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How AI (Artificial Intelligence) Is Transforming The Aerospace Industry

By Pranav Shah, Mitul Trivedi and Ruchi Tank (eInfochips)

1. Aerospace Artificial Intelligence Market (How is the Aerospace AI marketing shaping up)

1.1. Artificial Intelligence

AI (Artificial Intelligence) is a simulation of the human mind processes by machines, especially computer systems (Reference no:2). Specific applications of AI include specialized systems, natural language processing, speech recognition, and computer vision.

AI (Artificial Intelligence) broadly refers to any human-like behavior displayed by the machine or system. In AI's simplest form, computers are programmed to "mimic" human behavior using comprehensive data from past examples of similar behavior. This can vary from recognizing differences between a cat and a bird to execute complex activities in a factory environment.

AI systems work by consuming copious amounts of labeled training data, analyzing the data for relationships and models, and using these models to make predictions on future states. In this way, a chatbot powered examples of text chats can learn to produce realistic exchanges with people, or an image recognition tool can learn how to identify and describe objects in images by looking at millions of examples.

AI programming has been focused on three cognitive skills: learning, reasoning, and self-correction.

AI is important as it can give businesses insights into their operations that they may not have been aware of in the past. In certain cases, AI can perform tasks better than human beings. Especially in repetitive, meticulous tasks like analyzing large numbers of legal documents to ensure the appropriate fields are filled in properly, AI tools often complete jobs quickly with a few mistakes.

Today, AI makes it possible to improve the customer experience through automation and self-service solutions, optimize employee workflow, and ensure higher air safety with analytical and prescriptive aircraft maintenance. It also allows airlines to make informed decisions about pricing and market position through intelligent use of the information.

Briana Brownell also admits AI's key role in operations optimization. "I see many chances! For instance, optimizing operations including adding, changing, or removing routes, setting flight times, pricing, and product offerings. Achievement is driven by having a deep understanding of various customer segments and where new business opportunities exist," concludes Brownell.

1.2. Aerospace Artificial Intelligence Market

AI studies have been defined as the area of interest of intelligent agents, which refers to any system that recognizes its environment and takes actions that maximizes its chances of achieving its objectives.

AI can be used to help customers at the airport, and it can help a company reduce its operating expenses and employment costs simultaneously.

Image: Reference 1

The global aerospace industry artificial market was valued at $373.6 million in 2020 and is projected to reach $5,826.1 million in 2028, registering a CAGR of 43.4% (Reference no 3).

Artificial Intelligence in flight helps specialists to access historical and real-time data from everywhere. The systems compatible with mobile and desktop give alerts and notifications of the aircraft 's existing technical condition and help technicians to detect issues pointing at the breakdown and replace parts proactively.

The acceptance of AI in the aviation market is expected to increase because AI uses strong algorithms that automates large amounts of data across the airport, and it helps to improve performance and reduce queue length.

Use of AI technologies such as machine learning, natural language processing, computer vision, and environment awareness computing improves efficiency of various activities that fall under the aerospace domain(Reference no 8) such as airline operations, improved customer service, predictive airplane maintenance, and the production of aircraft components.

Artificial Intelligence in the aviation industry comprises an integration of services and systems such as automated luggage check-in, face recognition, customer care, and aviation fuel optimization, among other things.

These functions are also used to reduce employee work intensity and assure an effective and smooth functioning of procedures. Specific aspects of the aviation industry have been automated, allowing for more efficient handling of general systems, and increased customer satisfaction.

The AI in Aviation market is also being led by factors such as a rise in the capital investments made by aviation companies and the growing adoption of cloud-based applications and services in the airline industry.

Additionally, the increasing demand for process improvement serves as a major factor affecting the growth of AI in the aerospace market.

Another key factor that cushions AI in the aerospace market's growth rate is an automatic improvement of performance by machine learning.

