twins are a powerful tool for manufacturers looking to improve their operations, reduce costs, and increase productivity in a rapidly changing digital landscape. Here’s an image that illustrates the mammoth expected growth of Digital Twin Market:
Why do we need Digital Twins in Manufacturing?: The Benefits
Digital twin technologies offer numerous advantages, and a few of them are listed below:
Enhanced Overall Equipment Effectiveness (OEE) by reducing downtime;
Lower maintenance costs;
Better workforce training;
Improved supply chain management;
Save valuable time;
Digital Twins in Manufacturing Examples
Digital Twins are increasingly being used in manufacturing to optimize production processes, improve product quality, and reduce downtime Here are some examples of digital twins in manufacturing:
Bridgestone’s Digital Twin Technology Drives an Innovative Business Model and Improves Performance
Bridgestone, the global leader in tire and rubber manufacturing, is transforming to become a leader in mobility solutions. The company regularly uses digital twin technology to understand the impact of various factors, such as driving style, speed, to improve tire life and road conditions on performance and durability. With these insights, the company can advise its operators on preventing breakdowns and increasing the wheels’ lifespan.
Bridgestone has reaped several benefits from using digital twin technology in its tire manufacturing processes. These benefits include:
Improved Tire Design: By using digital twins to simulate tire designs, Bridgestone can optimize the design for better performance and longevity, resulting in higher-quality products.
Reduced Development Time: Bridgestone can design and test new tires more quickly, reducing the time it takes to bring new products to market. According to Bridgestone, this approach cuts development time by 50%.
Enhanced Production Efficiency: Digital twins help Bridgestone optimize its tire manufacturing processes, reducing downtime and improving production efficiency.
Better Predictive Maintenance: By monitoring equipment data in real-time, the digital twin can predict equipment failures before they occur, reducing downtime and maintenance costs.
Increased Sustainability: Digital twins can identify areas where waste can be reduced, leading to a more sustainable manufacturing process.
Power Generation Used Digital Twins to Predict the Performance of Gas Turbines
Siemens acquired Rolls-Royce’s energy gas turbine and compressor business and based on the acquired asset, introduced the SGT-A65 aero-derivative gas turbine. This posed new challenges for production and maintenance, including unforeseen issues. Siemens’ Excel-based forecasting tools were insufficient due to the high volume of data and lack of clear results. The business required a more powerful method to predict performance, forecast KPIs, and evaluate investment options. Siemens wanted to visualize the entire production and maintenance process, including critical supply-chain logistics. They needed the ability to run multiple scenarios to communicate investment options and improve decision-making.
Uses Cases of Digital Twins in Manufacturing
Digital twins have numerous use cases in manufacturing, such as:
Improving System Designs
Manufacturing teams use digital twins to plan and test new production lines. This means before creating a physical system; potential issues and optimization areas can be identified, resulting in a significant saving of both time and money. Similarly, the planning of warehouse designs can be done through digital twins in a more effective way. The utilization of digital twin visualization techniques has made issues much more conspicuous, thereby enhancing team communication and efficiency.
Testing New Products
Gone are the days when frontline workers had to undergo a tedious trial-and-error process to test new or updated products within an existing system. The advent of digital twins has made it possible for manufacturers to test out updated configurations with a significantly reduced risk of incurring costly miscalculations. The simulation of multiple scenarios has become faster, easier, and more efficient than physical testing.
Equipment Monitoring and Preventive Maintenance
Digital twins of machines offer a precise virtual equivalent in real-time, providing maintenance staff with a detailed breakdown of equipment performance and health. With the help of AI, digital twins can identify potential failures before they occur, enabling manufacturers to take proactive measures.
Field technicians can use augmented reality smart glasses to view accurate models overlaid on the physical machines on the factory floor. This provides precise specifications and a visual representation that the technician can rely on to carry out their work.
Training Employees
Digital twins in manufacturing can be used to train employees and simulate real-world scenarios, allowing them to gain experience and knowledge without the risk of physical harm or damage. For example, by creating a digital twin of a production line, employees can learn how to operate equipment, troubleshoot problems, and improve efficiency. This can improve safety, reduce training costs, and enhance workers’ productivity.
Quality Management
To ensure top-notch quality and reduce rework, it’s crucial to continuously monitor and respond to data during production. The digital twin can model every aspect of the production process to pinpoint any inconsistencies or identify areas where better materials or processes could be utilized.
Digital Twins vs Augmented Reality: What’s the Difference?
Both Digital Twins and Augmented Reality are two crucial concepts that are contributing significantly to the ongoing industrial revolution. In one way, these concepts complement each other. On the another way, DT provides the ability to represent physical assets digitally, while AR allows for the augmentation of physical space with digital information. Here’s a table that illustrates the difference between digital twins and augmented reality:
What if they both are combined?
Combining Augmented Reality with Digital Twins
Implementing AR technologies in the digital twin for design and management process not only improve productivity within many industries — most notably manufacturing, aerospace, and industrial — but it can also enhance experimentation and predictive analysis of existing products, with the potential of reducing unplanned downtime and incurred costs.
Combining AR technologies with Digital twins allows frontline workers to interact with virtual replicas of physical objects in a more immersive way. This technology has the potential to transform the way industries design, build, and operate complex systems by providing a more intuitive and visual way to interact with data.
