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市場調査レポート
商品コード
1660714
マシンビジョン市場レポート:製品、コンポーネント、用途、産業、地域別、2025年~2033年Machine Vision Market Report by Product, Component, Application, Industry, and Region 2025-2033 |
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カスタマイズ可能
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マシンビジョン市場レポート:製品、コンポーネント、用途、産業、地域別、2025年~2033年 |
出版日: 2025年02月10日
発行: IMARC
ページ情報: 英文 146 Pages
納期: 2~3営業日
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マシンビジョンの世界市場規模は2024年に141億米ドルに達しました。今後、IMARC Groupは、市場は2033年までに267億米ドルに達し、2025年から2033年の間に6.97%の成長率(CAGR)を示すと予測しています。製造業における自動化と品質管理の需要の増加、人工知能とディープラーニングアルゴリズムの数多くの進歩、効率的な検査に対するニーズの高まりは、市場を推進している主な要因の一部です。
コンピュータビジョンとしても知られるマシンビジョンは、人工知能(AI)および画像処理の一分野であり、機械(典型的にはコンピュータ)が世界からの視覚情報を解釈し理解することを可能にします。機械が画像や動画から意味のある洞察を分析、処理、抽出できるようにするアルゴリズムや技術の開発が含まれます。マシンビジョンシステムは、カメラやその他の撮像装置を利用して視覚データを取り込み、様々な計算方法を用いて、パターンの検出、物体の認識、動きの追跡、視覚的理解を必要とするタスクの実行を行う。その結果、マシンビジョン技術は、ロボット工学、自律走行車、品質管理、医療用画像処理など、さまざまな産業で応用されています。
製造業、自動車、エレクトロニクス、製薬など、各業界で自動化や品質管理の需要が高まっているため、マシンビジョンシステムの採用が増加しており、予測期間中の市場成長を刺激します。これらのシステムは生産効率を高め、エラーを減らし、一貫した製品品質を保証します。さらに、人工知能(AI)やディープラーニング(深層学習)技術の登場により、マシンビジョンが画像解析やパターン認識タスクにおいてより高い精度と汎用性を達成できるようになり、製品の採用率が加速しています。さらに、スマートシティ、交通、ヘルスケアなど様々な用途で安全性と監視の必要性が高まっているため、リアルタイムの監視と脅威検出のためにマシンビジョンが広く統合されていることが、市場の成長を促進しています。さらに、カメラ、センサー、処理ハードウェアのコスト低下により、マシンビジョンソリューションがより手頃な価格になり、幅広い企業が利用できるようになったことも、市場成長を後押ししています。
人工知能とディープラーニングの進歩
人工知能(AI)とディープラーニングの継続的な進歩により、マシンビジョンシステムの能力が大幅に向上しています。AIアルゴリズム、特に畳み込みニューラルネットワーク(CNN)のようなディープラーニング技術は、画像処理とパターン認識に革命をもたらしました。膨大なデータセットから学習する能力により、マシンビジョンシステムは現在、物体、顔、シーンを正確に識別し、分類することができます。この進歩により、顔認識、自律走行車、医療用画像処理、セキュリティ監視などのアプリケーションで目覚ましい改善が見られています。AIが進化を続ける中、マシンビジョンはより洗練され、適応性が高く、さらに複雑な視覚課題に取り組むことができるようになり、マシンビジョン分野の成長とイノベーションをさらに促進すると期待されています。
インダストリー4.0と自動化の到来
インダストリー4.0の到来と、さまざまな産業における自動化の普及は、市場成長を促進する主な要因です。スマートマニュファクチャリングの時代、企業は生産プロセスの最適化、一貫した製品品質の確保、不良品の最小化に努めています。マシンビジョン技術は、製造ワークフロー全体を通して自動検査、正確な欠陥検出、リアルタイムの品質管理を提供することで、これらの目的を達成する上で重要な役割を果たしています。マシンビジョンをロボットシステムやモノのインターネット(IoT)機器と統合することで、企業は作業を合理化し、人的ミスを減らし、全体的な効率を高めることができます。生産性向上と運用コスト削減の絶え間ない追求が、産業分野におけるマシンビジョンソリューションの需要を後押しし続けています。
アプリケーションと業種の拡大
マシンビジョンは汎用性が高いため、さまざまなアプリケーションや業界で広く採用されています。マシンビジョンは従来の製造業だけでなく、農業、ヘルスケア、小売業、エンターテイメントなど様々な分野で利用されています。農業分野では、作物のモニタリング、収穫量予測、精密農業に役立っています。ヘルスケア分野では、医療診断、画像解析、ロボット支援手術などに役立っています。小売業界では、レジ不要のチェックアウトシステム、在庫管理、顧客分析に役立っています。さらに、マシンビジョンは、ジェスチャー認識や拡張現実(AR)体験のために、エンターテインメントやゲームで採用されることが増えています。プロセスを強化し、貴重な洞察を提供し、様々な領域で意思決定を改善する技術の能力は、マシンビジョン市場の成長を刺激すると思われます。
The global machine vision market size reached USD 14.1 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 26.7 Billion by 2033, exhibiting a growth rate (CAGR) of 6.97% during 2025-2033. The increasing demand for automation and quality control in manufacturing industries, numerous advancements in artificial intelligence and deep learning algorithms, and the rising need for efficient inspection are some of the major factors propelling the market.
