세계의 AI 품질 검사 시장 - 예측(2024-2029년)

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.

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• 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.
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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