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人工智能

市場調查報告書

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1616434

製造業的人工智能市場:報價環，各技術，各終端用戶產業，各地區，2024年～2031年

Artificial Intelligence in Manufacturing Market By Offering, Technology (Machine Learning, Computer Vision, Natural Language Processing, Context Awareness), End-User Industry, & Region for 2024-2031

出版日期: 2024年09月03日 | 出版商:

Verified Market Research | 英文 202 Pages | 商品交期: 2-3個工作天內

價格

簡介目錄

2024-2031 年製造業人工智慧市場評估

人工智慧正在加快產品開發週期並推動製造業創新。因此，隨著產品開發與創新的加速，2024年市場規模將超過23.1億美元，2031年估值將達到359億美元。

人工智慧透過實現更準確、更有效率的缺陷檢測，正在徹底改變製造業的品質控制。因此，由於品質控制流程的加強，2024年至2031年市場將以47.80%的複合年增長率成長。

製造業人工智慧市場定義/概述

人工智慧 (AI) 正在利用先進演算法和機器學習來提高效率、生產和決策，從而改變製造業。神經網路、電腦視覺和機器人等技術使機器能夠執行模仿人類智慧的任務，例如預測性維護、品質控制和供應鏈優化。

在製造業中，人工智慧可以提前預測設備故障，減少停機時間和成本，並提高整體營運效率。機器學習模型可偵測缺陷並確保品質控制，並部署機器人來執行需要準確性和一致性的精確、重複性任務。人工智慧驅動的系統還透過簡化需求預測、庫存管理和物流來優化供應鏈管理，減少浪費並提高效率。

隨著人工智慧的不斷發展，它可能會推動以最少的人為幹預開發更多自主工廠。物聯網 (IoT) 整合促進的即時數據收集和分析使製造商能夠更靈活、快速地運作。它還支援敏捷生產的高級定制，使企業能夠快速適應不斷變化的市場需求。最終，人工智慧將促進製造業的創新、永續性和彈性，從而形成更有效率、更具適應性的生產系統。

人工智慧技術在製造業的快速採用將如何加速人工智慧在製造業市場的成長？

機器學習、電腦視覺、大數據分析等人工智慧技術在製造業迅速普及。這些技術提供即時數據處理和分析，從而實現更好的決策、優化的營運和更高的產品品質。根據麥肯錫全球研究院的報告，人工智慧有潛力在製造和供應鏈規劃中創造 1.2 兆美元至 2 兆美元的價值。世界經濟論壇預測，到 2025 年，人類、機器和演算法之間的分工可以創造 9,700 萬個新就業機會。

使用人工智慧進行預測維護在製造業中變得越來越重要，以減少停機時間和維護成本。根據美國能源部的報告，預測性維護可以降低 30% 的維護成本，消除 70% 的故障，並減少 40% 的停機時間。美國品質研究協會的一項研究表明，將人工智慧引入品質控制可以將缺陷率降低高達 50%。根據凱捷研究院的數據，51% 的歐洲製造商已經實施了由人工智慧驅動的品質控制解決方案，其中 28% 的製造商表示生產力提高了 30%。

人工智慧正在透過提高預測準確性和營運效率來改變供應鏈管理。 IBM 調查顯示，85% 的供應鏈領導者認為人工智慧將在未來三到五年內對供應鏈績效產生重大影響。據 Gartner 稱，到 2024 年，50% 的供應鏈組織將投資支援人工智慧和高級分析的應用程式。普華永道的一項研究顯示，目前有 35% 的製造商正在使用人工智慧來創新產品，另有 42% 的製造商計劃很快使用人工智慧。根據世界智慧財產權組織（WIPO）統計，2010年至2020年，人工智慧相關專利申請量成長了400%以上，反映了該領域技術創新的快速發展。人工智慧在提高製造流程的能源效率和永續性方面發揮關鍵作用。根據美國能源部的報告，人工智慧驅動的系統可以將製造工廠的能源消耗降低高達 20%。

缺乏熟練的人力資源以及高昂的初始投資和實施成本如何阻礙人工智慧在製造業市場的成長？

一個主要的抑制因素是缺乏在人工智慧和製造方面具備必要專業知識的人才。這種技能差距阻礙了人工智慧在製造業的發展和實施。根據世界經濟論壇《2020 年就業未來報告》，隨著技術採用的增加，到2025 年，50% 的員工將需要重新培訓，數據分析師、科學家、人工智慧和機器學習專家被列為最熱門的新增職位。人工智慧技術及其與現有製造系統的整合相關的高昂初始成本是一個重大障礙，特別是對於中小企業（SME）而言。根據資訊科技創新基金會（ITIF）的報告，工業機器人的平均成本約為27,000美元，加上軟體、整合和維護成本。

由於人工智慧系統嚴重依賴數據，對數據安全、隱私和智慧財產權保護的擔憂限制了一些製造商全面採用人工智慧技術。根據美國國家標準與技術研究所 (NIST) 的報告，製造業是第二大網路攻擊目標產業，佔所有事件的 23.2%。

Artificial Intelligence (AI) is transforming manufacturing by leveraging advanced algorithms and machine learning to enhance efficiency, production, and decision-making. Technologies such as neural networks, computer vision, and robotics empower machines to perform tasks that mimic human intelligence, including predictive maintenance, quality control, and supply chain optimization.

