Physical AI Powering the New Age of Industrial Operations 2025

Page 19 of 26 · WEF_Physical_AI_Powering_the_New_Age_of_Industrial_Operations_2025.pdf

Emerging roles and tasks across the value chain driven by physical AI FIGURE 5 Physical AI automation frees up humans for higher-level tasks Operators manually process and assemble parts. Tasks require precision, manual machine operation and full attention. Changeovers and packaging are fully manual and labour-intensive.Manufacturing engineers design, implement and optimize production systems, largely experience-driven. Updating inflexible automation requires high manual effort.Workers manually move materials using forklifts or carts. Human coordination is needed, leading to inefficiencies, accidents and misplacements.Direct manufacturing Material processing, assembly and packaging Products are visually inspected by workers. This is slow, subjective and prone to human fatigue. Random sampling may miss defects.Reactive or preventive maintenance schedules are followed (independent of machine conditions). Engineers rely on visual checks and logs, making issues hard to foresee.Indirect manufacturing LogisticsManufacturing engineeringQuality control Maintenance Today AI-enabled robots perform welding, assembly and packaging using real-time system feedback. Systems adapt to product and task variations automatically.Production systems are software-driven, intelligent and adaptive. Engineers plan factories, integrate intelligent robots and visual-based quality control systems.AI-driven autonomous mobile robots handle materials end-to-end, ensuring the right parts are delivered on time.Vision-guided robotic arms scan every unit in real time and perform automated inspection tests.AI-powered systems are becoming self-sufficient, with robots and drones handling some maintenance and inspection tasks while continuously generating data. – Supervise robotic workflows –/uni00A0Train robots for new tasks –/uni00A0Resolve exception cases– Optimize adaptive system – Oversee digital process design – Cross-disciplinary integration– Monitor robotic fleets – Reconfigure robot routes – Manage system alerts– Strategic oversight – Audit flagged defects – Optimize quality control– Perform complex repairs – Interpret data – Improve systemFuture – Systems thinking – Digital literacy – Robot programming/ teaching– Advanced digital and AI skills – Systems thinking – Creativity– Systems thinking – Digital literacy – Workflow design and safety– Analytical thinking – AI and big data – Creativity– Technical skills – Analytical thinking – AI and big dataScenario SkillsTasks Source: BCG, World Economic Forum. 19 Physical AI: Powering the New Age of Industrial Operations
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