Issue link: https://resources.mouser.com/i/1512203
Engineering a More Sustainable Future | ADI Mobile Robotics Autonomous mobile robots, automated guided vehicles, and collaborative robots further reduce consumption by increasing the efficiency with which materials and products move around a production facility. ADI's infrared proximity and motion, magnetic positioning, and LIDAR- based time of flight sensors can help optimize material and inventory management by providing processors and algorithms with the most accurate, real-time data on location and movement to guide automated robots/ vehicles. Intelligent AI processing and mapping can help design the most efficient processes for optimizing production cycles and material movement, and battery management provided by a 16-channel battery pack monitor can help optimize overall energy usage by developing processes designed to get the most out of a single charge. Industrial Power Supplies ADI's industrial power supplies reduce potential downtime due to outages or power supply failures. Scaled-up power requirements in complex production settings necessitate higher power density solutions for main power supplies and battery energy storage to ensure continuous operation. Real-time power consumption monitoring can also help design production cycles and schedules that optimize energy usage and reduce resource consumption. ADI's industrial power supply technology ecosystem includes power management tools for developers, isolated power conversion solutions, and isolated single and gate drive chains for switch control and multichannel monitoring. Industrial Wired Connectivity ADI's wired connectivity solutions utilize the most innovative Ethernet and wired serial technologies to provide high- performance, reliable connections that optimize data and power transfer paths. Low latency gigabit Ethernet, M-LVDS (multipoint low voltage differential signaling), and RS-485 technology is optimal for high-speed applications and industrial PC connectivity, and 10BASE-T1L single-pair Ethernet and IO-Link technologies ensure fast, robust connections to sensors and other edge devices. Wired connectivity is often a more reliable option in harsh industrial environments with lots of sources of interference, and reliable connections to sensors and edge devices that collect data are integral to collecting and analyzing that data to help optimize factory processes and unlock new efficiencies. Condition Based Monitoring Knowing what's happening on the factory floor in real-time – from the largest pieces of machinery to the smallest sensors and actuators – might be the most significant factor in advanced, more sustainable industrial practices. Predictive maintenance can all but eliminate prolonged downtime and reduce energy waste and carbon emissions by keeping equipment in optimal working order. ADI's condition-based monitoring solutions implement MEMS sensors to detect fluctuations in temperature, motion, magnetic polarity, etc., to allow facilities to continuously monitor performance and utilize algorithms to synthesize that data and more accurately predict poor equipment performance or failure. The long-term ramifications are longer equipment lifetimes and increased throughput due to process optimization and reduced downtime. Longer equipment lifetimes result in less material waste, and energy optimization reduces overall power consumption. Intelligent Edge Nodes In condition-based monitoring systems, gateway nodes that are efficient and reliable can provide localized information (things like aggregate, filter, check for out-of-bounds conditions, etc.) to improve efficiency and reduce data bottlenecks, thereby reallocating computational power further up the chain. Data transfer efficiency and more effectively allocating computational power can help reduce overall energy consumption and production delays. Intelligent edge and gateway nodes take smaller tasks off the hands of the PC mainframe, allowing the whole system to operate more efficiently. Intelligent edge nodes can also help to meet the changing requirements of modern manufacturing – as more data is collected and analyzed, algorithms evolve. Unplanned aggregation or filtering of data may be tasks intelligent edge nodes can assume, further freeing up valuable processing power for the central processing system. 5 REDUCING ENERGY CONSUMPTION CAN ALSO SIGNIFICANTLY REDUCE GREENHOUSE GAS EMISSIONS, WHICH IS CRUCIAL FOR ORGANIZATIONS SEEKING TO REDUCE THEIR CARBON FOOTPRINT. Adobe Stock / THANANIT – stock.adobe.com