Aviation Predictive Maintenance Market is anticipated to grow at a high CAGR from 2020 to 2030.

Market Industry Reports (MIR) has published a new report titled “Aviation Predictive Maintenance Market – Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2020–2030.” According to the report, the Aviation Predictive Maintenance Market is anticipated to grow at a high CAGR from 2020 to 2030.

Aviation predictive maintenance is anticipated to witness growth due to several factors such as growing industrialization and increasing the utilization of technologically-advanced machines and equipment. The increasing focus on reducing operational costs and surging competition has paved the way for predictive maintenance in the aviation sector across the globe. Aviation predictive maintenance enables aircraft carriers to decide whether any particular asset or component needs maintenance and considerably decrease unplanned machine downtimes.

Every aircraft type has unique operating characteristics and certain components that drive costly and frequent delays. Airlines need to act on and identify pertinent signals that are extremely suggestive of cancellations and potential delays during aircraft messages and maintenance activities. Predictive maintenance ensures that the machines are taken for maintenance to lessen production losses. The predictive maintenance method controls machine learning algorithms that assume critical historical data such as pressure, temperature, and vibration. These factors are used to predict aircraft conditions in real-time.

The aviation industry is looking for opportunities to reduce unplanned maintenance costs. Big data has been finding applications in a wide range of industries that are encouraging to transform the way businesses can make decisions. As new aircraft generate more in-flight data compared to older ones, innovative analysis methods summarized by data infrastructure and big data analytics enable the processing of huge amounts of data in short intervals of time. For instance, in September 2020, the U.S. Air Force engaged with C3.ai Inc., a California-based company that utilizes Artificial Intelligence (AI) for the predictive aircraft maintenance.

Browse key industry insights spread across 180 pages with market data tables & figures & charts from the report, Aviation Predictive Maintenance Market By Component (Engines, Landing Gear & Brakes, Spare Parts & Components, and Airframes), By Application (Aircraft, Ground Equipment, and Engineering Resources), By Type (Data acquisition & Transfer, Big Data infrastructure, and Analytics) – Global Analysis & Forecast 2020-2030. in detail along with the table of contents:https://www.marketindustryreports.com/aviation-predictive-maintenance-market/400

The aviation outlook of several industry players such as EXSYN Aviation Solutions shows that there is a reduction in maintenance budgets by 30% to 40%. Big Data analytics is being utilized by 54% of the aircraft, enhancing the Maintenance Repair and Overhaul (MRO) systems, and approximately 92% plan to utilize their fleet data to enhance predictive MRO and improve health monitoring.

The applications of predictive maintenance help through several benefits such as improvements in operations and reduction in costs. Improvements in operations comprise of forecast inventory and management of resources. Cost reductions include minimizing production hours that are lost in maintenance and reducing the costs of spare parts & supplies. The data analytics segment is projected to show the highest growth potential due to the need for efficient predictive maintenance of aircraft.

Some of the prominent players in the Aviation Predictive Maintenance Market include A J Walter Aviation Limited, AIR FRANCE-KLM Engineering & Maintenance, Evergreen Aviation Technologies (EGAT), General Electric Aviation, Exodus Aviation, Honeywell International Inc., Lufthansa Technik, MTU Aero Engines AG, Rolls-Royce plc, JSSI, Lufthansa Technik, Textron Inc., Turkish Technic Inc., and United Technologies.

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