67% Downtime Reduction with Real-Time OEE Tracking

A leading automotive component manufacturer operating 12 assembly lines was facing critical visibility gaps in their production operations. Despite investing in automation, the plant struggled with unpredictable downtime events that cascaded across multiple production lines.

Key Pain Points:

• No real-time visibility into line performance or equipment status
• Manual data collection through paper-based shift logs prone to errors and delays
• Unable to identify root causes of downtime until hours or days after events occurred
• Production planning based on estimates rather than actual OEE metrics
• Maintenance teams reacting to failures instead of preventing them
• Quality issues discovered downstream, resulting in costly rework
• Disconnected legacy PLCs with no unified monitoring system

The plant manager estimated that unplanned downtime was costing the facility over $3.5 million annually in lost production, overtime labor, and expedited shipping to meet customer commitments. With tight automotive industry margins, this was unsustainable.

Anexee deployed a comprehensive real-time OEE tracking system that unified all 12 assembly lines into a single monitoring platform. The implementation focused on automatic data collection, real-time visualization, and actionable analytics.

Implementation Approach:

• Connected 127 PLCs and control systems via OPC UA and Modbus protocols
• Deployed edge gateways for local data processing and buffering
• Configured custom OEE calculations aligned with automotive industry standards
• Created role-based dashboards for operators, supervisors, and plant management
• Integrated with existing ERP system for production scheduling synchronization
• Implemented mobile alerts for critical downtime events
• Established automated shift reports eliminating manual data entry

Implementation Timeline: The full deployment was completed in 8 weeks, with pilot testing on 3 lines followed by phased rollout to remaining production areas. Training was conducted in parallel, with operators becoming proficient in the new system within days.

Within three months of deployment, the manufacturing facility achieved remarkable improvements across all key performance indicators. The real-time visibility enabled rapid response to issues and data-driven decision making.

Additional Benefits Realized:

• Maintenance team shifted from 80% reactive to 70% preventive work orders
• Production scheduling accuracy improved by 34% through actual vs. estimated cycle times
• Quality defects reduced by 28% through early detection of process deviations
• Energy consumption per unit decreased 12% by identifying idle equipment
• New operator onboarding time reduced from 2 weeks to 4 days with visual work instructions
• Management gained confidence to take on additional customer contracts