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市场调查报告书
商品编码
1574132

人工智慧质检市场－2024年至2029年预测

AI Quality Inspection Market - Forecasts from 2024 to 2029
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 140 Pages | 商品交期: 最快1-2个工作天内

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简介目录

人工智慧质检市场预计复合年增长率为20.53%，市场规模将从2024年的278.08亿美元增加到2029年的707.47亿美元。

当使用软体主导的人工智慧和视觉技术时，人工智慧品质检测有助于检测和处理半导体、药品、纺织品和汽车製造等产品中的不一致性。基于人工智慧的品质测试应用因其高精度和节省时间而在半导体行业、医疗保健、服饰製造、汽车製造等领域越来越受欢迎。

人工智慧品质检测软体可以基于机器学习模型或作为预先训练的软体服务来製造。人工智慧品管技术提供的高精度是相对于手动品管的一大优势，使其成为全球主要製造公司的选择。因此，考虑到对基于人工智慧的产品的需求不断增加以及影响人工智慧质检软体消费的其他因素，基于人工智慧的品管市场预计在预测期内将达到更大的市场规模。

人工智慧质检市场驱动因素：

  • 製造业越来越多地采用基于人工智慧的品管软体，预计将增加需求

这种成长是由于生产劣质产品而导致製造公司的营运成本增加。例如，丰田汽车公司最近因製造缺陷而遭受了13亿美元的损失。损坏的部件常常未被发现并用于最终产品的製造过程。结果，製造企业的营运费用增加，并且有缺陷的产品无法在市场上销售。此类案例在大量生产产品的企业中屡见不鲜。

使用人眼进行手动品管可能无法侦测到大批量的缺陷。为了克服这一限制，世界各地的主要企业正在积极投资基于人工智慧的品质测试软体，以及早发现有缺陷的产品并防止额外成本。

人工智慧质检市场地域展望

  • 北美在预测期内将经历指数级增长

北美是国际人工智慧市场的强大技术进步力量，正积极投资扩大人工智慧软体的范围和应用，包括人工智慧品管和检测。顶级软体公司正在开发并竞相加强其人工智慧产品和服务组合。例如，微软推出了 Spyglass Visual Inspection，这是一款虚拟人工智慧品质检测产品，它整合了技术服务来识别任何产品缺陷。

此外，IBM还发布了其最新的人工智慧质检产品，该产品实现了联邦学习模型。除了这些老牌公司之外，美国的几家新兴企业也致力于创新新的模型和方法，以改善人工智慧辅助品质检测。例如，波士顿新兴企业Neurala Inc. 的基于人工智慧的品管应用程式已被世界领先製造商之一的 IHI 公司采用。因此，考虑到目前AI市场的趋势以及近期美国AI质检产品的市场开拓，可以预测北美AI质检市场在预测期内很可能会扩大。

为什么要购买这份报告？

  • 富有洞察力的分析：获得涵盖关键和新兴地区的深入市场洞察，重点关注客户细分、政府政策和社会经济因素、消费者偏好、行业部门和其他子区隔。
  • 竞争格局：了解世界主要企业采取的策略策略，并了解透过正确的策略渗透市场的潜力。
  • 市场驱动因素和未来趋势：探索动态因素和关键市场趋势以及它们将如何影响未来市场发展。
  • 可行的建议：利用洞察力做出策略决策，在动态环境中释放新的业务流和收益。
  • 面向广大受众：对于新兴企业、研究机构、顾问、中小型企业和大型企业有用且具有成本效益。

公司使用我们的报告的目的是什么？

产业和市场考量、机会评估、产品需求预测、打入市场策略、地理扩张、资本投资决策、法律规范与影响、新产品开发、竞争影响。

调查范围

  • 2022年至2029年历史资料与预测
  • 成长机会、挑战、供应链前景、法规结构、顾客行为、趋势分析
  • 竞争对手的市场状况、策略与市场占有率分析
  • 包括国家在内的细分市场和地区的收益成长和预测评估
  • 公司简介（策略、产品、财务资讯、主要动态等）

AI质检市场細項分析如下：

按类型

  • 预习型
  • 深度学习

按最终用户

  • 半导体
  • 製药
  • 车
  • 纤维
  • 其他的

按地区

  • 北美洲
  • 美国
  • 加拿大
  • 墨西哥
  • 南美洲
  • 巴西
  • 阿根廷
  • 其他的
  • 欧洲
  • 英国
  • 德国
  • 法国
  • 义大利
  • 西班牙
  • 其他的
  • 中东/非洲
  • 沙乌地阿拉伯
  • UAE
  • 其他的
  • 亚太地区
  • 中国
  • 日本
  • 印度
  • 韩国
  • 澳洲
  • 新加坡
  • 印尼
  • 其他的

