The Problem
- No real-time visibility into production performance
- Downtime causes disputed between production and maintenance
- Quality losses not captured until end-of-shift reports
- Cycle time variations hidden in averaged data
- Improvement initiatives lack baseline and tracking
Modern Approach
- Real-time OEE dashboards showing availability, performance, and quality
- Automatic capture of downtime events with reason coding
- Cycle-by-cycle tracking identifies variation sources
- Analytics show Pareto of losses by machine, product, and shift
- Improvement tracking with before/after comparison
Frequently Asked Questions
What is OEE and why does it matter?
OEE (Overall Equipment Effectiveness) measures how much of your theoretical capacity you actually use. It combines availability, performance, and quality into a single metric. World-class OEE is 85%+; most plants operate at 60-70%.
How does real-time OEE monitoring work?
Sensors on machines capture cycle counts, run time, and quality signals automatically. The system calculates OEE continuously and displays on dashboards. Operators and managers see performance as it happens, not in end-of-shift reports.
What improvements can OEE monitoring drive?
Common improvements include reduced changeover time, faster response to downtime, better scheduling, and focused maintenance. Most plants find 10-20% hidden capacity through systematic loss elimination.
How long does OEE implementation take?
Basic monitoring for a production line takes 2-4 weeks to install and configure. Comprehensive plant-wide systems typically take 2-3 months for full deployment and adoption.
What is the ROI of OEE monitoring?
ROI comes from recovered capacity (avoiding capital investment), reduced overtime, and improved delivery performance. Most plants see 3-6 month payback on monitoring investment.