Overview
Growing production complexity made static reporting insufficient. Operators needed immediate access to line-level performance signals.
The challenge
Integrate diverse IoT signals, convert raw telemetry into actionable KPIs, and expose clear operator-level insights in one interface.
Our approach
We built a microservice platform combining IoT ingestion, KPI computation, and performance dashboards for supervisors and operators.
What we delivered
- •Real-time process monitoring platform
- •KPI and production-position analytics layer
- •Employee performance reporting modules
- •Scalable microservice backend
Architecture and implementation
- •Telemetry ingestion and normalization pipelines
- •Service separation for analytics, reporting, and UI
- •Event-driven updates for real-time supervision
Delivery timeline
Phase 1
System design
Defined IoT integration points and telemetry schema.
Phase 2
Platform build
Implemented services, KPI engine, and dashboards.
Phase 3
Operational rollout
Connected production lines and tuned reporting views.
Phase 4
Optimization
Improved performance and operator usability.
Screens and artifacts
Platform capability coverage
Technology
Key outcomes
- ✓Faster operational decisions from live plant data
- ✓Higher transparency on process and workforce performance
- ✓Foundation ready for further automation initiatives
Related case studies
This case study is shown at a summary level due to NDA. Full technical detail and references are available on request. Production KPI baselines and plant identifiers are removed. Contact us.