目录

第一章简介

  • 市场概况
  • 市场定义
  • 调查范围
  • 市场区隔
  • 货币
  • 先决条件
  • 基准年和预测年时间表
  • 相关利益者的主要利益

第二章调查方法

  • 研究设计
  • 调查过程

第三章执行摘要

  • 主要发现
  • CXO观点

第四章市场动态

  • 市场驱动因素
  • 市场限制因素
  • 波特五力分析
  • 产业价值链分析
  • 分析师观点

第五章人工智慧质检市场：按类型

  • 介绍
  • 预训练
  • 深度学习

第六章人工智慧品质检测市场：依最终用户分类

  • 介绍
  • 半导体
  • 製药
  • 车
  • 纤维
  • 其他的

第七章 人工智慧质检市场：按地区

  • 介绍
  • 北美洲
    • 按类型
    • 按最终用户
    • 按国家/地区
  • 南美洲
    • 按类型
    • 按最终用户
    • 按国家/地区
  • 欧洲
    • 按类型
    • 按最终用户
    • 按国家/地区
  • 中东/非洲
    • 按类型
    • 按最终用户
    • 按国家/地区
  • 亚太地区
    • 按类型
    • 按最终用户
    • 按国家/地区

第八章竞争环境及分析

  • 主要企业及策略分析
  • 市场占有率分析
  • 合併、收购、协议和合作
  • 竞争对手仪表板

第九章 公司简介

  • Intel Corp
  • Kitov Systems
  • Mitutoyo America Corporation
  • Landing AI
  • NEC Corporation
  • tunic AG
  • Robert Bosch GmbH
  • deevio GmbH
  • craftworks GmbH
  • Pleora Technologies Inc
简介目录
Product Code: KSI061614653

The AI quality inspection market is expected to grow at a CAGR of 20.53%, reaching a market size of US$70.747 billion in 2029 from US$27.808 billion in 2024.

When it comes to using software-driven artificial intelligence and vision technologies, AI quality inspection helps detect and process inconsistencies in products, including semiconductors, pharmaceuticals, textiles, and automotive manufacturing. Hence, AI-owned applications that make quality checks are becoming more common in the semiconductor industry as well as in medicine, clothing production, car-making industries, and others because of their precision and ability to save time.

The AI quality inspection software can be manufactured either based on the machine learning model or as a pre-trained software service. The precision offered by AI-powered quality control techniques is a significant advantage over manual quality control, making it the preferred choice for leading manufacturing companies worldwide. Therefore, considering the increasing demand for AI-based products and other factors influencing the consumption of AI quality inspection software, it can be expected that the AI-based quality control market will reach a larger market size in the forecast period.

AI quality inspection Market Drivers:

  • Increasing adoption of AI-based quality control software in the manufacturing sector is anticipated to increase the demand

The growth can be attributed to the increase in operating costs for manufacturing companies as a result of the production of poor-quality products. For instance, Toyota Company incurred a recent loss of $1.3 billion as a result of manufacturing defects. Often, when a damaged component goes undetected, it is used in the process of manufacturing the final product. This results in a rise in the operating expenses for the manufacturing company and leads to defective goods not being sold in the market. Such cases are prevalent in companies that engage in mass production of goods in batches.

The manual quality control offered by the human eye can sometimes fail to detect such failures in large batches. To overcome this limitation, leading manufacturing companies worldwide are actively investing in AI-based quality inspection software to identify defective goods earlier and prevent additional expenses.

AI Quality Inspection Market Geographical Outlook

  • North America is witnessing exponential growth during the forecast period

North America, being a strong technological evolution force in the international artificial intelligence market, has been actively investing in expanding the scope and applications of AI software, including AI quality control and inspection. The top companies in the software sector are working on developing and competing with other companies to enhance their AI products and services portfolio. For instance, Microsoft has introduced its virtual AI quality inspection product, Spyglass Visual Inspection, which integrates technological services to identify any product defects.

In addition to this, IBM has introduced its latest AI quality inspection product, which implements a federated learning model. Apart from these established companies, several startups in the USA are dedicating their product line to innovating novel models and methods to improve AI-assisted quality inspection. For instance, the AI-based quality control application of Neurala Inc., a Boston startup, has been incorporated by one of the leading manufacturers in the world, IHI Corporation. Therefore, considering the present trends in the AI market and the recent developments in AI quality inspection products in the USA, it can be anticipated that the North American AI quality inspection market is likely to witness an expansion over the forecast period.

