Using motor application parameters to support root cause analysis

Using motor application parameters to support root cause analysis

There is a machine in your facility whose motor fails every couple of years. Your job is to find out why. Conducting a root cause analysis of the failures is the place to start. You need an understanding of the factors that should be considered in choosing the correct motor for the application so you can tell if the motor is the right one for the machine.

In the last installment, When building a PM system, decide which Failures Are Significant, we ranked a list of functional failures for our problem machine.

In my last post, Developing a Preventive Maintenance System - Step 1, I discussed how to make a list of the possible failures of a machine. We started by asking, what are the functions of the machine, and then how can it fail to meet those functions.

In a prior blog post, How to develop a preventive maintenance system , I outlined a Six Step process for determining what preventive maintenance should be done on a machine. This post describes the first step in more detail.

I believe that Reliability Centered Maintenance is the best approach developing maintenance tactics for critical machines. But not every plant can afford, can get approval, or has the manpower for a Reliability Centered Maintenance program.

Jonathan Guthrie in a comment on a LinkedIn discussion described what he called “Negative Work”. I think this might be a good tool for building a desire for change in the maintenance workforce.  I’ll let him describe it.

So you have this big MRO spares inventory. And you know you should be doing a physical count so you know what you have and where they are. But, where do you start. It’s been years since you really looked at it.

One of the major problems we run into when trying to do analysis of our equipment to find problems and improve reliability is the lack of information. Things like down time, as found condition, time to repair, time waiting (for parts, information, tools, support, the machine, …), cause, parts used, etc. You get the idea.

In a recent blog, I wrote about how to estimate the reliability of a machine in a production situation. Dave at Ramsoftuk rightly pointed out that the age of a machine at the time the reliability estimate is made can affect that estimate.