Informe de análisis del tamaño, la participación y las tendencias del mercado de visión artificial industrial en América del Norte: descripción general de la industria y pronóstico hasta 2031

Análisis del mercado de la visión artificial industrial

El creciente enfoque en el control de calidad y la inspección es un importante impulsor del mercado de la visión artificial industrial, y desempeña un papel crucial en su expansión. A medida que las industrias de diversos sectores se esfuerzan por cumplir con estrictos estándares de calidad y mantener una ventaja competitiva, la demanda de sistemas avanzados de visión artificial ha aumentado. Estos sistemas son esenciales para automatizar el proceso de inspección, lo que garantiza la consistencia, la precisión y la eficiencia en el control de calidad, lo que en última instancia impulsa el crecimiento del mercado. Además, el control de calidad y la inspección son aspectos fundamentales de los procesos de fabricación, que garantizan que los productos cumplan con los estándares predefinidos antes de llegar al mercado. En sectores como el automotriz, la electrónica, los productos farmacéuticos y los alimentos y bebidas, incluso los defectos menores pueden provocar pérdidas financieras significativas, retiradas de productos y daños a la reputación de la marca. Como resultado, las empresas invierten cada vez más en sistemas de visión artificial para detectar y corregir defectos en tiempo real, mejorando así la calidad del producto y reduciendo el desperdicio.

Tamaño del mercado de la visión artificial industrial

El tamaño del mercado de visión artificial industrial de América del Norte se valoró en USD 3.60 mil millones en 2023 y se proyecta que alcance los USD 6.47 mil millones para 2031, con una CAGR del 7.69% durante el período de pronóstico de 2024 a 2031. Además de la información sobre escenarios de mercado como valor de mercado, tasa de crecimiento, segmentación, cobertura geográfica y actores principales, los informes de mercado seleccionados por Data Bridge Market Research también incluyen análisis de importación y exportación, descripción general de la capacidad de producción, análisis de consumo de producción, análisis de tendencias de precios, escenario de cambio climático, análisis de la cadena de suministro, análisis de la cadena de valor, descripción general de materias primas / consumibles, criterios de selección de proveedores, análisis PESTLE, análisis de Porter y marco regulatorio.

Tendencias del mercado de visión artificial industrial en América del Norte

“Creciente atención al control de calidad y la inspección”

The growing focus on quality control and inspection is a significant driver of the industrial machine vision market, playing a crucial role in its expansion. As industries across various sectors strive to meet stringent quality standards and maintain competitive advantage, the demand for advanced machine vision systems has surged. These systems are essential in automating the inspection process, ensuring consistency, accuracy, and efficiency in quality control, which ultimately drives market growth. Also, quality control and inspection are fundamental aspects of manufacturing processes, ensuring that products meet predefined standards before reaching the market. In sectors like automotive, electronics, pharmaceuticals, and food & beverage, even minor defects can lead to significant financial losses, recalls, and damage to brand reputation. As a result, companies are increasingly investing in machine vision systems to detect and rectify defects in real time, thereby enhancing product quality and reducing wastage.

Report Scope and Industrial Machine Vision Market Segmentation   

Industrial Machine Vision Market Definition

Machine vision refers to the technology and methods used to provide imaging-based automatic inspection and analysis for various applications, such as automated inspection, process control, and robotic guidance. It combines hardware (cameras, sensors, and lighting) with software algorithms to capture and process images, enabling machines to "see" and make decisions based on visual data. Widely used in manufacturing, machine vision ensures quality control, improves productivity, and enhances accuracy by identifying defects, measuring dimensions, and guiding automation systems. This technology is essential in industries like automotive, electronics, food and beverage, and pharmaceuticals, driving efficiency and innovation in production processes.

North America Industrial Machine Vision Market Dynamics

Drivers  

• Growing Focus on Quality Control and Inspection

The growing focus on quality control and inspection is a significant driver of the industrial machine vision market, playing a crucial role in its expansion. As industries across various sectors strive to meet stringent quality standards and maintain competitive advantage, the demand for advanced machine vision systems has surged. These systems are essential in automating the inspection process, ensuring consistency, accuracy, and efficiency in quality control, which ultimately drives market growth. Also, quality control and inspection are fundamental aspects of manufacturing processes, ensuring that products meet predefined standards before reaching the market. In sectors like automotive, electronics, pharmaceuticals, and food & beverage, even minor defects can lead to significant financial losses, recalls, and damage to brand reputation. As a result, companies are increasingly investing in machine vision systems to detect and rectify defects in real time, thereby enhancing product quality and reducing wastage.