In manufacturing, AI helps reduce downtime and costs by predicting equipment failures before they occur, improving overall operational efficiency. Machine learning models can detect defects and ensure quality control, while robots are deployed for precise, repetitive tasks that require accuracy and consistency. AI-driven systems also optimize supply chain management by forecasting demand, managing inventory, and streamlining logistics, leading to reduced waste and enhanced efficiency.

As AI continues to evolve, it will drive the development of more autonomous factories with minimal human intervention. Real-time data collection and analysis, facilitated by Internet of Things (IoT) integration, will enable manufacturers to operate more flexibly and responsively. This will also support advanced customization for agile production, allowing companies to quickly adapt to changing market demands. Ultimately, AI will foster innovation, sustainability, and resilience in manufacturing, leading to more efficient, adaptable production systems.

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How does the Rapid Adoption of AI Technologies in Manufacturing Surge the Growth of Artificial Intelligence in the Manufacturing Market?

AI technologies such as machine learning, computer vision, and big data analytics are rapidly gaining traction in manufacturing. These technologies offer real-time data processing and analysis, resulting in better decision-making, optimized operations, and higher product quality. According to a McKinsey Global Institute report, AI has the potential to create between USD 1.2 Trillion and USD 2 Trillion in value in the manufacturing and supply chain planning sectors. The World Economic Forum predicts that by 2025, 97 million new jobs may emerge in the division of labor between humans, machines, and algorithms.

AI-powered predictive maintenance is becoming crucial in manufacturing to reduce downtime and maintenance costs. The U.S. Department of Energy reports that predictive maintenance can reduce maintenance costs by 30%, eliminate breakdowns by 70%, and reduce downtime by 40%. A study by the American Society for Quality found that implementing AI in quality control can reduce defect rates by up to 50%. According to Capgemini Research Institute, 51% of European manufacturers are implementing AI-powered quality control solutions, with 28% of them reporting a 30% increase in productivity.

AI is transforming supply chain management by improving forecasting accuracy and operational efficiency. A study by IBM found that 85% of supply chain leaders believe AI will significantly impact their supply chain performance in the next three to five years. According to Gartner, by 2024, 50% of supply chain organizations will invest in applications that support artificial intelligence and advanced analytics capabilities. A PwC study found that 35% of manufacturers are currently using AI to innovate products, with an additional 42% planning to do so shortly. According to the World Intellectual Property Organization (WIPO), AI-related patent applications increased by more than 400% from 2010 to 2020, indicating rapid innovation in the field. AI is playing a crucial role in making manufacturing processes more energy-efficient and sustainable. The U.S. Department of Energy reports that AI-powered systems can reduce energy consumption in manufacturing plants by up to 20%.

How the Lack of Skilled Personnel and High Initial Investment and Implementation Costs Impede the Growth of Artificial Intelligence in the Manufacturing Market?

The significant restraint is the shortage of personnel with the necessary expertise in both AI and manufacturing. This skills gap is hampering the growth and implementation of AI in the manufacturing sector. The World Economic Forum's "Future of Jobs Report 2020" found that 50% of all employees will need reskilling by 2025 as the adoption of technology increases, with data analysts and scientists, AI and machine learning specialists among the top emerging jobs. The substantial upfront costs associated with AI technologies and their integration into existing manufacturing systems pose a significant barrier, especially for small and medium-sized enterprises (SMEs). A report by the Information Technology and Innovation Foundation (ITIF) states that the average cost of an industrial robot is around $27,000, with additional costs for software, integration, and maintenance.

As AI systems rely heavily on data, concerns about data security, privacy, and intellectual property protection are restraining some manufacturers from fully embracing AI technologies. The U.S. National Institute of Standards and Technology (NIST) reported that manufacturing is the second most targeted industry for cyber-attacks, accounting for 23.2% of all incidents.

Category-Wise Acumens

How does the Increasing Popularity for Advanced Automation Surge the Growth of Computer Vision Segment?

The computer vision segment is poised for significant growth in artificial intelligence in the manufacturing market, driven by its ability to provide accurate and actionable insights for various manufacturing processes. The increasing demand for advanced automation and efficiency in manufacturing. Computer vision's integration with robotics plays a crucial role in process optimization, as it enables robots to "see" and interpret their environment, making production more efficient and precise.

In addition, the growing adoption of robotics across multiple industries, including automotive, electronics, and consumer goods, has further fueled the application of computer vision for process improvement and quality control. As industries continue to embrace automation and intelligent systems, computer vision is expected to play an increasingly vital role in driving efficiency, safety, and optimization within manufacturing environments.

