Time sensitive networking Market Overview
Time Sensitive Networking Market is expected to grow at a CAGR of 36.66% from 2023 to 2030, from an estimated USD 170 Million in 2023 reaching USD 1513.2 Million by 2030. The TSN market is being driven by the growing use of industrial automation within manufacturing industries, the increasing need for deterministic Ethernet for real-time applications, and demanding multiple controller applications.
TSN (Time-Sensitive Networking) is a type of IEEE Ethernet upgrade that accommodates the requirements of control systems that use regular Ethernet. Standard time synchronization plus deterministic network connection using standard Ethernet are two features of the technology. It improves interoperability and reduces costs by combining time-critical plus best information within a regular Ethernet network.
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One of the primary factors responsible for the growth of the time-sensitive networking industry is the use of industrial automation throughout manufacturing sectors around the world.
Time sensitive networking Market Segmentation
The global market for time-sensitive networking has been divided into four categories: standards, applications, components, and regions.
The global time-sensitive networking market is segmented into IEEE 802.1AS, IEEE 802.1AS-Rev, IEEE 802.1Qch, IEEE 802.1 Qca, IEEE 802.1Qbv, IEEE 802.1 CB, IEEE 802.1 Qci, IEEE 802.1 Qcc, and IEEE 802.1 CM based on kinds of standards.
Switches, routers, hubs, gateways, controllers and processors, connectors, isolators and convertors, communication interfaces, memory, power supply devices, and others make up the global time-sensitive networking market.
The global time-sensitive networking market has been segmented into industrial automation, automotive, power and energy, transportation, aerospace, oil gas, and others based on application.
Regional Classification
Over the projected period, the worldwide time-sensitive networking market is expected to grow at a healthy rate. For the Middle East and Africa, North America, Asia-Pacific, Europe, and South America, a geographic evaluation of the worldwide time-sensitive networking industry was undertaken.
In terms of the use of time-sensitive networking solutions, North America is likely to be the leading market. The advent of Industry 4.0 in North America has propelled the time-sensitive networking market to the top of the total revenue share for 2019. Government measures that encourage higher penetration and industrial automation are likely to have a direct impact on business.
Over the projection period, the Asia-Pacific time-sensitive networking market is projected to expand at the fastest rate, with the local market divided into Japan, China, India, as well as the rest of Asia-Pacific. The rapid economic expansion and growing awareness of time-sensitive networking in key countries such as Japan, China, and India are credited with this increase.
Industry News
Traditional fieldbuses are not meant to allow many controllers to interact in a deterministic fashion; thus, they must resort to fieldbuses or reflective memory, both of which are technically challenging and costly. TSN-enabled Ethernet, on the other hand, is more versatile and facilitates controller-to-controller interaction. As part of the proposed standard industrial interoperability connectivity, OPC UA (unified architecture) is growing to include Ethernet TSN, Ethernet advanced physical layer (APL), plus controller-to-controller communications.
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The need for automation controllers which can process many workloads simultaneously, such as video streams and traffic control, is growing by the day. This allows for the implementation of deep learning capabilities in a single machine that can connect with other controllers in the factory's network in real-time. With industrial applications like robotic arms as well as motion controllers, developers encounter both time sync and timetable issues. As a result, they use TSN in conjunction with Intel's real-time characteristics to synchronize networks of devices to improve the timely behavior of industrial systems.
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