Improving the sustainability of manufacturing involves optimizing entire product lifecycles - from material sourcing and transportation to design, production, distribution and end-of-life disposal.
According to the International Energy Agency, reducing the carbon footprint of industrial production by just 1% could save 90 million tons of CO emissions annually. That's equivalent to taking more than 20 million gasoline-powered cars off the road each year.
Technologies such as digital twins and accelerated computing are enabling manufacturers to reduce emissions, enhance energy efficiency and meet the growing demand for environmentally conscious production.
Siemens and NVIDIA are at the forefront of developing technologies that help customers achieve their sustainability goals and improve production processes.
Key Challenges in Sustainable Manufacturing Balancing sustainability with business objectives like profitability remains a top concern for manufacturers. A study by Ernst & Young in 2022 found that digital twins can reduce construction costs by up to 35%, underscoring the close link between resource consumption and construction expenses.
Yet, one of the biggest challenges in driving sustainable manufacturing and reducing overhead is the presence of silos between departments, different plants within the same organization and across production teams. These silos arise from a variety of issues, including conflicting priorities and incentives, a lack of common energy-efficiency metrics and language, and the need for new skills and solutions to bridge these gaps.
Data management also presents a hurdle, with many manufacturers struggling to turn vast amounts of data into actionable insights - particularly those that can impact sustainability goals.
According to a case study by The Manufacturer, a quarter of respondents surveyed acknowledged that their data shortcomings negatively impact energy efficiency and environmental sustainability, with nearly a third reporting that data is siloed to local use cases.
Addressing these challenges requires innovative approaches that break down barriers and use data to drive sustainability. Acting as a central hub for information, digital twin technology is proving to be an essential tool in this effort.
The Role of Digital Twins in Sustainable Manufacturing Industrial-scale digital twins built on the NVIDIA Omniverse development platform and Universal Scene Description (OpenUSD) are transforming how manufacturers approach sustainability and scalability.
These technologies power digital twins that take engineering data from various sources and contextualize it as it would appear in the real world. This breaks down information silos and offers a holistic view that can be shared across teams - from engineering to sales and marketing.
This enhanced visibility enables engineers and designers to simulate and optimize product designs, facility layouts, energy use and manufacturing processes before physical production begins. That allows for deeper insights and collaboration by helping stakeholders make more informed decisions to improve efficiency and reduce costly errors and last-minute changes that can result in significant waste.
To further transform how products and experiences are designed and manufactured, Siemens is integrating NVIDIA Omniverse Cloud application programming interfaces into its Siemens Xcelerator platform, starting with Teamcenter X, its cloud-based product lifecycle management software.
These integrations enable Siemens to bring the power of photorealistic visualization to complex engineering data and workflows, allowing companies to create physics-based digital twins that help eliminate workflow waste and errors.
Siemens and NVIDIA have demonstrated how companies like HD Hyundai, a leader in sustainable ship manufacturing, are using these new capabilities to visualize and interact with complex engineering data at new levels of scale and fidelity.
HD Hyundai is unifying and visualizing complex engineering projects directly within Teamcenter X.
Physics-based digital twins are also being utilized to test and validate robotics and physical AI before they're deployed into real-world manufacturing facilities.
Foxconn, the world's largest electronics manufacturer, has introduced a virtual plant that pushes the boundaries of industrial automation. Foxconn's digital twin platform, built on Omniverse and NVIDIA Isaac, replicates a new factory in the Guadalajara, Mexico, electronics hub to allow engineers to optimize processes and train robots for efficient production of NVIDIA Blackwell systems.
By simulating the factory environment, engineers can determine the best placement for heavy robotic arms, optimize movement and maximize safe operations while strategically positioning thousands of sensors and video cameras to monitor the entire production process.
Foxconn's virtual factory uses a digital twin powered by the NVIDIA Omniverse and NVIDIA Isaac platforms to produce NVIDIA Blackwell systems. The use of digital twins, like those in Foxconn's virtual factory, is becoming increasingly common in industrial settings for simulation and testing.
Foxconn's chairman, Young Liu, highlighted how the digital twin will lead to enhanced automation and efficiency, resulting in significant savings in time, cost and energy. The company expects to increase manufacturing efficiency while reducing energy consumption by over 30% annually.
By connecting data from Siemens Xcelerator software to its platform built on NVIDIA Omniverse and OpenUSD, the virtual plant allows Foxconn to design and train robots in a realistic, simulated environment, revolutionizing its approach to automation and sustainable manufacturing.
Making Every Watt Count One consideration for industries everywhere is how the rising demand for AI is
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Improving the sustainability of manufacturing involves optimizing entire product lifecycles - from material sourcing and transportation to design, production, distribution and end-of-life disposal.