2. How AI works in Aerospace (Working of AI in Aerospace)

2.1. Artificial Intelligence in Aviation

The Aerospace industry ( Reference no 9) faces significant challenges such as employment costs, human mistakes, and health and safety issues. Along with these challenges, production and development procedures can get more time-consuming due to industrial inspections, that are needed to evaluate whether a component matches necessary specifications.

The implementation of AI in the aerospace industry (Reference no: 1) development can allow businesses to simplify production of various components and reduce security problems. Also, AI systems can evaluate feedback from multiple assets and process copious amounts of data over a shorter span of time compared with manual inspections.

Use of Artificial Intelligence technologies such as machine learning, natural language processing, computer vision, and context awareness computing improves the efficiency of various activities that fall in the aerospace domain such as airline operations, better customer service, predictive airplane maintenance, and aircraft components manufacturing.

Image: Reference no. 2

The global AI in aviation market size was estimated at US$ 653.74 million in 2021 and it is expected to surpass ~US$ 9,985.86 million by 2030 with a registered CAGR of 35.38% from 2022 to 2030. (Ref no: 4)

Artificial Intelligence in the aviation industry comprises an integration of services and systems such as automatic luggage check-in, face recognition, customer care, and aviation fuel optimization, among other things.

3. Use Cases of AI in the Aerospace Industry

AI has two major purposes:

3.1. Dynamic ticket pricing

If you have any experience booking flight tickets, you may know that sometimes the same flight can have different prices. Based on the departure and arrival time, if it is within rush hour then prices may differ. E.G., If a flight drops you before office hours, then it could be highly priced compared to the middle of the day. Other parameters can also be considered for price difference, like destination, flight distance, and the number of available seats. When your travel start date comes near, the same ticket cost can change and sometimes it is changed within minutes.

How is that possible? This is what airline industry uses for pricing, called dynamic pricing. It is a technique of adjusting prices based on the current situation to the most profitable levels of course, from the airline's standpoint.

Dynamic pricing algorithm is one of the most used AI-based applications which uses intelligent solutions like machine learning and big data analysis.

3.2. Delay predictions

We must mention weather conditions yet another time today. Delays are unfortunately common, and they depend on dozens of varied factors. Over the world, Modern ML-based applications can help airlines and airports to predict flight delays and notify passengers as quickly as possible. This way, customers can have enough time to plan their travel and other arrangements, if necessary, meanwhile the aviation companies can also improve UX (User Experience) of such applications.

3.3. Flights optimization

Partially, we have already discussed this application. Modern ATM (Automated Teller Machines) systems enable airlines and air transportation companies to set optimal flight routes. This can lower the costs of flights, save travel time, and most importantly usage of fuel.

3.4. Crew scheduling

It is nothing more than a typical Workforce Management (WFM) feature. However, there are several elements of crew scheduling which must be taken into consideration:

Legal and contractual requirements

Given employee's qualifications and certifications

Personal preferences

Availability

Airlines must deal with complex networks of employees, and that includes flight attendants, pilots, engineers, and other specialists, making necessary pre-flight preparations.

Intelligent WFM systems help airlines in scheduling crew members for every flight without unnecessary complications or delays. This way, each flight has an ensured number of crew members and can go as scheduled, and potential errors are reduced to a minimum. It is also the best way to use the full potential of every crew member.

3.5. Smart maintenance

Predictive algorithms help airlines to predict flight delays, potential complications, and maintenance procedures from time to time. This type of intelligent solution makes predictive algorithms one of the most effective in the AI industry.

Unlike all other machines and vehicles, aircraft need more appropriate maintenance with more accuracy, so they can remain fully functional and safe. Using AI, we can make a digital twin, which is a virtual representation of an object that spans its lifecycle. This system can be updated from real-time data and uses machine learning to simulation to help decision-making.

Companies working with digital twins can replicate the exact state of the physical object or a system in their applications. It means, companies which are in the plane repair industry, can use this technology for decision-making based on data analysis. It is a terrific way to optimize work, save money, and make sure each plane is always in excellent shape.

