[185 Pages Report] The Computer Vision in Manufacturing Market size was estimated at USD 6.95 billion in 2023 and expected to reach USD 8.00 billion in 2024, at a CAGR 15.28% to reach USD 18.83 billion by 2030.
Computer vision in manufacturing is a technology that uses digital images and video to provide automated visual inspection and analysis. It enables machines to accurately detect, classify, and track objects in the environment. Computer vision is used for various tasks such as defect detection, quality control, automation of assembly lines, robotic navigation, and more. Computer vision systems are becoming more popular and widely adopted as manufacturers strive to increase efficiency and reduce costs. The inclination of industrial automation and the expansion of the manufacturing sector has considerably surged the usage of computer vision systems. On the other hand, the complexities related to deployment, the cost-intensive nature of technology, and the limited availability of skilled personnel hinder the adoption of the technology. However, continuous advancements in computer vision systems and utilization of robotics technology, and investments in smart factories worldwide are expected to proliferate the use of computer vision in manufacturing in the coming years.
The large manufacturing sector in China, the U.S., Germany, Italy, Canada, and other major economies and the year-on-year growth of the global production output from the industrialized economies supports the adoption of computer vision in manufacturing. The expansion of automotive manufacturing backed by electric vehicle initiatives and a surge in pharmaceutical research to lessen the burden of communicable and non-communicable disorders have stimulated rapid innovations in digital technologies and their deployment. In addition, Industry 4.0 policies launched in South Korea, India, the U.S., Saudi Arabia, Germany, France, China, Japan, and other countries provide huge scope for the utilization of computer vision systems as production facilities adopt lean manufacturing approaches and demand for smart manufacturing rises. Although high energy prices and disruptions in logistical operations of raw materials and components adversely affect the operation of manufacturing sectors, changes made in regulatory frameworks and initiatives launched to boost domestic production capacities coupled with the development of new products by market players are expected to encourage the use of computer vision in manufacturing in the near future.
The market dynamics represent an ever-changing landscape of the Computer Vision in Manufacturing Market by providing actionable insights into factors, including supply and demand levels. Accounting for these factors helps design strategies, make investments, and formulate developments to capitalize on future opportunities. In addition, these factors assist in avoiding potential pitfalls related to political, geographical, technical, social, and economic conditions, highlighting consumer behaviors and influencing manufacturing costs and purchasing decisions.
The market disruption analysis delves into the core elements associated with market-influencing changes, including breakthrough technological advancements that introduce novel features, integration capabilities, regulatory shifts that could drive or restrain market growth, and the emergence of innovative market players challenging traditional paradigms. This analysis facilitates a competitive advantage by preparing players in the Computer Vision in Manufacturing Market to pre-emptively adapt to these market-influencing changes, enhances risk management by early identification of threats, informs calculated investment decisions, and drives innovation toward areas with the highest demand in the Computer Vision in Manufacturing Market.
The porter's five forces analysis offers a simple and powerful tool for understanding, identifying, and analyzing the position, situation, and power of the businesses in the Computer Vision in Manufacturing Market. This model is helpful for companies to understand the strength of their current competitive position and the position they are considering repositioning into. With a clear understanding of where power lies, businesses can take advantage of a situation of strength, improve weaknesses, and avoid taking wrong steps. The tool identifies whether new products, services, or companies have the potential to be profitable. In addition, it can be very informative when used to understand the balance of power in exceptional use cases.
The value chain of the Computer Vision in Manufacturing Market encompasses all intermediate value addition activities, including raw materials used, product inception, and final delivery, aiding in identifying competitive advantages and improvement areas. Critical path analysis of the <> market identifies task sequences crucial for timely project completion, aiding resource allocation and bottleneck identification. Value chain and critical path analysis methods optimize efficiency, improve quality, enhance competitiveness, and increase profitability. Value chain analysis targets production inefficiencies, and critical path analysis ensures project timeliness. These analyses facilitate businesses in making informed decisions, responding to market demands swiftly, and achieving sustainable growth by optimizing operations and maximizing resource utilization.
The pricing analysis comprehensively evaluates how a product or service is priced within the Computer Vision in Manufacturing Market. This evaluation encompasses various factors that impact the price of a product, including production costs, competition, demand, customer value perception, and changing margins. An essential aspect of this analysis is understanding price elasticity, which measures how sensitive the market for a product is to its price change. It provides insight into competitive pricing strategies, enabling businesses to position their products advantageously in the Computer Vision in Manufacturing Market.
The technology analysis involves evaluating the current and emerging technologies relevant to a specific industry or market. This analysis includes breakthrough trends across the value chain that directly define the future course of long-term profitability and overall advancement in the Computer Vision in Manufacturing Market.
