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Global Smart Manufacturing Market to reach USD 765.09 billion by the end of 2030.

Global Smart Manufacturing Market Size study & Forecast, by Component (Hardware, Software, Services) by Technology (Machine Execution Systems, Programmable Logic Controller, Enterprise Resource Planning, SCADA, Discrete Control Systems, Human Machine Interface, Machine Vision, 3D Printing, Product Lifecycle Management, Plant Asset Management), by End-use (Automotive, Aerospace & Defense, Chemicals & Materials, Healthcare, Industrial Equipment, Electronics, Food & Agriculture, Oil & Gas, Others) and Regional Analysis, 2023-2030

Product Code: OIRIA-62824026
Publish Date: 30-10-2023
Page: 200

Global Smart Manufacturing Market is valued approximately USD 277.81 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 13.5% cover the forecast period 2023-2030. Smart Manufacturing, also known as Industry 4.0 or the Fourth Industrial Revolution, refers to the integration of advanced technologies and data-driven systems in manufacturing processes to improve efficiency, productivity, and flexibility. It involves the use of automation, digitalization, and connectivity to create intelligent, interconnected systems within the manufacturing environment. Smart Manufacturing leverages technologies such as the Internet of Things (IoT), artificial intelligence (AI), big data analytics, cloud computing, robotics, and additive manufacturing (3D printing) to transform traditional manufacturing into a more efficient and intelligent process. These technologies enable machines, devices, and systems to communicate and collaborate with each other, leading to a more streamlined and automated production flow. The Smart Manufacturing market is expanding because of factors such as proliferation of internet of Things, increasing spending on digital transformation technologies and Increasing demand for automation to achieve efficiency and quality across the industries.

The proliferation of IoT devices and connectivity has revolutionized the manufacturing industry. IoT enables real-time monitoring, data collection, and analysis of various components and processes within a manufacturing environment. The integrating IoT devices and sensors, enabled the manufacturers to achieve greater visibility, predictive maintenance, and improved decision-making capabilities. According to Statista, Number of Internet of Things (IoT) connected devices worldwide in year 2019 stood at 8.6 billion devices which increased to 13.14 billion in year 2022 and it is projected to reach at 29.42 billion devices by year 2030. Digital transformation technologies enable manufacturers to automate processes, streamline operations, and optimize resource utilization. By leveraging real-time data and advanced analytics, manufacturers can identify bottlenecks, reduce downtime, and make data-driven decisions, leading to improved operational efficiency. Further, from the same source it has been found that Spending on digital transformation technologies and services worldwide in year 2019 stood at USD 1.18 Trillion which increased to USD 1.85 trillion in year 2022 and it is projected to reach at USD 3.4 trillion by year 2026. Thus rising proliferation of IoT devices and increasing spending on digital transformation technologies is driving the market growth. In addition, advancement in connectivity technologies and investment in new network infrastructure are creating new opportunities to the market growth. However, cybersecurity concerns and lack of standards and regulations stifles market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Smart Manufacturing Market study include Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. Asia Pacific dominated the market in 2022 owing to factors such as rising government support, development of new manufacturing facilities, rising investment in adoption of digital technologies in manufacturing units, rising adoption of IoT devices, rising government investment in the industry. Whereas Europe is projected to have significant growth owing to factors such as rising investment in development of smart manufacturing units, rising adoption of digital technologies, and favorable government support to the industry.

Major market player included in this report are:
HP Development Company, L.P.
Emerson Electric Co.
General Electric
Honeywell International, Inc.
Mitsubishi Electric Corporation
Robert Bosch GmbH
Rockwell Automation, Inc.
Schneider Electric
Siemens AG

Recent Developments in the Market:
Ø In September 2021, Honeywell International, Inc. developed the “Smart Flexible Depalletizer” robot to lessen the number of labor-intensive jobs. With this innovation, warehouse productivity is increasing and workplace accidents are declining.
Ø In March 2021, General Electric Company announced the launch of Connectix, a portfolio of user-friendly software applications and expert services. The service is designed to be applied in smart manufacturing applications. The services help to use data analytics to boost energy efficiency, optimise daily operations in manufacturing, and speed up decision-making.
Global Smart Manufacturing Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Component, Technology, End-use, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü 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:

By Technology:
Machine Execution Systems
Programmable Logic Controller
Enterprise Resource Planning
Discrete Control Systems
Human Machine Interface
Machine Vision
3D Printing
Product Lifecycle Management
Plant Asset Management

By End-use:
Aerospace & Defense
Chemicals & Materials
Industrial Equipment
Food & Agriculture
Oil & Gas

By Region:

