{"id":70065,"date":"2026-06-25T07:02:10","date_gmt":"2026-06-25T07:02:10","guid":{"rendered":"https:\/\/www.europesays.com\/britain\/70065\/"},"modified":"2026-06-25T07:02:10","modified_gmt":"2026-06-25T07:02:10","slug":"unilever-expands-ai-digital-twins-after-success-at-north-carolina-manufacturing-plant","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/britain\/70065\/","title":{"rendered":"Unilever expands AI digital twins after success at North Carolina manufacturing plant"},"content":{"rendered":"

Unilever is expanding the use of AI-enabled digital twins across its global manufacturing network after successful deployments at its North Carolina production facility demonstrated significant improvements in quality, efficiency and waste reduction.<\/p>\n

The consumer goods giant is partnering with Accenture on a multi-year programme that will see more than 40 new digital twins developed over the next 18 months, building on technology already delivering measurable results at manufacturing sites around the world.<\/p>\n

Among the programme\u2019s standout successes is Unilever\u2019s facility in Raeford, North Carolina, where AI-powered digital twin technology is helping manufacture personal care brands including Dove, Degree and Axe. The system predicts 95% of process flow restrictions in deodorant stick production, reducing waste by 20% while increasing manufacturing capacity by 10%.<\/p>\n

Digital twins are virtual replicas of factory equipment and production lines that use live production data to model how machinery and processes perform. Combined with AI-driven analytics and agentic capabilities, they enable manufacturers to predict maintenance needs, identify production issues earlier and simulate process improvements before implementing them on the factory floor.<\/p>\n

The expanded rollout forms part of Unilever\u2019s wider strategy to accelerate AI adoption across its manufacturing operations and supply chain.<\/p>\n

Scaling AI across our operations isn\u2019t just a technological shift, it\u2019s a commitment to superior products, sustainability and empowering our teams across our factories.<\/p>\n

Through our partnership with Accenture to accelerate digital twins, we are turning innovation into measurable impact to create desirable brands for our 3.7 billion consumers worldwide.
Adam Raeburn-James, Global VP for Digital Business Operations at Unilever<\/p>\n

Accenture is supporting the deployment of industrial AI capabilities that combine advanced analytics with AI agents to help predict equipment maintenance requirements, improve operational performance and enable manufacturing teams to respond more quickly to changing production conditions. As confidence in the technology grows, certain process adjustments could increasingly be carried out automatically while remaining under human oversight.<\/p>\n

Nicole van Det, CEO of Accenture Netherlands and Nordics and global account lead for Unilever, said: \u201cUnilever has long been recognised for its supply chain excellence, and expanding the use of manufacturing digital twins reflects the company\u2019s continued focus on both technology and people.<\/p>\n

\u201cHaving invested early in AI, the company is setting the standard for pairing advanced tools with smart process design and disciplined execution on the shop floor. Together, we\u2019re setting the benchmark for how industrial AI creates long-lasting value in the consumer goods sector.\u201d<\/p>\n

Beyond North Carolina, Unilever has deployed digital twins across several international manufacturing facilities. An energy-focused digital twin at its Haldia, India plant has reduced thermal energy consumption during detergent production, while systems at facilities in Poland, India and Vietnam have helped improve product consistency, reduce production stoppages and cut raw material waste.<\/p>\n

The company says the next phase of deployment will create more than 40 additional digital twins over the next 18 months, establishing a scalable blueprint for adoption across its global manufacturing network as it seeks to improve efficiency, product quality and sustainability through AI-enabled operations.<\/p>\n

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