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Global Computer-aided Engineering Market to reach USD 12.33 billion by the end of 2029

Global Computer-aided Engineering Market Size study & Forecast, by Deployment (Cloud, On-premise), by Type (Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Thermal Analysis, Multibody Dynamics, Others), by End-user (Automotive, Medical Devices, Industrial Equipment, Defense & Aerospace, Electronics, Others) and Regional Analysis, 2022-2029

Product Code: ICTNGT-87182904
Publish Date: 10-04-2023
Page: 200

Global Computer-aided Engineering Market is valued at approximately USD 5.75 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 10.0% over the forecast period 2022-2029. Computer-aided engineering is the method of simulating performance by adopting software in order to enhance product designs or aids in solving engineering complications across various sectors. This encompasses testing, modelling, and process improvement for manufacturing goods, equipment, and techniques. In addition, various businesses are installing private cloud through the hyper-converged infrastructure (HCI) platform, which presents new storage and computing services, in turn, is projected to bolsters the market expansion. The rise in proliferation of IoT and 3D printing, increased outsourcing of manufacturing processes to emerging economies, coupled with the rising inclination towards cloud-based computing are the key factors that are stipulating the market demand across the globe.

The increase in the sales and production of energy-efficient aircraft and commercial aviation is further fueling the demand for computer-aided engineering in the global market. The Deloitte report 2020 stated that China produced over 1,900 commercial aircraft in 2020, which is an increase of 1,450 aircraft over 2019. Additionally, according to the Federal Aviation Administration aerospace, it is estimated that there are about 34,000 civil aircraft in operation worldwide by the year 2036. In addition, electrical battery-powered airplane engines and low-emission aircraft with wing-mounted solar panels are being designed using computer-aided engineering techniques. This program has produced the most advanced passenger aircraft as well as the most ecologically friendly next-generation aircraft designs. Consequentially, the high usage of CAE in designing aircraft and commercial aviation is expected to propel the demand for these solutions during the forecast period. Moreover, the rising investment in the development of digital technologies, as well as the increasing proliferation of digital twins for processes and objects are presenting various lucrative opportunities over the forecasting years. However, the lack of technical expertise and high installation costs are hampering the market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Computer-aided Engineering Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. Europe dominated the market in terms of revenue, owing to the growing automation in the manufacturing sector and the increasing developers of virtual vehicles and high presence of connected car providers. Whereas, the Asia Pacific is also expected to grow with the highest CAGR during the forecast period, owing to factors such as rising concerns about greenhouse gas emissions, increasing government spending on manufacturing industry development, as well as growing automation of industrial equipment in the market space.

Major market players included in this report are:
ESI Group
Siemens AG
Hexagon AB
Aveva Group
SimScale
ANSYS, Inc.
Altair Engineering Inc.
Autodesk, Inc.
Bentley Systems, Inc.
Dassault Systemes

Recent Developments in the Market:
 In May 2022, Siemens announced that the company launched its new Simcenter Femap- an enhanced simulation application for creating, editing, and reviewing finite element models of complex systems or products.
 In July 2021, Dassault Systèmes declared the introduction of DELMIAworks for manufacturing firms, which is specially designed to deliver real-time control and visibility over the complete manufacturing supply chain. It is a collaborative environment of the Manufacturing Execution System (MES) and Enterprise Resource Planning (ERP) suite of applications supporting manufacturers to report on end-to-end manufacturing processes.

Global Computer-aided Engineering Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Deployment, Type, End-user, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Deployment:
Cloud
On-premise

By Type:
Finite Element Analysis (FEA)
Computational Fluid Dynamics (CFD)
Thermal Analysis
Multibody Dynamics
Others

By End-user:
Automotive
Medical Devices
Industrial Equipment
Defense & Aerospace
Electronics
Others

