/ Articles / Future Forward Full Interview: BIM’s New Definition: Building an Information Model

Future Forward Full Interview: BIM’s New Definition: Building an Information Model

Parul Dubey on April 3, 2020 - in Articles, Interview

Theo Agelopoulos is the senior director of Infrastructure Strategy and Marketing at Autodesk.


V1 Media: Please provide a brief background about your education and career?

Agelopoulos: For the past 12 years I have worked at Autodesk in various roles focused on infrastructure. Prior to joining Autodesk I spent 13 years at Intergraph working primarily in the areas of transportation, geospatial and remote sensing. The majority of my career has been spent in the software industry servicing the civil engineering and infrastructure.


V1 Media: Can you describe your current position and role at Autodesk?

Agelopoulos: I currently lead the infrastructure strategy and marketing team at Autodesk, which includes business strategy, industry marketing, product marketing and technical marketing. I work closely with our product development organizations building multiple products, and together, we develop market plans to bring different types of technologies to market to solve infrastructure problems that meet our customers’ needs. 


V1 Media: Please describe what “design automation for infrastructure” means to you, and how you think that area of technology has evolved.

Agelopoulos: When I think of design automation, I think of it in a couple different ways. There’s the element that is all about reducing tedious and repeatable tasks: how do you take a high-value employee such as a civil engineer and ensure they spend the majority of their time on high-value activities. The other part I see is design optimization: how do you use a computer to help an engineer make the best decision possible to deliver a better outcome. It’s about taking multiple input criteria and allowing the computer to optimize for the optimum solution. Many people tend to loop them together, but I think they’re very different. 


V1 Media: Can you cite some specific examples of some of the things you’re talking about? Like how they fit into each category?

Agelopoulos: If you look over the last 10 to 15 years, you’ve seen the industry move away from the traditional ratio of an engineer to draftsman, because with a lot of the software that’s been built–especially around infrastructure–drawing’s become the derivative of the modelling. So as we’ve moved from 2D to 3D, and then 3D to building information modeling (BIM), the drawing becomes a derivative, it’s a 2D representation of a rich 3D model. So what a draftsman did 15 to 20 years ago versus what a draftsman may do today looks very different.

Traditionally a civil engineer would design something, and a draftsman would document the design on a drawing. I believe that’s changed today, if you go to most engineering companies, you’ll see they are hiring fewer traditional draftsmen but more engineers, because they generate more revenue per employee. The software allows them to automate the process. So think of Civil 3D or Revit: if you are designing a road, building, bridge or whatever, you can model that asset in 3D, and then automatically publish documents that represent that asset. Then if that asset changes, the documents get updated automatically. That would be one example.

On the design automation side, if you are designing a road, there are a lot of different tasks and disciplines that have to come together to design the road. An example we’ve done is connect products like Dynamo from Autodesk, which allows a user to script different scenarios together, and then that allows them to automate the production of that roaad model in a very automated way. We have customers today who have gone from designing roads–or other linear assets like rail, that historically has taken three months and have been able to optimize that down to three weeks. It’s primarily because they built a lot of very intelligent scripts that take a lot of the tedious, repetitive aspects out of what they’ve traditionally done. 

We’re starting to use more of the term “generative design.” We’re working on a couple different projects at Autodesk: one is optimizing site grading, where you can set certain input criteria–the slope of a parking lot or the way you want water to drain across some land–and let the computer optimize the grading of that particular area based on the  input criteria required. Last year at Autodesk University, we had a customer we worked with who wanted to use generative design inside and outside a building as part of a a residential subdivision design. The customer was Van Wijnen, and they looked to use generative design to optimize the way they were laying out subdivisions, both the physical structure and the land parcel. They were able to optimize for profit, cost, backyard size, solar gain, etc. They let the computer optimize for all these criteria and presented the designers with the best options to select from. 


V1 Media: When you think of automation, people picture robots, but you’ve been talking about automation in computer programming. Can you describe a little bit more about how that works? Is it just the generative design, or are there other aspects in the computer side that involves physical things doing some of that automation?

