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Global PLM in Discrete Manufacturing Market to reach USD 36.05 billion by the end of 2029

Global PLM in Discrete Manufacturing Market Size study & Forecast, by Component (Software and Service), by Deployment Model (On-Premises and Cloud), by Enterprise Size (Large Enterprises and Small & Medium Enterprises), by End-Use Industries (Automotive & Transportation, Industrial Machinery & Heavy Equipment, High-Tech & Consumer Electronics, Aerospace & Defense and Others) and Regional Analysis, 2022-2029

Product Code: ICTICTI-89250198
Publish Date: 8-02-2023
Page: 200

Global PLM in Discrete Manufacturing Market is valued at approximately USD 21.30 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 6.8% over the forecast period 2022-2029. Discrete Manufacturing can be defined as the production of objects that are intended to be sold as distinct units such as electronic devices, vehicles, smartphones, furniture, and toys among others. Whereas PLM Solution deals with the management of a product’s data from its inception, to throughout the designing, manufacturing, servicing, and disposal process. It includes the data from items, parts, products, documents, requirements, engineering change orders, and quality workflows among others. There are different benefits associated with the application of PLM in discrete manufacturing such as it improves production quality and also increases an organization’s efficiency & productivity. The rising adoption of PLM Software and growing penetration of SaaS solutions across industries as well as strategic initiatives from leading market players are key factors accelerating the market growth.

The increasing adoption of PLM software across industries is contributing to the growth of the Global PLM in Discrete Manufacturing Market. For instance, according to Statista – in 2020, the global PLM and engineering software market was estimated at USD 20.95 billion, and the market is projected to grow to USD 23 billion by 2025. Moreover, another key factor driving the market space is rising expansion of global SaaS industry. For instance, as per Statista – In 2021, the software as a service (SaaS) market was valued at USD 152 billion, and the market is projected to grow to USD 208 billion by 2023. Also, rising adoption of industrial IoT in manufacturing sector and growing advancements in PLM software would create a lucrative growth prospectus for the market over the forecast period. However, the high cost of PLM software and services stifles market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global PLM in Discrete Manufacturing Market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America dominated the market in terms of revenue, owing to the presence of leading software vendors and increasing adoption of PLM software across the industries to enhance supply chain visibility in the region. Whereas Asia Pacific is expected to grow with the highest CAGR during the forecast period, owing to factors such as rising expansion of automotive & defense manufacturing industries and growing adoption of industrial IoT solutions in the region.

Major market players included in this report are:
Ansys Inc.
Arena Solutions Inc.
Autodesk Inc.
Dassault Systèmes SE
Infor Inc.
Oracle Corporation
PTC Inc.
SAP SE
Siemens AG
Synopsys Inc.

Recent Developments in the Market:
 In February 2022, KloudPLM announced the launch of its new Cloud-First, PLM platform built on Salesforce.com. This new platform would enable organizations to streamline and automate their entire product development cycle.

 In October 2022, Melbourne-headquartered EV company Applied EV partnered with Siemens for deployment of Siemens’ product lifecycle management (PLM) software for managing the design, quality assurance and assembly of autonomous vehicles.

Global PLM in Discrete Manufacturing 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 Component, Deployment Model, Enterprise Size, End-Use Industries, 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 Component
Software
Service

