Global Automated Textile Sorting Equipment Market Strategic Research Report
By Type: Conveyor-fed Air-ejection Textile Sorting Equipment, Robotic Singulation and Picking Textile Sorting Equipment, Overhead Rail Garment Sorting Equipment, Unit Sorter Apparel Sorting Equipment
By Application: Textile-to-textile Recycling Feedstock Preparation, Textile Manufacturing Scrap Recycling, Second-hand Garment Reuse and Resale Sorting, Commercial Laundry and Textile Rental Sorting, Apparel Retail and E-commerce Fulfillment Sorting
Regional Forecast: Asia Pacific, Latin America, MEA, Europe, North America
Key Players: TOMRA Recycling Sorting (TOMRA Systems ASA), Pellenc ST, Valvan Baling Systems NV, PICVISA Machine Vision Systems S.L., REDWAVE (BT-Systems GmbH), STADLER Anlagenbau GmbH, ANDRITZ AG, NewRetex A/S, Refiberd, Inc., Sortile, Inc., Softrol Systems, Inc., Planiform, EuroSort B.V., Kannegiesser GmbH, Metalprogetti S.p.A., JENSEN-GROUP NV, ADEC Co., Ltd., Asahi Seisakusho Co., Ltd., Hangzhou DataBeyond Technology Co., Ltd., Pade Technology Co., Ltd.
Übersicht
Scope of the Report
The global Automated Textile Sorting Equipment market size is predicted to grow from US$ 875 million in 2025 to US$ 1,683 million in 2032; it is expected to grow at a CAGR of 9.8% from 2026 to 2032.
Automated Textile Sorting Equipment is an intelligent recycling system that uses artificial intelligence, machine vision, and near-infrared (NIR) spectroscopy to identify and separate textile materials based on fiber composition, color, and quality. It is mainly used in textile recycling plants, second-hand clothing sorting centers, and circular economy waste processing facilities. The system integrates conveyor platforms, optical sensors, AI classification algorithms, and automated mechanical separation units to improve sorting efficiency and recycling accuracy. Main product types include conveyor-based optical sorting systems, NIR fiber identification systems, robotic sorting units, and fully automated textile recycling lines. This category excludes manual sorting systems, general municipal waste sorting equipment, and non-AI-based conveyor sorting systems.The industrial chain of Automated Textile Sorting Equipment includes upstream suppliers of machine vision cameras, NIR sensors, AI chips, industrial robots, conveyors, pneumatic systems, and control software. Midstream manufacturers integrate AI recognition models, fiber classification algorithms, robotic sorting mechanisms, and automation platforms into complete textile sorting solutions. Downstream applications include textile recycling companies, second-hand clothing processing centers, waste management firms, and circular economy infrastructure projects. Supporting services include AI model training, fiber recognition calibration, system maintenance, sorting optimization, and software upgrades.In 2025, global Automated Textile Sorting Equipment production reached approximately 1,417 units, with an average global market price of around US$600,000 per system. The gross profit margin of major companies in the industry is between 25%–42%. In 2025, the global production capacity of automated textile sorting equipment was approximately 2,024 units.
The Automated Textile Sorting Equipment market is emerging as an important segment within the broader waste recycling and circular economy industry. Growth is driven by increasing volumes of textile waste, stricter environmental regulations, and rising demand for efficient material recovery systems in Europe, China, and North America. These systems leverage artificial intelligence, machine vision, and near-infrared (NIR) spectroscopy to identify and separate textile fibers by composition, color, and quality, significantly improving sorting accuracy and recycling efficiency compared with manual or semi-automated processes. Adoption is expanding in textile recycling facilities, second-hand clothing processing centers, and municipal waste management systems. However, the market remains in an early development stage, with relatively low automation penetration and high dependence on regional recycling infrastructure. High initial investment costs, variability in waste composition, and lack of standardized sorting processes remain key challenges. Despite these limitations, regulatory pressure on textile waste reduction and growing circular economy initiatives are expected to drive steady growth in the long term.
This report presents a comprehensive overview of the global Automated Textile Sorting Equipment market, covering market size and forecast, segmentation by product type and application, competitive landscape, leading players and regional and country-level outlook.