3.6. Better Fuel Efficiency

Did you know that the climb phase of a flight consumes the most fuel? To optimize fuel usage during this phase, AI models can analyze the fuel consumption of various aircraft and pilots and develop climb phase profiles tailored to individual pilots.

By using these AI-based profiles, pilots can optimize fuel consumption very effectively during the climb phase.

AI models can analyze how much fuel is consumed in the climb phase for different aircraft to develop climb phase profiles for fuel conservation.

A typical commercial flight uses around 4 liters (0.9 gallons) per second, 240 liters (about 63.4 gallons) per minute, and 14,400 liters (about half the volume of large U-Haul truck) per hour of fuel) (Ref no: 6). We can reduce fuel usage by 5 to 7%, with the help of AI technology.

Using AI-powered technologies, we may reduce fuel usage. For example, a machine learning program can improve take-off and landing activities for pilots before each trip. Climbing consumes gasoline the most, and by improving this, we can save a lot of money.

3.7. Training

AI coupled with virtual reality can be used to develop stimulated training programs for pilots.

AI-enabled simulators can generate a realistic simulation of the flying experience. AI can also collect and analyze training data which shows every pilot's strength and weakness to create a detailed report which can be presented to their trainer.

The collected data can also be used to develop personalized training programs for each pilot.

These personalized training programs can improve pilot's individual challenges. This way personalized training programs work more effectively compared to conventional training programs.

3.8. Improved Customer Experience

Customer happiness and service quality are important in commercial aviation. AI is one of the techniques which industry can use to provide outstanding customer service and boost consumer engagement.

Chatbots are AI-powered automated systems that can answer customer questions in a human-like manner and real-time basis. These online chatbots improve the user experience. By automating customer care, it can save time and effort for companies. There are several different ways to do such things, such as:

Suggesting products to customers for purchase with accurate and personalized options.

Chatbots powered with AI provide quick and polite assistance.

24x7 automatic assistance available.

3.9. Passenger Identification

Smart cameras with AI capabilities can recognize suspicious individuals at airports using facial recognition.

Smart cameras with AI capabilities can utilize facial recognition to recognize suspicious passengers at airports. AI systems can be trained for this purpose using pictures of individuals with criminal histories. Similarly, malicious activity in an airport can also be found using AI-powered smart cameras.

3.10. Recommendation Engine

The airport's recommendation engines also use Artificial Intelligence. Recommendation engines are prominent in well-known online businesses like Netflix and Amazon, and you can also find them in a variety of travel booking websites.

The AI platform examines the passenger's earlier data like past reservations, behavior-tracking techniques, metadata, purchase history, and real-time data to highly personalize offers for passengers, increasing retention and a customer's lifetime value.

3.11. Chatbots/Bots

Chatbots can provide flight information, guide passengers with certain services or outlets, and more, freeing up humans to focus on more worthwhile tasks and minimizing human contact.

Chatbots and customer service automation are human-like, understand simple questions and respond in a casual, conversational style. Airports may offer 24/7 customer support and lessen human interaction by using chatbots.

In 2018, chatbot name Juliet was released by Canadian airline WestJet. Juliet was able to handle passengers' questions including managing itineraries and mobile check-in. It also has a luggage calculator that informs passengers whether their items can be checked-in or need to be carried out.

By integrating Chatbots into the aerospace sector, the following procedures can be carried out in a more efficient way with less human effort.

Make reservations

Booking management

Update management

Baggage tracking and claims

Staff scheduling

3.12. Baggage Screening

The luggage of the passenger is screened more efficiently, using Artificial Intelligence - robotic assisted convenience system which quickly troubleshoots and diverts high-risk baggage for deeper inspection.

Today's AI-powered facial recognition solutions for live video give insights into how individuals are moving through space and enable much faster access.

3.13. AI Thermal cameras/AI-based video analytics

Facial recognition technology and a fever detector AI thermal camera can be used to detect passengers having fever.