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
RoLA
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Billion)
1.2.1. Computer-aided Engineering Market, by Region, 2019-2029 (USD Billion)
1.2.2. Computer-aided Engineering Market, by Deployment, 2019-2029 (USD Billion)
1.2.3. Computer-aided Engineering Market, by Type, 2019-2029 (USD Billion)
1.2.4. Computer-aided Engineering Market, by End-user, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Computer-aided Engineering Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Computer-aided Engineering Market Dynamics
3.1. Computer-aided Engineering Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Increasing sales and production of energy-efficient aircraft and commercial aviation
3.1.1.2. Rise in proliferation of IoT and 3D printing
3.1.2. Market Challenges
3.1.2.1. Lack of technical expertise
3.1.2.2. High installation costs
3.1.3. Market Opportunities
3.1.3.1. Rising investment in the development of digital technologies
3.1.3.2. Increasing proliferation of digital twins for processes and objects
Chapter 4. Global Computer-aided Engineering Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. Industry Experts Prospective
4.7. Analyst Recommendation & Conclusion
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Computer-aided Engineering Market, by Deployment
6.1. Market Snapshot
6.2. Global Computer-aided Engineering Market by Deployment, Performance – Potential Analysis
6.3. Global Computer-aided Engineering Market Estimates & Forecasts by Deployment 2019-2029 (USD Billion)
6.4. Computer-aided Engineering Market, Sub Segment Analysis
6.4.1. Cloud
6.4.2. On-premise
Chapter 7. Global Computer-aided Engineering Market, by Type
7.1. Market Snapshot
7.2. Global Computer-aided Engineering Market by Type, Performance – Potential Analysis
7.3. Global Computer-aided Engineering Market Estimates & Forecasts by Type 2019-2029 (USD Billion)
7.4. Computer-aided Engineering Market, Sub Segment Analysis
7.4.1. Finite Element Analysis (FEA)
7.4.2. Computational Fluid Dynamics (CFD)
7.4.3. Thermal Analysis
7.4.4. Multibody Dynamics
7.4.5. Others
Chapter 8. Global Computer-aided Engineering Market, by End-user
8.1. Market Snapshot
8.2. Global Computer-aided Engineering Market by End-user, Performance – Potential Analysis
8.3. Global Computer-aided Engineering Market Estimates & Forecasts by End-user 2019-2029 (USD Billion)
8.4. Computer-aided Engineering Market, Sub Segment Analysis
8.4.1. Automotive
8.4.2. Medical Devices
8.4.3. Industrial Equipment
8.4.4. Defense & Aerospace
8.4.5. Electronics
8.4.6. Others
Chapter 9. Global Computer-aided Engineering Market, Regional Analysis
9.1. Computer-aided Engineering Market, Regional Market Snapshot
9.2. North America Computer-aided Engineering Market
9.2.1. U.S. Computer-aided Engineering Market
9.2.1.1. Deployment breakdown estimates & forecasts, 2019-2029
9.2.1.2. Type breakdown estimates & forecasts, 2019-2029
9.2.1.3. End-user breakdown estimates & forecasts, 2019-2029
9.2.2. Canada Computer-aided Engineering Market
9.3. Europe Computer-aided Engineering Market Snapshot
9.3.1. U.K. Computer-aided Engineering Market
9.3.2. Germany Computer-aided Engineering Market
9.3.3. France Computer-aided Engineering Market
9.3.4. Spain Computer-aided Engineering Market
9.3.5. Italy Computer-aided Engineering Market
9.3.6. Rest of Europe Computer-aided Engineering Market
9.4. Asia-Pacific Computer-aided Engineering Market Snapshot
9.4.1. China Computer-aided Engineering Market
9.4.2. India Computer-aided Engineering Market
9.4.3. Japan Computer-aided Engineering Market
9.4.4. Australia Computer-aided Engineering Market
9.4.5. South Korea Computer-aided Engineering Market
9.4.6. Rest of Asia Pacific Computer-aided Engineering Market
9.5. Latin America Computer-aided Engineering Market Snapshot
9.5.1. Brazil Computer-aided Engineering Market
9.5.2. Mexico Computer-aided Engineering Market
9.5.3. Rest of Latin America Computer-aided Engineering Market
9.6. Rest of The World Computer-aided Engineering Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. ESI Group
10.2.1.1. Key Information
10.2.1.2. Overview
10.2.1.3. Financial (Subject to Data Availability)
10.2.1.4. Product Summary
10.2.1.5. Recent Developments
10.2.2. Siemens AG
10.2.3. Hexagon AB
10.2.4. Aveva Group
10.2.5. SimScale
10.2.6. ANSYS, Inc.
10.2.7. Altair Engineering Inc.
10.2.8. Autodesk, Inc.
10.2.9. Bentley Systems, Inc.
10.2.10. Dassault Systemes
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

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Data Collection:
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To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
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