Industry 5.0 refers to the next evolution of industrial production that leverages advanced technologies like artificial intelligence, big data, robotics, and the Internet of Things (IoT).

The goal of Industry 5.0 is to create smart factories, smart manufacturing, smart fulfillment, and smart business operations and best practices that combine the best of human and artificial intelligence to enable flexible, resilient and human-centric mass production. It builds on previous industrial revolutions but adds a new level of intelligence, connectivity and efficiency.

Before we go into detail of some of the novel methodologies of Industry 5.0, to understand what is different compared to generations past, let’s start with a little background on the iterations of Industry from the 1970’s and on.

Industry 3.0 (1970s – present):

  • Introduction of early electronics, IT and automation (PLC controllers).
  • Mass production and early assembly lines.
  • Analog/mechanical systems still dominate.
  • Hierarchical, centralized manufacturing control.

Industry 4.0 (2010s – present):

  • Digitalization through advanced sensors, connectivity, data and analytics.
  • Cyber-physical systems monitor physical processes.
  • Internet of Things (IoT), cloud computing and AI drive smart automation.
  • Increased adaptability, efficiency, productivity, customization.
  • Decentralized decisions through smart networks.

Each industrial revolution builds new capabilities on top of the prior ones, leveraging more advanced technologies like automation, connectivity, analytics, AI, distributed systems, and human-centric design to create smarter, more flexible, and more sustainable manufacturing environments.

Developing now, and in the near future, even newer technology and processes are emerging, which is now called Industry 5.0.

Industry 5.0 (emerging now and beyond):

  • AI-driven autonomous, self-optimizing processes.
  • Broad human-machine collaboration, not just automation.
  • Sustainable manufacturing through renewable energy, waste reduction.
  • Customized mass production at scale.
  • Human-centered design focusing on human well-being over profits.
  • Distributed, localized production through technologies like 3D printing.
  • Resilient, self-healing value networks between partners.

Some key operational platforms and technologies of Industry 5.0 include:

Industrial Internet of Things (IIoT) A network of intelligent, interconnected devices and sensors that collects and shares data to optimize industrial processes.

  • Smart sensors – Sensors embedded in equipment can monitor conditions like vibration, temperature, pressure, etc. and send real-time data to analytics systems to optimize performance.
  • Asset tracking – RFID tags, GPS, and other tracking devices can pinpoint the location of industrial equipment, parts, and inventory through the facility.
  • Condition monitoring – Sensors detect when machines need maintenance and trigger automated alerts and work orders. Enables predictive maintenance.
  • Inventory management – Connected barcode and RFID scanners automatically track parts as they move through the facility, update inventory records.
  • Fleet management – Telematics and GPS tracking provides real-time location and performance data from industrial vehicles like forklifts. Enables route optimization.
  • Connected assembly lines – Machines and robots with sensors and connectivity collaborate more efficiently on production lines.
  • Smart energy management – Utilities metering allows real-time monitoring of energy consumption by different machines to minimize waste.
  • Workflow optimization – Sensors identify production bottlenecks and excess capacity allowing dynamic adjustments for better flow.

5G connectivity – Next generation wireless networks that provide high-speed, low latency data transfer critical for industrial automation and real-time control.

Edge computing – Processing power located near the edge of the network, close to IIoT devices, enabling real-time localized data analysis and response.

  • Real-time quality assurance – Computer vision cameras equipped with edge computing can inspect products as they come off the line and immediately flag any defects without needing to send data to the cloud. This enables rapid corrective action.
  • Dynamic inventory optimization – Edge servers equipped with AI analyze locally collected IoT sensor data to optimize just-in-time inventory levels, storage locations, and predict demand.
  • Predictive maintenance – Vibration, temperature and other sensor data is analyzed locally on edge devices to identify signs of impending equipment failure and trigger proactive maintenance.
  • Augmented reality assistance – Edge computing powers AR headsets with real-time data so workers can access guides, instructions, and expertise exactly when and where they need it.
  • Autonomous material handling – Forklifts, conveyors and AGVs use on-board edge computing for real-time navigation, path planning, and hazard avoidance as they move materials autonomously.
  • Rapid control adjustments – Algorithms at the edge of the network can make instant control tweaks in response to sensor input rather than waiting for the cloud.
  • Distributed coordination – Local edge servers enable machines, robots and logistics to coordinate production schedules, material flow and more.
  • So in essence, intelligent edge computing allows time-sensitive, mission-critical industrial data to be processed at the source of the data for faster response times. This is key for the flexible automation of the future.

Artificial intelligence – Machine learning, deep learning and other AI technologies to add intelligence, automation and analytics.

Digital twin technology – Virtual models of physical assets and processes that mirror real-world counterparts. Used for simulation, testing and optimization.

Augmented reality – AR overlays project digital information and controls onto the physical environment to assist workers.

  • Assembly and production guidance – AR headsets overlay step-by-step instructions and animations to guide workers in complex assembly tasks and optimize workflow.
  • Maintenance and repair – Technicians can visualize holographic overlays with repair procedures, required tools, and diagrams to assist troubleshooting equipment issues efficiently.
  • Inspection – AR allows inspectors to compare parts and products with ideal 3D models to instantly identify defects or deviations.
  • Inventory picking – Warehouse pickers have information like item locations and order details visually overlayed onto the physical environment to improve accuracy and speed.
  • Training – Workers learn skills faster through immersive AR simulations of dangerous environments or expensive equipment before having to perform tasks live.
  • Remote assistance – Experts can digitally annotate and guide workers’ real-world field of view during repairs or inspections, providing virtual over-the-shoulder support.
  • Logistics optimization – AR systems project optimal packing patterns, pallet configurations, and material routes through facilities based on real-time data.
  • Human-robot collaboration – Augmented environments help human workers safely coordinate with robots by visualizing things like robot movement paths.

Cloud computing – On-demand, scalable computing power and data storage/sharing located on external servers.

Cybersecurity – Essential for securing connected systems, data, and communications from cyber threats.

Additive manufacturing – 3D printing technology enables on-demand, flexible and customized production.

Robotics – Collaborative robots aka “cobots”, drones and AGVs (Automated Guided Vehicle) bring intelligent automation, efficiently move goods around facilities 24/7 while eliminating human-driving costs and safety risks.

Renewable energy – Sustainable power sources like solar, wind or hydropower for greener manufacturing.

The integration of these advanced technologies will enable the flexibility, efficiency, automation and sustainability that defines Industry 5.0. But successful implementation requires care around change management, cost, technical complexity and skills development, which definitely require human expertise and leadership to help usher in the next advancements in Industry, for today and beyond.