Machine vision, also known as computer vision, is a field of artificial intelligence (AI) and image processing that enables machines, typically computers, to interpret and understand visual information from the world. It involves the development of algorithms and techniques that allow machines to analyze, process, and extract meaningful insights from images or videos. Machine vision systems utilize cameras or other imaging devices to capture visual data and then use various computational methods to detect patterns, recognize objects, track movements, and perform tasks that require visual understanding. As a result, machine vision technology finds applications in diverse industries, such as robotics, autonomous vehicles, quality control, and medical imaging.
The rising adoption of machine vision systems due to the increasing demand for automation and quality control across industries, including manufacturing, automotive, electronics, and pharmaceuticals, will stimulate the growth of the market during the forecast period. These systems enhance production efficiency, reduce errors, and ensure consistent product quality. Moreover, the advent of artificial intelligence (AI) and deep learning technologies that empower machine vision to achieve greater accuracy and versatility in image analysis and pattern recognition tasks has accelerated the product adoption rate. Furthermore, the widespread integration of machine vision for real-time monitoring and threat detection owing to the escalating need for safety and surveillance in various applications, such as smart cities, transportation, and healthcare, is propelling the market growth. Additionally, the decreasing costs of cameras, sensors, and processing hardware that makes machine vision solutions more affordable and accessible to a broader range of businesses has catalyzed the market growth.
Advancements in artificial intelligence and deep learning
The continuous advancements in artificial intelligence (AI) and deep learning have significantly boosted the capabilities of machine vision systems. AI algorithms, especially deep learning techniques like convolutional neural networks (CNNs), have revolutionized image processing and pattern recognition. With the ability to learn from vast datasets, machine vision systems can now accurately identify and categorize objects, faces, and scenes. This progress has led to remarkable improvements in applications such as facial recognition, autonomous vehicles, medical imaging, and security surveillance. As AI continues to evolve, machine vision is expected to become more sophisticated, adaptable, and capable of tackling even more complex visual challenges, further driving growth and innovation in the machine vision landscape.
Advent of Industry 4.0 and automation
The advent of Industry 4.0 and the widespread adoption of automation across different industries represent the major factors fueling the market growth.. In the era of smart manufacturing, businesses strive to optimize their production processes, ensure consistent product quality, and minimize defects. Machine vision technology plays a crucial role in achieving these objectives by providing automated inspection, precise defect detection, and real-time quality control throughout the manufacturing workflow. By integrating machine vision with robotic systems and the Internet of Things (IoT) devices, companies can streamline operations, decrease human errors, and enhance overall efficiency. The relentless pursuit of improved productivity and reduced operational costs continues to propel the demand for machine vision solutions in the industrial sector.
Expansion of applications and industry verticals
Machine vision's versatility has led to its widespread adoption in an expanding array of applications and industry verticals. Beyond its traditional use in manufacturing, machine vision now finds applications in diverse sectors such as agriculture, healthcare, retail, and entertainment. In the agriculture industry, it aids in crop monitoring, yield prediction, and precision farming. In healthcare, machine vision assists with medical diagnostics, image analysis, and robotic-assisted surgeries. In the retail sector, it facilitates cashier-less checkout systems, inventory management, and customer analytics. Furthermore, machine vision is increasingly being employed in entertainment and gaming for gesture recognition and augmented reality (AR) experiences. The technology's ability to enhance processes, provide valuable insights, and improve decision-making across various domains will stimulate the growth of the market for machine vision.
Vision systems dominate the market
Vision systems, also known as machine vision systems, are sophisticated technologies that enable machines to perceive and interpret visual information from the surrounding environment. These systems consist of cameras or other imaging devices, image processing software, and advanced algorithms that analyze and extract meaningful data from images or videos. Vision systems can perform various tasks, including object recognition, defect detection, measurement, sorting, and tracking. By providing machines with the ability to ""see"" and understand the world, vision systems aid in revolutionizing industries across the board.