For instance,

According to an article published Toyota has integrated machine vision systems into its assembly lines to inspect welds, paint quality, and component assembly. The systems detect defects such as misalignment, scratches, and inconsistent welds that are often challenging to identify manually. This integration ensures that only vehicles meeting Toyota's stringent quality standards leave the production facility, reducing recalls and enhancing customer satisfaction.

• Increasing Adoption of Automation Across Various Industries

The increasing adoption of automation across various industries is a significant driver for the global industrial machine vision market. As companies strive to enhance operational efficiency, reduce labor costs, and improve product quality, automation technologies, including machine vision systems, are becoming essential components of modern manufacturing and production processes. Automation has revolutionized industries by streamlining operations and boosting productivity. Machine vision systems play a central role in this transformation, offering precise and reliable inspection, measurement, and control capabilities. By automating tasks such as quality inspection, sorting, and assembly, these systems enable manufacturers to operate at higher speeds and with greater accuracy. This results in faster production rates and more consistent outcomes, minimizing human error and enhancing overall operational efficiency. As industries increasingly adopt automation to maintain competitiveness, the demand for sophisticated machine vision solutions that integrate seamlessly into automated systems continues to rise.

For instance,

• In January 2023, according to an article published in Autobody New, Tesla has begun implementing automated quality control at its Fremont, California factory, focusing on vehicle interior build quality. This system includes robots dedicated to inspecting fascia, or dashboard quality, to enhance overall product reliability. This move is part of Tesla's broader efforts to address previous criticisms related to manufacturing consistency. The new inspection robots form a core component of Tesla's "Automatic Inspection System," showcasing the company’s commitment to refining production standards through automation.

Opportunities

• Advancements in AI and Deep Learning

Advancements in AI and deep learning present significant opportunities for the industrial machine vision market. These technologies enable more accurate image analysis, real-time decision-making, predictive maintenance, improving accuracy and efficiency in various industrial processes such as PCB (Printed Circuit Board) inspection in the electronics industry, quality inspection and assembly verification in the automotive industry, packaging and label inspection in the pharmaceutical industry and among other industrial processes. Deep learning algorithms, particularly convolutional neural networks (CNNs), significantly enhance image recognition capabilities. This advancement allows machine vision systems to accurately identify and classify objects, defects, and anomalies in real-time. For instance, AI-driven systems can detect minute defects in manufacturing processes that traditional systems might miss, leading to higher quality control standards and reduced waste.

For instance,

According to an article published by Supply Chain Today, Tesla's revolutionary use of Artificial Intelligence (AI) in manufacturing, particularly at the Gigafactory, distinguishes it from other automakers. Known as the “machine that builds machines,” the Gigafactory exemplifies Tesla's commitment to Industry 4.0 by integrating AI, IoT, and robotics into its production processes. Although Tesla faces challenges in its supply chain, its success lies in its ability to identify and address inefficiencies. This approach to continuous improvement and technological innovation offers valuable insights for professionals in supply chain management, manufacturing, and automation.

• Technological Advancements in Various Components of Industrial Machine Vision

Modern machine vision systems leverage sophisticated algorithms and high-resolution imaging sensors to achieve unparalleled precision in defect detection and quality control. Advances in optics and imaging technology enable these systems to identify minute defects and inconsistencies that were previously undetectable. This improvement in accuracy ensures higher product quality and reduces waste, providing a competitive edge for manufacturers.

The incorporation of Artificial Intelligence (AI) and deep learning technologies into machine vision systems has revolutionized their capabilities. AI enables machine vision systems to learn from data, adapt to new scenarios, and improve over time. This allows for more complex visual analysis, such as recognizing patterns and anomalies in real time, which enhances decision-making and operational efficiency.

For instance,

According to an article published by Cognex Corporation, P&G India, known for its Ariel and Tide brands, faced challenges with its high-volume detergent packing lines, which operated around the clock and handled over 50 product types. The risk of errors was significant, particularly with laminate mix-ups and incorrect maximum retail prices (MRP), leading to costly repacking and pricing issues. To address this, P&G integrated Cognex In-Sight® vision systems, utilizing Optical Character Verification (OCV) and the PatMax algorithm for accurate, real-time inspection. This upgrade reduced errors, enhanced productivity, and eliminated manual checks, boosting efficiency significantly.

