OptimalAvailability Studio™ Wiki / Value and deployment
Value and config
Value and deployment
What structured reliability engineering returns, what data it needs, and how it is configured to deliver, in general terms.
Potential value
Across Optimal client engagements, structured reliability and maintenance strategy return value in these ranges, shown for context, not as a guarantee:
Availability rises as the right failures are caught and the wrong maintenance is stopped; maintenance cost falls as calendar tasks give way to on-condition and run-to-failure where justified; productivity follows from both.
What it takes: the inputs
| Asset register and hierarchy | A clean asset breakdown and taxonomy, ideally to ISO 14224, so analysis is reusable across like assets. |
|---|---|
| Functions and operating context | What each asset must do, and the duty and environment it does it in. |
| Failure history | Work orders and failure records from the CMMS, coded well enough to fit distributions and rank causes. |
| Generic reliability data | Industry failure rates and Weibull parameters (OREDA-type) to seed the model where local history is thin. |
| Cost and production data | Repair costs, downtime cost and production rates, so consequences are in money not adjectives. |
Config to deliver value (general)
In general terms, the model earns out when: the taxonomy and failure coding are clean (ISO 14224), so history is analysable; criticality is ranked first, so effort goes to the vital few not the trivial many; the critical assets are modelled in depth and the rest by class; and the model is kept live from the CMMS rather than done once and shelved. No sensors are required to start, this is design and analysis, though the model gets sharper as OptimalTREND™ condition data flows back into it.
A typical path
Rank criticality across the asset base; run RCM and FMECA on the critical few; package the tasks into the CMMS; build the RBD and RAM model to size redundancy and spares and to predict availability; feed the on-condition tasks to OptimalTREND™, the spares to OptimalSPARES™ and the indicators to the ARaaS® Dashboard; then review on a set cadence as real failure and condition data accrue.
Where do you stand?
Before you invest, the GARPI™ benchmark shows your asset-management maturity against industry peers: an independent, ISO 55001 and GFMAM-aligned score from 0 to 100 across eight weighted dimensions and five maturity tiers, free and anonymous. It is a fast way to see where you are today, and where OptimalAvailability Studio™ moves you first. Take the GARPI™ benchmark.