Textile Quality Control with RedX ​
Case Study: Automated Textile Defect Check
Background:
In the fast-paced telecommunications industry, ensuring the safety of workers during the construction and maintenance of tower infrastructure is paramount. A leading tower company, which specializes in erecting and leasing tower structures to telecom operators, aimed to elevate its safety protocols. To achieve this, they turned to innovative AI technology and partnered with us to deploy a state-of-the-art solution.
The Challenge:
Quality Control (QC) is paramount in any production-based industry. The client wanted an automated computer vision solution to detect and categorize textile defects in real-time to streamline their QC process.
The Solution: RedX AI Automation Platform:
To automate the quality control process, we set up hardware including high-speed USB cameras and a PLC-based label applicator, and connected them to our AI platform. Next, we deployed AI models on the platform that could visually identify 45 different types of textile defects.
As the textile product progressed on the production line, the USB cameras scanned it, and if a defect is found, the platform triggered the PLC label applicator device to apply a relevant label to the defective cloth. Moreover, the status of the defect identification process is displayed on the dashboard. This helped the client automate the entire end-to-end Quality Control (QC) process for their textile product.
Impact & Results:
The deployment of the RedX platform transformed safety monitoring from a manual, error-prone process to an automated, efficient, and reliable system. The ground-based human tracing cameras provided comprehensive coverage of the site, enabling real-time detection and alerts for any safety gear non-compliance.
This not only streamlined the monitoring process but also significantly enhanced the safety culture among workers. The tower company experienced a marked reduction in safety incidents and non-compliance, highlighting the effectiveness of integrating AI technology into safety protocols.
Conclusion:
The integration of RedX at the tower company’s construction sites has set a new industry standard for safety and efficiency. This case study exemplifies our dedication to harnessing AI for meaningful applications, ensuring safer work environments, and leading the charge in technological innovation within traditional sectors.
This case study highlights our commitment to improving workplace safety through technological innovation, demonstrating how AI can be leveraged to make traditional industries safer and more efficient.