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Q3 MMS Predictive Maintenance Case
P-02Predictive Maintenance · Sep 2025 – Jan 2026

Tasked with inheriting and building on top of a previous year's prototype, the team developed a full-stack monitoring system in collaboration with Fontys and industry partner Q3 Concept B.V.. The system monitors machine operations and mold health based on real-time production data. To resolve severe bottlenecks from rendering massive datasets, I implemented viewport-based chart loading, reducing historic data chart load times from ~2 minutes down to 4–7 seconds. The updated platform also introduces real-time energy monitoring to track and analyze power consumption across machines.
Core features
- Legacy codebase refactoring to inherit and build on top of a previous year's prototype, resolving technical debt
- Machine & Mold Monitoring dashboards showing operational status with clickable mold detail pop-ups and historical weekly graphs
- Optimized viewport-based chart loading to keep dashboards responsive, cutting load times by over 95%
- Energy monitoring system tracking heating, production, and idle kWh usage alongside estimated cost breakdowns
Tech Stack
Next.jsReactSupabasePostgreSQLTailwind CSSDockerJestAgile
Gallery
Gallery · 1 shot
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Historic data chart speed fix (1 / 1)
Team
All documentation can be found on GitHub.