Digital twins in manufacturing: benefits, technologies and use cases

Digital twins are virtual replicas of products, production assets, processes, or entire factories that can accelerate development, improve quality, and reduce costs. They are improving manufacturing by providing real-time virtual representations of factories, enabling better decision-making, increased efficiency, and improved problem-solving. According to McKinsey, approximately $30T in corporate revenues will rely on products not yet available in the market in the next five years. Digital twins in manufacturing are transforming product development by offering a virtual environment for testing and refining products before they are physically created. Many businesses are turning to manufacturing software development services to take full advantage of digital twins and gain a competitive advantage.

Executives across various industries are increasingly aware of the benefits of digital twins, with 47.2% understanding their potential and 63% planning to adopt them by 2029. The digital twin market is rapidly expanding, projected to reach $110.1B by 2028, driven by a 30% CAGR. Adoption rates are high, with 29% of global manufacturing companies already implementing digital twin strategies.

Digital twins are set to transform company operations by replacing the current coordination of isolated automation systems with a dynamic, continuously evolving system driven by data. They will provide leaders with comprehensive insights across the organization, enabling better planning and implementation of those plans. Additionally, digital twins will learn from outcomes and continually optimize to achieve specific corporate objectives. Let's look at the benefits of the digital twin, technologies, and use cases.

Benefits of digital twins in manufacturing

Manufacturing companies are using digital twins to work faster and smarter. In addition, digital twins in manufacturing can be utilized to make more efficient factory floor plans, lower downtime, and better understand the physical assets under your control. Here are the top examples of digital twin benefits in manufacturing:

Enhancing productivity

By monitoring processes and systems continuously, even after the start of production, digital twin systems help ensure consistent operational efficiency. They can detect hidden obstacles in manufacturing by accurately simulating real-time blockages on the production line. By integrating with existing manufacturing execution systems (MES), Internet of Things (IoT) devices, and inventory databases, digital twins in manufacturing optimize the sequencing of various product lines to minimize downtime. For instance, an industrial company might adjust its production schedule using a digital twin, which can reduce overtime and result in monthly savings of 5-7%. A Deloitte study shows that predictive maintenance, enabled by digital twins, can increase productivity by 25%, cut breakdowns by 70%, and lower maintenance costs by 25%.

Cost reduction

Digital twins let companies try out different materials or ways of making things before they actually do them. This can help them find cheaper ways to make products. By using digital twins, manufacturers can find more affordable ways to make products. They can make fewer prototypes and waste less material. For example, General Electric saved $11M by using digital twins. They were able to reduce unplanned maintenance by 40% and increase reliability to 99.49%. Similarly, BMW Group anticipates a 30% cost reduction due to optimized facility planning and highly efficient processes.

Accelerating time to market

Digital twins enable manufacturers to make timely product design, development, testing, and manufacturing decisions through AI-driven insights, real-time data analysis, and advanced modeling techniques. Digital twins in manufacturing can help companies make products faster and cheaper because they don't need to make as many physical models.

Improving quality

By modeling intricate operational processes, manufacturers can easily detect and rectify inefficiencies. Many companies have reported that products developed as digital twins encounter 25% fewer quality issues upon entering production because extensive testing, validation, and customer acceptance activities can be conducted in a virtual environment. For example, Rolls-Royce's platform has allowed for a significant extension in the maintenance intervals for certain engines, increasing them by up to 50% and enabling a notable reduction in spare parts inventory.

Fostering eco-friendly manufacturing practices

Digital twins in manufacturing enhance control over production processes and resource consumption, promoting environmentally sustainable manufacturing practices. They help reduce waste, ensure compliance with environmental regulations, and identify potential energy-saving opportunities. By optimizing processes and improving efficiency, digital twins assist industries in transitioning to more sustainable and socially responsible manufacturing methods. For instance, Siemens is utilizing a digital twin to model energy demand and infrastructure in a project with a German city of around 200,000 residents, finding that a 70% reduction in emissions by 2035 is achievable.

Digital twins in manufacturing use cases

Digital twinning has numerous applications in manufacturing, such as monitoring, simulation, and remote control. Here are a few examples of these applications.

Manufactory design planning

• Factory planning

Using virtual replicas of manufacturing plants allows planners to optimize layouts, robotics, logistics, and interactions between different systems and devices before construction begins. Before building the factory, planners simulate production workflows and test processes to minimize errors and expensive physical changes. This approach cuts downtime and boosts efficiency, ensuring smooth factory operations.

Example: BMW's virtual Debrecen EV plant uses Omniverse to animate processes in the factory, performing tasks such as visualizing and identifying optimal placement for robots in constrained spaces.

• Simulating workflows

Digital factory twins allow you to simulate production workflows and help you track the location of parts and equipment, reducing the number of factory visits. They also enable simulation of situations, allowing engineers to make changes without risking safety and quality. This technology provides a detailed 3D survey, allowing informed decisions on physical implementation.

Example: Digital replicas of Toyota factories use a NavVis 360 mapping device to create a digital replica of their manufacturing operations.

Product design planning

• Product design

Engineers and designers may develop things more quickly and in a risk-free setting with the help of digital twins. Digital twins in manufacturing make it easier to test things in many simulated settings. Designers can use realistic digital twins to quickly and inexpensively prototype new ideas. The twins can also simulate various what-if scenarios, involving product testing, system interactions, and customer experience.