Segment by Type
- Conveyor-fed Air-ejection Textile Sorting Equipment
- Robotic Singulation and Picking Textile Sorting Equipment
- Overhead Rail Garment Sorting Equipment
- Unit Sorter Apparel Sorting Equipment
Segment by Sorting Technology
- Near-infrared Spectroscopy Textile Sorting Equipment
- Hyperspectral Imaging Textile Sorting Equipment
- RGB Vision and AI Textile Sorting Equipment
- RFID and Barcode Textile Sorting Equipment
- Multi-sensor Fusion Textile Sorting Equipment
Segment by Throughput Range
- Below 1 Ton Per Hour Textile Sorting Equipment
- 1 to 3 Tons Per Hour Textile Sorting Equipment
- 3 to 10 Tons Per Hour Textile Sorting Equipment
- Above 10 Tons Per Hour Textile Sorting Equipment
Segment by Application
- Textile-to-textile Recycling Feedstock Preparation
- Textile Manufacturing Scrap Recycling
- Second-hand Garment Reuse and Resale Sorting
- Commercial Laundry and Textile Rental Sorting
- Apparel Retail and E-commerce Fulfillment Sorting
Who Can Use This Report?
This report is written for decision-makers who need a clear, data-backed view of the global Automated Textile Sorting Equipment market:
- Manufacturers, suppliers and solution providers benchmarking their position and planning product, capacity and go-to-market strategy
- Distributors, channel partners and end users in Textile-to-textile Recycling Feedstock Preparation, Textile Manufacturing Scrap Recycling, Second-hand Garment Reuse and Resale Sorting evaluating demand and sourcing options
- Investors, financial analysts and consultants assessing growth opportunities, competitive dynamics and M&A potential
- Government agencies, industry associations and research institutions tracking industry developments and policy impact
Market snapshot
Global Automated Textile Sorting Equipment Market Strategic Research Report snapshot, 2025–2032
© MarketResearchReports.comDisclaimer: The actual data may vary in the final report which undergoes verification check post order confirmation.Segments covered in this report
Table of contents
01Executive Summary
02Industry Overview & Forecast
- 2.1.1 Market Definition and Scope
- 2.1.2 Market Size and Growth Forecast
- 2.1.3 Volume Analysis
- 2.1.4 Segment Outlook by Type
- 2.1.5 Segment Outlook by Application
- 2.1.6 Regional Outlook
- 2.1.7 Structural Developments Shaping the Forecast
- 2.1.8 Forecast Risks and Sensitivities
03Market Segmentation by Type
- 3.1 Market Segmentation by Type
- 3.1.1 Market by Type Overview
- 3.1.2 Conveyor-fed Air-ejection Textile Sorting Equipment
- 3.1.3 Robotic Singulation and Picking Textile Sorting Equipment
- 3.1.4 Overhead Rail Garment Sorting Equipment
- 3.1.5 Unit Sorter Apparel Sorting Equipment
- 3.1.6 Volume Analysis
04Market Segmentation by Application
- 4.1 Market Segmentation by Application
- 4.1.1 Market by Application Overview
- 4.1.2 Textile-to-textile Recycling Feedstock Preparation
- 4.1.3 Textile Manufacturing Scrap Recycling
- 4.1.4 Second-hand Garment Reuse and Resale Sorting
- 4.1.5 Commercial Laundry and Textile Rental Sorting
- 4.1.6 Apparel Retail and E-commerce Fulfillment Sorting
- 4.1.7 Volume Analysis
05Regional Market Forecast
- Asia Pacific
- North America
- Europe
- Middle East & Africa
- Latin America
06Country-Level Market Forecast
- 6.1 Asia Pacific
- 6.1.1 China
- 6.1.2 Japan
- 6.1.3 Korea
- 6.1.4 Southeast Asia
