FEATURE
Automation & AI
A BRAND NEW ERA
Christian Pedersen, Chief Product
E
volving from the groundwork set by Industry 4.0, organisations that operate in asset-intensive environments, such as
manufacturing, are producing and gathering extensive data every day. Beyond its use in routine tasks, that data holds the secret to transitioning into Industry 5.0, a stage of industrial development where human insight and machine intelligence work and sustainable.
Industry 4.0’s emphasis on digitalisation
ushered in sensors, connected devices, data analytics, and automation to enhance production and streamline processes. Industry 5.0 takes these elements further by blending physical assets and digital infrastructure so that human labour and machines complement each other more
As part of this new phase, AI and cloud supply chains to product design, but only if the data is relevant, properly managed, and accurately analysed. Using AI to integrate data points from physical assets will unlock new avenues for innovation and variation. Real-time insights from production machinery and equipment will help drive operational excellence and deliver a competitive edge. The greater alignment of AI and data with physical processes helps achieve multiple goals: heightened productivity, reduced resource consumption, and improved Environmental, Social, and Governance (ESG) performance. By harnessing AI-driven insights, companies can optimise their processes from a manufacturing-based level, with AI proposing opportunities to reduce waste use of time, and sustainability. Through advanced decision analytics, asset-rich enterprises can optimise capital allocation,
22 March 2025 | Automation
A BRAND NEW ERA
manage risk, and drive more precise, data- driven business decisions. Servitisation, the practice of renting or leasing industrial equipment instead of buying it outright, is also on the rise. This shift encourages manufacturers to build smarter machines designed to last longer, since performance and reliability become essential to retaining customers. AI can detect anomalies and maintenance issues in this equipment early, triggering preventive maintenance or re-routing tasks so that disruptions are minimal. Taking something from the physical world
and replicating it virtually is a technical concept: a concept that becomes vital in an environment with integrated Manufacturing Execution Systems. In the past, these worlds were separate, but now digital twins bridge the divide by processing information in real-time, breaking down the silos between the virtual and physical environments faster than humans can. There’s a cycle that occurs: simulation informs business practices which change the parameters for simulation, and so on. Simulations help identify the areas needed for improvement, allowing for iterative adjustments until desired outcomes are tested, proven and achieved. A useful illustration is agriculture. Rather than waiting for harvest time to run trials in based on these simulations can reduce harvesting times from days to hours, all without risking real crops. The same principle applies to factories, utility grids,
and large-scale construction projects. Adopting AI solutions and digital twins can be challenging. Data regulations vary across regions, and gathering high-quality, relevant information takes careful planning and consistent monitoring. making it important for companies to from targeted analysis. Organisations should also be realistic about the costs. While these technologies can budgets can quickly balloon if the scope is too broad or not matched to genuine operational needs. Partnering with experts who understand both the technology and the industry context often leads to a more measured, results-driven approach. Manufacturers that blend AI with clear, accurate data are well positioned for the next phase of industrial evolution. As machinery grows smarter and analytics become more sophisticated, industries that manage physical assets can reduce downtime, waste, and emissions, while also improving their products and workforce conditions.
create practical, lasting improvements. By focusing on data quality, adopting AI in the right places, and seeking knowledgeable support, any business using large-scale assets can reshape its processes and remain competitive as this new era takes hold.
IFS
www.ifs.com
automationmagazine.co.uk
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