Restraints/Challenges

• High Initial Costs of Setting Up Industrial Machine Vision Systems

The high initial costs associated with setting up industrial machine vision systems represent a significant restraint for the global industrial machine vision market. Despite their numerous benefits, including enhanced quality control, increased efficiency, and reduced labor costs, the substantial upfront investment required for these systems can be a barrier for many companies, particularly small and medium-sized enterprises (SMEs) and those operating in emerging markets. The primary component of the high initial costs includes the expense of purchasing advanced machine vision hardware, such as high-resolution cameras, lenses, lighting, and sensors. In addition, sophisticated machine vision systems often require complex software for image processing and analysis, which further add to the cost. The integration of these systems into existing production lines may also necessitate significant modifications to equipment and infrastructure, leading to additional expenses.

For instance,

According to a blog published on IndMALL, industries faced a substantial initial investment when implementing machine vision systems. The costs included high-resolution cameras, advanced lighting, powerful processors, and specialized software. In addition, expenses extended to integrating the system into existing workflows and developing custom solutions for specific applications.

• Complexity of Integration of Industrial Machine Vision Systems

The complexity of integrating industrial machine vision systems is a significant restraint for the industrial machine vision market. Integrating these systems into existing manufacturing environments involves intricate technical challenges that can impede widespread adoption. This complexity is compounded by the need for seamless compatibility with existing machinery and infrastructure, often leading to additional costs and potential disruptions in production. Machine vision systems typically comprise a combination of hardware, such as high-resolution cameras, lenses, and lighting, and software for image processing and analysis. Integrating these components into existing production lines requires careful planning and execution. The complexity arises from several factors, including the need for precise alignment of cameras, calibration of imaging systems, and customization of software to meet specific application requirements.

The integration process ensures compatibility with existing equipment and systems. Manufacturing environments often involve a diverse range of machinery and technologies, and incorporating machine vision systems requires seamless integration with these components. Achieving this compatibility can be technically challenging and may require modifications to existing infrastructure.

For instance,

Integrating machine vision systems into existing processes can be both complex and time-consuming. These systems demand precise calibration and alignment, and any errors in configuration can result in inaccurate outcomes. The integration process requires ensuring compatibility with current hardware and software, often necessitating substantial modifications. This complexity demands meticulous planning and coordination, frequently involving specialized knowledge and skills. Consequently, the setup phase can prolong project timelines and escalate costs, potentially disrupting ongoing operations.

This market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

Impact and Current Market Scenario of Raw Material Shortage and Shipping Delays

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Apart from the standard report, we also offer in-depth analysis of the procurement level from forecasted shipping delays, distributor mapping by region, commodity analysis, production analysis, price mapping trends, sourcing, category performance analysis, supply chain risk management solutions, advanced benchmarking, and other services for procurement and strategic support.

Expected Impact of Economic Slowdown on the Pricing and Availability of Products

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Industrial Machine Vision Market Scope

The market is segmented on the basis of component, product, type, deployment, applications, and end user. The growth amongst these segments will help you analyze meagre growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.

Component

• Hardware
  • Cameras
    • Cameras, By Frame Rate
      • More than 125 FPS
      • 25-125 FPS
      • <25 FPS
    • Cameras, By Format
      • Area Scan
      • Line Scan
    • Cameras, By Sensor type
      • CMOS
      • CCD
    • Cameras, By Interface Standards
      • USD 2.0
      • USD 3.0
      • Gige(Gigabit Ethernet)
      • Ethernet
      • Camera Link
      • Coaxpress
      • EMVA-1288
      • Genicam
      • Firewire
      • Others
  • Lighting
    • Lighting, By Type
      • LED
      • Fluorescent
  • Processors
    • Processors, By Type
      • Vision Processors Unit
      • Field-Programmable Gate Array
      • Digital Signal Processor
      • Microcontrollers & Microprocessors
  • Others
    • Others, By Type
      • Cables
      • Communication Accessories
• Software
  • Traditional Software
  • Deep Learning Software

Product

• Smart camera
• Hybrid smart camera
• PC based

Type

• 2D Vision
• 3D Vision
• 1D Vision

Deployment

• Robotic Cell
• General

Applications

• Defect Detection
• Product Inspection
• Surface Inspection
• Packaging Inspection
• Identification
• OCR/OCV
• Pattern Recognition
• Gauging, Guidance
• Part Tracking
• Web Inspection