By Deployment Model
On-Premises
Cloud

By Enterprise Size
Large Enterprises
Small & Medium Enterprises

By End-Use Industries
Automotive & Transportation
Industrial Machinery & Heavy Equipment
High-Tech & Consumer Electronics
Aerospace & Defense
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. PLM in Discrete Manufacturing Market, by Region, 2019-2029 (USD Billion)
1.2.2. PLM in Discrete Manufacturing Market, by Component, 2019-2029 (USD Billion)
1.2.3. PLM in Discrete Manufacturing Market, by Deployment Model, 2019-2029 (USD Billion)
1.2.4. PLM in Discrete Manufacturing Market, by Enterprise Size, 2019-2029 (USD Billion)
1.2.5. PLM in Discrete Manufacturing Market, by End-Use Industries, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global PLM in Discrete Manufacturing 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 PLM in Discrete Manufacturing Market Dynamics
3.1. PLM in Discrete Manufacturing Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Increasing adoption of PLM Software
3.1.1.2. Growing penetration of SaaS solutions across the industries
3.1.1.3. Strategic initiatives from leading market players
3.1.2. Market Challenges
3.1.2.1. High Cost of PLM Software and services
3.1.3. Market Opportunities
3.1.3.1. Rising adoption of industrial IoT in manufacturing sector
3.1.3.2. Growing advancements in PLM software
Chapter 4. Global PLM in Discrete Manufacturing 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 PLM in Discrete Manufacturing Market, by Component
6.1. Market Snapshot
6.2. Global PLM in Discrete Manufacturing Market by Component, Performance – Potential Analysis
6.3. Global PLM in Discrete Manufacturing Market Estimates & Forecasts by Component 2019-2029 (USD Billion)
6.4. PLM in Discrete Manufacturing Market, Sub Segment Analysis
6.4.1. Software
6.4.2. Services
Chapter 7. Global PLM in Discrete Manufacturing Market, by Deployment Model
7.1. Market Snapshot
7.2. Global PLM in Discrete Manufacturing Market by Deployment Model, Performance – Potential Analysis
7.3. Global PLM in Discrete Manufacturing Market Estimates & Forecasts by Deployment Model 2019-2029 (USD Billion)
7.4. PLM in Discrete Manufacturing Market, Sub Segment Analysis
7.4.1. On premises
7.4.2. Cloud
Chapter 8. Global PLM in Discrete Manufacturing Market, by Enterprise Size
8.1. Market Snapshot
8.2. Global PLM in Discrete Manufacturing Market by Enterprise Size, Performance – Potential Analysis
8.3. Global PLM in Discrete Manufacturing Market Estimates & Forecasts by Enterprise Size 2019-2029 (USD Billion)
8.4. PLM in Discrete Manufacturing Market, Sub Segment Analysis
8.4.1. Large Enterprises
8.4.2. Small & Medium Enterprises
Chapter 9. Global PLM in Discrete Manufacturing Market, by End-Use Industries
9.1. Market Snapshot
9.2. Global PLM in Discrete Manufacturing Market by End-Use Industries, Performance – Potential Analysis
9.3. Global PLM in Discrete Manufacturing Market Estimates & Forecasts by End-Use Industries 2019-2029 (USD Billion)
9.4. PLM in Discrete Manufacturing Market, Sub Segment Analysis
9.4.1. Automotive & Transportation
9.4.2. Industrial Machinery & Heavy Equipment
9.4.3. High-Tech & Consumer Electronics
9.4.4. Aerospace & Defense
9.4.5. Others
Chapter 10. Global PLM in Discrete Manufacturing Market, Regional Analysis
10.1. PLM in Discrete Manufacturing Market, Regional Market Snapshot
10.2. North America PLM in Discrete Manufacturing Market
10.2.1. U.S. PLM in Discrete Manufacturing Market
10.2.1.1. Component breakdown estimates & forecasts, 2019-2029
10.2.1.2. Deployment Model breakdown estimates & forecasts, 2019-2029
10.2.1.3. Enterprise Size breakdown estimates & forecasts, 2019-2029
10.2.1.4. End-Use Industries breakdown estimates & forecasts, 2019-2029
10.2.2. Canada PLM in Discrete Manufacturing Market
10.3. Europe PLM in Discrete Manufacturing Market Snapshot
10.3.1. U.K. PLM in Discrete Manufacturing Market
10.3.2. Germany PLM in Discrete Manufacturing Market
10.3.3. France PLM in Discrete Manufacturing Market
10.3.4. Spain PLM in Discrete Manufacturing Market
10.3.5. Italy PLM in Discrete Manufacturing Market
10.3.6. Rest of Europe PLM in Discrete Manufacturing Market
10.4. Asia-Pacific PLM in Discrete Manufacturing Market Snapshot
10.4.1. China PLM in Discrete Manufacturing Market
10.4.2. India PLM in Discrete Manufacturing Market
10.4.3. Japan PLM in Discrete Manufacturing Market
10.4.4. Australia PLM in Discrete Manufacturing Market
10.4.5. South Korea PLM in Discrete Manufacturing Market
10.4.6. Rest of Asia Pacific PLM in Discrete Manufacturing Market
10.5. Latin America PLM in Discrete Manufacturing Market Snapshot
10.5.1. Brazil PLM in Discrete Manufacturing Market
10.5.2. Mexico PLM in Discrete Manufacturing Market
10.5.3. Rest of Latin America PLM in Discrete Manufacturing Market
10.6. Rest of The World PLM in Discrete Manufacturing Market

Chapter 11. Competitive Intelligence
11.1. Top Market Strategies
11.2. Company Profiles
11.2.1. Ansys Inc.
11.2.1.1. Key Information
11.2.1.2. Overview
11.2.1.3. Financial (Subject to Data Availability)
11.2.1.4. Product Summary
11.2.1.5. Recent Developments
11.2.2. Arena Solutions Inc.
11.2.3. Autodesk Inc.
11.2.4. Dassault Systèmes SE
11.2.5. Infor Inc
11.2.6. Oracle Corporation
11.2.7. PTC Inc.
11.2.8. SAP SE
11.2.9. Siemens AG
11.2.10. Synopsys Inc.
Chapter 12. Research Process
12.1. Research Process
12.1.1. Data Mining
12.1.2. Analysis
12.1.3. Market Estimation
12.1.4. Validation
12.1.5. Publishing
12.2. Research Attributes
12.3. Research Assumption

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We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
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Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
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.
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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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