| | Cons | |----------|----------| | High cleaning efficiency at relatively low power consumption. | Initial cost is higher than basic ultrasonic cleaners. | | Flexible frequency & temperature options cover a broad range of materials. | Requires periodic maintenance of transducer surfaces. | | Robust safety interlocks reduce risk of overheating or dry‑run. | The 4 L tank may be limiting for very large batch jobs (though expansion kits are available). | | Easy integration into automated production lines via Modbus. | Noise level, while reduced, is still noticeable in very quiet environments. | | Compact footprint for a 250 W unit. | Learning curve for advanced programming (but the UI is intuitive). |
| Sprint | Deliverable | |--------|-------------| | (2 weeks) | - Set up data extraction pipeline (article‑tag pairs). - Define taxonomy sync job. | | Sprint 2 (2 weeks) | - Train baseline model (quick‑test). - Create API contract (OpenAPI spec) & stub server. | | Sprint 3 (2 weeks) | - Implement suggestion service (FastAPI / Spring Boot). - Add rate‑limiting & fallback logic. | | Sprint 4 (2 weeks) | - Front‑end prototype: dropdown UI, keyboard shortcuts, acceptance logging. | | Sprint 5 (2 weeks) | - Integrate with taxonomy service (validation, hierarchy enforcement). | | Sprint 6 (2 weeks) | - Add feedback logging pipeline (Kafka → Snowflake). - Build basic analytics dashboard (Grafana/Looker). | | Sprint 7 (2 weeks) | - Load testing & performance tuning. - Accessibility testing & bug‑fixes. | | Sprint 8 (2 weeks) | - Beta rollout to 10 % of authors (feature flag). - Collect early acceptance data, refine model. | | Sprint 9 (2 weeks) | - Full production rollout, monitoring dashboards live. | | Post‑Launch (ongoing) | - Weekly model retraining (using latest feedback). - Quarterly taxonomy audit. | MUKD-482
Clustered micro-edge with central control | | Cons | |----------|----------| | High cleaning