Issue link: https://te.mouser.com/i/1472768
AEROSPACE / WHITE PAPER CONNECTING THE FUTURE OF FLIGHT 13 Integrated Modular Avionics (IMA) for embedded and edge computing VALUE There are two main avionics architectures: 1. Federated architecture for distributed avionics that are packaged as self-contained units, such as LRUs. 2. Integrated modular avionics (IMA) architecture for a partitioned environment where multiple avionics functions varying in criticality are hosted on a shared computing platform. By enabling resource sharing, IMA makes it possible to use fewer computing resources to reduce weight and power requirements. With either approach, electronics must be packaged to provide structural integrity, environmental protection (e.g., thermal, radiation), secure Circuit Card Assembly (CCA) attachment points, thermal relief paths, and structural stability. STANDARDS The evolution of ARINC standards has facilitated the move to IMA architecture. ARINC 600 In the 1970s, the Aeronautics Radio, Inc. (ARINC) 404 standard defined "black box" enclosures and racks within aircraft. The ARINC 600 standard—which defined a Modular Concept Unit (MCU)—is the basic building block module for conventional Integrated Modular Avionics (IMA). An ARINC 600 metal enclosure can hold up to 12 MCUs, allowing a lot of computing power to be placed in a centralized "box." A centralized IMA approach offers: • Reduced size and weight • Easier maintenance with standardized cards that are easily replaceable. However, a big box can be a problem in UAM airframes where electronics must fit in tight enclosures in any orientation and where the center of gravity (COG) of the airframe must be carefully tuned. ARINC 800 ARINC 800 standards respond to the embedded-computing trend using a distributed architecture of loosely coupled boxes with fixed functions. Processors are embedded on miniaturized printed circuit boards (PCBs) that can be deployed locally within the airframe to handle higher data loads. ARINC 800 standards define modules for embedded processors to reduce package weight and size, improve thermal management, and push intelligence closer to the point where control decisions are made. Edge computing is another trend that brings processors equipped with artificial intelligence (AI) software to the data source at the so-called "edge" of the network. With edge-computing architecture, cable weight, connector count, and 4. Architecture Solutions EXPLORE THE PAPER: CHALLENGES ARCHITECTURE SENSORS IMPLEMENTATION OPPORTUNITIES NETWORK