Two decades of reliability engineering delivered across rotating equipment, steam systems, and critical plant assets for Fortune-500 operators — now amplified by applied AI.
Predictive maintenance is the practice of measuring an asset's condition while it is running, recognizing the early signature of a failure mode, and scheduling the repair before unplanned downtime occurs. Droz's predictive maintenance practice is built on four diagnostic disciplines — vibration analysis, thermography, ultrasound, and laser alignment — run by senior field engineers and indexed against twenty years of reference data. Programs are scoped to your critical asset population, calibrated to your plant cadence, and integrated into your existing CMMS so recommendations land where the work happens. Where applicable, Droz layers AI-driven anomaly detection and failure prediction on top of the field program (see Pillars B and C) so the operating model compounds over time. The result: unplanned downtime cut at the source, OEM tolerances held, and a maintenance budget that converges instead of escalates.
FFT spectral analysis and time-waveform diagnostics identify bearing wear, imbalance, misalignment, and looseness on motors, pumps, compressors, fans, and gearboxes.
Infrared imaging under operating load screens switchgear, MCCs, transformers, and mechanical drive trains for thermal anomalies — captured against baseline comparison.
Acoustic detection of lubrication regime, gas/air leaks, electrical partial discharge, and bearing pre-failure regimes — captured before vibration onset.
Coupled rotating equipment aligned to OEM tolerance — reducing seal failure, coupling wear, and vibration-driven downtime.
Across rotating equipment, static assets, electrical & control systems, and full production lines — the predictive maintenance practice covers the full plant surface.
Focus — condition monitoring, alignment, balancing.
Focus — integrity, monitoring, reliability.
Focus — thermography, diagnostics, AI insight.
Focus — efficiency, uptime, throughput.
Each asset family maps to an industry program — see all industries.
Field instrumentation and wireless sensors stream condition data from your critical assets. Scope, sensor placement, and sampling cadence are set by the lead reliability engineer in a kickoff walk-down.
Engineering practice and AI software interpret signal patterns against twenty years of reference data — bearing signatures, motor faults, and gearbox harmonics are matched to known failure modes.
Deviations from healthy baselines are flagged before they propagate into failure modes. Severity is graded and routed by criticality.
Models estimate remaining useful life and recommend the optimal intervention window so production loss is minimized.
Work orders, alerts, and operator recommendations are dispatched into your CMMS, email, and chat channels — closing the loop with maintenance planning.
Droz reliability engineers hold CMVA certification; all vibration programs follow CMVA category and reporting protocols.
Acceptance and severity thresholds for rotating machinery vibration are assessed against ISO 10816 zone limits A–D.
Field engineers are certified across Vibration Institute Categories I–IV, the global benchmark for vibration analyst competency.