By Muneeb Ali – Chief Technology Officer, Hosanna Textile Mills
In the fast-paced world of textile manufacturing, efficiency and accuracy in quality control are critical to maintaining consistency and trust. At Hosanna Textile Mills, we have always believed in combining traditional craftsmanship with technological innovation to stay ahead.
Under the direction of Syed Muneeb Ali, Chief Technology Officer, the company recently implemented an AI-powered Greige Fabric Inspection System, a breakthrough project that integrates artificial intelligence and real-time defect detection into our production process.
The Challenge
In the Greige department, manual inspection of unprocessed fabric has long been a labor-intensive task. Operators visually examine each roll to identify weaving defects, shade variations, and other surface faults. While experienced staff can detect most issues, the process is time-consuming and prone to human fatigue, resulting in inconsistencies and delayed reporting.
The Solution: AI-Based Greige Inspection System
To address these challenges, Muneeb Ali led the development of a custom AI inspection module that uses tablet cameras and machine learning algorithms to detect, record, and categorize fabric faults in real time — without requiring expensive external hardware.
Key features of the system include:
Real-time Fault Detection: The camera captures the running fabric and identifies defects such as holes, stains, thick/thin places, and shade variations during live inspection.
Automated Data Logging: Every defect is instantly saved in a digital report with roll number, meter count, and fault type.
Safe and Streamlined Operation: The system runs continuously alongside production without interrupting workflow, ensuring both safety and efficiency.
AI Learning Capability: With each batch, the system improves its detection accuracy through ongoing machine learning.
Integration with Dispatch Module: Final inspection data syncs directly to dispatch records, supporting faster decision-making and improved traceability.
Impact on Operations
Since deployment, the AI Greige Inspection System has significantly improved inspection speed and reduced manual errors. Supervisors can now review digital summaries of each batch, identify problem areas quickly, and make data-driven decisions for quality assurance.
This innovation has also enhanced transparency between departments — from Greige to Finishing — leading to better coordination and fewer production delays.
Leadership and Vision
According to Muneeb Ali, “Our goal was not just to automate a process, but to redefine how textile quality control works in real-time production environments. By building this system in-house, we’ve proven that meaningful innovation can come from within the industry itself — without relying on costly imported solutions.”
His leadership has encouraged Hosanna Textile’s internal teams to explore further applications of AI and automation in other departments, paving the way for a smarter, data-driven manufacturing environment.
Moving Forward
Following the success of this project, Hosanna Textile Mills aims to expand the use of AI and IoT-based systems across its production lines — from fabric tracking to energy monitoring — reinforcing its commitment to continuous improvement and technological advancement.
About the Author:
Muneeb Ali serves as the Chief Technology Officer at Hosanna Textile Mills, where he leads digital transformation, process automation, and innovation initiatives. His focus is on integrating AI-driven systems within traditional manufacturing environments to enhance operational performance and global competitiveness.
