4 Ways to Achieve Industry 4.0 Manufacturing Modernization

Today’s Industry 4.0 umbrella covers not just greater digitization of production, but also extensive digital connections to the supply chain, sustainability, and even the customer experience. Companies like Unilever are overhauling their operations with this in mind. In fact, according to ABI Research, total spending on digitalization by the fast-moving consumer goods sector is forecast to reach $23.8 billion in 2030 (a 15% CAGR).“The application of digital technologies has delivered significant impact across all performance metrics of our business operations, which resulted in improved service levels for our customers,” Biswaranjan Sen, beauty and wellbeing chief product supply chain officer at Unilever, told CGT. How can consumer goods companies upgrade their systems and infrastructures to adopt some of these Industry 4.0 technologies and prepare for the future of manufacturing? Consider these best practices, with examples from Unilever, Heinken, Nestle, and more. Advancements in Industry 4.0 follow the eras of mechanization, automation, and computerization and are often defined by “intelligentization.” Artificial intelligence, including generative AI, is just one of the technologies fueling this new iteration of Industry 4.0; others include digital twins, IoT, advanced analytics, and, in the future, the industrial metaverse. “Leveraging technology and advanced AI models has led to a breakthrough in customer connectivity as we drive a ‘One E2E Supply Chain’ mindset from customer to factory/supplier across our go-to-market channels,” says Sen. While these technologies boast myriad benefits, some of Industry 4.0’s greatest opportunities can be frustratingly complex to implement. This is how consumer goods companies can push past challenges to modernize their tech stack and embrace the future of manufacturing.1. Build use cases for your data.While the expanded scope of Industry 4.0 can make it overwhelming to get started, CPG companies can begin by dedicating specific use cases for data-powered approaches that are supported by technologies like digital twins and artificial intelligence. Unilever, for example, tapped these technologies to improve cost efficiency and agility while significantly cutting their environmental footprint in the highly complex manufacturing of laundry powders at their facility in Indaiatuba, Brazil. The digital twin uses machine learning to predict the optimal process parameters for new formulations. “This eliminated the need for physical trials, significantly speeding up the launch of new laundry detergent innovations,” says Sen. Unilever is also leveraging AI to enable better and faster decision-making at an individual machine or process level to create fully autonomous factories.Upgrades in analytics can also help with real-time decision-making and introducing efficiencies into manufacturing processes. Over the last five years, General Mills has been fortifying its digital foundation, which includes using data and external monitoring to predict and manage upstream disruptions in the supply chain. The real-time data is deployed to manufacturing line operators to improve throughput, reduce costs, and minimize waste across the value chain ecosystem. In addition, CPGs should implement analytics-driven modernization into their consumer-facing practices, tapping feedback and behavioral insights to inform decisions in R&D and in customer care to expedite innovation and elevate experiences. Unilever does this with its digital voice of the consumer’ (DVOC) application, designed to bring real-time consumer feedback from e-commerce websites, carelines, and social media platforms directly onto the shop floor. They use the data to quickly identify key emerging trends, analyze the strength of the ideas, and evaluate which to take forward. R&D then uses a digital product development tool to build the final proposition that directly meets the needs of the consumer. “Initial pilots have seen a reduction in innovation cycle times by 75%,” says Sen.2. Establish a data foundation for scalable technologiesBehind these high-profile Industry 4.0 wins, considerable challenges stand in the way of achieving the vision of a fully digitized, efficient, sustainable manufacturing and supply chain environment. One of the biggest obstacles? Data quality. The 2024 Retail and Consumer Goods Analytics Study notes that 53% of CGs say their data quality significantly lags that of industry leaders, and data sharing from retailers is still not where CGs would like it to be (just 26% receive daily POS data, for example). The more accurate, relevant, real-time data, the better technologies such as digital twins and artificial intelligence and other advanced analytics functions can perform. Manufacturers with legacy production equipment will need to be able to build in a solid foundation of clean, structured data to support smart factories — something that is often complicated by the differing brands and models across their network. “The digital twin is exciting, but many are still battling to actually remove paper from data collection,” says Michael Larner, industrial and manufacturing research director at global technology intelligence firm ABI Research. “They haven't been willing to do a lot of incremental steps and a lot of hard work to get to the digital twin stage.”Scaling these efforts isn’t always easy. “It's hard to scale innovation,” such as deploying an energy reduction solution across every site, says Larner. “You have to get buy in from the local, portfolio or local brands, and they'll have their own objectives in their own facilities.” Indeed, even a company the size of Unilever has only managed to earn “Lighthouse” status for seven of its more than 280 factories worldwide. This designation is part of the World Economic Forum’s network of Advanced Fourth Industrial Revolution (4IR) Lighthouses, recognizing companies that incorporate 4IR technologies such as artificial intelligence to maximize efficiency and competitiveness, and drive sustainable and responsible business growth.3. Create a ‘smart’ workforcePushing toward Industry 4.0 goals also has implications for people and data security. Internally, CGs must not only attract talent capable of leading their efforts to innovate with technology; they must also support and retrain those whose roles shift as a result of its adoption. Ensuring future hires are prepared to work in smarter facilities is also a concern. Nestlé Purina, for example, created a manufacturing experience center in part to educate the next-generation workforce, as well as to showcase the company’s modern manufacturing operations.Creating factories that are fully online and connected also vastly expands the threat vector when it comes to cybersecurity. “Consumer goods companies have got to keep up to date and focused on that in terms of intellectual property, in terms of the ingredients, the designs, as well as production data,” says Larner. 4. Implement systems that drive productivity but also efficiencyHigh stakes are nothing new for consumer goods companies, which are accustomed to competing for the attention and dollars of a highly changeable public. CGs remain under unrelenting pressure to move faster and more efficiently. Now they must also ensure their work pushes further toward new goals in sustainability, collaboration, compliance, and more. This is why companies should not only take steps within their Industry 4.0 efforts to drive efficiency and innovation, but also support sustainability goals to satisfy regulations that require manufacturers to drive carbon and resource waste out of their production and supply chain processes. This includes reducing water consumption and lowering energy use to satisfy rules such as the U.S. Securities and Exchange Commission Scope 1 and Scope 2 requirements, Scope 3 reporting requirements, carbon reduction goals set at COP28, and previous climate action forums, along with emerging EU sustainable product requirements.Heineken used an “energy digital twin” of a typical Heineken brewery to identify potential significant energy savings. After a simulation showed about 70% of energy use came from the heating and cooling necessary for the brewing process, it began developing renewable energy sources and monitoring systems expected to garner 15% to 20% energy savings and 50% CO2 reductions at each brewery. Heineken’s Connected Brewery Ecosystem combines IoT, analytics, and robotics to optimize manufacturing and distribution, providing employees with increased visibility into operations. Traceability and security regulations also loom, requiring meticulous data collection, reporting, and protection of the digital aspects of production. Progressing on Industry 4.0 GoalsWhile the CG industry — and its leaders in particular — have made significant progress toward digitizing their factories in a way envisioned by the developers of the Industry 4.0 concept, it’s a moving target. In addition to expanding in scope, new technologies continue to emerge on the to-do list. This includes the “industrial metaverse,” a far more extensive version of the digital twin concept. It reportedly “mirrors and simulates real machines, factories, cities, transportation networks, and other highly complex systems — and will offer to its participants fully immersive, real-time, interactive, persistent, and synchronous representations and simulations of the real world,” according to academic researchers, who predict this will have a significant impact on manufacturing in the years to come. As it turns out, the goal of complete intelligentization of production may be far off, but CGs can work diligently to leverage the full array of today’s technologies to make factories smarter, more efficient, and better for the planet.

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