Customer
A leading global manufacturer of industrial safety products.
Technology
Digital Twin, Agentic AI, Zoho IoT, PLC/CNC Integration, SCADA, Edge Gateways, Industrial Sensors, Data Historian, Analytics Dashboards
Business Objective
The client sought to create a scalable digital manufacturing environment by improving shop-floor visibility, machine utilization monitoring, production tracking, and operational intelligence.
Key objectives included:
- Improve real-time shop-floor visibility.
- Accurately monitor machine utilization and production counts.
- Automate downtime classification.
- Strengthen batch-to-furnace traceability.
- Enhance Overall Equipment Effectiveness (OEE).
- Establish an Industry 5.0-ready digital manufacturing environment.
Scope of services
BXI Technology designed and implemented a Digital Twin and Agentic AI architecture integrated with Zoho IoT across diverse manufacturing equipment and processes.
The engagement included:
- PLC and CNC machine integration.
- Integration with furnaces, laser cutting, grinding, drilling, stamping, welding, and injection moulding equipment.
- Sensor retrofits and edge gateway implementation.
- Industrial protocol integration and real-time data acquisition.
- KPI dashboards and operational analytics.
- Predictive analytics and AI-driven monitoring.
- Batch traceability and batch-to-furnace tracking.
- Standardized IoT architecture across diverse machines.
- Implementation without disrupting existing machine operations.
Benefits
- Real-time visibility into machine status, production counts, downtime, rejects, and cycle times.
- Improved batch-to-furnace traceability.
- Enhanced OEE monitoring.
- Automated operational insights.
- Standardized IoT architecture across diverse manufacturing equipment.
- Scalable foundation for predictive manufacturing.
- Readiness for Industry 5.0 initiatives.
Impact
BXI Technology established a unified Digital Twin and Industrial IoT framework that transformed fragmented shop-floor data into actionable operational intelligence. The solution enabled centralized monitoring, improved production transparency, strengthened quality traceability, and created a scalable foundation for AI-driven manufacturing optimization across multiple production processes.