End-User

• Automotive
  • Automotive, By Type
    • Electric Vehicle
    • Passenger Vehicle
    • Commercial Vehicle
  • Automotive, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Consumer Electronics
  • Consumer Electronics, By Type
    • Smartphones
    • Digital Cameras
    • Home Appliances
    • Others
  • Consumer Electronics, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Food and Packaging
  • Food and Packaging, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Pharmaceuticals
  • Pharmaceuticals, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Metals
  • Metals, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Printing
  • Printing, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Aerospace
  • Aerospace, By Type
    • Commercial and General Aviation
    • Military Aircraft
    • Space Systems
  • Aerospace, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Glass
  • Glass, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Rubber and Plastics
  • Rubber and Plastics, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Mining
  • Mining, By Type
    • Surface Mining
    • Underground Mining
  • Mining, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Textiles
  • Textiles, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Wood and Paper
  • Wood and Paper, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Machinery
  • Machinery, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Solar Panel Manufacturing
  • Solar Panel Manufacturing, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based
• Others
  • Others, By Product
    • Smart Camera/Smart Sensor Vision System
    • Hybrid Smart Camera Vision System
    • PC Based

Industrial Machine Vision Market Regional Analysis

The market is analyzed and market size insights and trends are provided by component, product, type, deployment, applications, and end-user as referenced above.

The countries covered in the market are U.S., Canada, and Mexico.

U.S. is expected to dominate the market due to many leading technology companies, research institutions, and universities that drive innovation in computer vision, AI, and machine learning. This environment fosters the rapid development and deployment of advanced machine vision technologies.

La sección de países del informe también proporciona factores de impacto de mercado individuales y cambios en la regulación en el mercado a nivel nacional que afectan las tendencias actuales y futuras del mercado. Puntos de datos como análisis de la cadena de valor aguas arriba y aguas abajo, tendencias técnicas y análisis de las cinco fuerzas de Porter, estudios de casos son algunos de los indicadores utilizados para pronosticar el escenario del mercado para países individuales. Además, la presencia y disponibilidad de marcas de América del Norte y sus desafíos enfrentados debido a la competencia grande o escasa de las marcas locales y nacionales, el impacto de los aranceles nacionales y las rutas comerciales se consideran al proporcionar un análisis de pronóstico de los datos del país.

Cuota de mercado de la visión artificial industrial

El panorama competitivo del mercado proporciona detalles por competidores. Los detalles incluidos son una descripción general de la empresa, las finanzas de la empresa, los ingresos generados, el potencial de mercado, la inversión en investigación y desarrollo, las nuevas iniciativas de mercado, la presencia en América del Norte, los sitios e instalaciones de producción, las capacidades de producción, las fortalezas y debilidades de la empresa, el lanzamiento de productos, la amplitud y variedad de productos, y el dominio de las aplicaciones. Los puntos de datos proporcionados anteriormente solo están relacionados con el enfoque de las empresas en relación con el mercado.

Los líderes del mercado de visión artificial industrial que operan en el mercado son:

• KEYENCE CORPORATION (Japón)
• Corporación OMRON (Japón)
• Sony Semiconductor Solutions Corporation (Japón)
• Corporación Cognex (Estados Unidos)
• SICK AG (Estados Unidos)
• Teledyne FLIR LLC (Estados Unidos)
• NATIONAL INSTRUMENTS CORP. (EE.UU.)
• BASLER AG (Alemania)
• ISRA VISION (Alemania)
• Corporación Intel (Estados Unidos)
• Texas Instruments Incorporated (Estados Unidos)
• Cadence Design Systems, Inc. (Estados Unidos)
• Ceva Inc. (Estados Unidos)
• The Imaging Source, LLC (Estados Unidos)
• Kalypso: una empresa de Rockwell Automation (Estados Unidos)
• Tecnologías Qualitas (India)
• Integro Technologies Corp. (Estados Unidos)

Últimos avances en el mercado de la visión artificial industrial

• En marzo de 2023, KEYENCE CORPORATION presentó su último sistema de visión, la Serie VS, diseñado para mejorar significativamente la automatización industrial. Este nuevo sistema cuenta con capacidades avanzadas de procesamiento de imágenes, inspección de alta velocidad y un funcionamiento sencillo, lo que lo hace ideal para mejorar el control de calidad y la eficiencia en entornos de fabricación. La Serie VS subraya el compromiso de Keyence de proporcionar tecnología de visión de vanguardia para diversas aplicaciones industriales.
• En febrero de 2024, OMRON Automation presentó los robots colaborativos de la serie TM S en India, con articulaciones más rápidas y mayor seguridad, lo que mejoró la eficiencia de la fábrica en espacios de trabajo compartidos.

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