Executive Summary
Equipment downtime and inefficiencies are among the top challenges in manufacturing operations today. This whitepaper outlines how a large-scale industrial manufacturer enhanced equipment performance, reduced waste, and improved decision-making using Analyzio’s OEE Analytics Dashboard. By tracking availability, performance, and quality in real time, the client gained unprecedented insight into operations and significantly improved their plant’s overall effectiveness.
Business Challenges
The client faced significant inefficiencies that limited throughput and predictability:
- Unclear Equipment Performance: Managers lacked visibility into how machines were truly performing across shifts.
- Frequent Unplanned Downtime: Downtime causes weren’t consistently tracked or categorised, delaying root-cause analysis.
- Inconsistent Quality:Production teams couldn’t easily identify when quality dipped below acceptable thresholds.
- Manual KPI Tracking: OEE and related metrics were calculated manually, often after the fact—limiting proactive response.
These issues not only led to lower production output, but also increased cost per unit and delayed deliveries.
The Analyzio Solution
To address these challenges, Analyzio implemented an integrated OEE Analytics Dashboard, designed to offer real-time monitoring and analysis across all core efficiency metrics:
- Monthly & Daily KPIs: Trends in downtime, OEE losses, and production output helped identify long-term patterns and daily fluctuations.
- Machine-Level Analysis: Each machine’s availability, performance, and quality metrics were monitored to spot inefficiencies.
- Improved Production Accuracy: Accurate tracking of parts quantity manufacturing helps the client maintain consistent production levels, reducing waste and ensuring that targets are met more reliably.
- Downtime Categorization: Real-time insights into causes of loss by shift and machine enabled immediate action.
- Production Comparison: Tracked planned vs. actual output for each shift to detect deviations early.
The dashboard provided a unified view across teams—from floor operators to plant managers—enabling a shift from reactive firefighting to proactive optimization.
Results & Impact
Just two months post-deployment, the client reported clear, measurable operational gains:
| Metric | Before | After | Change |
|---|---|---|---|
| Overall Equipment Effectiveness (OEE) | 58% | 75% | ↑ +17 points |
| Average Downtime per Shift | 112 minutes | 65 minutes | ↓ -42% |
| Production Plan Adherence | 68% | 91% | ↑ +23 pts |
| Machine-Specific Loss Tracing | Manual | Automated with visuals | ↑ Real-time visibility |
| Response Time to Anomalies | > 24 hours | < 1 hour | ↓ Vastly improved |
These gains resulted in faster delivery cycles, higher asset utilization, and reduced cost of poor quality (COPQ).
Key Takeaways
- Real-time visibility into OEE, downtime, and defects
- Faster issue resolution through shift-wise and machine-level insights
- Improved production consistency with better plan vs. actual tracking
- Proactive operations are driven by daily and monthly trend monitoring.
- Empowered decision-makers across plant and management levels.
Conclusion
Analyzio’s OEE Analytics Dashboard empowered this manufacturer to break through performance blind spots, uncover actionable insights, and significantly elevate equipment effectiveness. The holistic and intuitive view of their production landscape transformed decision-making and unlocked new levels of efficiency.
Contact Us to discover how our OEE-Analysis solution can drive similar improvements for your business.