North America


Asia Pacific
South Korea

Latin America

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Smart Manufacturing Market, by Region, 2020-2030 (USD Billion)
1.2.2. Smart Manufacturing Market, by Component, 2020-2030 (USD Billion)
1.2.3. Smart Manufacturing Market, by Technology, 2020-2030 (USD Billion)
1.2.4. Smart Manufacturing Market, by End-use, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Smart Manufacturing Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Smart Manufacturing Market Dynamics
3.1. Smart Manufacturing Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Proliferation of internet of Things Increasing spending on digital transformation technologies Increasing demand for automation to achieve efficiency and quality across the industries
3.1.2. Market Challenges Cybersecurity concerns Lack of standards and regulations
3.1.3. Market Opportunities Advancement in connectivity technologies Investment in new network infrastructure
Chapter 4. Global Smart 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. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Smart Manufacturing Market, by Component
5.1. Market Snapshot
5.2. Global Smart Manufacturing Market by Component, Performance – Potential Analysis
5.3. Global Smart Manufacturing Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
5.4. Smart Manufacturing Market, Sub Segment Analysis
5.4.1. Hardware
5.4.2. Software
5.4.3. Services
Chapter 6. Global Smart Manufacturing Market, by Technology
6.1. Market Snapshot
6.2. Global Smart Manufacturing Market by Technology, Performance – Potential Analysis
6.3. Global Smart Manufacturing Market Estimates & Forecasts by Technology 2020-2030 (USD Billion)
6.4. Smart Manufacturing Market, Sub Segment Analysis
6.4.1. Machine Execution Systems
6.4.2. Programmable Logic Controller
6.4.3. Enterprise Resource Planning
6.4.4. SCADA
6.4.5. Discrete Control Systems
6.4.6. Human Machine Interface
6.4.7. Machine Vision
6.4.8. 3D Printing
6.4.9. Product Lifecycle Management
6.4.10. Plant Asset Management
Chapter 7. Global Smart Manufacturing Market, by End-use
7.1. Market Snapshot
7.2. Global Smart Manufacturing Market by End-use, Performance – Potential Analysis
7.3. Global Smart Manufacturing Market Estimates & Forecasts by End-use 2020-2030 (USD Billion)
7.4. Smart Manufacturing Market, Sub Segment Analysis
7.4.1. Automotive
7.4.2. Aerospace & Defense
7.4.3. Chemicals & Materials
7.4.4. Healthcare
7.4.5. Industrial Equipment
7.4.6. Electronics
7.4.7. Food & Agriculture
7.4.8. Oil & Gas
7.4.9. Others
Chapter 8. Global Smart Manufacturing Market, Regional Analysis
8.1. Top Leading Countries
8.2. Top Emerging Countries
8.3. Smart Manufacturing Market, Regional Market Snapshot
8.4. North America Smart Manufacturing Market
8.4.1. U.S. Smart Manufacturing Market Component breakdown estimates & forecasts, 2020-2030 Technology breakdown estimates & forecasts, 2020-2030 End-use breakdown estimates & forecasts, 2020-2030
8.4.2. Canada Smart Manufacturing Market
8.5. Europe Smart Manufacturing Market Snapshot
8.5.1. U.K. Smart Manufacturing Market
8.5.2. Germany Smart Manufacturing Market
8.5.3. France Smart Manufacturing Market
8.5.4. Spain Smart Manufacturing Market
8.5.5. Italy Smart Manufacturing Market
8.5.6. Rest of Europe Smart Manufacturing Market
8.6. Asia-Pacific Smart Manufacturing Market Snapshot
8.6.1. China Smart Manufacturing Market
8.6.2. India Smart Manufacturing Market
8.6.3. Japan Smart Manufacturing Market
8.6.4. Australia Smart Manufacturing Market
8.6.5. South Korea Smart Manufacturing Market
8.6.6. Rest of Asia Pacific Smart Manufacturing Market
8.7. Latin America Smart Manufacturing Market Snapshot
8.7.1. Brazil Smart Manufacturing Market
8.7.2. Mexico Smart Manufacturing Market
8.8. Middle East & Africa Smart Manufacturing Market
8.8.1. Saudi Arabia Smart Manufacturing Market
8.8.2. South Africa Smart Manufacturing Market
8.8.3. Rest of Middle East & Africa Smart Manufacturing Market

Chapter 9. Competitive Intelligence
9.1. Key Company SWOT Analysis
9.1.1. Company 1
9.1.2. Company 2
9.1.3. Company 3
9.2. Top Market Strategies
9.3. Company Profiles
9.3.1. HP Development Company, L.P. Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
9.3.2. ABB Ltd
9.3.3. Emerson Electric Co.
9.3.4. General Electric
9.3.5. Honeywell International, Inc.
9.3.6. Mitsubishi Electric Corporation
9.3.7. Robert Bosch GmbH
9.3.8. Rockwell Automation, Inc.
9.3.9. Schneider Electric
9.3.10. Siemens AG
Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
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.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
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.
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.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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