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Explore cutting-edge robotic solutions designed to optimize your packaging operations, enhance efficiency, and boost productivity. From palletizing to picking and packing, Yaskawa (Booth #N-5736) collaborative and industrial robots deliver precision and flexibility for any job.
Global challenges and industrial competitiveness are having an impact on the training and continuous education of skilled workers and students. In addition to theoretical principles, practical knowledge is also in demand, particularly with regard to digitized and networked manufacturing processes. Virtual learning factories based on 3D simulation platforms offer interesting possibilities when it comes to Industry 4.0: The Mechatronic Simulation Wall developed by MHJ Software GmbH & Co. KG is a mirror image of real mechatronic systems and can include up to four different stations, e.g. magazine, processing, quality assurance and sorting. This type of configuration makes it possible to program each station individually, or run the entire system, which opens up a wide range of learning scenarios with varying degrees of complexity.
With the launch of its Inspector83x 2D vision sensor, SICK has enabled out-of-the-box Artificial Intelligence machine vision inspections for common inline inspection tasks in demanding high-speed production.
UGRacing is the University of Glasgow’s Formula Student team. Since its inception in 2005, the team has been working to compete at Formula Student UK (FSUK). Over the last decade, the team has grown to over 150 members across ten disciplines. With a strong focus on knowledge transfer and iterative design, the team has worked year after year to develop new technologies and a more refined package. In 2022, the team saw a culmination of all their hard work when they placed first overall in FSUK with their final internal combustion vehicle. The following switch to an electric powertrain brought new challenges. Through the constraint of a new powertrain architecture, the team has explored and innovated drivetrain concepts which, in future years, will improve vehicle performance.
Siemens’ annual event Realize LIVE Americas never fails to disappoint on the technology front. Automation, AI, IIoT, the Industrial Metaverse, additive manufacturing—you name the technology—Siemens has it covered. The factory of the future is no different. The company spends a great deal of time discussing smart manufacturing, analytics and services examining what a typical shop floor might look like in 15–20 years.
Digital Transformation. IIoT. Industry 4.0. While they may seem like trending buzzwords, the technologies are critical to operations being efficient and competitive, and reducing unplanned downtime. Every industry strives for maximum efficiency; be that manufacturing, oil & gas, or water/wastewater. For capturing production data, the days of the clipboard and manual data analysis are gone.
Trucks automatically driving behind one another on the highway, 'platooning', or cars automatically changing lanes: Here vehicle movements have to be calculated and executed precisely and quickly without a human driver. Software and AI algorithms safely control the drive, brakes, front and rear wheel steering and damping systems. The more efficient the AI algorithms are, the better the available computing power can be used.