Unilever is creating AI twins of factories to boost efficiency
What's the story
Unilever has joined forces with Accenture to scale the use of artificial intelligence (AI)-powered digital twins across Unilever's global manufacturing network. Over the next 18 months, the two companies will create more than 40 new digital twins. These virtual replicas of factory equipment and production lines will leverage live data from physical systems for monitoring and predicting performance.
Tech innovation
Digital twins and their impact on manufacturing
Digital twins are virtual models of physical assets, processes, or systems. They use real-time data to simulate and predict performance. Unilever plans to combine these digital twins with AI insights and capabilities. This will help factory teams detect problems sooner, simulate scenarios faster, and make better decisions. "Scaling AI across our operations isn't just a technological shift, it's a commitment to superior products, sustainability and empowering our teams across our factories," said Adam Raeburn-James, Unilever's VP for digital business operations.
Strategic partnership
How Accenture is helping Unilever
Accenture is assisting Unilever in deploying industrial AI capabilities. These include advanced analytics and AI agents to predict maintenance needs, improve performance, and help teams take corrective action faster. The company has already seen measurable gains from digital twins across several factories globally. For instance, at its Raeford facility in North Carolina, a digital twin predicted 95% of process flow restrictions in deodorant production. This led to a 20% reduction in waste and a 10% increase in capacity.
Global impact
Success stories from Unilever's factories
In India, Unilever's Haldia factory uses an energy twin to optimize fan speeds, temperature settings, and moisture controls. This has resulted in reduced thermal energy consumption over two years. At its Gandhidham plant, a digital twin helped cut quality defects in Dove soap by 30% over four years. Other applications include reducing waste in mayonnaise production in Poland and optimizing ingredient use in Vietnam with AI-powered systems delivering savings of 1-2% while keeping product quality intact.