Digital Twins Hold Potential to Transform Sustainable Factory Design and Operations Planning amid Demand for Eco-Conscious Manufacturing

In the constantly evolving manufacturing sector, sustainability is fast becoming a leading objective for organizations globally. According to the International Energy Agency (IEA), the manufacturing sector accounted for 25% of global Carbon Dioxide (CO2) emissions in 2022. Pressure is increasing for manufacturing organizations to maintain compliance with new sustainability regulations, meet customer demand for sustainable products, and future-proof operations.

Digital twins have emerged as a critical technology, enabling manufacturers to model and simulate production processes in a virtual environment. The technology is being used to define optimal factory layout, material flow, and production processes to enhance factory performance. In more recent years, the application of digital twins to achieve sustainability goals has become increasingly apparent, enabling opportunities for energy consumption and waste management optimization, enhanced material/resource utilization, and predictive maintenance.

One of the most significant challenges in driving sustainable manufacturing and cost-savings is data silos between an organization’s plants, production teams, and departments. Silos may arise due to the presence of legacy systems, skills gaps, conflicting priorities, and poor data management practices. Managing operational data can be difficult with many manufacturing companies unable to convert these huge data lakes into actionable insights to support achieving business goals. Digital twins help break down these silos, aggregating operational data from various sources and contextualizing that to create a Three-Dimensional (3D) virtual representation of a real-world factory or process. By combining the real and digital worlds through digital twins, users can create “what-if” scenarios by simulating design, planning, and processes of manufacturing facilities to drive sustainable outcomes and optimize operations. Key sustainability use cases of digital twins for enabling sustainable factory design include:

• Efficient Factory Layout: Creating virtual replicas of physical factories enables visualization and optimization of layouts, allowing for better decision-making and testing to cut planning time and costs. Validate layout design and processes by optimizing throughput configurations, space allocation, clearances, ergonomics, and employee movement with the factory floor.
• Reduce Power Consumption: By monitoring and simulating energy consumption, digital twins provide greater insight into the energy consumption of products and production systems. Through interactions of testing, this can be improved to boost energy efficiency and performance. Manufacturing organizations can also use the technology to assess the potential of integrating renewable energy into factory operations based on access to renewable sources, compatibility with current infrastructure, and impact on costs.
• Reduce Waste: Digital twin tools can help reduce waste in two ways. First, it can be used to refine the manufacturing processes of specific products by reducing the quantity of materials required or developing lower waste-generating production methods. Second, digital twins can minimize waste going into landfills, streamlining recycling processes for improved reusability of wasted materials like scrap metal.
• Asset Performance Management: Monitor and optimize assets and processes by gathering data on metrics, including energy consumption, emissions, temperature, vibration, and asset health. Real-time monitoring of assets helps users to perform predictive maintenance to maximize machine uptime, extend asset longevity, and reduce Capital Expenditure (CAPEX). Current solutions that support Asset Performance Management (APM) are Overall Equipment Effectiveness (OEE) and analytics solutions. However, these only provide insight into well-established production lines and do not provide insight into greenfield or virtual factories.

By creating virtual replicas of physical factories with real-time data integration and predictive analytics capabilities, digital twins can empower manufacturers to make informed decisions, optimize operations, and embrace innovative solutions with precision and effectiveness. The following are notable examples of the application of digital twins for sustainable factory design:

• Siemens and Mercedes Energy Twin: In April 2024, Siemens and Mercedes-Benz announced a strategic partnership to co-create a Digital Energy Twin that supports the integration of energy efficiency and sustainability measures in factory designs and upgrades. The Digital Energy Twin enables better and faster decision-making in the early factory planning stages by modeling operational and energy consumption scenarios. By simulating the physical energy system, users can verify proposed planning scenarios and better understand optimization opportunities in building processes, including energy efficiency, emission reductions, and cost savings.
• Tata Steel: The company continues to invest in technologies to innovative and digitally transform legacy industries to develop more agile operations. Tata Steel has introduced digital twins to develop a more energy-efficient steelmaking method. Digitalizing thermal process management at its plants by using simulation-based digital twin modeling, the company was able to identify inefficient points in the process and solve them cost-effectively through iterations of solution testing. Digital twins also enabled remote factory management, identification of process failures, and enablement of smart mining.
• Foxconn and NVIDIA: In November 2024, Foxconn announced a collaboration with NVIDIA to build digital twins for enhancing manufacturing processes and supply chain management. Foxconn has incorporated NVIDIA’s Omniverse platform to create a 3D digital twin of its Taiwan Hsinchu factory. Virtually simulating processes prior to deployment helped Foxconn quickly implement high-quality and efficient production lines, while boosting adaptability and resilience. Foxconn plans to extend the use of the Omniverse platforms to its factories worldwide.

Digital twins have set new standards in flexibility, efficiency, sustainability, and digitalization. Today, the application of digital twins in manufacturing is most common in the automotive sector, being one of the most digitally mature manufacturing industries that is often scrutinized on its sustainability performance. Continuous adoption of digital twins across manufacturing sectors for both the design of greenfield factories and optimization of brownfield factories will be necessary in order to reduce the environmental impact of the industry as a whole.