Use Case Measurable Impact Quick Overview:
Many manufacturers still rely on manual production reporting to calculate OEE, especially the performance component. Operators record counts manually, log downtime events inconsistently, or update spreadsheets long after issues occur. This creates a fundamental measurement problem: the OEE data is delayed, subjective, and often inaccurate.
The biggest losses are hidden in performance because traditional reporting fails to capture:
These small inefficiencies accumulate throughout the day, silently reducing output and pushing OEE downward. Because they are rarely logged, supervisors cannot diagnose them or intervene early. Without a real-time OEE monitoring system, factories operate reactively and only learn about inefficiencies after the shift has ended, when it is too late to correct the root cause.
This leads to:
In short, manual reporting cannot support high-performance manufacturing.
By adopting visionAI’s OEE Plus+ solution, manufacturers transform their existing CCTV cameras into a real-time OEE monitoring system that automatically measures production counts, cycle speeds, and performance losses with complete accuracy.
visionAI OEE Plus+ delivers:
The system exposes exactly when and where performance loss begins, whether caused by operator delays, upstream feeding issues, small jams, or inconsistent line flow, enabling supervisors to address issues proactively. Because the solution uses existing CCTV, deployment requires no hardware changes.
Manufacturers using visionAI’s OEE Plus+ solution consistently report significant improvements. Most achieve 20–30% increases in OEE, driven by accurate performance counts and rapid corrective action.
One food manufacturer improved from approximately 70% to above 85% OEE within six months, reducing downtime, stabilising throughput, and unlocking higher production capacity without new equipment.
Real-time OEE data empowers teams to make decisions in the moment, improving performance, reducing waste, and maximising line potential.
