aRTi-D™ ΟΕΕ,Production Analytics
OEE that leads to real
production improvements
production improvements
SEEMS’s aRTi-DTM OEE application shows how efficiently machines are operating—in real time and based on historical data—helping to identify delays, losses, and areas for improvement.
// 01 — The problem
Why OEE Often Doesn’t Lead to Improvement
In most industries, OEE is measured—but often that’s as far as it goes.
In many cases, it’s based on unreliable data, or even when the data is accurate, it doesn’t guide subsequent actions.
11%
of time is lost due to unplanned downtime – in the world’s 500 largest industrial companies (Siemens, 2024).
800h
of downtime per year is the average for every industry sector, more than 15 hours per week of lost production (Aberdeen Research).
2/3
of industries experience at least one unexpected downtime event every month—at an average cost of $125,000 per hour(ABB, 2024).
× Which losses have a real impact on production
×Where to start making improvements
× Whether interventions pay off over time
Result: improvements without prioritization and decisions based on assumptions.
// 02 — The Approach
What makes SEEMS' OEE different?
It goes beyond mere measurement. It combines reliable data, analysis, and recommendations to turn OEE into a tool for continuous improvement.
▮▮▮
01
Reliable data
Right setup, right insights.
Connection to a PLC and proper production mapping for data that reflects actual operations.
◔
02
Real-time analysis
Not metrics, but causes
Downtime, losses, speeds, and quality by shift, machine, operator, and line—complete operational transparency.
★
03
AI-powered recommendations
Clear next steps
Trend analysis and alerts based on historical and real-time data.
// 03 – Features
What it actually offers
Real-Time Production Intelligence
• Real-time OEE per machine and line (Availability, Performance, Quality)
• Automatic recording of downtime and losses
• Monitoring of production targets with a continuous performance overview
• Integration with ERP for production, scrap, and order tracking
AI Driven Optimization
• Recommendations for improvement based on actual production data
• Forecasts for future production trends
Enterprise Analytics & Dashboards
• Comparative analysis by product, shift, and production line
• Alerts for timely decision support
• Performance and loss reports by period
• Dashboards for production and management
// 04 – Results
What You Gain in Practice
In typical applications, SEEMS helps achieve:
→ OEE evolves from a monitoring KPI into a tool for evidence-based action and continuous improvement.
// 05 – Flexibility
For every type of production
It supports both batch and continuous production, tailoring the analysis and recommendations to the logic of each process.
DISCRETE
Discrete production
Analysis by batch, order, and product—with a comparison of planned versus actual output.
CONTINUOUS
Continuous production
Real-time monitoring of flow, speed, and quality deviations.
// 06 – Unified platform
OEE as part of a unified platform
The OEE application does not operate in isolation. It integrates seamlessly with the other modules, providing deeper insights and more meaningful recommendations.
OEE — Central Analytics Hub
CONNECTED TO
Production Orders
Comparison of planned and actual performance per order.
Quality Control
Correlation between quality losses and production processes and conditions.
Predictive maintenance
Understanding the role of equipment and failures in performance.
Energy & Environment
Interconnectivity between performance, energy consumption, and operating conditions.
As a result, OEE evolves from a standalone metric into a central focus of production analysis—drawing on data and correlations from across the entire platform.
