I’m building a browser-based OEE application that zeroes-in on one problem: understanding and visualising every minute of downtime on our manufacturing machines. The system has to sit on a web server (self-hosted or cloud), collect run/stop signals in real time or through manual entry, let operators assign a reason code, and then convert that stream of events into clear OEE, MTTR, and loss-Pareto dashboards. Core workflow • Data capture – REST, OPC-UA, MQTT or CSV upload from each machine, with a fallback manual form for operators. • Downtime reason logging – configurable hierarchy of loss codes, mandatory before a machine can be restarted. • Analytics – live OEE gauges, shift/day/week reports, reason-code heat maps, export to CSV/Excel, and an API for BI tools. • User & asset management – roles, permissions, and a simple interface to add or clone machines, shifts, and products. • Responsive UI – works smoothly in any modern browser on desktop or tablet. Acceptance criteria 1. Demonstrate with at least one simulated machine that start/stop events generate an accurate OEE timeline. 2. Selecting a downtime reason instantly updates live dashboards without refresh. 3. Database script, build instructions, and a one-click deploy (Docker or similar) are provided. 4. Code is clean, commented, and handed over with admin credentials. I’m flexible on the stack: Python (Django/FastAPI), Node.js (Express/Nest), or ASP.NET Core are all fine as long as the final result is fast, easily maintained, and open-source friendly. If you’ve built shop-floor MES or similar OEE tools before, I’d love to see a quick demo or screenshots when you bid.