Using AR Smart Glasses, workers in an industrial setup can visualize machinery and its key data outputs and workings. This can improve efficiency and reduce turn-around time. The same can be applied to servicing and, repair & maintenance.
Moreover, with AR-powered digital twins 3D models of machines, the industry can train workers without actual machines. This can help to reduce the risk of accidents and errors.
Overall, the use of AR in digital twins can help improve the understanding, operation, and performance of complex systems, leading to better outcomes and increased efficiency.
How Do You Build Digital Twins in Manufacturing?
Building digital twins in manufacturing involves several key steps:
Step 1. Identify the Assets
Firstoff, it is essential to identify the assets or processes that need to be replicated digitally. For manufacturing industry, these assets could be as simple as a machine, warehouse, components or machine parts.
Step 2. Scan Physical Counterparts
For creating a virtual replica, digital twins require a real-time flow of data from physical objects, systems, or processes that are scanned in the real world. The scanning can be done from a QR code or machine code.
Step 3. Generate Real-time Flow of Data from IoT Devices, Sensors
In order to require a thorough understanding of the physical system and the data that needs to be collected to create an accurate representation. This data can come from various sources, including sensors, IoT devices, and other data collection methods.
Step 4. Create a Computational Analytical Model
Next, the data needs to be processed and analyzed to create a digital model that accurately represents the physical system. This involves using sophisticated algorithms and software to create a 3D model of the physical system and its behavior. In the industrial sector, 3D models of workstations, components, and machines are commonly utilized for various purposes, such as designing new products, testing workstation layouts, and evaluating ergonomics. These models can be typically created through the use of CAD or 3D creation tools.
Step 5: Display 3D Model on AR Glasses
The resulting models are displayed through 3D visualizations and AR techniques to simulate real-world conditions and visualize outcomes on any device, including smartphones, computers, and AR/VR devices. AR overlays the digital twin onto a real-world view, allowing frontline workers to see how the virtual model would interact with the physical world. This can be especially useful for testing and prototyping, as well as for training purposes.
Usually, digital twin deployment begins on a small scale by focusing on the performance of a single component within a product, but it eventually grows and changes over time. Yet this occurs in two different ways. Firstly, a few digital twins are combined to provide a comprehensive view of the asset, process, or system. Secondly, more advanced capabilities are added to the existing digital twin to predict the future performance of its physical counterpart.
Unlock The Power of Digital Twins and Augmented Reality With Plutomen Assist
As manufacturing becomes increasingly complex and competitive, the use of AR and digital twin technology can give manufacturers a competitive advantage in the marketplace. AR and Digital Twin technologies play a crucial role in smart manufacturing. By visualizing Digital Twin data through AR technology, it is possible to create a more intuitive and comprehensive integration of the physical and virtual aspects of Digital Twin.
Digital twins in manufacturing can help to enhance their performance and ensure the safety of their operations by enabling operator training and advanced testing of equipment and processes through dynamic simulation. And for all this, Plutomen Assist is a one-stop solution for the manufacturing industry.
From maintenance and repair to training and simulation, we can help you integrate these technologies and ultimately improve decision-making and reduce costs.
Plutomen Assist is the most dynamic Augmented Reality Training software, which enables industry experts to develop their own training model. At Plutomen, each 3D model is highly detailed, which helps in better knowledge transfer and comprehension. Moreover, by simply scanning the barcode or QR code on a machine, businesses can quickly and easily access training materials and guides linked to specific machines or parts. This innovative solution enables frontline workers to easily access critical training materials even in complex and emergency situations.
Plutomen’s approach has always been consistent – providing the most effective solution that is agile, flexible, and scalable. It doesn’t matter what industry you’re in or what product or system you want to model; Plutomen can handle it all.
So, are you ready to take your manufacturing operations to the next level with the power of Augmented Reality and digital twin technology? Book a demo, today!
A digital twin is a virtual representation of a physical product, process, or system. In the context of smart manufacturing, a digital twin is a digital replica of a physical manufacturing process or system. The use of digital twins in smart manufacturing can help manufacturers reduce costs, improve product quality, and increase efficiency.
The best example of using digital twin technology in manufacturing is to provide training in assembly processes. Say, for example, a manufacturing facility that produces complex machinery with many components. A digital twin of the machinery can be created, which includes all the parts and how they fit together. Using AR, a worker can see the digital twin overlaid onto the physical machinery, allowing them to visualize the assembly process step-by-step in a highly interactive and engaging way. This improves the speed and accuracy of assembly while reducing errors and increasing worker safety.
The role of digital twins in today's manufacturing and predictive maintenance is significant. Digital twins enable manufacturers to create virtual representations of physical manufacturing systems, processes, and products, which can be used to optimize production processes, improve asset performance, reduce maintenance costs, and reduce machine downtime.
Digital twins are being used in various industries such as manufacturing, healthcare, aerospace, defense, construction, automotive, and many more. However, the manufacturing industry has been one of the early adopters of digital twins, which are being used to optimize production processes, improve product quality, and reduce costs.
Chirag brings with him 15+ Years of experience in Digital Transformation, and IT Leadership. At Plutomen, he holds deep experience in business with a track record of customer-centric approaches helping them build business transformation.
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