AI-based video analysis analyzes video feeds collected from cameras, using algorithms and computer vision technology to help identify the patterns and trends. Real-time analysis provides actionable intelligence such as crowd gathering, people's emotions and behaviors, general temperature mapping, and so on.

3.14. Predictive aircraft maintenance

Artificial Intelligence in aviation enables technicians to access historical and real-time data from any location. The systems are mobile and desktop compatible, and they provide alerts and notifications of the aircraft's current technical status. They also enable technicians to identify problems that may indicate a malfunction and replace parts before they become a severe problem.

3.15. Factory Automation

The automotive industry already has highly invested in factory automation to get a continuous supply of products. However, the same is not possible in the aviation industry due to less volume of investment. By introducing factory automation, it can channelize supply chain and monitor manufacturing. AI-enabled machines/robots can perform multiple tasks at a time to manage supply chain. Smart AI can improve by self-learning.

4. Future of AI in Aerospace Industry

Artificial Intelligence is now being used in different industries throughout the world. Airlines are continuing experimenting with how AI can make flights faster, safer, and easier to use.

AI in aviation has only been applied on the ground, where machine learning is used to identify trends and anomalies in massive amounts of data collected from aircraft.

However, the technology's use is rapidly expanding in all fields, from voice recognition for computerized air traffic management to techniques for conducting war tactics, to machine learning for autonomous detect-and-avoid technologies and understanding airport signage during unmanned taxiing.

4.1. Air Traffic Management

One of the most significant responsibilities of the airport and the airline is air traffic control. Air traffic control might become incredibly difficult if billions of people decide to travel by plane. As a result, applying AI to air traffic control may be an innovative idea.

AI-based assistants can suggest alternative routes to pilots based on weather data from sensors and flight data.

Using such data, AI-based assistants can suggest alternate routes to pilots to make air travel safer and quicker.

AI and smart cameras may also be used to recognize airplanes as they leave the runway and alert flight attendants. This knowledge helps air traffic controllers clear the landing runway for the upcoming aircraft.

This technique can be quite helpful in conditions with poor vision, like fog. AI in the aircraft industry can help control air traffic and lessen congestion at airports in this way.

4.2. Autonomous Flight Operations

Flight operation is a process starting from takeoff to landing and passengers from boarding to departure. So, there are many activities included in such a lengthy process. It also means a specific operation of a particular flight during a particular period. E.G., some flight BA2490 operates twice in a week, then, it has eight operations in a month. By extending innovative machine learning and analyzing data, it can identify the occupancy of passengers and manage the flight days, based on the past data.

5. Conclusion

AI is used to assist customers at the airport which is helping the companies reduce their operational and labor costs. Also, by using AI technologies, airline companies can resolve the issues of their passengers using chatbots by providing them with correct information. Artificial Intelligence in aviation enables technicians to access historical and real-time data from any location. Alerts and notifications with aircraft's current technical status are provided by using mobile and web applications which would help technicians in identifying malfunctioning and can replace malfunctioning parts before they occur. It is expected that AI in the aviation market is increasing because of the algorithms which automate large amounts of data, resulting in increasing productivity and decreasing queue length.

6. Reference

How Artificial Intelligence is transforming the Aerospace Industry (einfochips.Com)

https://www.Techtarget.Com/searchenterpriseai/definition/AI-Artificial-Intelligence

https://www.Alliedmarketresearch.Com/aerospace-artificial-intelligence-market-A11337

Artificial Intelligence in Aviation Market Report 2022-2030 (precedenceresearch.Com)

https://www.Analyticssteps.Com/blogs/8-applications-ai-aerospace-industry

The fastest way aviation could cut its carbon emissions - BBC Future

Artificial Intelligence in Aviation Market Size, Share, Industry Growth, Demand & Forecast 2029 (databridgemarketresearch.Com)

https://www.Einfochips.Com/domains/aerospace/

https://www.Einfochips.Com/blog/technology-trends-insights-to-watch-for-in-aerospace-industry/

