[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 FPNV Positioning Matrix is pivotal in evaluating the Computer Vision in Manufacturing Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis 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: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).
The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the Computer Vision in Manufacturing Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. 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 this expanded level of detail, 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 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: It presents comprehensive information on the market provided by key players.
- Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.
- Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.
- Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.
- Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.
- What is the market size and forecast of the Computer Vision in Manufacturing Market?
- Which products, segments, applications, and areas should one consider investing in over the forecast period in the Computer Vision in Manufacturing Market?
- What are the technology trends and regulatory frameworks in the Computer Vision in Manufacturing Market?
- What is the market share of the leading vendors in the Computer Vision in Manufacturing Market?
- Which modes and strategic moves are suitable for entering the Computer Vision in Manufacturing Market?
- 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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