The patent analysis involves evaluating patent filing trends, assessing patent ownership, analyzing the legal status and compliance, and collecting competitive intelligence from patents within the Computer Vision in Manufacturing Market and its parent industry. Analyzing the ownership of patents, assessing their legal status, and interpreting the patents to gather insights into competitors' technology strategies assist businesses in strategizing and optimizing product positioning and investment decisions.
The trade analysis of the Computer Vision in Manufacturing Market explores the complex interplay of import and export activities, emphasizing the critical role played by key trading nations. This analysis identifies geographical discrepancies in trade flows, offering a deep insight into regional disparities to identify geographic areas suitable for market expansion. A detailed analysis of the regulatory landscape focuses on tariffs, taxes, and customs procedures that significantly determine international trade flows. This analysis is crucial for understanding the overarching legal framework that businesses must navigate.
The regulatory framework analysis for the Computer Vision in Manufacturing Market is essential for ensuring legal compliance, managing risks, shaping business strategies, fostering innovation, protecting consumers, accessing markets, maintaining reputation, and managing stakeholder relations. Regulatory frameworks shape business strategies and expansion initiatives, guiding informed decision-making processes. Furthermore, this analysis uncovers avenues for innovation within existing regulations or by advocating for regulatory changes to foster innovation.
The FPNV positioning matrix is essential in evaluating the market positioning of the vendors in the Computer Vision in Manufacturing Market. This matrix offers a comprehensive assessment of vendors, examining critical metrics related to business strategy and product satisfaction. This in-depth assessment empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success, namely Forefront (F), Pathfinder (P), Niche (N), or Vital (V).
The market share analysis is a comprehensive tool that provides an insightful and in-depth assessment of the current state of vendors in the Computer Vision in Manufacturing Market. By meticulously comparing and analyzing vendor contributions, companies are offered a greater understanding of their performance and the challenges they face when competing for market share. These contributions include overall revenue, customer base, and other vital metrics. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With these illustrative details, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.
Cognex : Launches Embedded AI-Based Vision System with Applications for OEMs in Life Sciences
Cognex Corporation recently launched its latest Advantage 182 vision system with applications for OEMs in life sciences. The system is designed to provide a comprehensive suite of hardware and software components, enabling OEMs to embed deep learning-based inspection systems into various industrial processes quickly. This technology is expected to revolutionize the manufacturing industry by providing a cost-effective solution that can accurately inspect products in real time [Published On: 2023-05-31]
Landing AI's Visual Prompting Makes Building and Deploying Computer Vision Easy with NVIDIA Metropolis
Landing AI partnered with NVIDIA corporation to use the new NVIDIA Metropolis for Factories platform to deliver its cutting-edge Visual Prompting technology to computer vision applications in smart manufacturing and other applications. This solution simplifies leveraging AI-infused cameras to deliver automated inspections, real-time analytics, and predictive maintenance capabilities for industrial use cases. With this powerful combination of technologies, manufacturers can shift from manual processes to automated operations faster and more cost-effectively. [Published On: 2023-05-29]
TKH Group acquires Machine Vision company Euresys
TKH Group recently acquired Machine Vision company Euresys to become a machine vision product provider in the market of computer vision solutions for manufacturing. This acquisition of two companies ensures to provide customers with advanced technology and an even wider range of services than before. Through their combined expertise, they can provide the next level of automation and intelligence to their customers' production lines. [Published On: 2023-05-09]
The strategic analysis is essential for organizations seeking a solid foothold in the global marketplace. Companies are better positioned to make informed decisions that align with their long-term aspirations by thoroughly evaluating their current standing in the Computer Vision in Manufacturing Market. This critical assessment involves a thorough analysis of the organization’s resources, capabilities, and overall performance to identify its core strengths and areas for improvement.
The report delves into recent significant developments in the Computer Vision in Manufacturing Market, highlighting leading vendors and their innovative profiles. These include ABB Ltd., Artemis Vision, Basler AG, Baumer Holding AG, Clarifai, Inc., Cognex Corporation, Fastec Imaging Corporation, Fujitsu Limited, General Electric Company, Google LLC by Alphabet, Inc., Heliovision, IFM Electronic GmbH, Industrial Video & Control Co., Intel Corporation, International Business Machines Corporation, ISRA VISION GmbH, Keyence Corporation, Microsoft Corporation, ML2Grow, Nexus Integra, NVIDIA Corporation, OMRON Corporation, Oracle Corporation, Sick AG, Siemens AG, Softengi, Teledyne Technologies Incorporated, Xometry Europe GmbH, and Zebra Technologies Corporation.
