Archive / current issue
Month: September 2026
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6–9 minutes
Predictive-Maintenance Auditability for AI Data Centers: Building an Evidence Trail from Alert to Verified Closure
A practical framework for preserving source evidence, decisions, work-order traceability, retesting, acceptance and retention across the predictive-maintenance control loop.
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5–7 minutes
Predictive-Maintenance Exception Management for AI Data Centers: Keeping Degraded Controls Visible, Owned and Time-Bound
A practical exception-management framework for keeping degraded predictive-maintenance controls visible, risk-assessed, owned, escalated and time-bound until verified closure.
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6–10 minutes
Predictive-Maintenance Change Control for AI Data Centers: Protecting Trust When Baselines, Rules and Models Change
How AI data centers can control predictive-maintenance changes to baselines, thresholds, sensors, models, OT integrations and CMMS/DCIM routing without weakening decision trust.
Data Center Health 