製造业的人工智能市场:报价环，各技术，各终端用户产业，各地区，2024年～2031年

2024-2031 年製造业人工智慧市场评估

人工智慧正在加快产品开发週期并推动製造业创新。因此，随着产品开发与创新的加速，2024年市场规模将超过23.1亿美元，2031年估值将达到359亿美元。

人工智慧透过实现更准确、更有效率的缺陷检测，正在彻底改变製造业的品质控制。因此，由于品质控制流程的加强，2024年至2031年市场将以47.80%的复合年增长率成长。

製造业人工智慧市场定义/概述

人工智慧 (AI) 正在利用先进演算法和机器学习来提高效率、生产和决策，从而改变製造业。神经网路、电脑视觉和机器人等技术使机器能够执行模仿人类智慧的任务，例如预测性维护、品质控制和供应链优化。

在製造业中，人工智慧可以提前预测设备故障，减少停机时间和成本，并提高整体营运效率。机器学习模型可侦测缺陷并确保品质控制，并部署机器人来执行需要准确性和一致性的精确、重复性任务。人工智慧驱动的系统还透过简化需求预测、库存管理和物流来优化供应链管理，减少浪费并提高效率。

随着人工智慧的不断发展，它可能会推动以最少的人为干预开发更多自主工厂。物联网 (IoT) 整合促进的即时数据收集和分析使製造商能够更灵活、快速地运作。它还支援敏捷生产的高级定制，使企业能够快速适应不断变化的市场需求。最终，人工智慧将促进製造业的创新、永续性和弹性，从而形成更有效率、更具适应性的生产系统。

人工智慧技术在製造业的快速采用将如何加速人工智慧在製造业市场的成长？

机器学习、电脑视觉、大数据分析等人工智慧技术在製造业迅速普及。这些技术提供即时数据处理和分析，从而实现更好的决策、优化的营运和更高的产品品质。根据麦肯锡全球研究院的报告，人工智慧有潜力在製造和供应链规划中创造 1.2 兆美元至 2 兆美元的价值。世界经济论坛预测，到 2025 年，人类、机器和演算法之间的分工可以创造 9,700 万个新就业机会。

使用人工智慧进行预测维护在製造业中变得越来越重要，以减少停机时间和维护成本。根据美国能源部的报告，预测性维护可以降低 30% 的维护成本，消除 70% 的故障，并减少 40% 的停机时间。美国品质研究协会的一项研究表明，将人工智慧引入品质控制可以将缺陷率降低高达 50%。根据凯捷研究院的数据，51% 的欧洲製造商已经实施了由人工智慧驱动的品质控制解决方案，其中 28% 的製造商表示生产力提高了 30%。

人工智慧正在透过提高预测准确性和营运效率来改变供应链管理。 IBM 调查显示，85% 的供应链领导者认为人工智慧将在未来三到五年内对供应链绩效产生重大影响。据 Gartner 称，到 2024 年，50% 的供应链组织将投资支援人工智慧和高级分析的应用程式。普华永道的一项研究显示，目前有 35% 的製造商正在使用人工智慧来创新产品，另有 42% 的製造商计划很快使用人工智慧。根据世界智慧财产权组织（WIPO）统计，2010年至2020年，人工智慧相关专利申请量成长了400%以上，反映了该领域技术创新的快速发展。人工智慧在提高製造流程的能源效率和永续性方面发挥关键作用。根据美国能源部的报告，人工智慧驱动的系统可以将製造工厂的能源消耗降低高达 20%。

缺乏熟练的人力资源以及高昂的初始投资和实施成本如何阻碍人工智慧在製造业市场的成长？

一个主要的抑制因素是缺乏在人工智慧和製造方面具备必要专业知识的人才。这种技能差距阻碍了人工智慧在製造业的发展和实施。根据世界经济论坛《2020 年就业未来报告》，随着技术采用的增加，到2025 年，50% 的员工将需要重新培训，数据分析师、科学家、人工智慧和机器学习专家被列为最热门的新增职位。人工智慧技术及其与现有製造系统的整合相关的高昂初始成本是一个重大障碍，特别是对于中小企业（SME）而言。根据资讯科技创新基金会（ITIF）的报告，工业机器人的平均成本约为27,000美元，加上软体、整合和维护成本。

