INSTRUMENTATION AND ELECTRONICS
PRESCRIPTIVE FROM PREDICTIVE TO
Dijam Panigrahi COO of GridRaster explores how agentic AI is reshaping manufacturing operations
T
he progression of intelligent automation in manufacturing and supply chain management has been pretty
groundbreaking. From the early days of the Industrial Revolution to today’s era of smart factories and agentic AI, the journey has been marked by continuous innovation and adaptation. The recent integration of
information technology with automation led to the development of programmable logic controllers
(PLCs) and computer numerical control (CNC) machines, allowing for more complex and precise automation processes. The introduction of the internet further transformed logistics, enabling real-time tracking and data analytics to optimise supply chains.
HOW INDUSTRY 4.0 IS EVOLVING Today, we fi nd ourselves in the midst of Industry 4.0, characterised by the fusion of digital, physical, and
biological worlds through advanced technologies such as the Internet of Things (IoT), artifi cial intelligence (AI), and big data analytics. This new era has given rise to smart factories, where machines can communicate with each other and make autonomous decisions to optimise production processes.
INTRODUCING AGENTIC AI IN MANUFACTURING The latest frontier in this evolution is the emergence of agentic AI, a progressive technology that combines autonomous decision-making with real-time adaptability. Unlike traditional automation, agentic AI enhances eff iciency, reduces costs, and fosters sustainable practices, making it indispensable for smart factories. Agentic AI is reshaping
Industry 4.0 is characterised by the fusion of digital, physical and biological worlds
manufacturing processes in several key areas. One of the most signifi cant is predictive maintenance. Traditional maintenance models are reactive, addressing failures after they occur. In contrast, agentic AI enables predictive maintenance, where systems monitor machinery in real-time, identifying signs of wear or potential failure before they disrupt production. This not only saves costs but also enhances eff iciency by allowing manufacturers to schedule repairs at optimal times, avoiding unexpected disruptions.
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