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市場調查報告書
商品編碼
1574132

人工智慧質檢市場－2024年至2029年預測

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個工作天內

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簡介目錄

人工智慧質檢市場預計複合年成長率為20.53%，市場規模將從2024年的278.08億美元增加到2029年的707.47億美元。

當使用軟體主導的人工智慧和視覺技術時，人工智慧品質檢測有助於檢測和處理半導體、藥品、紡織品和汽車製造等產品中的不一致性。基於人工智慧的品質測試應用因其高精度和節省時間而在半導體行業、醫療保健、服飾製造、汽車製造等領域越來越受歡迎。

人工智慧品質檢測軟體可以基於機器學習模型或作為預先訓練的軟體服務來製造。人工智慧品管技術提供的高精度是相對於手動品管的一大優勢，使其成為全球主要製造公司的選擇。因此，考慮到對基於人工智慧的產品的需求不斷增加以及影響人工智慧質檢軟體消費的其他因素，基於人工智慧的品管市場預計在預測期內將達到更大的市場規模。

人工智慧質檢市場促進因素：

  • 製造業擴大採用基於人工智慧的品管軟體，預計將增加需求

這種成長是由於生產劣質產品而導致製造公司的營運成本增加。例如，豐田汽車公司最近因製造缺陷而遭受了13億美元的損失。損壞的部件常常未被發現並用於最終產品的製造過程。結果，製造企業的營運費用增加，並且有缺陷的產品無法在市場上銷售。此類案例在大量生產產品的企業中屢見不鮮。

使用人眼進行手動品管可能無法偵測到大批量的缺陷。為了克服這一限制，世界各地的主要企業正在積極投資基於人工智慧的品質測試軟體，以及早發現有缺陷的產品並防止額外成本。

人工智慧質檢市場地域展望

  • 北美在預測期內將經歷指數級成長

北美是國際人工智慧市場的強大技術進步力量，正積極投資擴大人工智慧軟體的範圍和應用，包括人工智慧品管和檢測。頂級軟體公司正在開發並競相加強其人工智慧產品和服務組合。例如，微軟推出了 Spyglass Visual Inspection，這是一款虛擬人工智慧品質檢測產品，它整合了技術服務來識別任何產品缺陷。

此外，IBM還發布了其最新的人工智慧質檢產品，該產品實現了聯邦學習模型。除了這些老牌公司之外，美國的幾家新興企業也致力於創新新的模型和方法，以改善人工智慧輔助品質檢測。例如，波士頓新興企業Neurala Inc. 的基於人工智慧的品管應用程式已被世界領先製造商之一的 IHI 公司採用。因此，考慮到目前AI市場的趨勢以及近期美國AI質檢產品的市場開拓，可以預測北美AI質檢市場在預測期內很可能會擴大。

為什麼要購買這份報告？

  • 富有洞察力的分析：獲得涵蓋關鍵和新興地區的深入市場洞察，重點關注客戶細分、政府政策和社會經濟因素、消費者偏好、行業部門和其他子區隔。
  • 競爭格局：了解世界主要企業採取的策略策略，並了解透過正確的策略滲透市場的潛力。
  • 市場促進因素和未來趨勢：探索動態因素和關鍵市場趨勢以及它們將如何影響未來市場發展。
  • 可行的建議：利用洞察力做出策略決策，在動態環境中釋放新的業務流和收益。
  • 面向廣大受眾：對於新興企業、研究機構、顧問、中小型企業和大型企業有用且具有成本效益。

公司使用我們的報告的目的是什麼？

產業和市場考量、機會評估、產品需求預測、打入市場策略、地理擴張、資本投資決策、法律規範與影響、新產品開發、競爭影響。

調查範圍

  • 2022年至2029年歷史資料與預測
  • 成長機會、挑戰、供應鏈前景、法規結構、顧客行為、趨勢分析
  • 競爭對手的市場狀況、策略與市場佔有率分析
  • 包括國家在內的細分市場和地區的收益成長和預測評估
  • 公司簡介（策略、產品、財務資訊、主要動態等）

AI質檢市場細分分析如下：

按類型

  • 預習型
  • 深度學習

按最終用戶

  • 半導體
  • 製藥
  • 車
  • 纖維
  • 其他

按地區

  • 北美洲
  • 美國
  • 加拿大
  • 墨西哥
  • 南美洲
  • 巴西
  • 阿根廷
  • 其他
  • 歐洲
  • 英國
  • 德國
  • 法國
  • 義大利
  • 西班牙
  • 其他
  • 中東/非洲
  • 沙烏地阿拉伯
  • UAE
  • 其他
  • 亞太地區
  • 中國
  • 日本
  • 印度
  • 韓國
  • 澳洲
  • 新加坡
  • 印尼
  • 其他

目錄

第1章簡介

  • 市場概況
  • 市場定義
  • 調查範圍
  • 市場區隔
  • 貨幣
  • 先決條件
  • 基準年和預測年時間表
  • 相關利益者的主要利益

第2章調查方法

  • 研究設計
  • 調查過程

第3章執行摘要

  • 主要發現
  • CXO觀點

第4章市場動態

  • 市場促進因素
  • 市場限制因素
  • 波特五力分析
  • 產業價值鏈分析
  • 分析師觀點

第5章人工智慧質檢市場：按類型

  • 介紹
  • 預訓練
  • 深度學習

第6章人工智慧品質檢測市場：依最終用戶分類

  • 介紹
  • 半導體
  • 製藥
  • 車
  • 纖維
  • 其他

第7章 人工智慧質檢市場：按地區

  • 介紹
  • 北美洲
    • 按類型
    • 按最終用戶
    • 按國家/地區
  • 南美洲
    • 按類型
    • 按最終用戶
    • 按國家/地區
  • 歐洲
    • 按類型
    • 按最終用戶
    • 按國家/地區
  • 中東/非洲
    • 按類型
    • 按最終用戶
    • 按國家/地區
  • 亞太地區
    • 按類型
    • 按最終用戶
    • 按國家/地區

第8章競爭環境及分析

  • 主要企業及策略分析
  • 市場佔有率分析
  • 合併、收購、協議和合作
  • 競爭對手儀表板

第9章 公司簡介

  • Intel Corp
  • Kitov Systems
  • Mitutoyo America Corporation
  • Landing AI
  • NEC Corporation
  • tunic AG
  • Robert Bosch GmbH
  • deevio GmbH
  • craftworks GmbH
  • Pleora Technologies Inc
簡介目錄
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