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Where the IoT meets the Facility Engineer

kellyhensen

In the good old days (two facility engineers talking).

Engineer 1:  “The conveyor in the southeast corner is making that noise again.”

Engineer 2:  “The grinding noise or the squeak?”

Engineer 1:  “The grind.  I hit it with the wrench yesterday afternoon and it was fine the rest of the day, but it’s making the noise again this morning.”

Engineer 2: “Better order what you need to repack the bearings before is seizes up again.”

 

Enter the IoT. . .

Engineer installs sensors on 127 mission critical areas of the facility measuring rotations, temperature, noise levels and power consumption.

Engineer has to convince IT department to invest in a server to store all the data that the sensors are collecting – outside of the DMZ, so the consultants can access the data real-time.

Wireless gateways are installed throughout the facility to communicate with the sensors and send the data to the new server.

Data is collected.

Data is modeled.

Predictive analysis algorithms are developed and tested.

 

And then, in the brave new IoT world. . .

A sensor monitoring noise attributes starts logging higher than usual levels.

An order is automatically placed for replacement parts.

The engineer receives a work order for preventative maintenance to repack the bearings.

 

The question is:  Is it all worth it?  And how to we prove that it is (or it isn’t)?

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    Ask an experienced MBA executive this question and he will commission a team to work out the business case. The business case will be ambiguous, with a bunch of "if" qualifiers because nobody wants to be wrong. The executive will make a decision, because that is what they are paid to do. If the decision is to automate, and it turns out to be exorbitantly expensive, the original decision will never be revisited because current conditions are different from when the decision was made. This isn't good or bad, it is just the way it works - ask any executive - their decisions are based on the best information available at the time.

    Ask an experienced scientist this question and he will go away and do a scientific study which concludes something unexpected - like the Internet isn't secure enough to trust with motor maintenance. He will be correct but it will leave more questions than answers. Because good science is like that.

    Ask an experienced engineer this question and he will always say automate. Ask him why and he will say - its the same reason engineer 1 and 2 knew what to do with the motor bearing - training and experience. Ask him what about Internet security and he will say - if that is a problem, we will fix that too.

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    Ask an experienced MBA executive this question and he will commission a team to work out the business case. The business case will be ambiguous, with a bunch of "if" qualifiers because nobody wants to be wrong. The executive will make a decision, because that is what they are paid to do. If the decision is to automate, and it turns out to be exorbitantly expensive, the original decision will never be revisited because current conditions are different from when the decision was made. This isn't good or bad, it is just the way it works - ask any executive - their decisions are based on the best information available at the time.

    Ask an experienced scientist this question and he will go away and do a scientific study which concludes something unexpected - like the Internet isn't secure enough to trust with motor maintenance. He will be correct but it will leave more questions than answers. Because good science is like that.

    Ask an experienced engineer this question and he will always say automate. Ask him why and he will say - its the same reason engineer 1 and 2 knew what to do with the motor bearing - training and experience. Ask him what about Internet security and he will say - if that is a problem, we will fix that too.

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