Pubblicata il 02 ott 2026 · Abbiamo verificato il 02 ott 2026 che è ancora attiva
Questa azienda è tua?US$ 15 – US$ 25 per progetto
We are building an AI-powered root-cause investigation workspace designed for industrial maintenance and reliability teams. When critical assets (e.g., centrifugal pumps, booster compressors) fail, engineers lose days hunting for evidence scattered across historians (AVEVA PI), DCS/SCADA alarm logs, work order histories (SAP PM / IBM Maximo), and shift notes. We are looking for an experienced Industrial Reliability / Maintenance Engineer to partner with us to review our investigation workflows, test simulated plant failure datasets, and validate our automated evidence collection workspace. You’ll walk through our guided investigation flow, centered on centrifugal pumps, booster compressors, and heat exchangers, and tell me where the logic, data mapping, or user experience falls short of real-world practice. I’ll share time-series data, alarm storms, and maintenance histories; you replicate how you would normally investigate the event, compare that to what the workspace serves up, and flag any missing context or misleading correlations. Deliverables • Written review outlining gaps, false positives/negatives, and improvement suggestions • Marked-up screenshots or screen recordings highlighting issues in the UI/UX • A ranked list of additional data signals or reliability KPIs you would require before signing off on an RCFA Acceptance criteria Your feedback should be actionable, reference the exact tag names or work-order fields involved, and be detailed enough that a developer can implement changes without follow-up. If you’ve chased bad actors across PI tags, SCADA logs, or backlog in Maximo and know how a real plant team thinks under pressure, I’d love your critical eye.
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