In advanced manufacturing, digital twins are more than just R&D tools. Simon Francis, group quality director at leading international quality group G&P, explores how this AI-enabled technology can help strengthen OEM-supplier collaboration and build more resilient supply chains.
Digital twins are one of the driving forces behind the fourth industrial revolution. This technology, underpinned by real-time data, machine learning and AI, has already revolutionised multiple areas of advanced manufacturing from R&D to production lines. As AI capabilities continue to grow, the transformative power of digital twins now extends across the entire supply chain.
Earlier this year, the World Economic Forum warned that supply chains had entered the “era of structural volatility”. As material shortages and supply disruption become the norm, building resilience into supply chains is vital, and this is where digital twin technology is proving to be an extremely effective asset.
The technologies behind supply chain digital twins
A digital twin is a live, virtual representation of a real-world object, system or process. This technology can simulate, monitor and predict how its physical twin will perform and behave under multiple scenarios. By utilising this technology, organisations can constantly optimise products and processes, from design to production, preventing potential issues from arising in the real world.
As digital twin technology evolves, its potential applications now extend well beyond R&D and production. In areas such as advanced manufacturing, for example, it is now possible to create live digital replicas of entire supply chains connecting OEMs and their supplier ecosystem.
These enhanced digital twin capabilities are made more powerful by advancements in reinforcement learning which improves digital twins’ ability to analyse data and make decisions, while generative AI makes these analytics more accessible than ever before.
Turning supply chain weaknesses into strengths
Given the growing capabilities of digital twin technologies, they have the potential to provide companies with end-to-end transparency within internal and third-party supply chains. The ability to accurately model existing supply chain structures would enable OEMs to forecast supplier performance, identify potential bottlenecks and inefficiencies, and act accordingly.
A digital supply chain twin would continuously evaluate variables such as material flows and demand fluctuations and simulates potential outcomes, enabling OEMs to build a reliable, live picture of risk throughout the supply chain. In addition, access to comprehensive, real-time supplier data, such as quality incident analytics and production data would make it possible to predict disruption within the chain before it occurs. Armed with this intelligence, OEMs could undertake targeted interventions to prevent issues such as delivery shortfalls, misaligned capacity with demand, or inconsistent adherence to quality and on-time performance metrics.
But digital twin technology doesn’t only benefit OEMs. It also empowers suppliers to forge more synergic and productive relationships with their customers, enabling them to deliver more consistent quality and service levels. Research from Deloitte suggests that digital twins encourage “suppliers to deliver high-quality data and become active parts of the ecosystem”, improving pricing and reducing risk in the process.
Preventing disruption with simulation
Real-time visibility of the entire supply chain, from customers to tier-n suppliers, enables organisations to simulate the impact of potential disruption, leading to earlier, more effective intervention. In this way, OEMs and suppliers can manage stock more effectively , shorten planning cycles and improve decision-making and responsiveness to changing market dynamics. Digital twin technology also empowers organisations to shift from static to dynamic planning, constantly adjusting to live forecasts to enhance responsiveness to changes in customer behaviour or disruptions.
Another core benefit of integrating digital twin technology into supply chain management is the ability to identify and test “what if?” scenarios. By introducing stress points into a model, businesses can identify weak links, assess resilience and develop contingency plans ahead of time, effectively developing a “plan B” before disruption.
This is particularly valuable in complex manufacturing sectors such as defence, aerospace and automotive, where supply chains are highly interconnected. A change in one area can create consequences across multiple suppliers, production lines and end customers. A supply chain twin could help identify those interdependencies before a small disruption becomes a crisis.
A recent study from BCG suggests that digital twins can help companies evaluate the likelihood of disruption and anticipate risks several months in advance3. The research shows that, by assessing the interdependencies of demand, supply and production volatility, organisations can identify and implement alternative production and delivery plans more effectively.
Overcoming barriers to adoption with stronger collaboration
While the benefits of leveraging digital twins are clear, many businesses across the advanced manufacturing sector are still reluctant to adopt this technology. A 2025 study commissioned by the Department for Science, Innovation & Technology (DSIT) identified multiple barriers to business adoption of advanced technologies such as digital twins4. These barriers include high capital investment, inadequate access to external finance, skills gaps and the perceived complexity of new technologies. There is also evidence of reluctance from many tier-n suppliers to volunteer the data required to properly build out digital twins.
This is where collaboration becomes crucial.
Stronger collaboration between OEMs and suppliers is essential to bridge existing knowledge gaps, share best practices and identify financing opportunities to help organisations invest in new technology, while suppliers should be incentivised to provide the levels of transparency required to make digital twins effective. Specialist providers of supply chain quality services, such as G&P, have a pivotal role to play in facilitating and strengthening these collaborations throughout the supply chain.
As AI technology continues to advance, digital twins will increasingly empower companies to make better decision and plan more effectively. With this technological capability at hand, OEMs and suppliers across the advanced manufacturing sector will be better prepared to mitigate future volatility and build long-term supply chain resilience.