Predictive programs usually fail at the handoff, not the model. Here is an explicit ownership model for alert triage, disposition, scheduling, and verification that keeps alerts from expiring.
How to decide when maintenance work should happen: read the P-F curve, pick the right trigger for each failure mode, and balance reactive and proactive cost of work on your own assets.
A practitioner workflow for pairing vibration, temperature, and load data with utility meters and maintenance history so energy findings survive technical review.
A working framework for deciding when a condition alert should change a purchase order: signal confidence, asset criticality, supplier lead time, and work-order readiness.
Stop working the backlog first-in-first-out. Score every item on asset criticality, failure consequence, signal confidence, work readiness, and operating constraints.
Most predictive maintenance pilots prove detection and fail at the planner handoff. Use a production-readiness checklist and go/no-go rubric to turn alerts into scheduled, verified work.
A practitioner's method for combining vibration, thermal, ultrasound, oil analysis, and operator rounds around named failure modes, plus planner rules for conflicting evidence.
A step-by-step method for setting an OEE target from your plant's documented availability, performance, quality, and constraint data, using external benchmarks as context only.