LoomIQ is designed to help textile manufacturers maximise the utilisation of their looms, minimise unplanned downtime, and improve overall productivity. By combining constraint-based scheduling with real-time performance monitoring and analytics, LoomIQ gives operations managers deep visibility into loom performance and enables proactive maintenance leading to smoother production, better throughput, and reduced disruption.

• Constraint-based Loom Scheduling: LoomIQ intelligently plans the loom schedule by considering critical manufacturing constraints such as yarn type, beam width, job priority, and machine availability. This ensures that production runs are sequenced optimally, reducing setup times and avoiding conflicts. By aligning jobs with compatible yarns and machine constraints, LoomIQ maximises throughput while respecting technical limitations.
• Real-time OEE Dashboards: Operators and supervisors can view live dashboards that track key OEE metrics such as availability, performance, and quality for each loom and operator. This provides a clear picture of which machines are underperforming, when they are idling, or when inefficiencies are emerging, allowing rapid decision-making to enhance efficiency.
• Downtime Cause Classification: When a loom stops, LoomIQ classifies the reason for the downtime into categories (e.g., mechanical fault, material shortage, power outage), supporting root-cause analysis. This helps maintenance and operations teams understand the biggest disruption sources and allocate resources or changes more effectively.
• Digital Maintenance Requests: With LoomIQ’s mobile or tablet interface, operators can instantly log maintenance issues as they happen. Requests are raised directly from the shop floor, enabling quicker response times. Maintenance teams receive structured, actionable reports reducing the lag between fault detection and repair and preventing extended machine idle time.

At a knitwear unit in Faisalabad, LoomIQ enabled a significant operational boost: loom runtime utilisation increased by 11%, leading to higher throughput. By optimising scheduling and reducing downtime, the factory was able to add an extra weekly shipment all without investing in new machinery, proving that smart scheduling and analytics can deliver capacity gains without capital expenditure.

A knitwear manufacturing unit in Faisalabad implemented LoomIQ across its weaving section and saw a measurable improvement in operational efficiency. By optimising loom scheduling, reducing idle time, and enabling faster maintenance responses, the factory achieved an 11% increase in runtime utilisation within the first operational cycle. This uplift in machine availability and performance translated directly into higher weekly output, allowing the facility to add one additional shipment per week without installing new looms or expanding its workforce. The gains came entirely from better planning, reduced changeovers, and more informed decision-making demonstrating how LoomIQ can unlock hidden capacity.