Furthermore, they enhance automation and quality control in manufacturing, optimize processes in logistics and packaging, improve medical diagnostics and healthcare, and bolster security and surveillance systems. The increasing demand for intelligent, data-driven solutions to boost productivity, accuracy, and efficiency will propel the growth of the market as vision systems become indispensable tools for businesses across diverse sectors.
Hardware holds the largest share in the market
Hardware refers to the physical components and devices used to capture, process, and transmit visual data. It typically includes cameras, lenses, image sensors, lighting systems, frame grabbers, processing units (such as GPUs or specialized vision processors), and communication interfaces. These hardware components form the foundation of machine vision systems, enabling the acquisition of visual information from the environment. The performance, accuracy, and capabilities of the hardware directly impact the overall effectiveness and efficiency of machine vision applications.
As hardware technology advances, with improvements in sensor resolution, faster processing speeds, and higher data throughput, machine vision systems become more powerful, versatile, and accessible. Upgraded hardware allows real-time processing, higher-quality imaging, and more complex algorithms, which in turn favors the expansion of machine vision into new industries and applications, making it a major driving force behind the growth of the market.
Flaw detection represents the leading application segment
Flaw detection refers to the process of identifying defects, imperfections, or abnormalities in products or materials during manufacturing or quality control processes. Machine vision systems use advanced imaging techniques and algorithms to analyze visual data and compare it against predefined standards to detect flaws accurately and efficiently. Flaw detection plays a crucial role in ensuring product quality, reducing waste, and maintaining consistent standards in various industries such as manufacturing, automotive, electronics, and pharmaceuticals. As industries increasingly prioritize quality control and automation, the demand for reliable flaw detection solutions has grown significantly. Machine vision's ability to provide fast, non-destructive, and precise flaw detection has become a driving force behind the adoption of machine vision technology. As the market recognizes the potential of machine vision in flaw detection to optimize production processes, enhance product reliability, and reduce costs, its growth and integration across industries continue to accelerate.
Electronics and semiconductor account for the majority of the share in the market
The electronics and semiconductor industry significantly contributes to the market growth due to its rigorous demand for high-quality production and precision manufacturing processes. In this industry, the miniaturization of components and the complexity of integrated circuits require meticulous inspection and defect detection at microscopic levels. Machine vision systems offer a reliable and efficient solution for inspecting semiconductor wafers, PCBs, electronic components, and assembly processes. They ensure consistent product quality, reduce defects, and improve overall manufacturing efficiency. As technological advancements continue to push the boundaries of electronics and semiconductors, the need for advanced machine vision solutions becomes even more critical. The ability of machine vision to perform high-speed, accurate inspection and analysis enables electronics and semiconductor manufacturers to stay competitive and meet the ever-increasing demands for quality and innovation. Therefore, the growth of the electronics and semiconductor industry goes hand in hand with the expansion of the machine vision market.
Asia Pacific exhibits a clear dominance in the market
The report has also provided a comprehensive analysis of all the major regional markets, which include North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa. According to the report, Asia Pacific accounted for the largest market share.
Asia Pacific is a significant driving force behind the growth of the machine vision market due to several key factors. Firstly, the region's thriving manufacturing industries, particularly in countries like China, Japan, South Korea, and India, are increasingly adopting automation and robotics to improve productivity and product quality. Machine vision plays a vital role in these processes by providing precise inspection, defect detection, and assembly verification. Secondly, the rising demand for consumer electronics, automotive, and semiconductor products in the Asia Pacific region fuels the need for stringent quality control, which further boosts the adoption of machine vision systems.
Additionally, the increasing focus on industrial automation, Industry 4.0 initiatives, and smart manufacturing practices in the region drive the integration of machine vision technologies to optimize production processes and enhance efficiency. The rapid technological advancements and the presence of major machine vision solution providers in Asia Pacific also contribute to its driving role in the expansion of the global machine vision industry.
The market is experiencing a lower-than-anticipated demand compared to pre-pandemic levels. However, this is likely to witness a paradigm shift over the next decade with the growing integration of machine vision with edge computing and IoT devices, enabling real-time analysis and decision-making at the edge of networks, leading to reduced latency and improved responsiveness in various applications. Additionally, key players are developing 3D machine vision technologies that enable precise depth perception and object reconstruction, revolutionizing applications such as robot guidance and augmented reality. Furthermore, ongoing advancements in multispectral and hyperspectral imaging have enhanced the ability to capture and analyze data beyond the visible spectrum, leading to new possibilities in fields such as precision agriculture, medical diagnostics, and materials inspection. We also expect the market to witness new entrants, consolidation of portfolio and increased collaborations among key players to drive healthy competition within the machine vision domain.