AW: Today most asset information that operations and maintenance people are working with are old or out-of-date drawings. Being able to capture these reality models and bring that kind of information to their environment, they can start to make better connections between what engineering and design information they have with operations information and maintenance information and understand what options they have and make better decisions.
Visual software in the same way as sensors is flagging to the maintenance people visual information – there’s something changing about this view. Something’s beginning to shift a bit, move, shake a bit maybe. You can start to use digital photography almost instead of putting sensors on everything. You can imagine having a camera looking at a whole area of the plant and the software constantly comparing differences between photographs. It can direct your maintenance to those areas where they should be focusing their attention.
PS: What excites you about where all of this is going, about the future of predictive modeling?
AW: You’ve got literally unlimited computing capability now in the cloud. You can analyze all of this data, and if you then combine that with modeling technologies and you test against reality to make sure you’re models are OK, you can model into the future and predict asset life, how much longer something has got under the circumstances you have now, how much more life you’ve got in your assets. You can put all of this information together. Predictive modeling absolutely is something that is booming. It’s what people want. They want to know how much longer they’ve got before something is going to fail. That’s the whole thing about RCM, risk-based inspections – they want to direct their limited resources on the things that matter.
[sidebar id="4"]