- 6.1.5 India
- 6.1.6 Australia
- 6.1.7 Rest of Asia Pacific
- 6.2 North America
- 6.2.1 United States
- 6.2.2 Canada
- 6.2.3 Mexico
- 6.2.4 Rest of North America
- 6.3 Europe
- 6.3.1 Germany
- 6.3.2 France
- 6.3.3 UK
- 6.3.4 Italy
- 6.3.5 Russia
- 6.3.6 Rest of Europe
- 6.4 Middle East & Africa
- 6.4.1 Egypt
- 6.4.2 South Africa
- 6.4.3 Israel
- 6.4.4 Turkey
- 6.4.5 GCC Countries
- 6.4.6 Rest of Middle East & Africa
- 6.5 Latin America
- 6.5.1 Brazil
- 6.5.2 Rest of Latin America
07Growth Drivers & Inhibitors
- 7.1 Growth Drivers & Inhibitors
- 7.1.1 Section Overview
- 7.1.2 Growth Drivers
- 7.1.3 Growth Inhibitors
- 7.1.4 Driver and Inhibitor Impact Assessment
- 7.1.5 Analyst Perspective
08Key Company Profiles
- 8.1 TOMRA Recycling Sorting (TOMRA Systems ASA)
- 8.1.1 Company Overview
- 8.1.2 Key Products & Segments
- 8.1.3 Financial Performance (2023–2025)
- 8.1.4 Business Strategy
- 8.1.5 SWOT Analysis
- 8.1.6 Strategic Implications (2026–2032)
- 8.2 Pellenc ST
- 8.2.1 Company Overview
- 8.2.2 Key Products & Segments
- 8.2.3 Financial Performance (2023–2025)
- 8.2.4 Business Strategy
- 8.2.5 SWOT Analysis
- 8.2.6 Strategic Implications (2026–2032)
- 8.3 Valvan Baling Systems NV
- 8.3.1 Company Overview
- 8.3.2 Key Products & Segments
- 8.3.3 Financial Performance (2023–2025)
- 8.3.4 Business Strategy
- 8.3.5 SWOT Analysis
- 8.3.6 Strategic Implications (2026–2032)
- 8.4 PICVISA Machine Vision Systems S.L.
- 8.4.1 Company Overview
- 8.4.2 Key Products & Segments
- 8.4.3 Financial Performance (2023–2025)
- 8.4.4 Business Strategy
- 8.4.5 SWOT Analysis
- 8.4.6 Strategic Implications (2026–2032)
- 8.5 REDWAVE (BT-Systems GmbH)
- 8.5.1 Company Overview
- 8.5.2 Key Products & Segments
- 8.5.3 Financial Performance (2023–2025)
- 8.5.4 Business Strategy
- 8.5.5 SWOT Analysis
- 8.5.6 Strategic Implications (2026–2032)
- 8.6 STADLER Anlagenbau GmbH
- 8.6.1 Company Overview
- 8.6.2 Key Products & Segments
- 8.6.3 Financial Performance (2023–2025)
- 8.6.4 Business Strategy
- 8.6.5 SWOT Analysis
- 8.6.6 Strategic Implications (2026–2032)
- 8.7 ANDRITZ AG
- 8.7.1 Company Overview
- 8.7.2 Key Products & Segments
- 8.7.3 Financial Performance (2023–2025)
- 8.7.4 Business Strategy
- 8.7.5 SWOT Analysis
- 8.7.6 Strategic Implications (2026–2032)
- 8.8 NewRetex A/S
- 8.8.1 Company Overview
- 8.8.2 Key Products & Segments
- 8.8.3 Financial Performance (2023–2025)
- 8.8.4 Business Strategy
- 8.8.5 SWOT Analysis
- 8.8.6 Strategic Implications (2026–2032)
- 8.9 Refiberd, Inc.
- 8.9.1 Company Overview
- 8.9.2 Key Products & Segments
- 8.9.3 Financial Performance (2023–2025)
- 8.9.4 Business Strategy
- 8.9.5 SWOT Analysis
- 8.9.6 Strategic Implications (2026–2032)
- 8.10 Sortile, Inc.
- 8.10.1 Company Overview
- 8.10.2 Key Products & Segments
- 8.10.3 Financial Performance (2023–2025)
- 8.10.4 Business Strategy
- 8.10.5 SWOT Analysis
- 8.10.6 Strategic Implications (2026–2032)
- 8.11 Softrol Systems, Inc.
- 8.11.1 Company Overview
- 8.11.2 Key Products & Segments
- 8.11.3 Financial Performance (2023–2025)
- 8.11.4 Business Strategy
- 8.11.5 SWOT Analysis
- 8.11.6 Strategic Implications (2026–2032)
- 8.12 Planiform
- 8.12.1 Company Overview
- 8.12.2 Key Products & Segments
- 8.12.3 Financial Performance (2023–2025)
- 8.12.4 Business Strategy
- 8.12.5 SWOT Analysis
- 8.12.6 Strategic Implications (2026–2032)
- 8.13 EuroSort B.V.
