Telit Cinterion’s Dr. Linir Zamir discusses how Artificial Intelligence is moving closer to the factory floor through edge-based systems that keep data on site and enable faster decision-making.
In January, Samsung Electronics forecast a worsening chip shortage this year, thanks to burgeoning demand for AI data centers. The race to build AI infrastructure has prompted chipmakers to divert manufacturing capacity toward high-bandwidth memory for AI servers, squeezing the supply of conventional memory chips.
To error-proof assembly, engineers wanted to implement a system to guide workers through each fastening step while ensuring complete traceability. The Nexonar real-time location system from Desoutter fit the bill.
The placement of the battery introduces new challenges for engineers, such as packaging, structural reinforcement and crash management. Also, heavy battery packs must be offset with lighter and stronger structural components to improve cornering and suspension load.
The new machine replaces a legacy system that was in operation for more than 40 years, offering at least twice the throughput and close to double the efficiency of the previous equipment.
This dual experimental-numerical approach provides a rare, holistic view of bonded joint performance under ballistic loading, bridging the critical gap between laboratory testing and real-world service demands.
Microfactories are not just smaller replicas of mega-factories. They operate with radically different assumptions. Data is real-time and transient, not batch-processed. Production is modular, not linear. And, decision-making is distributed, not centralized.
By choosing compatible specialty resins and copolymers rather than commodity plastics for laser-transparent and laser-absorbent layers, manufacturers can add value in terms of aesthetics, specific performance attributes, durability and regulatory compliance.