OptimalAvailability Studio™Reliability engineering

Use cases → Reliability engineer

For the reliability engineer.

You have to justify the maintenance strategy and predict the availability. OptimalAvailability Studio™ gives you both, from one model rather than five spreadsheets.

The problem

A strategy in spreadsheets that never quite agree.

The FMEA, the task list, the block diagram and the life data live in separate files, so a change in one never reaches the others and nobody can defend the number.

One connected model

Functions feed the FMECA, the FMECA feeds the RCM and the RBD, the life data feeds the RAM.

Decide by consequence

RCM sorts every failure mode by consequence and picks the task that is worth doing.

Predict the availability

Monte Carlo RAM turns it into a system and production availability you can act on.

The outcome

What good reliability engineering returns.

Ranges confirmed across Optimal client engagements. Illustrative, not a guarantee.

+10–25%
Productivity
+3–7%
Asset availability
−8–20%
Maintenance cost
−5–10%
Spares inventory

"When the model showed the redundant pump bought less availability than a shorter repair, the spend moved and the number went up."

Illustrative of the reliability-engineer workflow. Replace with a named client quote in the build.

Build a reliability model you can defend.

Start a 14-day trial and design the strategy on your real assets.

14-day trial · access issued by hand · no card required