What the team was up against.
[Placeholder] The manufacturing floor was running blind — production data was collected on paper and entered into spreadsheets at the end of each shift.
[Placeholder] By the time managers saw the data, it was 8+ hours old. Quality issues weren't caught until downstream, costing thousands in rework.
How I thought about it.
[Placeholder] Mapped the entire production line to identify the 12 critical data points that would provide the most operational insight.
[Placeholder] Designed a system that could handle 10,000+ sensor readings per minute while providing sub-second visualization updates.
"Real-time data is only valuable if people can actually act on it. We designed alerts and views around decision points, not just raw metrics."
What shipped.
[Placeholder] Deployed IoT sensors across the production line with edge computing for initial data processing and anomaly detection.
[Placeholder] Built a real-time dashboard with D3.js visualizations that updates instantly and sends alerts for out-of-spec conditions.
Built with.
What it produced.
[Placeholder] The dashboard is now the command center for the entire manufacturing floor. Operators can spot and address issues in real-time, and the predictive maintenance features have prevented 12 unplanned equipment failures.
What I'd do differently.
[Placeholder] Industrial environments are harsh on electronics — we underestimated the need for ruggedized sensor enclosures and had to replace several in the first month.
[Placeholder] The operators were initially skeptical of the new system. Getting them involved in the design process earlier would have accelerated adoption.