Image References

https://www.Alliedmarketresearch.Com/aerospace-artificial-intelligence-market-A11337

https://www.Precedenceresearch.Com/artificial-intelligence-in-aviation-market

Authors –

Pranav Shah - Pranav Shah is a technology leader specializing in digital technologies such as audio-video, cloud, AR-VR, automation, IoT, and AI. With over a decade of experience at eInfochips and 14+ years in designing and developing software products, Pranav focuses on creating solutions in virtual reality, artificial intelligence, and data science to enhance the overall customer experience.

Mitul Trivedi - Mitul Trivedi is working at eInfochips as a Senior Engineer, with over 12+ years of experience in various platforms such as mobile applications, frontend, backend, and DevOps. With a focus on audio-video applications for over 4 years, Mitul provides solutions to real-time challenges. Currently, he is working on proof-of-concept applications to incorporate the latest technologies like Artificial Intelligence.

Ruchi Tank – She is a Senior Engineer with four years of experience who specializes in offering Cabin Management System solutions.Her experience primarily involves creating mobile applications for private aircraft in the avionics industry.

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Artificial Intelligence And Robotics In Aerospace And Defense Market Scope By Trend Forecast 2031

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Which Manufacturer holds the Top position in the Artificial Intelligence and Robotics in Aerospace and Defense Market Report?

Iris Automation Inc.

The Boeing Company

Nvidia Corporation

Thales SA

Airbus SE

IBM

SITA

Lockheed Martin Corporation

General Electric

Intel Corporation

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In this report analysis, we thoroughly examine the Artificial Intelligence and Robotics in Aerospace and Defense Market by exploring it into different segments, including size, share, and end-users etc. Furthermore, we present forecasts covering the period from 2023 to 2031. Additionally, we provide insights into the current status of the Compound Annual Growth Rate (CAGR) for the upcoming period, and we shine a spotlight on the top players in the industry. Ask for A Sample Report

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What are the various Type present in the Artificial Intelligence and Robotics in Aerospace and Defense Market?

Hardware

Software

Service

What are the different Applications found in the Artificial Intelligence and Robotics in Aerospace and Defense Market?

Military

Commercial Aviation

Space

Key Points of Artificial Intelligence and Robotics in Aerospace and Defense Market Report are: -

Market Size Estimates:

Artificial Intelligence and Robotics in Aerospace and Defense market size estimation in terms of value and sales volume from 2018-2028

Market Trends and Dynamics:

Artificial Intelligence and Robotics in Aerospace and Defense market drivers, opportunities, challenges, and risks

Macro-economy and Regional Conflict:

Influence of global inflation and Russia and Ukraine War on the Artificial Intelligence and Robotics in Aerospace and Defense market

Segment Market Analysis:

Artificial Intelligence and Robotics in Aerospace and Defense market value and sales volume by type and by application from 2018-2028

Regional Market Analysis:

Artificial Intelligence and Robotics in Aerospace and Defense market situations and prospects in North America, Asia Pacific, Europe, Latin America, Middle East, Africa

Country-level Studies on the Artificial Intelligence and Robotics in Aerospace and Defense Market

: Revenue and sales volume of major countries in each region

Artificial Intelligence and Robotics in Aerospace and Defense Market Competitive Landscape and Major Players:

Analysis of 10-15 leading market players, sales, price, revenue, gross, gross margin, product profile and application, etc.

Trade Flow:

Import and export volume of the Artificial Intelligence and Robotics in Aerospace and Defense market in major regions.

Artificial Intelligence and Robotics in Aerospace and Defense Industry Value Chain:

Artificial Intelligence and Robotics in Aerospace and Defense market raw materials and suppliers, manufacturing process, distributors, downstream customers

Artificial Intelligence and Robotics in Aerospace and Defense Industry

News, Policies and Regulations

To Understand How COVID-19 Impact is Covered in This Report.

