PS: I've heard people argue that one of the best ways to avoid a problem is not to touch the machine when you don't have to. Otherwise, you introduce problems by doing work that's not necessary. Is that part of what you see, specifically that safety improved and also perhaps reliability because people simply were touching machines only when they had to?
JL: I couldn't tell you the statement is true. It kind of depends on the equipment you're working on, honestly. You'd have some of your PMs they're intrusive and you're actually taking the equipment out of service and you're lifting and landing leads and doing a number of things. Those are obviously going to be more at risk for maintenance-induced types of failures.
I will say that the preventive program that we use, it's like our core business, that program. It factors into induced errors into the account maintenance calculations. That helps a lot. Other equipment, you're not maybe as intrusive on it, so you're not going to see the near-error rate. You need to be aware of it but it is definitely a factor. If you track your maintenance-induced errors, you'll see an improvement in that arena as you reduce the amount of intrusive maintenance that you're doing.
PS: John just brought up the issue of using data from historians, time-series data, since we also have technology for sensor data. Is there really that much value from work order data alone?
DV: Again, depending on where each customer may be, obviously some are more mature than others. So a less mature customer is going to drive a lot more value from work order data to start with. That's part of our journey, to take our customers up that maturity curve by starting with optimizing their maintenance strategies, and then from there that can lead into some condition monitoring maintenance work where equipment is sensored.
To be honest with you, what we find ultimately is that most people are going to end up with some kind of a blended maintenance strategy. It's not cost-effective to sensor everything on your non-critical equipment, but you may have some monitoring that is possible. But there's still going to be some schedule-based maintenance, whether it’s calendar-based, or runtime based, or whatever.
And really the combination of the two is probably going to get you the most cost-effective maintenance strategy. That's one thing that we try very hard to understand is that, when I implement a predictive solution, what failure modes am I now detecting? What failure modes am I mitigating and what time-based tasks or calendar-based tasks can I now go relook at and see if I can relax and drive that cost savings that way? Back to your original question on how much value is in a work order data, I think it's an overlooked source of value if you put it that way.
JL: One of the more exciting things that's happened in the last year with the Uptake solution for us is they updated our ability to change our wear data in the failure distributions on each failure mechanism. That has added a lot of value for us because now we can go in on a specific mechanism and maybe the awareness started five years at the fifth centile in a mild environment. We're looking at our data, it's more like eight years and that will change our solution when we change that wear time but you have to have the ability to mine your data to do that. I would argue that the more mature your plant is, the more mature your plan is, the better your data is for doing failure mode effect analysis and things like that.
