INSTRUMENTATION AND ELECTRONICS For inventory management, agentic
AI systems use real-time data and demand forecasts to optimise stock levels, ensuring the availability of raw materials while avoiding overstocking. Autonomy here reduces carrying costs and improves supply chain efficiency, allowing manufacturers to maintain lean inventories while meeting production schedules seamlessly. In robotic assembly lines, agentic
AI enables dynamic task allocation and real-time adaptability. Unlike traditional robots that follow pre- programmed instructions, AI-powered robots learn from their environment and adjust to changing tasks on the fly. This significantly reduces errors, optimises resource usage, and enables scalability in production, making them a cornerstone of smart factory operations. It’s important to understand that
the implementation of intelligent automation and agentic AI in manufacturing is not about replacing human capital. Instead, it’s about reallocating human resources to other critical areas of manufacturing planning, business operations, analysis, operations, and reporting functions. Through automating repetitive and time-consuming tasks, agentic AI
frees up human resources for strategic decision-making activities, which allows manufacturers to leverage their workforce’s creativity, problem-solving skills, and adaptability in areas where human input is most valuable. The adoption of intelligent
automation and agentic AI is also changing the paradigm of how manufacturers view software solutions. Instead of merely leveraging software as a service, the industry is evolving toward service as software functions within the business through agentic automated decisioning opportunities. This shift allows for more integrated, customised, and responsive solutions that can adapt to the unique needs of each manufacturing operation.
THE USE OF DIGITAL TWINS A key component in the implementation of automated decisioning across these industries is the use of digital twins. A digital twin is a virtual representation of a physical object or system, updated in real-time using data from sensors in the physical world. In manufacturing, digital twins of production lines or
entire factories allow for real-time monitoring, predictive maintenance, and optimisation of operations. For example, in aerospace
manufacturing, a digital twin of an aircraft engine can be used to simulate different operating conditions, predict wear and tear, and optimise maintenance schedules. In automotive production, a digital twin of the assembly line can help identify bottlenecks, optimise workflows, and even test new production configurations virtually before implementing them in the physical world. The integration of digital twins with
agentic AI takes this concept even further. AI algorithms can analyse the vast amounts of data generated by digital twins to make autonomous decisions and optimisations. For instance, an AI system could use data from a digital twin of a manufacturing plant to automatically adjust production parameters in real- time, optimising for factors such as energy efficiency, output quality, and equipment lifespan. As we look to the future, the
AI is about reallocating human resources to other critical areas
potential of intelligent automation and agentic AI in manufacturing seems boundless. These technologies are not just improving efficiency and reducing costs; they’re enabling new levels of customisation, sustainability, and innovation. By 2025, it’s predicted that AI-powered automation could save manufacturers up to 25% of their operational costs. The evolution of intelligent
automation, culminating in the current era of agentic AI, represents a true shift in manufacturing and supply chain management. By embracing these technologies, manufacturers can improve their operational efficiency and decision- making processes while also freeing up their human workforce to focus on more strategic, creative, and value-adding activities. Dijam Panigrahi is co-founder and
COO of GridRaster, a provider of cloud-based platforms that power high-quality digital twin experiences on mobile devices for enterprises.
For more information visit:
www.gridraster.com
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www.engineerlive.com
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