Why Choose Nidle?
Nidle helps you track, optimize, digitize your RMG production processes with real time visibility anytime, anywhere to improve efficiency, quality and decrease wastage.
Ensure Your Apparel Factory Productivity Remains at the Desired Threshold!
Nidle helps you track, optimize, digitize your RMG production processes with real time visibility anytime, anywhere to improve efficiency, quality and decrease wastage.
Nidle Input
Nidle In-Line
Nidle End-Line
Reduce defects & increase efficiency with End-Line Quality Management System
Nidle Finishing
Nidle Cut

Pre-Production
• Size Set Tracking
• PP Meeting Scheduling
• Operation Breakdown
• Technical Attachment
• Line Layout
• Style Changeover Time Tracking
Cutting
• Fabric Roll Management
• CAD Width vs Fabric Width
• Right Roll Selection
• Cutting Plan
Cutting Production
• Lay Chart Tracking
• Cutting Table Utilization
• Re-cutting/Part Replacement
Production
• Material Input Management
• In-Line Production
• Work-Study Management
• Quality Management
Finishing
• Packed Quantity Tracking
• Packing List Preparation
• Pre-final Inspection
• Final Inspection
• Customer/Buyer Module
Library
• Product Library
• Fabric Library
• Sewing Method (Point Kaizen)
Machine Maintenance
• ANDON
• Breakdown Maintenance
• Schedule Maintenance
• Spare Parts Tracking
• Machine Inventory
Customer Portal
• Production Performance
• Quality Performance
• Final Inspection Report
YUNUSCO Group
Yunusco (BD) Ltd is a leading state of the art lingerie, underwear, active wear manufacturer in Bangladesh.
4A Yarn Dyeing Ltd.
4A Yarn Dyeing Ltd. is a 100% export-oriented outerwear manufacturing company, established in 2009. It specializes in producing all kinds of high-quality outerwear garments.
The “Business Intelligence Dashboard” facilitates a helicopter view of shop floor performance with drill-down information. The production manager has the visibility to monitor production performance through one screen.
The “Live Monitoring Dashboard” provides the floor managers with a real-time view of the operations being carried out. The total number of allocated devices are displayed, which are further broken down into running & idle devices. Individual operator status is also displayed, calculating their non-productive time & cumulative/hourly production.
Once we have enough production data in the system, we will be able to make predictive analysis with AI for style or order.
Machine learning can enable a different dimension to our solution and we will be able to take automation to a different level.
Making our technology available to all size of RMG companies and making it as affordable as possible.