Fabric Defect Detection Artificial Intelligence (AI) Global Market Report 2025

The fabric defect detection artificial intelligence (AI) market size has grown rapidly in recent years. It will grow from $0.4 billion in 2024 to $0.46 billion in 2025 at a compound annual growth rate (CAGR) of 15.6%. The growth in the historic period can be attributed to increasing investments in advanced inspection technologies, the rising need for defect-free fabrics in the apparel industry, the growing adoption of industrial automation across textile manufacturing, increasing awareness of global product quality standards, and the expanding implementation of AI-based quality monitoring systems to enhance production efficiency and consistency.

The fabric defect detection artificial intelligence (AI) market size is expected to see rapid growth in the next few years. It will grow to $0.81 billion in 2029 at a compound annual growth rate (CAGR) of 15.2%. The growth in the forecast period can be attributed to the increasing adoption of AI-powered fabric inspection systems, the rising demand for smart manufacturing solutions, the growth in global textile production, the increasing focus on reducing manufacturing waste, and the rising investments in research and development for quality enhancement. Key trends anticipated during the forecast period include advancements in AI and machine learning integration, the development of fully automated inspection systems, innovations in real-time defect detection technologies, progress in cloud-based monitoring and analytics platforms, and the emergence of smart sensors for precise fabric quality control.

The increasing demand for textiles is expected to drive the growth of the fabric defect detection artificial intelligence (AI) market in the coming years. A textile refers to a material produced by weaving, knitting, or bonding fibers together to create fabric used in clothing, furnishings, or other applications. The demand for textiles is increasing due to the growing global population and urbanization, which raise the need for clothing, home furnishings, and industrial fabrics to support expanding lifestyles and infrastructure. Fabric defect detection artificial intelligence (AI) supports the textile industry by maintaining consistent quality, as it rapidly identifies and corrects defects, minimizes material waste, and ensures products meet high consumer standards. For example, in October 2025, according to the World Trade Organization (WTO), a Switzerland based international organization, the trade of textile products increased by 2 percent in 2024 compared to 2023, followed by a significant 7 percent growth in the first half of 2025 compared to the same period in 2024. Therefore, the growing demand for textiles is fueling the expansion of the fabric defect detection artificial intelligence (AI) market.

Key companies operating in the fabric defect detection artificial intelligence (AI) market are concentrating on developing advanced solutions such as fabric scanning technologies to enable continuous real time monitoring. Fabric scanning technology involves the use of sensors or imaging systems to examine textiles and automatically identify defects or irregularities during production. For example, in March 2024, Serkon Teknoloji Inc., a Turkey based AI solutions provider, introduced QBar.AI, an artificial intelligence fabric scanning technology that detects defects on the fabric surface at the flow rate. QBar.AI captures high resolution images of fabrics and processes them through an AI system that accurately identifies defects such as holes, stains, or weave inconsistencies across knitted, woven, and denim materials. When a defect is detected, it immediately alerts the operations team and can automatically stop the machine to prevent further production of faulty fabric. The system also indicates the exact location of each imperfection, enabling quick corrective measures and reducing dependence on manual inspection. Compatible with existing production lines through Ethernet, COM port, Wi Fi, or Bluetooth, QBar.AI exports data in multiple formats, improving reporting efficiency, reducing waste, and ensuring consistent product quality.

In March 2023, Smartex, a Portugal based provider of AI powered fabric inspection systems, acquired Tuvis for an undisclosed amount. Through this acquisition, Smartex aims to enhance its technological capabilities in AI driven textile inspection, enabling real time defect detection and data based analysis for textile manufacturers. Tuvis is a Turkey based company specializing in fabric defect detection artificial intelligence (AI).

Major players in the fabric defect detection artificial intelligence (ai) market are Keyence Corporation, Shenzhen Chaoqiang Technology Co. Ltd., BarcoVision, Zhejiang Cixing Co. Ltd., VITRONIC Machine Vision Ltd., Datacolor AG, Uster Technologies AG, Elbit Systems Ltd., Jiangsu Yingyou Textile Machinery Co. Ltd., VisionTex, Loepfe Brothers Ltd., TEXPA Maschinenbau GmbH & Co. KG, Inviya, TEXAID, Acsys Lasertechnik GmbH, Pixevia, Prowise Solutions Inc., Sensing Tex SL, Shenzhen Tailorwin Intelligent Technology Co. Ltd., and Smartex.

North America was the largest region in the fabric defect detection artificial intelligence (AI) market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in fabric defect detection artificial intelligence (AI) report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The rapid escalation of U.S. tariffs and the resulting trade tensions in spring 2025 are significantly impacting the information technology sector, particularly in hardware manufacturing, data infrastructure, and software deployment. Higher duties on imported semiconductors, circuit boards, and networking equipment have raised production and operational costs for tech firms, cloud service providers, and data centers. Companies relying on globally sourced components for laptops, servers, and consumer electronics are facing longer lead times and increased pricing pressures. In parallel, tariffs on specialized software tools and retaliatory measures from key international markets have disrupted global IT supply chains and reduced overseas demand for U.S.-developed technologies. To navigate these challenges, the sector is accelerating investments in domestic chip fabrication, diversifying supplier bases, and adopting AI-driven automation to enhance operational resilience and cost efficiency.

The fabric defect detection artificial intelligence (AI) market research report is one of a series of new reports that provides fabric defect detection artificial intelligence (AI) market statistics, including fabric defect detection artificial intelligence (AI) industry global market size, regional shares, competitors with a fabric defect detection artificial intelligence (AI) market share, detailed fabric defect detection artificial intelligence (AI) market segments, market trends and opportunities, and any further data you may need to thrive in the fabric defect detection artificial intelligence (AI) industry. This fabric defect detection artificial intelligence (AI) market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

Fabric defect detection artificial intelligence (AI) refers to the application of AI technologies to automatically identify flaws or inconsistencies in textile materials. It utilizes machine learning and computer vision algorithms to examine fabric surfaces and detect defects such as holes, stains, uneven weaving, or color variations.

The primary components of fabric defect detection AI include software, hardware, and services. The software component comprises advanced algorithms, machine learning models, and image processing platforms designed to identify defects in real time. The system can be deployed through on-premises or cloud-based modes and incorporates various technologies, including machine learning, deep learning, computer vision, and others. It is utilized by multiple end users such as the textile industry, the apparel industry, home furnishing, automotive textiles, and other related sectors.

The countries covered in the fabric defect detection artificial intelligence (AI) market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The fabric defect detection artificial intelligence (AI) market consists of revenues earned by entities by providing services automated defect inspection, real-time fabric quality monitoring, weaving defect detection, and yarn irregularity analysis. The market value includes the value of related goods sold by the service provider or included within the service offering. The fabric defect detection artificial intelligence (AI) market also includes sales of high-resolution industrial cameras, line scan cameras, area scan cameras, and hyperspectral imaging cameras. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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