George Williams, founder and CEO of ReliabilityX, is a CRL, CMRP, a Black Belt in Reliability and a CMRP of the Year recipient. During the Q&A portion of the webinar, “Case Studies: 7 Companies Reveal Their Secrets to PdM/RxM Success,” Williams explores how to achieve PdM success and get the most out of your CMMS.
PS: What, in your opinion, has been the biggest change in the past 20-25 years? Is it the knowledge base? Is it the adoption rate, or has technology shifted?
GW: Well, that's interesting. There's expanded use of technology and the technology has become much more available from a price point perspective. If you look at the infrared camera, we were using that pieces, you have a $60,000 infrared camera and now you can get a FLIR ONE for your phone for 399 bucks and it honestly has better clarity than a P66. So it doesn't have as many sensors, but the visual clarity is even better. And the ability to overlay the physical photo with the infrared photo is dramatically different.
There are some, some additional technologies. The advent of motion amplification is kind of shaking the world up a little bit. The other big factor is the cost of wireless sensors. Wireless sensors, when we were first doing this, were extremely expensive and not cost-prohibitive and now that's not really the case. Now they're relatively inexpensive and you can put in a wireless system assuming you have the wireless infrastructure in place at a relatively low cost across the plant.
PS: Could you comment a little bit on how the success of PdM relates to the ability to get data into the CMMS and onto the right people? My takeaway from what you said was if you do the work and it never gets in the CMMS, there's a good chance nothing might happen.
GW: Yeah, no doubt. Without the work order to do the corrective repair your predictive technologies are relatively useless, you're not getting the work done. Ultimately the goal is to have planned and scheduled work prepared and ready to go. Now, you may make a business decision that you can't take that unit down. Maybe this unit only comes down at shut down and you're hoping you reach shut down, but you have an opportunity at that point with the work order in the system to get the parts ready to mobilize, to have everything prepared to go in the event you don't make it the shutdown.
There's options open and work gets done with work orders, and without the follow-up work order it becomes very cumbersome. One of the places that technology can go that it hasn't gone effectively enough is standardizing the language of some of these databases so that it's easily incorporated directly into your CMMS. I know that can be a challenge, but with data historians and the ability to pull data from a historian and put it in and create integrations that 20 years ago were very complex and required lots of code, the advent of data historian should make that much easier now.
PS: How did you calculate your avoided costs when it comes to PdM? And you and I have talked about this at events, that some plant teams accept avoided costs as a real thing, yet others treat them as imaginary numbers until you can show them hard cost savings. How are some of those costs calculated?
GW: If you actually have data around the manufacturing space, then this becomes much easier because you can use the loss time associated with: Should the unit go down reactively? What did it cost to get the unit? What would you have lost in production output? And if you are not, if you are in a service industry this is much less available, what's the cost of research?
When you're talking about a motor that's showing a bearing issue and the motor goes down, what does it cost the business or what risk exists to the business, if that fan or blower or pump is out of commission? In some cases, if you have redundancy, you deal with, say, water utility organizations and their significant redundancy. What is the cost of one pump going down? Well, then we have to understand that what you're trying to do is avoid risk because there's a significant risk if you're down to just one.
So you're using these predictive technologies essentially two plants scheduled at work to have it readily available in the event that one unit goes down. My advice would be, make a conservative case. Even conservatively, it's easily justifiable that these technologies work is easily a savings, whether it is an avoided cost or an actual savings back to the business.
The other thing I would do is, if you're getting things like bad bearings, you get a vibration reading for bad bearing before and after amp reading because that bad bearing is costing you electricity. Take your “before” and “after” amp readings; that is immediate and actual savings.
PS: What type of data aggregators have you used, or have you seen being used to collect display and alarm equipment-melted PdM sensors? Maybe the ones you're talking about when you said that the cost is coming down for those wireless sensors?
GW: I guess this is a solution mostly at the vendor level. If they have a system in place already that collects this data, the interesting thing is, it's usually in isolation. If you have vibration per company, they have one system, if you're using a company that has a mounted UE ultrasound system, they're in a different software. And so combining all that stuff is not the easiest thing in the world. That's really what the question is geared towards then my suggestion would be to use those data. If you have a data historian then you can pretty much compile that data and display it in many, many solutions.
So if your company has OSISoft Pi or they have a business warehouse, or they have Azure then you have a data historian that this database information from multiple places can get dumped. And then what you need to do is something that can take it out of the historian and display it. And that's as simple as Power BI, or Excel, or business objects, or even crystal reports. All those things can then grab it from the data historian and display it.
There's lots of solutions out there for that type of information. I know in the past, not to necessarily promote anyone, but we've worked with companies like Asset Analytics and that's exactly what they do for a living. They figure out how to pull all your information into one place and display it for you and whatever tools your company already owns.