市场调查报告书
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1504907
製造业人工智慧市场规模、份额和成长分析:按组件、按技术、按应用、按最终用户、按地区 - 行业预测,2024-2031 年Artificial Intelligence in Manufacturing Market Size, Share, Growth Analysis, By Component, By Device Type, By End User, By Region - Industry Forecast 2024-2031 |
2022 年製造业人工智慧的市场规模预计为25.8 亿美元,预计到2031 年将达到646.3 亿美元,高于2023 年的32 亿美元,预测期(2024-2031 年)复合年增长率预计为45.6 。
近年来,在广泛采用先进技术来优化和改进製造流程的推动下,製造业市场的人工智慧经历了显着成长。人工智慧在该领域的应用涵盖预测性维护、品管、供应链优化和即时监控。随着製造商努力提高效率、降低成本并保持竞争力,整合人工智慧技术变得至关重要。该市场包括针对製造业特定需求量身定制的各种解决方案,包括机器学习、电脑视觉和自然语言处理。工业 4.0 的趋势强调了技术对全球工业格局的变革性影响,特别是在製造业中,透过资料分析、自动化和智慧系统整合来提高业务效率。
Artificial Intelligence (AI) in Manufacturing Market size was valued at USD 2.58 Billion in 2022 and is expected to grow from USD 3.20 Billion in 2023 to reach USD 64.63 Billion by 2031, at a CAGR of 45.6% during the forecast period (2024-2031).
The market for Artificial Intelligence (AI) in manufacturing has experienced significant growth recently, fuelled by the widespread adoption of advanced technologies aimed at optimizing and refining manufacturing processes. Applications of AI in this sector span predictive maintenance, quality control, supply chain optimization, and real-time monitoring. As manufacturers strive to enhance efficiency, reduce costs, and maintain competitiveness, integrating AI technologies has become crucial. This market encompasses diverse solutions such as machine learning, computer vision, and natural language processing, tailored to meet the specific needs of manufacturing. The trend towards Industry 4.0 underscores the transformative impact of technology on global business landscapes, particularly in enhancing operational efficiency through data analytics, automation, and smart system integration within manufacturing.
Top-down and bottom-up approaches were used to estimate and validate the size of the Artificial Intelligence (AI) in Manufacturing market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Artificial Intelligence (AI) in Manufacturing Market Segmental Analysis
Artificial Intelligence (AI) in manufacturing market is segmented into several key categories, reflecting its comprehensive scope and varied applications. By Component, the market is divided into hardware, software, and services. By Technology, the market includes machine learning (ML), computer vision, context awareness, and natural language processing (NLP). In Application, AI in manufacturing is applied to material movement, predictive maintenance and machinery inspection, production planning, field services, quality control and reclamation, and others. By End User, the market serves various industries, including semiconductors and electronics, energy and power, medical devices, automobiles, heavy metal and machine manufacturing, and others.
Drivers of the Artificial Intelligence (AI) in Manufacturing Market
Automation leverages advanced technology to execute tasks with enhanced accuracy, efficiency, and uniformity, resulting in heightened productivity and minimized labour expenditures. AI-driven robotics and autonomous systems are fundamentally transforming conventional manufacturing techniques by simplifying repetitive operations, maximizing the efficient use of resources, and facilitating instantaneous decision-making processes. In today's industrial landscape, automation plays a pivotal role in enhancing operational efficiencies across various sectors. By harnessing AI-powered robotics and autonomous systems, businesses can achieve higher levels of precision and speed in their production processes. This technological integration not only reduces manual labour costs but also optimizes resource allocation, thereby fostering a more sustainable and competitive manufacturing environment. Moreover, the ability of these systems to make real-time decisions based on vast datasets enhances overall agility and responsiveness, ensuring businesses can adapt swiftly to dynamic market demands. Ultimately, automation represents a transformative shift towards more efficient, cost-effective, and adaptable industrial practices in the modern era.
Restraints in the Artificial Intelligence (AI) in Manufacturing Market
Implementing AI in manufacturing typically involves substantial financial investments, such as acquiring AI tools, upgrading networks, modifying production lines, and training personnel. These initial costs can be prohibitive for many organizations, especially smaller companies and SMEs, hindering their ability to adopt AI solutions. These financial commitments are necessary to integrate AI seamlessly into existing manufacturing processes, ensuring efficiency gains and competitive advantages. However, the challenge lies in balancing the upfront expenditures with long-term benefits, which may deter smaller enterprises despite the potential for enhanced productivity and innovation that AI promises in the manufacturing sector.
Market Trends of Artificial Intelligence (AI) in Manufacturing Market
The AI market is increasingly driven by specialized hardware, a crucial trend influencing supply-side dynamics. Such hardware is designed specifically to accelerate the execution of AI applications while optimizing energy consumption. Examples include Lisp machines, neuromorphic engineering, event cameras, and physical neural networks, each catering to distinct AI functionalities. Semiconductor firms are strategically adjusting their strategies to align with market needs, aiming to ensure seamless integration across different layers of the technology stack.