Transitioning from Industry 4.0 to 5.0: It’s not simple
The shift from Industry 4.0 to 5.0 is not an easy task. Industry 5.0 implementation will be complex, with connected devices and systems sharing data in real time at the edge. It encompasses a host of technologies and systems, including a high-speed network infrastructure, edge computing, control systems, IoT devices, smart sensors, AI-enabled robotics, and digital twins, all designed to work together seamlessly to improve productivity, lower energy consumption, improve worker safety, and meet sustainability goals.
In the November/December issue, we take a look at evolving Industry 4.0 trends and the shift to the next industrial evolution: 5.0, building on existing AI, automation, and IoT technologies with a collaboration between humans and cobots.
Technology innovations are central to future industrial automation, and the next generation of industrial IoT technology will leverage AI to deliver productivity improvements through greater device intelligence and automated decision-making, according to Jack Howley, senior technology analyst at IDTechEx. He believes the global industry will be defined by the integration of AI with robotics and IoT technologies, transforming manufacturing and logistics across industries.
As factories become smarter, more connected, and increasingly autonomous, MES, digital twins, and AI-enabled robotics are redefining smart manufacturing, according to Leonor Marques, architecture and advocacy director of Critical Manufacturing. These innovations can be better-interconnected, contributing to smarter factories and delivering meaningful, contextualized, and structured information, she said.
One of those key enabling technologies for Industry 4.0 is sensors. TDK SensEI defines Industry 4.0 by convergence, the merging of physical assets with digital intelligence. AI-enabled predictive maintenance systems will be critical for achieving the speed, autonomy, and adaptability that smart factories require, the company said.
Edge AI addresses the volume of industrial data by embedding trained ML models directly into sensors and devices, said Vincent Broyles, senior director of global sales engineering at TDK SensEI. Instead of sending massive data streams to the cloud for processing, these AI models analyze sensor data locally, where it’s generated, reducing latency and bandwidth use, he said.
Robert Otręba, CEO of Grinn Global, agrees that industrial AI belongs at the edge. It delivers three key advantages: low latency and real-time decision-making, enhanced security and privacy, and reduced power and connectivity costs, he said.
Otręba thinks edge AI will power the next wave of industrial intelligence. “Instead of sending vast streams of data off-site, intelligence is brought closer to where data is created, within or around the machine, gateway, or local controller itself.”
AI is no longer an optional enhancement, and this shift is driven by the need for real-time, contextually aware intelligence with systems that can analyze sensor data instantly, he said.
Lisa Trollo, MEMS marketing manager at STMicroelectronics, calls sensors the silent leaders driving the industrial market’s transformation, serving as the “eyes and ears” of smart factories by continuously sensing pressure, temperature, position, vibration, and more. “In this industrial landscape, sensors are the catalysts that transform raw data into insights for smarter, faster, and more resilient industries,” she said.
Energy efficiency also plays a big role in industrial systems. Power management ICs (PMICs) are leading the way by enabling higher efficiency. In industrial and industrial IoT applications, PMICs address key power challenges, according to contributing writer Stefano Lovati. He said the use of AI techniques is being investigated to further improve PMIC performance, with the aim of reducing power losses, increasing energy efficiency, and reducing heat dissipation.
Don’t miss the top 10 AC/DC power supplies introduced over the past year. These power supplies focus on improving efficiency and power density for industrial and medical applications. Motor drivers are also a critical component in industrial design applications as well as automotive systems. The latest motor drivers and development tools add advanced features to improve performance and reduce design complexity.
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