What, actually, IS “an optimal solution”

An optimal preventive maintenance, or (predictive maintenance) decision means finding the best balance between the risk of a costly in-service failure and the goal of getting as much usage out of the part as you can. This is the “lowest-cost” point. The best replacement time.

To start, here's a non-maintenance example. You intend to buy a high quality roast of lamb. There are a number of shops that carry lamb roasts. They differ in the level of quality of their meats, and some shops are nearer to you than others.

The ideal choice would be to pick the shop that had the best meat, the lowest price and was nearest to you. But life seldom works that way. Quality is the most important factor for you (you're having the boss to dinner). Price is also a factor so you de-list outlets that charge outrageous prices. Driving time is not that important, but still you'd rather not drive farther than you had to. So you make your choice — the shop with high (but not necessarily the very highest) quality; that has fair, but not necessarily the lowest, price; and is not around the corner but not the farthest away either.

That's your optimal choice. You satisfy your requirements by balancing your risks and your costs. You end up with the optimal solution. everything consid-ered.

That's how RelCode works. It finds the optimal answer to the replacement dilemma …

“If we replace the part now, maybe it would have lasted quite a while longer … but … if we wait for a scheduled overhaul, the component may fail on-the-job — and cause a costly emergency repair”.

You want to run you components a long time (you get more usage for your money if you do), but not so long that a large number will fail in service. You want to keep your costs down so you aim to replace as many components as possible on a planned basis, not an emergency basis.

Go directly to our next question on Weibull analysis (aka Weibull distribution) and other optimization-related matters,
OR
Return to the Questions Page.