SAG_Twitter_MEME_Time_to_Trust_Predictive_MaintenanceI was in the car when my six-year-old son said: “I have learned two important things from watching TV.”

Intrigued, I asked: “What is the first?”

“Time is the most valuable commodity in the world. It’s more valuable than money.”

I was impressed that he managed to learn anything at all from TV, let alone something so profound.

Intrigued, I asked: “Why is time so valuable?”

“Because once it is gone, you’ll never get it back.”

I considered his response. Time is the most valuable commodity we have. Often we equate time with money, as if it has only a monetary value. But time can mean more than that. It can’t be purchased and once it is gone, it is lost forever.

If the car I was driving had broken down in the middle of, say, a desert where there was no cellphone coverage and no garage for miles, I would miss work and maybe lose a big deal with a new customer. That would cost me and the company money. But the time that was wasted - spent swearing alternatively at the car manufacturer and the cellphone company and then walking pointlessly in the wrong direction to get help - I would never get back. (More importantly, our lives might have been endangered.)

If you are a manufacturer, if a mission-critical machine breaks down and there are no spare parts and no experienced technicians within 60 miles, your plant could go offline for a time. Yes, it could cost you money, but it also could cost you your reputation as a reliable supplier - especially if it happens a lot.

Preventive or planned maintenance, where manufacturers do routine replacement of parts and machines, is an accepted practice for mission-critical machinery. You cannot afford to have broken equipment, so you replace it even if it does not need replacing – just in case.

Run-to-fail, where it breaks and then you fix it, is standard for less critical equipment. The attitude is that it is cheaper to fix it after it fails than to replace it before it does.

Predictive maintenance is where analytics are applied to data from sensors in the equipment, in order to anticipate when problems might arise - and fix them before they do. This is less accepted, mainly because manufacturers believe it is expensive. But is it? Using predictive maintenance gives you time to fix something before it breaks. You know that it is going to break – and when.

Using my car as an example, why should I change the oil every 3,000 miles if the car can run 25,000 miles on the oil that is in it? By monitoring the quality of the oil (is it breaking down?) and the lubricity of it (is it getting to where it is needed?), I can predict when it is necessary to change it. This saves me money ($35 each oil change) and time (taking the car in and waiting, doing a dipstick test each week).

I am fixing it before it WILL fail, not before it MIGHT fail. Better yet, I am fixing it on actual performance requirements and usage.

If you have a gigantic production facility and are doing manual diagnostics, you are wasting a lot of time and money on having employees running around checking on the equipment. Using sensors and predictive analytics in this scenario saves both money and time.

Because time is our most valuable commodity, predictive maintenance is one of the most valuable tools available to manufacturers. I think it is time to trust it.

I was thoroughly impressed that my six year old could learn something so profound from television. Clearly, he is a genius beyond his years. But there was something else. My expectations had been raised and my pride had swelled at the supernatural intelligence of my six year old.

“What was the second thing you learned from television?” I asked.

“Daddy, this is the most important thing of all. Never trust a friendly looking alien who says I come in peace. They never do.”

And with that, all was well in my world again.

 

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