Example: EcoStruxure™ Machine Expert Twin enables prototyping and virtual commissioning, allowing designers to simulate and test various configurations, reducing the need for physical prototypes and speeding up the design process.

• Production personalization

Digital twins assist manufacturers in swiftly modifying manufacturing methods and configurations to match unique client requirements without sacrificing efficiency or cost. This enables the mass customization of products. This feature helps manufacturers satisfy customer needs by supporting the trend toward personalized products and providing them with a competitive advantage.

Example: Rather than just gathering data points, a digital twin of a customer offers context and forecasts future behaviors. It integrates both online and offline interactions and is dynamic, continuously updating with new information and acknowledging that one individual can represent multiple personas, reports Gartner.

Supply chain management

• Simulation and prediction

Digital twins in manufacturing can simulate several possible situations, forecast future behavior, and assess the effects of suggested changes using advanced analytics and modeling tools. Since virtual replicas enable predictive decision-making, they assist businesses in improving efficiency, increasing productivity, and lowering risks.

Example: EcoStruxure™ Machine Expert Twin empowers engineers to leverage real-time physics simulation and validation to identify potential issues early in the design phase, optimizing machine performance before production.

• Supply chain optimization

Digital twins make it possible to optimize inventory quantity, identify any problems, and monitor the supply chain in real time. Businesses may reduce risk and improve their ability to meet market demands by increasing the visibility and resilience of their supply chains.

Example: Azure Digital Twin can create a virtual model of a supply chain. This model shows how different parts of the supply chain work together. By studying this model, businesses can make changes to improve how their supply chain works.

• Demand forecasting

Digital twins analyze market trends, customer behavior, historical sales data, and other data from various supply chain components, including manufacturing and production planning data, to allow more dynamic and accurate demand forecasting. This lowers inventory costs, reduces overproduction, and improves stock management.

Example: Walmart implemented a digital twin solution to enhance its supply chain by integrating real-time data from various sources, such as sales, inventory, and weather forecasts. This technology allows Walmart to accurately predict demand, optimize inventory, improve logistics, and conduct scenario planning, resulting in better inventory management, reduced waste, and increased customer satisfaction.

Equipment monitoring

• Predictive maintenance

Digital twins in manufacturing use machine learning algorithms and predictive analytics to determine when equipment may break down before an incident happens. This enables businesses to plan maintenance using real-time performance data, reducing downtime and increasing essential equipment's lifetime.

Example: Phoenix Contact Electronics engineers use Ansys software to integrate real-time sensor data with simulation results to predict future failures.

• Real-time data analysis

With real-time data analysis, digital twins in manufacturing continuously monitor the functioning equipment. Because of this deep insight, defects may be found quickly. This helps cut downtime and increase output. Operators may make well-informed decisions quickly thanks to such information.

Example: Sight Machine is a leading AI-enabled analytics platform that allows manufacturers to analyze plant floor data in real time. Creating these digital twins allows them to find new insights, transform operations, and unlock new value.

• Optimize productivity

Digital twins can help managers identify the ideal manufacturing circumstances, known as the "golden batch." Managers may simulate and analyze different parameters in real time using virtual copies of production processes. This allows them to identify the exact combination of characteristics that produce the most efficient and high-quality production cycles. Managers can change production parameters using this feature to achieve optimal output, including machine speed, operator assignments, worker shifts, processing times, etc. After identifying the golden batch in the digital environment, manufacturers can increase Overall Equipment Effectiveness (OEE) by implementing these ideal conditions in a physical production line.

Example: Moelven, a wood processing company, uses Cognite's platform to optimize its production processes. By creating digital twins of its machinery and production lines, Moelven can monitor real-time performance, identify inefficiencies, and adjust operations to enhance productivity and reduce waste.

• Remote monitor and control

Digital twins in manufacturing break down physical limitations with their ability to monitor and manage remotely. Data engineers may monitor their remote devices without being physically there and make necessary corrections. This improves predictive maintenance procedures and minimizes the need for direct interventions.

Example: The digital twin environment ContiVerse duplicates every move made on the real manufacturing line, enabling engineers to easily assess performance and quickly find and fix problems.

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Training

• Enhanced learning experiences and onboarding process

Digital twin in manufacturing offers realistic interactive learning experiences that transform training programs. The virtual representation of the production environment is interactive for learners. They receive practical experience without running the dangers of the actual system. This approach reduces the learning curve by promoting an improved understanding of the tools and procedures.

Wrap-up

Digital twins in manufacturing are a powerful tool for businesses looking to improve their operations, reduce costs, and stay competitive. By creating virtual replicas of products, processes, and systems, manufacturers can gain valuable insights, optimize workflows, and make data-driven decisions.

N-iX is your trusted partner for digital twin implementation. Our team of experts has deep knowledge of IoT, AI, cloud solutions, and other essential technologies. We can help you create a digital twin strategy, collect and organize your data, build accurate models, and use AI to improve your operations. We'll also make sure your digital twin is safe and secure. Let N-iX guide you toward operational excellence and unlock the full potential of digital twins for your business, contact us!