In 2024, the transportation logistics sector is evolving to sustain the pressure of meeting various sustainability targets owing to a global shift in environmental...
The shift from reactive inspections to proactive intervention is redefining the standard of excellence in the production of vehicles and infrastructure. By leveraging advanced analytics and real-time sensor data, predictive quality control in transport manufacturing allows for the identification of potential defects before they manifest as physical flaws. This data-driven methodology ensures that every component, from aerospace turbines to high-speed rail bogies, meets the highest safety and performance criteria with minimal waste.
The rapid digitization of global infrastructure has necessitated a shift from centralized cloud processing to localized intelligence. By processing data at the source, edge computing in transport real time systems minimizes latency, enhances safety for autonomous vehicles, and optimizes urban traffic flow. This decentralized approach ensures that mission-critical decisions are made in milliseconds, providing the foundational architecture for the next generation of smart, connected mobility.
Modern logistics is undergoing a radical shift as additive manufacturing allows the transport industry to move from physical warehouses to digital inventories. By producing critical components on-demand, companies can significantly reduce the weight of parts, eliminate long-lead times for obsolete equipment, and maintain fleet availability with unprecedented precision. This evolution effectively bridges the gap between traditional manufacturing and the fast-paced requirements of contemporary global supply chains.
Trenitalia has initiated a 2 billion EUR programme that is focused on the expansion of high-speed rail and broader fleet renewal, as Gianpiero Strisciuglio, the chief executive, has confirmed plans to bring about another 74 Frecciarossa 1000 fleet of trains by 2030.
This...
The shift from reactive inspections to proactive intervention is redefining the standard of excellence in the production of vehicles and infrastructure. By leveraging advanced analytics and real-time sensor data, predictive quality control in transport manufacturing allows for the identification of potential defects before they manifest as physical flaws. This data-driven methodology ensures that every component, from aerospace turbines to high-speed rail bogies, meets the highest safety and performance criteria with minimal waste.
The rapid digitization of global infrastructure has necessitated a shift from centralized cloud processing to localized intelligence. By processing data at the source, edge computing in transport real time systems minimizes latency, enhances safety for autonomous vehicles, and optimizes urban traffic flow. This decentralized approach ensures that mission-critical decisions are made in milliseconds, providing the foundational architecture for the next generation of smart, connected mobility.
Modern logistics is undergoing a radical shift as additive manufacturing allows the transport industry to move from physical warehouses to digital inventories. By producing critical components on-demand, companies can significantly reduce the weight of parts, eliminate long-lead times for obsolete equipment, and maintain fleet availability with unprecedented precision. This evolution effectively bridges the gap between traditional manufacturing and the fast-paced requirements of contemporary global supply chains.
Last year, together with DRONEII, we conducted a Drone Barometer Survey to produce a free whitepaper with perspectives from the drone industry. The paper...
From Michelin Challenge Bibendum to Movin’On: a new leg in our collective journey towards sustainable mobility.
For almost 20 years, the Michelin Challenge Bibendum was...