Which Regions are focusing in the Artificial Intelligence and Robotics in Aerospace and Defense Market?

North America (United States, Canada)

Europe (Germany, UK, France, Italy, Spain, Russia, Netherlands, Turkey, Switzerland, Sweden)

Asia Pacific (China, Japan, South Korea, Australia, India, Indonesia, Philippines, Malaysia)

Latin America (Brazil, Mexico, Argentina)

Middle East and Africa (Saudi Arabia, UAE, Egypt, South Africa)

Outline of Chapters for the Artificial Intelligence and Robotics in Aerospace and Defense Market Report: -

-Chapter 1: of the Artificial Intelligence and Robotics in Aerospace and Defense Market report begins with a concise introduction to the research scope, providing definitions of the target market and its subdivisions.

-Chapter 2: effectively summarizes the research findings and conclusions in a clear and straightforward manner.

-Chapter 3: offers insight into the competitive landscape by presenting sales, revenue, and market shares of the top players. It also provides profiles of major market participants, including their business introductions, sales, pricing, revenue, gross profit, growth rates, and more.

-Chapter 4: dissects the market by various product types, sharing corresponding data to help readers understand the market's distribution by type.

-Chapter 5: segments the Artificial Intelligence and Robotics in Aerospace and Defense Market based on its downstream industries, with data covering sales, revenue, and growth rates dating back to 2018.

-Chapter 6: conducts a comprehensive analysis of the entire market industrial chain, from upstream raw materials to downstream customers, while considering regional variations.

-Chapter 7: delves into market dynamics, listing factors that drive, challenge, or hinder the market. It also includes industry news, opportunities, the impact of COVID-19, and a SWOT analysis.

-Chapter 8: presents data breakdown at the regional level, allowing readers to visualize the regional competitive landscape and learn about revenue, sales, and market share in all major regions.

-Chapters 9 to 13: focus on each major region individually, namely, North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa. These chapters provide detailed information on sales, pricing, revenue, gross profit, gross margin, and other relevant aspects.

-Chapter 14: forecasts the future trends of the Artificial Intelligence and Robotics in Aerospace and Defense Market, offering insights not only for the market as a whole but also from the perspective of each segment.

Here are some of the key questions addressed in this report: -

What is the regional and country level market size for Artificial Intelligence and Robotics in Aerospace and Defense?

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Who are the prominent global manufacturers in the Artificial Intelligence and Robotics in Aerospace and Defense Market?

What opportunities and challenges do vendors in the Artificial Intelligence and Robotics in Aerospace and Defense Market encounter?

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Detailed TOC of the Artificial Intelligence and Robotics in Aerospace and Defense market:

1 Artificial Intelligence and Robotics in Aerospace and Defense Market Definition and Overview 1.1 Objectives of the Study 1.2 Overview of Artificial Intelligence and Robotics in Aerospace and Defense 1.3 Artificial Intelligence and Robotics in Aerospace and Defense Market Scope and Market Size Estimation 1.4 Market Segmentation 1.4.1 Types of Artificial Intelligence and Robotics in Aerospace and Defense 1.4.2 Applications of Artificial Intelligence and Robotics in Aerospace and Defense 1.5 Market Exchange Rate

