Pushing 3-D Models Beyond BIM Dimensions
How did an obscure French convict end up becoming the father of 3-D modelling?
During World War 2, French engineer Pierre Bézier was sitting in prison and thinking about curves when he got the big idea that would eventually lay the foundations of modern 3-D modelling and CAD.
The Bézier curve defines the shape of a curve on either side of a common node, and it allows complex shapes to be defined in 3-D models that would otherwise produce a much boxier world made of nodes connected by straight lines.
In America, the Bézier curve quickly found its way into trailblazing computer graphics programmes like Sketchpad. It then continued its curvaceous journey into the first modern CAD programmes for visualising buildings, and ground-breaking animated movies like Pixar’s Toy Story. All of it a long way from the Renault 4CV cars that Bézier originally conceived the curve for.
The story here is that 3-D models came from the design world, and the notion of using them as centralised reference models only began further down the line.
Building Information Modelling or BIM is a parametric modelling approach that goes beyond describing the 3-D geometry of a building. It includes the non-geometric design and construction information that is pertinent to the design or the installation of components.
Parametric models enable dimensions and properties in the form of attributes to be stored alongside the 3-D geometry. This gives context to the features of the building, as well as providing change and variation histories.
In our story, this was the first step in delivering a 3-D model that had applications beyond the design world. It’s become known as BIM 3-D, the shared information model.
But this was just the beginning of an increasingly complex journey that links extra ‘dimensions’ of data to the 3-D models of construction projects.
The objective of 3-D, 4-D (construction sequencing), 5-D (cost) and 6-D BIM (project lifecycle information) is to enable the people working on BIM projects to make better decisions and, ultimately, better buildings.
This is good. But in the world of the asset, we believe there is a better way.
Introducing the Super Model
In the asset world, the focus of forward-thinking owner operators is on harnessing innovation in the form of digital transformation to deliver capital discipline.
Essentially, it’s people who are working in and on the asset who are going to deliver these efficiency objectives, so we need a model that’s going to empower them to be more efficient.
The tools that the teams in the asset have at their disposal are data, process and knowledge. To manage these effectively, therefore, we need a model that is designed from the ground up.
Each and every piece of data that is used in the operation of the asset needs to be made available in the model, to create a single source of the truth. Where possible, the data should be geo-positioned so that it is stored on nodes in the 3-D model. We’re not just talking about BIM data here, we’re talking about every conceivable data source in the plane, from operator manuals to IoT monitoring streams, which are stored as metadata on the nodes of the model.
The model needs to serve as a process repository, storing and describing the processes of the facility in the form of metadata.
Knowledge is the sum of all ‘lessons learned’ by everyone, together with real-time insights gathered by predictive analytics. This, too, must be stored and made available in the model.
Some guiding principles to building a Super Model
1. Start with a single source of the truth
In the Super Model, all of this data, process and knowledge is stored in a knowledge graph that intersects with the nodes of the 3-D model.
2. Own the data, process and knowledge
The Operator owns the Super Model and mandates that everyone in the asset interacts with and maintains the data, process and knowledge stored in the model.
3. Make the Super Model available in real time to everyone
By streaming the model and its information to the right AR tools on site, the Super Model facilitates new collaborations between personnel, even when those people are separated by distance.
In summary, reliable and easily accessible information brings people together, making for better decisions.
Beyond the curve
Once installed at the heart of an asset, the Super Model will begin to deliver an immediate step change in operational efficiencies, but it also equips the asset for the longer term.
Intelligent data is going to make huge and unpredictable demands going forwards. Your model needs the power and flexibility to handle it. That’s what the Super Model can do. The Super Model gets stronger and more intelligent as it absorbs knowledge.
The Super Model is effectively a living digital twin of everything relating to the physical asset. When initiated during conception and kept running after decommissioning, the Super Model will outlast the physical asset itself.
Just like the Bézier curve, in fact, which is still going strong, long after the Renault cars it helped design and build have rusted away.
When we add augmented reality tools, the benefits of the Super Model extend all the way out into the field.
That’s what AssetHive does. With its unique ability to manage and store intelligent metadata, AssetHive delivers the outputs of predictive analytics to where they’re needed, leading to better decisions.
In other words, it makes all of the information available to all of the people, all of the time, in real-time.
Because this great information allows management by exception to become a reality, even greater operational efficiency is within reach. Decisions are made where they’re needed, before something goes wrong.
Technicians at work can see the virtual asset super-imposed on the real one. This improves orientation and can alert them to hidden hazards, for example, bringing up associated checklists as required. Expert support can be piped in remotely, reducing the need for on-site visits, because the asset’s digital twin is accessible for all to see, wherever they may be in the world.
If a piece of equipment is likely to fail, AssetHive can provide the evidence – without requiring the equipment to actually break down.
It means fewer unexpected failures, and therefore less asset downtime. With a more predictable asset, repairs and maintenance can be planned and prioritised more effectively. The physical asset becomes safer and more reliable, leading to a longer, more productive life.
That’s capital discipline being exercised, right there.