Reasons for buying this report:-

  • Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, other sub- segments.
  • Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
  • Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape up future market developments.
  • Actionable Recommendations: Utilize the insights to exercise strategic decision to uncover new business streams and revenues in a dynamic environment.
  • Caters to a Wide Audience: Beneficial and cost-effective for startups, research institutions, consultants, SMEs, and large enterprises.

What do businesses use our reports for?

Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

  • Historical data & forecasts from 2022 to 2029
  • Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, Customer Behaviour, and Trend Analysis
  • Competitive Positioning, Strategies, and Market Share Analysis
  • Revenue Growth and Forecast Assessment of segments and regions including countries
  • Company Profiling (Strategies, Products, Financial Information, and Key Developments among others)

The AI quality inspection market is segmented and analyzed as follows:

By Type

  • Pre-trained
  • Deep learning

By End-Users

  • Semiconductor
  • Pharmaceutical
  • Automotive
  • Textile
  • Others

By Geography

  • North America
  • USA
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Others
  • Europe
  • United Kingdom
  • Germany
  • France
  • Italy
  • Spain
  • Others
  • Middle East and Africa
  • Saudi Arabia
  • UAE
  • Others
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Singapore
  • Indonesia
  • Others

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. Market Overview
  • 1.2. Market Definition
  • 1.3. Scope of the Study
  • 1.4. Market Segmentation
  • 1.5. Currency
  • 1.6. Assumptions
  • 1.7. Base and Forecast Years Timeline
  • 1.8. Key Benefits to the Stakeholder

2. RESEARCH METHODOLOGY

  • 2.1. Research Design
  • 2.2. Research Processes

3. EXECUTIVE SUMMARY

  • 3.1. Key Findings
  • 3.2. CXO Perspective

4. MARKET DYNAMICS

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porter's Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis
  • 4.5. Analyst View

5. AI QUALITY INSPECTION MARKET BY TYPE

  • 5.1. Introduction
  • 5.2. Pre-trained
  • 5.3. Deep learning

6. AI QUALITY INSPECTION MARKET BY END-USER

  • 6.1. Introduction
  • 6.2. Semiconductor
  • 6.3. Pharmaceutical
  • 6.4. Automotive
  • 6.5. Textile
  • 6.6. Others

7. AI QUALITY INSPECTION MARKET BY GEOGRAPHY

  • 7.1. Introduction
  • 7.2. North America
    • 7.2.1. By Type
    • 7.2.2. By End-User
    • 7.2.3. By Country
      • 7.2.3.1. USA
      • 7.2.3.2. Canada
      • 7.2.3.3. Mexico
  • 7.3. South America
    • 7.3.1. By Type
    • 7.3.2. By End-User
    • 7.3.3. By Country
      • 7.3.3.1. Brazil
      • 7.3.3.2. Argentina
      • 7.3.3.3. Others
  • 7.4. Europe
    • 7.4.1. By Type
    • 7.4.2. By End-User
    • 7.4.3. By Country
      • 7.4.3.1. United Kingdom
      • 7.4.3.2. Germany
      • 7.4.3.3. France
      • 7.4.3.4. Italy
      • 7.4.3.5. Spain
      • 7.4.3.6. Others
  • 7.5. Middle East and Africa
    • 7.5.1. By Type
    • 7.5.2. By End-User
    • 7.5.3. By Country
      • 7.5.3.1. Saudi Arabia
      • 7.5.3.2. UAE
      • 7.5.3.3. Others
  • 7.6. Asia Pacific
    • 7.6.1. By Type
    • 7.6.2. By End-User
    • 7.6.3. By Country
      • 7.6.3.1. China
      • 7.6.3.2. Japan
      • 7.6.3.3. India
      • 7.6.3.4. South Korea
      • 7.6.3.5. Australia
      • 7.6.3.6. Singapore
      • 7.6.3.7. Indonesia
      • 7.6.3.8. Others

8. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 8.1. Major Players and Strategy Analysis
  • 8.2. Market Share Analysis
  • 8.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 8.4. Competitive Dashboard

9. COMPANY PROFILES

  • 9.1. Intel Corp
  • 9.2. Kitov Systems
  • 9.3. Mitutoyo America Corporation
  • 9.4. Landing AI
  • 9.5. NEC Corporation
  • 9.6. tunic AG
  • 9.7. Robert Bosch GmbH
  • 9.8. deevio GmbH
  • 9.9. craftworks GmbH
  • 9.10. Pleora Technologies Inc