Is the use of digital twins to improve sustainability on the rise?
Digital twins, which are virtual replicas of physical objects or processes, are becoming increasingly valuable tools for supply chain management and optimisation, including sustainability.
A sustainability trend in supply chains is driven by several factors:
Increasing environmental concerns:
As climate change and environmental issues become more pressing, companies are under growing pressure to reduce their environmental impact.
Regulatory compliance:
Many countries are implementing stricter environmental regulations, pushing companies to adopt more sustainable practices.
Consumer demand:
Customers are increasingly favouring environmentally responsible companies, creating a market incentive for sustainability improvements.
Technological advancements:
As digital twin technology becomes more sophisticated and accessible, its application to sustainability challenges is expanding.
Cost savings:
Many sustainability improvements also lead to cost reductions in the long term, making them attractive to businesses.
Digital twins are particularly useful for sustainability efforts because they allow companies to:
– Model complex supply chain systems and their environmental impacts
– Test different scenarios without real-world consequences
– Identify inefficiencies and areas for improvement
– Produce and gather sustainability information against targets more accurately
While this use of digital twins is growing, it’s worth noting that adoption rates can vary by industry and company size. Larger companies and those in sectors with significant environmental impacts (e.g., manufacturing, logistics) are often at the forefront of this trend.
Here’s a more detailed look at how Digital Twins are being used to improve sustainability in supply chains:
Carbon footprint reduction:
Digital twins can model the entire supply chain, for example integrating data on energy consumption, emissions, and waste generation.
This helps companies identify areas of high carbon emissions. Companies are able to locate areas with the biggest environmental footprint and target them for improvement.
By simulating different scenarios, businesses can test various strategies to reduce their carbon footprint without disrupting actual operations.
This might include optimising transportation routes, adjusting production schedules, changing sourcing locations or reducing inventory.
Energy efficiency:
Digital twins can model energy consumption across the supply chain, from manufacturing facilities to warehouses and transportation.
Companies can use these models to identify energy-intensive processes and test energy-saving measures virtually before implementing them in real life.
This might include optimising equipment usage, improving HVAC systems, or implementing renewable energy sources.
Waste reduction:
Using product lifecycle simulations, digital twins can indicate potential areas of waste in the supply chain.
This could involve optimising packaging, reducing overproduction, or improving inventory management to minimise spoilage of perishable goods.
Circular economy initiatives:
Digital twins can model the entire lifecycle of a product, from raw material extraction to end-of-life disposal or recycling.
This helps companies design products and supply chains that better support circular economy principles, such as easier disassembly for recycling or reuse of components.
Product design for sustainability:
By simulating product performance and lifecycle, digital twins can help design more sustainable products while maintaining product protection, eco-friendly packaging choices and production configurations.
This could involve reducing material use, improving energy efficiency, enhancing recyclability, and in planning reverse logistics for product take-back programs.
Water management and conservation:
In industries where water usage is significant, digital twins can model water consumption and help optimise its use throughout the supply chain.
This allows for the identification of high-consumption areas and the testing of water-saving strategies.
This is particularly relevant in sectors like agriculture, food processing, and textiles.
Sustainable sourcing:
Digital twins can help companies model the environmental impact of different sourcing decisions.
This can support more sustainable choices in raw materials and suppliers based on factors like transportation distances, production methods, and local environmental impacts.
This supports more informed decision-making in supplier selection and material choices.
Green logistics optimisation:
Digital twins can simulate different transportation and warehousing strategies to minimise environmental impact.
This might include optimising load consolidation, route planning, multi-modal transport options, streamline delivery processes, reduce fuel consumption, improving energy efficiency in warehouses and ultimately decrease carbon emissions associated with transportation.
As digital twins can provide a detailed, real-time view of the entire supply chain, it also helps companies monitor and manage resources more effectively identifying inefficiencies, waste, downtime, maintenance, and opportunities for improvement.
Compliance and reporting:
As environmental regulations become stricter, digital twins can help companies track and report on various sustainability metrics across their supply chains.
This can aid in compliance with regulations and in meeting voluntary sustainability targets.
Innovation and Collaboration:
The use of digital twins fosters innovation by allowing companies to experiment with new processes and technologies in a virtual environment before implementing them in the real world. It also enhances collaboration across the supply chain, as stakeholders can access and act on the same data.
By providing a virtual environment to test and optimise sustainability initiatives, digital twins allow companies to make more informed decisions and implement more effective sustainability strategies across their supply chains. It’s important however to note that the effectiveness of these tools depends on the quality of data input and the accuracy of the models used.
Several industries, including manufacturing, automotive, aerospace, and retail, are adopting digital twins to streamline their supply chain operations. According to various industry reports and market research, the adoption of digital twins is expected to continue growing in the coming years as more businesses recognise their potential benefits.
In summary, digital twins offer a powerful tool for improving supply chain sustainability by providing comprehensive insights, enabling predictive analytics, enhancing resource efficiency, reducing environmental impact, and supporting regulatory compliance and innovation. As these benefits become more apparent, their adoption in supply chains is expected to continue growing.