由于人工智慧系统严重依赖数据，对数据安全、隐私和智慧财产权保护的担忧限制了一些製造商全面采用人工智慧技术。根据美国国家标准与技术研究所 (NIST) 的报告，製造业是第二大网路攻击目标产业，占所有事件的 23.2%。

目录

第1章 简介

• 市场定义
• 市场区隔
• 调查手法

第2章 摘要整理

• 主要调查结果
• 市场概要
• 市场亮点

第3章 市场概要

• 市场规模与成长的可能性
• 市场趋势
• 推动市场要素
• 阻碍市场要素
• 市场机会
• 波特的五力分析

第4章 製造业的人工智能市场:报价环

• 硬体设备
• 软体
• 服务

第5章 製造业的人工智能市场:各技术

• 机器学习
• computer vision
• 自然语言处理(NLP)
• 情境感知

第6章 製造业的人工智能市场:各产业

• 汽车
• 医疗设备
• 半导体·电子产品
• 能源·电力
• 重金属·机器製造
• 食品和饮料
• 其他

第7章 地区分析

• 北美
• 美国
• 加拿大
• 墨西哥
• 欧洲
• 英国
• 德国
• 法国
• 义大利
• 亚太地区
• 中国
• 日本
• 印度
• 澳洲
• 南美
• 巴西
• 阿根廷
• 智利
• 中东·非洲
• 南非
• 沙乌地阿拉伯
• 阿拉伯联合大公国

第8章 市场动态

• 推动市场要素
• 阻碍市场要素
• 市场机会
• COVID-19对市场的影响

第9章 竞争情形

• 主要企业
• 市场占有率分析

第10章 企业简介

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

第11章 市场展望和机会

• 新兴技术
• 今后的市场趋势
• 投资机会

第12章 附录

• 简称清单
• 出处和参考文献

Artificial Intelligence in Manufacturing Market Valuation - 2024-2031

AI is speeding up product development cycles and fostering innovation in manufacturing. Thus, the acceleration of product development and innovation surged the growth of market size surpassing USD 2.31 Billion in 2024 to reach the valuation of USD 35.9 Billion by 2031.

AI is revolutionizing quality control in manufacturing by enabling more accurate and efficient defect detection. Thus, the enhancement of quality control processes enables the market to grow at a CAGR of 47.80% from 2024 to 2031.

Artificial Intelligence in Manufacturing Market: Definition/ Overview

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.

TABLE OF CONTENTS

1. Introduction

• Market Definition
• Market Segmentation
• Research Methodology

2. Executive Summary

• Key Findings
• Market Overview
• Market Highlights

3. Market Overview

• Market Size and Growth Potential
• Market Trends
• Market Drivers
• Market Restraints
• Market Opportunities
• Porter's Five Forces Analysis

4. Artificial Intelligence In Manufacturing Market, By Offering

• Hardware
• Software
• Services

5. Artificial Intelligence In Manufacturing Market, By Technology

• Machine Learning
• Computer vision
• Natural Language Processing (NLP)
• Context Awareness

6. Artificial Intelligence In Manufacturing Market, By Industry

• Automotive
• Medical Devices
• Semiconductor & Electronics
• Energy & Power
• Heavy Metal & Machine Manufacturing
• Food & Beverages
• Others

7. Regional Analysis

• North America
• United States
• Canada
• Mexico
• Europe
• United Kingdom
• Germany
• France
• Italy
• Asia-Pacific
• China
• Japan
• India
• Australia
• Latin America
• Brazil
• Argentina
• Chile
• Middle East and Africa
• South Africa
• Saudi Arabia
• UAE

8. Market Dynamics

• Market Drivers
• Market Restraints
• Market Opportunities
• Impact of COVID-19 on the Market

9. Competitive Landscape

• Key Players
• Market Share Analysis

10. Company Profiles

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

11. Market Outlook and Opportunities

• Emerging Technologies
• Future Market Trends
• Investment Opportunities

12. Appendix

• List of Abbreviations
• Sources and References