Unilever factory named WEF Lighthouse site

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Hindustan Unilever Limited (HUL), the Indian division of FMCG manufacturing giant Unilever, has announced that its Dapada factory, manufacturing Home Care products including Surf excel, Rin, and Vim, has joined the Lighthouse Network, making it the first FMCG manufacturing site in India to accorded this status.

The Global Lighthouse Network is a community of manufacturing sites recognised by the World Economic Forum (WEF) for applying advanced technologies, innovations, and sustainable practices to modernise business operations. The Network includes sites that have implemented end-to-end digitisation across the value chain, pushing the boundaries of technological advancement. These revolutionary technologies result in reduced manufacturing cost, greater agility, and speed.

Established in 2001, the Dapada site produces three million units per day for brands like Surf excel, Vim, Rin and Wheel. This site started its digital journey in 2018 and is known to be the first Unilever dedicated Home Care site globally to be recognised as an E2E lighthouse factory, paving the way for rapid digital transformation in South Asia.

Sanjiv Mehta, President of Unilever South Asia and Chairman and Managing Director of Hindustan Unilever, said: “The WEF recognition is a testament to our sustained focus on making the Supply Chain future fit as part of our ‘Reimagine HUL’ agenda. This is the first time an FMCG factory in India has been awarded this status, and I hope more will follow as Unilever increasingly digitises its supply chain function. I would like to thank all our employees in Dapada who have leveraged the factory’s transformation and transitioned to this new, digital way of working.” 

Through this transformation, the factory was able to reduce its carbon footprint, enhance productivity and provide superior product quality to consumers while being mindful of cost competitiveness in an increasingly challenging market. “Using Fourth Industrial Revolution (4IR) technologies like augmented reality, big data and analytics, and IoT, the Dapada factory deployed artificial intelligence/machine learning-led solutions to accelerate the pace of innovation and speed of response to consumer demand,” says Willem Uijen, Unilever’s Head of Supply Chain for South Asia and Southeast Asia.

As a result of this digital transformation, the Dapada site has shown a clear impact through the reduction of manufacturing cost (per ton) by 39% and end-to-end product development lead time by 50%. Similarly, the site has been able to reduce quality defects by about 50%. On the sustainability front, there has been a reduction in Scope 1 greenhouse gas emissions by 54% and water consumption by 31%. A key aspect pivotal in the digitisation journey included making our people future fit. As part of the transformation, 48% of the workforce were upskilled and reskilled.

An independent expert panel at World Economic Forum has recognised HUL’s Dapada factory for implementing a series of advanced 4IR use cases, which are generating an impact on tangible metrics in productivity, agility and mass customisation.  

  • Consumer-centric agile innovation using Digital Voice of Consumer: Digital Voice of Consumer allows faster reporting of consumer insights from various social media platforms and the Unilever Care Line, which are analysed and sorted into predefined categories using natural language processing (NLP) and Machine Learning algorithms for faster translation into action. With a digitally enabled innovation process using digital twin and other simulation tools, the site has shown agility and speed in innovations and in rolling out new formulations.
  • Predictive analytics to deliver superior products also with product formulation changes: Process efficiency improved in the most complex and patented manufacturing portfolio with unique chemical reactions using advanced and customised data capturing tools and advanced analytics, reducing potential defects, hence supporting predictive analytics of the batch. Data insights were used to develop a digital twin of the formulation resulting in a reduction in lead time for the rollout of formulation changes.
  • Machine learning-enabled demand planning & customer replenishment: With fast increasing distributor landscape and product assortment led by increasing sales, changing consumer preferences and increased volatility, machine learning was deployed over 6.5 billion combinations across 2.2 million stores based on multiple internal/external demand drivers to provide accurate and responsive forecasts at lowest granularity along with optimum replenishment norms for the distributors to reduce blocked cash, reduce lead time to market, reduce inventory in the value chain.
  • Smart manning allocation with AI-enabled skill building: App-based platform built with advanced analytics for maximising production and pre-allocating workstations to employees across 80K man-machine combinations to improve manpower productivity and eliminate OEE loss at shift start and maximize outputs for priority lines by matching high skills to priority lines.
  • Auto Loss correction system basis data backed real time root cause analyser: Auto loss correction system to mitigate top 80% contributors of packing speed loss using dynamic root cause analyser built through decision tree algorithm. Data collection through IoT enabled unique data capturing devices act as an enabler to connect packing losses with Upstream process phenomenon and prescribe real time actions resulting in increased manpower productivity, reduction in manual intervention & lower mean time to repair.

Articulating on the Global Lighthouse network, Francisco Betti, Head of Shaping the Future of Advanced Manufacturing and Value Chains, World Economic Forum, said: “As the world grapples with many challenges, it is remarkable to see how Lighthouses are yielding sustainability benefits while achieving business goals, which we call eco-efficiency. We need them to continue illuminating the way forward for the global manufacturing community by shaping a responsible future of manufacturing that works for people, society and the environment.”