This research report categorizes the Computer Vision in Manufacturing Market to forecast the revenues and analyze trends in each of the following sub-markets:
- Product
- PC-based Machine Vision Systems
- Smart Camera-Based Vision Systems
- Component
- Hardware
- Cameras
- Frame Grabbers
- Image Sensors
- LED Lighting
- Optics
- Processors
- Software
- Hardware
- Application
- Identification
- Measurement
- Positioning & Guidance
- Predictive Maintenance
- Quality Assurance & Inspection
- Region
- Americas
- Argentina
- Brazil
- Canada
- Mexico
- United States
- California
- Florida
- Illinois
- New York
- Ohio
- Pennsylvania
- Texas
- Asia-Pacific
- Australia
- China
- India
- Indonesia
- Japan
- Malaysia
- Philippines
- Singapore
- South Korea
- Taiwan
- Thailand
- Vietnam
- Europe, Middle East & Africa
- Denmark
- Egypt
- Finland
- France
- Germany
- Israel
- Italy
- Netherlands
- Nigeria
- Norway
- Poland
- Qatar
- Russia
- Saudi Arabia
- South Africa
- Spain
- Sweden
- Switzerland
- Turkey
- United Arab Emirates
- United Kingdom
- Americas
- Market Penetration: This section thoroughly overviews the current market landscape, incorporating detailed data from key industry players.
- Market Development: The report examines potential growth prospects in emerging markets and assesses expansion opportunities in mature segments.
- Market Diversification: This includes detailed information on recent product launches, untapped geographic regions, recent industry developments, and strategic investments.
- Competitive Assessment & Intelligence: An in-depth analysis of the competitive landscape is conducted, covering market share, strategic approaches, product range, certifications, regulatory approvals, patent analysis, technology developments, and advancements in the manufacturing capabilities of leading market players.
- Product Development & Innovation: This section offers insights into upcoming technologies, research and development efforts, and notable advancements in product innovation.
- What is the current market size and projected growth?
- Which products, segments, applications, and regions offer promising investment opportunities?
- What are the prevailing technology trends and regulatory frameworks?
- What is the market share and positioning of the leading vendors?
- What revenue sources and strategic opportunities do vendors in the market consider when deciding to enter or exit?
- Preface
- Research Methodology
- Executive Summary
- Market Overview
- Market Insights
- Computer Vision in Manufacturing Market, by Product
- Computer Vision in Manufacturing Market, by Component
- Computer Vision in Manufacturing Market, by Application
- Americas Computer Vision in Manufacturing Market
- Asia-Pacific Computer Vision in Manufacturing Market
- Europe, Middle East & Africa Computer Vision in Manufacturing Market
- Competitive Landscape
- Competitive Portfolio
- List of Figures [Total: 22]
- List of Tables [Total: 382]
- List of Companies Mentioned [Total: 29]
Improved Quality Control:
Computer vision is being used to improve quality control in manufacturing by analyzing real-time images to detect any defects in the production process. These defects can range from a misaligned component or a missing fixture, and detecting them early can save the manufacturer time and money. Object recognition algorithms can be used to identify not only specific parts but also missing bolts or screw detection, which can be a life-altering change.
Increased Efficiency:
Computer vision can be used to optimize the manufacturing process to increase efficiency. Manufacturing equipment can be equipped with cameras, making it possible to track assemblies as they move down the line. This allows managers to see where bottlenecks are forming and where processes can be improved. Improving the manufacturing process increases efficiency, saves time, and ultimately results in cost savings for the manufacturer.
Reducing Human Error:
Human error is a common problem in manufacturing and can have a severe impact on the quality and safety of the products produced. Computer vision provides the ability to detect and correct human error in real time, reducing the likelihood of errors and improving the overall quality of the product. This is especially important with the increase in automation and robotics in manufacturing, where mistakes can have serious consequences.
Predictive Maintenance:
One of the most significant benefits of computer vision in manufacturing is predictive maintenance. Monitoring equipment using computer vision technologies allows for the early detection of equipment failures. This means that manufacturers can schedule maintenance before a breakdown occurs, improving equipment uptime and reducing the risk of production downtime. By avoiding equipment failure, manufacturers can reduce costs associated with wasted raw materials, scrapped products, and lost production time.
Improved Safety:
Manufacturing is a hazardous environment for workers, especially when operating heavy machinery or working in dangerous conditions. Computer vision can help manufacturers improve safety by monitoring for hazards in real time and alerting operators when dangerous situations arise. Additionally, computer vision technologies can detect anomalies in the production line that could cause safety issues and alert operators to take corrective actions. As a result of this, workers' safety levels can record considerable hikes, and frequent accidents or injuries can reduce magically.
From improved quality control to increased efficiency and reduced human error to safety improvements, computer vision is revolutionizing the manufacturing industry. By providing real-time monitoring and analysis of production lines, predictive maintenance, and safety monitoring, computer vision technologies are helping manufacturers reduce operating costs, increase productivity, and improve their products' overall quality. With the adoption of these advanced technologies, manufacturers can gain a competitive edge by reducing risk and staying ahead of the competition.
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