A graduate from NED University in Karachi has developed an AI-powered system aimed at addressing a major challenge in Pakistan’s textile industry: detecting fabric defects before production. The system, named IntelliInspect, offers real-time identification of fabric quality issues, which could save millions annually by reducing waste and preventing defective textiles from reaching export markets.
The innovation, created by Suboohi Arif, an expert in automation and application engineering, is touted as the world’s first analytical system of its kind. IntelliInspect can detect a range of defects, including broken threads, stains, and holes, in both knitted and woven fabrics, whether unprocessed or dyed.
Through tests on over 3,000 fabric samples, the system demonstrated high accuracy, with defect detection times ranging from 40 to 77 seconds. Equipped with high-speed sensors and cameras, IntelliInspect works on textile manufacturing lines, quickly spotting issues during production and helping manufacturers avoid faulty fabrics in finished products.
The system is versatile, applicable across various segments such as garment production, automotive textiles, home furnishings, and industrial textiles. By improving production efficiency, accuracy, and cost-effectiveness, IntelliInspect has the potential to boost profitability and enhance the quality of Pakistan’s textile exports.
Suboohi Arif is eager to partner with industry stakeholders to implement the system and transform Pakistan’s textile sector, which is responsible for over half of the countryβs exports. The widespread adoption of IntelliInspect could improve quality control, enhance global competitiveness, and provide valuable data for better decision-making in the industry.
