125% OEE Growth Achievement: Real-time Machine Monitoring in Cable Manufacturing

@Faclon Team

November 14, 2025

1min read

About the Company

A globally recognized leader in cable manufacturing operating across diverse sectors including power transmission, telecommunications, and automotive. With $2+ billion in revenue, the company operates across 9 verticals with 10,000+ employees distributed across 15 manufacturing locations. The organization plays a crucial role in delivering high-performance cables to industries both domestically and internationally, focusing on innovation and operational excellence to maintain market leadership.

Problem Statement

Critical operational challenges threatening manufacturing efficiency

Manual data dependency Organization relied on error-prone manual analysis lacking accuracy, preventing management from making precise productivity improvement decisions
High delivery time Unscheduled downtimes, production bottlenecks, operator inefficiencies, and unoptimized planning increased time and cost of delivery
Insufficient innovation Absence of real-time insights, KPI benchmarking, and data analysis prevented unlocking true production potential and optimization opportunities
Scalability limitations Management struggled to implement solutions rapidly across different machine makes with minimal OEM dependencies and accurate downtime measurement

How Faclon Solved the Problem

I/O Sense Platform: Comprehensive Industry 4.0 deployment for energy management and process optimization

Production management integration

Managers enter job specifications (machine name, process type, rated speed, material consumption) on I/O Sense platform with NPD marking capability

Operator interface deployment

HMI screens enable operators to record job duration, downtimes with machine interlocks ensuring data accuracy and automated production switching

PLC and energy integration

Connected with existing PLCs for line speed data and energy meters via Modbus 485 for comprehensive process parameter capture

Multi-case implementation

Three flexible approaches: existing HMI customization, separate low-cost HMI deployment, and Panel IPC implementation for enhanced performance

Quality assurance integration

Quality teams update rejection percentages directly on generated report forms for complete production tracking

The Outcome

Comprehensive results across operational efficiency

125% OEE improvement

From 11.13% (2022-23) to 25% (Current FY), demonstrating continuous operational enhancement

E-beam productivity gains

Utilization improved by 7% and Beaming improved by 5% on year-over-year basis

100+ active users

Comprehensive stakeholder adoption from operators to CXOs with seamless platform utilization

1M+ daily data points

Massive data processing capability enabling deep analytical insights and decision-making

6+ improvement plans initiated

Data-driven optimization strategies implemented based on real-time insights

Behind the Scenes

Advanced technical implementation and strategic deployment considerations

Multi-machine deployment strategy

104 machines across 9 categories: PVC Compounding (2), Extrusion (63), Armouring (4), Electronic Beaming (4), Wire Drawing (8), and others

Flexible hardware architecture

Three implementation approaches based on machine capabilities: Profinet protocol integration, MODBUS TCP with separate PLCs, and Panel IPC deployment

Comprehensive dashboard ecosystem

KPI Dashboard, Machine Analysis, Job Directory, Machine Status TV displays, Machine Timeline with edit capabilities, and specialized E-beam monitoring

Advanced alerting system

Conditional alerts for line speed deviations, extended downtimes, machine underutilization, and disconnection monitoring

Scalable reporting framework

Pre-built report library including Daily Job Summary, OEE Reports, Operator Report Cards, plus custom Excel report generation using Compute Reports feature

Data quality assurance

Machine interlocking systems, operator accountability mechanisms, and timeline editing capabilities maintaining original and modified data for audit trails

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