How the Increasing Prevalence of Diseases and Growing Advanced Medical Equipment Foster the Growth of Medical Devices Segment?

The medical devices segment is emerging as a dominant segment in the artificial intelligence (AI) manufacturing market, driven by the rising prevalence of diseases globally and the growing need for advanced medical equipment. As healthcare systems expand and modernize, there is increasing demand for innovative, efficient, and reliable medical devices that can enhance patient outcomes and streamline medical processes. AI plays a pivotal role in this transformation, offering opportunities to manufacture cutting-edge devices that disrupt traditional methods and improve diagnostic and treatment capabilities.

AI integration in the manufacturing of medical equipment allows for the development of smarter, more precise devices that can operate with greater efficiency. From surgical robots to AI-driven diagnostic tools, these advancements are enabling manufacturers to create equipment that delivers real-time insights and enhances patient care. One notable example is Australia-based EMVision, which has harnessed NVIDIA's AI platform and DGX systems to develop a lightweight, portable brain scanner. This AI-powered device can diagnose brain strokes within minutes, revolutionizing stroke care by providing quick, accurate diagnoses in emergencies.

Country/Region-wise Acumens

How the Strong Presence of Tech Giants and AI Startups Foster the Growth of Artificial Intelligence in Manufacturing Market in North America?

North America substantially dominates artificial intelligence in the manufacturing market owing to the strong presence of tech giants and AI startups. North America, particularly the United States, is home to many of the world's leading tech companies and AI startups, driving innovation and adoption in AI manufacturing solutions. According to the National Science Foundation, the United States leads the world in AI research output, producing 27% of all AI research papers globally in 2020. A report by the Center for Data Innovation shows that the US has 1,393 AI companies, compared to 736 in China and 521 in the EU.

Both the U.S. and Canadian governments are making significant investments in AI research and development, as well as in modernizing the manufacturing sector. The U.S. National Science Foundation (NSF) and the National Institute of Standards and Technology (NIST) announced over USD 201 Million in funding for artificial intelligence research institutes in 2021.

According to the U.S. Government Accountability Office, federal agencies obligated USD 1.5 Billion in AI-related research and development spending in fiscal year 2020. North American manufacturers are increasingly embracing Industry 4.0 technologies, including AI, to improve efficiency and competitiveness. A survey by the National Association of Manufacturers found that 77% of manufacturers say increasing productivity is the top reason to adopt new technologies, including AI.

How the Rapid Digitization and Industry 4.0 Adoption Accelerates the Growth of Artificial Intelligence in the Manufacturing Market in Asia Pacific?

Asia Pacific is anticipated to witness the fastest growth in artificial intelligence in the manufacturing market. The Asia Pacific region is experiencing a swift transition towards digitization and Industry 4.0, driving the adoption of AI in manufacturing. According to a report by McKinsey, Asia could account for 40% of the world's total Industry 4.0 market by 2030. The Asian Development Bank Institute states that the digital economy in Asia Pacific is expected to reach USD 1.7 Trillion by 2025, up from USD 1.35 Trillion in 2019. Many countries in the Asia Pacific region have launched national AI strategies and are heavily investing in smart manufacturing initiatives. China's State Council announced plans to build a USD 150 Billion AI industry by 2030. According to the International Federation of Robotics, five major Asian markets China, Japan, South Korea, Taiwan, and India accounted for 74% of global industrial robot installations in 2020.

The Asia Pacific region's significant manufacturing base, coupled with rising labor costs, is driving the adoption of AI to improve efficiency and reduce expenses. The United Nations Conference on Trade and Development (UNCTAD) reports that Asia's share of global manufacturing output increased from 31.6% in 1990 to 51.1% in 2018. According to the International Labour Organization, average wages in Asia and the Pacific grew by 3.5% in 2019, the highest among all regions globally.

Competitive Landscape

The competitive landscape of the Artificial Intelligence in Manufacturing Market is dynamic and evolving, with a growing number of players vying for market share. The ability to develop and deliver innovative AI solutions that address the specific needs of manufacturing customers will be critical for success in this competitive market.

The organizations are focusing on innovating their product line to serve the vast population in diverse regions. Some of the prominent players operating in the artificial intelligence in the manufacturing market include:

Siemens
IBM
Intel Corporation
NVIDIA Corporation
General Electric Company
Microsoft Corporation
Google
Amazon Web Services
Rockwell Automation

Latest Developments:

In October 2023, Google Cloud announced the launch of dedicated generative AI solutions for the healthcare and manufacturing industries, to enhance efficiency and promote digital transformation. This technique marked a significant advancement in employing AI to achieve industry-specific solutions.
In April 2023, Siemens announced the collaboration with Microsoft to enhance industrial AI and transform product lifecycle management. The integration of Siemens Teamcenter software with Microsoft Teams and Azure OpenAI Service's language models is intended to increase creativity and effectiveness.