Today, we're going to take a step back, moving away from individual technologies and look at the bigger picture. I've been fortunate enough to spend time with some of the biggest thought leaders in the oil and gas industry. My particular focus has been on robotics and I’m most interested in making data acquisition faster, easier and more useful.
Certain types of inspections will lend themselves well to automation and I predict we’ll see exponential increases in the amount of data inspectors can collect in a short amount of time. Manual processes are not going away anytime soon but field operators will be armed with better tools and technologies to yield robust data sets.
This data will present a new challenge, requiring the digitization of the filing and storage of historical data on asset reliability. NDE 4.0 emphasizes the automation of the processes connecting inspectors in the field to the servers that will house inspection data. Once these servers are in place, we’ll have digital ways to connect a broad variety of data inputs, creating one single-source of truth that the company can reference.
I was working with a client on scanning work that was going to take place in a pipe rack. And this was a pretty big pipe rack, it went a few hundred yards in both directions, and it also had multiple decks.
We formed a vision for organizing information on this asset. For example, combining a laser scan of the piping with a multi-skip touchpoint analysis, and corrosion mapping. We thought, how we could put all that together in one place so an engineer could easily digest it and make actionable decisions.
We're already seeing the practical manifestations of the digitization of inspection data. NDE 4.0 is going to take these two initial steps and it's going to leverage them into higher values.
There's going to be new capabilities for inspecting individual components and using that to create models of predicting asset failure, reaching a cost benefit analysis that will optimize the dollars spent on maintenance as compared to the total lifespan of the asset.
I sat down with Kimberly Hayes to fully grasp and understand NDE 4.0. Kimberley's been in the inspection and reliability industry for about 25 years. She's a member of many professional committees such as ASL, API, ASNT and she participates globally in the Sprint Robotics Committee. Kimberly is the founder of Valkim Technologies and she has the pulse of the past, current and future state of inspection technology.
Below are a few excerpts from our interview, edited for length.
Tell us about NDE 4.0. What is NDE 4.0 to you? How would you explain it to someone who is unfamiliar?
To me, it's taking advantage of the advancements that technology has to offer, not so much of a legacy linkage to the physics that we're so used to dealing with for decades. The technician’s expertise and nuance is essential. But now with robotics and in-situ sensors and the massive, massive amounts of data, there's a high importance for data management. The domain knowledge is essential, but there needs to be an overlap of statistics and data science, which is not a new thing. It’s new to the NDT mindset because it's heavily latent on the evaluation and conclusions but not necessarily leveraging technology.
In my personal opinion, it's important to not look at this adoption and path as a commercial value proposition. It's imperative that we take the industry collectively and globally through the whole value chain for it to be adopted. It’s critical to know that NDE saves lives and assets but another fundamental part of it is elevating reliability. We need to do it collectively.
The technician’s importance in this is also going to be enhanced with some additional skill sets that aren't currently the focus of the training programs. There needs to be a level of data science and statistics taught to the technicians. The co-mingling of all three converge to benefit the true NDE 4.0. If you bring that into forefront, you can bring increased reliability, confidence and data output.
I've had a theory that a combination of better data and storage, as is relevant to repeatability and risk-based inspections, could all combine and show a decrease in the costs over the life cycle of an asset. Granted, I’m referring to decades of asset management-- but is that going to be a tangible benefit?
In every aspect, more data if utilized properly, can inherently produce higher productivity and confidence levels. I think that's where the oil and gas industry is headed in their macro processing as well.
We've got to understand that data flow and stream injects into their processing control. It's definitely the longevity that feeds into the RBI, but also fits into their processing controls and their feedstock management.
It’s going to be more and more digital data intensive instead of a PDF document or a hard drive stored under someone’s desk. It needs to be dynamic and live. The more we homogenize our datasets into the whole value stream of the plant process, the faster the industry realizes the benefits of adoption.
Oh, for sure, for sure. The homogenous and usable data-- if we spend X at this point, knowing the current state of the asset, we're going to realize these benefits and optimize the spend for the ultimate payout as measured in years of usability. Would you say that's a pretty good case?
Definitely, the ones that embrace it early, are the ones that need to share their success stories as well.
I'm sure you've seen a lot of changes in your time in the industry. Could you give us a little bit of your perspective through the lens of working in a heavily male-dominated field?
I never really noticed because you get so used to it. It's unfortunate that NDT has not attracted more women. Right now I believe we're like 4 percent. NDE 4.0 may offer more appeal to females.
I think the industry itself is going to migrate from a blue collar role, into a white collar, data intensive management and analytics.
There was a recent publication in Materials Evaluation that had a good take on the fact that women inherently have prime multi-tasking capabilities. Not only the fact that it's going to involve less physical labor in harsh environments, but it’s also going to be more data driven. The diversity of us all can create more holistic thinking. I think women will find that it’s an exciting industry to be in, but I don't think a lot of people even know about it.
Yeah, NDT will probably never be a clean job, but it’s going to require a variety of people with different skill sets, from operation to analysis.
Once we grasp big data and have the systems to process it, the real-time monitoring of corrosion, coatings and structural integrity becomes possible.
Listen to the full, in-depth interview with Kimberley on Route to Reliability.