Asset Lifecycle Information Management

As pressure mounts to deliver projects on time and on budget in the face of accelerating economic and environmental shifts, actionable and intelligent data is increasingly seen as key to achieving market competitiveness, regulatory compliance, and operational excellence.

But for industries that build and operate asset-intensive facilities or infrastructure, the sheer volume and disparity of data presents its own challenges: how to collect, store, manage, and analyze the data in a way that enables better decision-making across the entire asset lifecycle.

Hexagon is addressing this challenge by applying automation and intelligence to improve the value extracted from data in each lifecycle phase, most recently with the acquisition of the Infor EAM (Enterprise Asset Management) business to expand the company’s capabilities in operations and maintenance.

We recently spoke with leaders across Hexagon to understand their perspectives on the challenges of putting data to work and the opportunities that come with it to make asset-intensive projects more profitable, safe and sustainable. The following is an edited transcript of what we learned.

Q: Thinking about industrial design, construction and operation, what are there lags when it comes to the gathering, interpretation and sharing of data? Give us an example.

The problems go back to legacy systems that don't talk very much with each other, and that may exist in different departments which don't often share data. And when they do share data, it's expensive to do the integration to make it work. Take the example of designing and operating a new asset. If something breaks, the maintenance organization might refurbish or put in a new piece of equipment. But that also might change how the asset behaves and functions. The design people didn't make the change and they don't know anything about it. So, when new data comes in from the new or refurbished asset, it appears to be operating outside of its performance expectations, which means the lack of data consistency and sharing just created a potential problem.

Q: That sounds like a bear to get back on track.

It’s why this segment of the market is evolving so rapidly. We need to understand what performance we're getting out of an asset in real time from an engineering, production environment, and design perspective. And from a maintenance perspective, all that information must be shared and collectively owned, because we must obtain a certain degree of efficiency, safety, reliability, and performance. This must be part of a culture change where these systems now talk to each other.

Q: That sounds like quite the challenge when it comes to leveraging data across projects.

Projects generate a lot of data in different formats. And it's not only project data that gets generated within our data creation tools. The majority of it comes from outside. The challenge is how to leverage that data throughout the asset, building and/or infrastructure lifecycle.

Q: How does that manifest itself in practice?

There’s just a lot to get our hands around. It's coming from everywhere in all different types and formats. And then we must aggregate that into something that's intelligible and something where you can find a needle in the haystack, so to speak. So, when we look for a piece of data, we know what we’re looking for, where it lives and how it is relevant across the lifecycle. These are really big challenges that we're helping to solve.

Q: What will owners/operators, contractors, and EPCs need to do in terms of changing workflows and work processes and managing data in a more powerful, more cohesive way to generate real insights?

We need to transition project execution into an ecosystem that doesn't yet exist. That means every digital form should be connected with a standard set of work processes that customers have defined for their businesses and are applicable across all projects. This is a big lift from where customers are today in a very siloed projects world. We’re working hard with our customers to try and knock down the walls of those silos.

Q: This must also present major challenges when you think about digital transformation projects.

Let’s recognize that digital transformation is a hard thing and lagging in general. A big part of it is that people are still stuck in their spreadsheets for a lot of their data and they're not leveraging enterprise systems.

Q: So how do we share data that, as you put it, is stuck in people's spreadsheets?

The question is how to share information that's not in an enterprise system and globally accessible to reap the benefits of digital transformation. Is Excel really part of the digital transformation? I wouldn't say that it is. That's not defining assets and activities in a digital way. Even though it’s digital, it's still not part of an ecosystem where you can go and access this information and view all the different dimensions of the activities and the assets that we're dealing with from an industrial facility standpoint.

Q: From an Enterprise Project Performance (EPP) perspective, where do you see the opportunity in digital transformation?

It's around taking projects out of Excel and moving them into an enterprise system. EPP is about moving to something that is enterprise-level and using that to lay the foundation because if you're not on an enterprise system, then you can't take advantage of all the coming technologies.

Q: Conceptually, how should organizations think about improving data management throughout the asset, infrastructure or building lifecycle?

At Hexagon, our asset management system takes real conditions in real time and makes adjustments about how to work more efficiently.

In mining, for example, they might have 600 trucks hauling tons of ore around the country. With the telemetry systems they have on board, they have an idea when preventive maintenance should get done. But what if I had the metadata with the history of asset work that was performed?

At that point, I’m able to say whether we can actually run this to 750 hours instead of 600 hours. We know the point where it’s going to fail and can even guarantee that it's going to fail with this component in that section. I can have a maintenance person ready to go, equipped with the replacement materials, to fix the problem immediately. So that metadata turns this into a standard operating procedure that runs nearly autonomously.

Q: What's the rational way to approach this when it comes to unlocking the potential in data?

That goes back to the customer’s top concern – which is security with people going in and out of their system, especially as they dealt with COVID and so many employees accessing the network from home.

We've been in the cloud since 2001 and know how to migrate customers to this environment without sacrificing security. They don't have to worry about access control because security control is built into our system.

Q: The Holy Grail is that one day all these companies will inhabit a world where they're integrating data across the entire asset lifecycle. How realistic is that?

Companies nowadays may have a lot of data, but they don't know what to do with it. They need to have somebody come in, analyze it and look for anomalies and contextualize it. The connection points are becoming more pervasive when you talk to them.

But how do you deal with all of it? There's such a deluge of information, a veritable tsunami that's coming in. That's why you need a collaboration environment to keep those assets running. Getting the data is not the hard part. It's what to do with the data once you get it.

Q: What insights have Hexagon customers gained because of improved data management?

Those customers are seeing better predictability, better reliability, and better sustainability because their equipment can run more efficiently and encounter far fewer problems during its lifecycle.

Q: What’s the role of Hexagon’s Smart Digital Reality in helping to unlock the potential of data, and how is it different from a digital twin?

The Smart Digital Reality goes well beyond the industry-standard digital twin by embedding real-time and autonomous capabilities right into the platform to enable it to identify and address potential issues quickly – thus, increasing the asset’s performance and life.

We can get a notice on our interface when a failure is going to happen on a particular piece of equipment. The Smart Digital Reality provides safe directions for a technician to reach the asset with ease, armed with all the design and historic data needed to understand the potential issue, including a visual representation of all the variables involved.

Viewing these data elements, our customers can predict when an asset will exceed its temperature limit and cause a gasket to fail, for example. They can then make the decision to repair, replace or defer maintenance until the next shift, understanding how each option will have an impact in terms of downtime and costs.

The Smart Digital Reality empowers customers to make these decisions with eyes wide open, and to help with preventive maintenance. If I can tell you a part is going to fail on Thursday at three o'clock, I can prescribe to you what you should do now to avoid that failure. That’s a huge difference.

This Q&A was compiled from interviews with: Corey Short, Enterprise Project Performance (EPP); Jay Schwartz, Projects; Kevin Price, Enterprise Asset Management (EAM); Paul Miles, Buildings & Infrastructure.