2 Research Method and Logic 2.1 Methodology 2.2 Research Data Source

3 Market Competition Analysis 3.1 Iris Automation Inc. Market Performance Analysis 3.1.1 Iris Automation Inc. Basic Information 3.1.2 Product and Service Analysis 3.1.3 Strategies for Company to Deal with the Impact of COVID-19 3.1.4 Iris Automation Inc. Sales, Value, Price, Gross Margin 2016-2021 3.2 The Boeing Company Market Performance Analysis 3.2.1 The Boeing Company Basic Information 3.2.2 Product and Service Analysis 3.2.3 Strategies for Company to Deal with the Impact of COVID-19 3.2.4 The Boeing Company Sales, Value, Price, Gross Margin 2016-2021 3.3 Nvidia Corporation Market Performance Analysis 3.3.1 Nvidia Corporation Basic Information 3.3.2 Product and Service Analysis 3.3.3 Strategies for Company to Deal with the Impact of COVID-19 3.3.4 Nvidia Corporation Sales, Value, Price, Gross Margin 2016-2021 3.4 Thales SA Market Performance Analysis 3.4.1 Thales SA Basic Information 3.4.2 Product and Service Analysis 3.4.3 Strategies for Company to Deal with the Impact of COVID-19 3.4.4 Thales SA Sales, Value, Price, Gross Margin 2016-2021 3.5 Airbus SE Market Performance Analysis 3.5.1 Airbus SE Basic Information 3.5.2 Product and Service Analysis 3.5.3 Strategies for Company to Deal with the Impact of COVID-19 3.5.4 Airbus SE Sales, Value, Price, Gross Margin 2016-2021 3.6 IBM Market Performance Analysis 3.6.1 IBM Basic Information 3.6.2 Product and Service Analysis 3.6.3 Strategies for Company to Deal with the Impact of COVID-19 3.6.4 IBM Sales, Value, Price, Gross Margin 2016-2021 3.7 SITA Market Performance Analysis 3.7.1 SITA Basic Information 3.7.2 Product and Service Analysis 3.7.3 Strategies for Company to Deal with the Impact of COVID-19 3.7.4 SITA Sales, Value, Price, Gross Margin 2016-2021 3.8 Lockheed Martin Corporation Market Performance Analysis 3.8.1 Lockheed Martin Corporation Basic Information 3.8.2 Product and Service Analysis 3.8.3 Strategies for Company to Deal with the Impact of COVID-19 3.8.4 Lockheed Martin Corporation Sales, Value, Price, Gross Margin 2016-2021 3.9 General Electric Market Performance Analysis 3.9.1 General Electric Basic Information 3.9.2 Product and Service Analysis 3.9.3 Strategies for Company to Deal with the Impact of COVID-19 3.9.4 General Electric Sales, Value, Price, Gross Margin 2016-2021 3.10 Intel Corporation Market Performance Analysis 3.10.1 Intel Corporation Basic Information 3.10.2 Product and Service Analysis 3.10.3 Strategies for Company to Deal with the Impact of COVID-19 3.10.4 Intel Corporation Sales, Value, Price, Gross Margin 2016-2021

4 Market Segment by Type, Historical Data and Market Forecasts 4.1 Global Artificial Intelligence and Robotics in Aerospace and Defense Production and Value by Type 4.1.1 Global Artificial Intelligence and Robotics in Aerospace and Defense Production by Type 2016-2021 4.1.2 Global Artificial Intelligence and Robotics in Aerospace and Defense Market Value by Type 2016-2021 4.2 Global Artificial Intelligence and Robotics in Aerospace and Defense Market Production, Value and Growth Rate by Type 2016-2021 4.2.1 Hardware Market Production, Value and Growth Rate 4.2.2 Software Market Production, Value and Growth Rate 4.2.3 Service Market Production, Value and Growth Rate 4.3 Global Artificial Intelligence and Robotics in Aerospace and Defense Production and Value Forecast by Type 4.3.1 Global Artificial Intelligence and Robotics in Aerospace and Defense Production Forecast by Type 2021-2026 4.3.2 Global Artificial Intelligence and Robotics in Aerospace and Defense Market Value Forecast by Type 2021-2026 4.4 Global Artificial Intelligence and Robotics in Aerospace and Defense Market Production, Value and Growth Rate by Type Forecast 2021-2026 4.4.1 Hardware Market Production, Value and Growth Rate Forecast 4.4.2 Software Market Production, Value and Growth Rate Forecast 4.4.3 Service Market Production, Value and Growth Rate Forecast

Continued....

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