- 8.13.1 Company Overview
- 8.13.2 Key Products & Segments
- 8.13.3 Financial Performance (2023–2025)
- 8.13.4 Business Strategy
- 8.13.5 SWOT Analysis
- 8.13.6 Strategic Implications (2026–2032)
- 8.14 Kannegiesser GmbH
- 8.14.1 Company Overview
- 8.14.2 Key Products & Segments
- 8.14.3 Financial Performance (2023–2025)
- 8.14.4 Business Strategy
- 8.14.5 SWOT Analysis
- 8.14.6 Strategic Implications (2026–2032)
- 8.15 Metalprogetti S.p.A.
- 8.15.1 Company Overview
- 8.15.2 Key Products & Segments
- 8.15.3 Financial Performance (2023–2025)
- 8.15.4 Business Strategy
- 8.15.5 SWOT Analysis
- 8.15.6 Strategic Implications (2026–2032)
- 8.16 JENSEN-GROUP NV
- 8.16.1 Company Overview
- 8.16.2 Key Products & Segments
- 8.16.3 Financial Performance (2023–2025)
- 8.16.4 Business Strategy
- 8.16.5 SWOT Analysis
- 8.16.6 Strategic Implications (2026–2032)
- 8.17 ADEC Co., Ltd.
- 8.17.1 Company Overview
- 8.17.2 Key Products & Segments
- 8.17.3 Financial Performance (2023–2025)
- 8.17.4 Business Strategy
- 8.17.5 SWOT Analysis
- 8.17.6 Strategic Implications (2026–2032)
- 8.18 Asahi Seisakusho Co., Ltd.
- 8.18.1 Company Overview
- 8.18.2 Key Products & Segments
- 8.18.3 Financial Performance (2023–2025)
- 8.18.4 Business Strategy
- 8.18.5 SWOT Analysis
- 8.18.6 Strategic Implications (2026–2032)
- 8.19 Hangzhou DataBeyond Technology Co., Ltd.
- 8.19.1 Company Overview
- 8.19.2 Key Products & Segments
- 8.19.3 Financial Performance (2023–2025)
- 8.19.4 Business Strategy
- 8.19.5 SWOT Analysis
- 8.19.6 Strategic Implications (2026–2032)
- 8.20 Pade Technology Co., Ltd.
- 8.20.1 Company Overview
- 8.20.2 Key Products & Segments
- 8.20.3 Financial Performance (2023–2025)
- 8.20.4 Business Strategy
- 8.20.5 SWOT Analysis
- 8.20.6 Strategic Implications (2026–2032)
09Competitive Landscape
- 9.1 Competitive Landscape Overview
- 9.2 Competitive Intensity Assessment
- 9.3 Key Player Strategies & Positioning
- 9.4 Competitive Dynamics & Strategic Outlook
- 9.4.1 Emerging Competitive Threats
- 9.4.2 Consolidation vs. Fragmentation Outlook
- 9.4.3 Competitive Response Matrix
- 9.4.4 Strategic Recommendations, 2026–2032
10Porter's Five Forces Analysis
- 10.1 Threat of New Entrants
- 10.2 Bargaining Power of Buyers
- 10.3 Bargaining Power of Suppliers
- 10.4 Threat of Substitutes
- 10.5 Competitive Rivalry
11PESTLE Analysis
- 11.1 Political
- 11.2 Economic
- 11.3 Social and Demographic
- 11.4 Technological
- 11.5 Legal and Regulatory
- 11.6 Environmental
- 11.7 Strategic Implications of the PESTLE Assessment
12SWOT Analysis
13Future Trends & Outlook
- 13.1 Future Trends & Outlook
- 13.1.1 Trend Summary and Commercial Maturity Assessment
- 13.1.2 Technology and Innovation Trends
- 13.1.3 Long-Term Market Outlook
- 13.1.4 Investment & M&A Activity Outlook
- 13.1.5 Overall Outlook Assessment
Frequently asked questions
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Research Methodology
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Dual-validation approach: bottom-up sizing aggregates segment-level production, consumption, and trade data; top-down sizing cross-validates against macroeconomic indicators and total addressable market estimates. Discrepancies >5% trigger analyst review.
Company profiles built from public financial disclosures, product launches, M&A activity, job postings (as capability proxies), and supply chain mapping. Market share estimates triangulated across revenue, capacity, and shipment data.
CAGR projections use time-series regression on 5-10 years of historical data, adjusted for identified demand drivers (technology adoption curves, regulatory catalysts, demographic shifts) and demand inhibitors (cost barriers, substitution risk). Scenario modeling covers base, optimistic, and conservative cases.
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