Agelopoulos: What I’ve talked about is primarily automation and optimization in the design process. And then there’s automation on what we call the “make” or “build” process. If you look at a typical infrastructure project, planning and design represents probably less than 5 to 7 percent of the cost of that asset. 20 percent is probably construction, then more than 75 to 80 percent can be in operation and maintenance. The biggest return is to optimize in the operation and maintenance phase but in order to do that you need to make changes upstream to reap the benefits downstream . 

When we talk about building information modeling, the world building is not referring to a physical building. The word “building” is a verb, it’s about building a rich information model, and the data in the information model can be used to optimize each phase of asset lifecycle. So what I described was obviously design, but we’re currently seeing the increased utilization of that rich information model to automate the build phase, at the same time we are beginning to see the adoption of manufacturing methodshttps://youtu.be/xibgv9ckcYU to improve the construction productivity.  

So what does the building site of the future look like? It looks more like a car production line. That’s where you’re going to start seeing robots and other types of automation hardware optimize the way we build. We’re already seeing things like automated brick-laying machines, robots being used to 3D print bridges , and companies are even building fabrication equipment to automatically assemble prefab sections of bridges. All of these new construction approaches is reliant on having a rich information model.

Considering that the success rate of projects over $1B is less than 10% we need a better way to plan, design and build infrastructure projects of the future.  The challenge becomes “how can we use technology and the computing power available to design and build something better, faster and cheaper?” But also, how does that translate into a lower total cost of ownership over the assets lifetime?


V1 Media: Can you describe a couple key improvements that automation can bring to infrastructure, and why would you make those improvements?

Agelopoulos: In the short term, what we see and certainly what we’re focused on is developing ways the computer or the cloud helps engineers and designers make better decisions earlier. It’s interesting because in a past life I lived through the digitalization of the aerial photogrammetry industry, we went through the journey of moving from analog film photography to digital. A similar digitization is what we’re seeing in the engineering and in the construction business today.  Digital completely disrupted the aerial photogrammetry business: it started by moving from aerial film cameras to large-format digital cameras. Then you saw this convergence between satellite imagery, and as the resolution improved, with large format digital cameras being deployed in aircraft. Now we are seeing further disruption with the broad use of drones. As you go from satellites, to airborne digital cameras to drones the cost goes down exponentially.

I mention that, because of this disruption we now have a much better way to create a digital representation of the physical as an outcome. Today we can build a digital twin that’s a combination of imagery, point clouds– terrestrial or airborne point clouds. This allows us to very rapidly and in a cost effective way create a digital representation of the physical world. We have a much more accurate geospatially accurate and context-relevant model that can be used to make better planning and design decisions earlier, which means the cost of change is lower. It allows engineers to do a better job of designing a road, putting a bridge in the right place, and  ensuring they minimize risk during construction. In the end it’s about achieving a better outcome.  


V1 Media: So would you call optimizing the process one of the key benefits?

Agelopoulos: Here’s how I would describe it: building information modeling is a process, and the process is there to help optimize project delivery. That’s why people are moving to BIM. Within each discipline or each areas of the process, I think there’s an additional level of optimization. So in survey and mapping, we’re seeing disruptions in acquisition techniques as I mentioned earlier.  Drones continue to increase in precision at a lower price. In design, the optimization is around automating certain techniques as well as using the computer to present better options to mitigate risk downstream in construction and operations and maintenance.

I believe there’s optimization opportunities across all disciplines and phases of a project, which we position BIM across the whole project lifecycle. 


V1 Media: Compared to other technical professions, how far along is engineering in the automation adoption curve, and why is that?

Agelopoulos: I feel we’ve been slow as an industry. I think a lot of the hesitation has been due to the nature of the contract vehicles that have been in place for many years that discourage innovation. And a lot of those contract vehicles have been very traditional contract vehicles, and they’ve been put in place to manage risk. 

We are definitely starting to see contract and delivery models change, especially in the  last 10 years, we’ve seen a shift from traditional bid-build to design-build and private-public partnerships. These new delivery models have enabled and accelerated the adoption of technology and automation. On a PPP project for example, the owner is incentivizing the PPP consortium to deliver the project faster and better by eliminating a lot of red-tape in traditional delivery models. 

But I still think, especially in civil engineering, there’s been a resistance to change. When you look at the typical project, ultimately the project manager gets measured on success or failure of the project. And at the project level, in many cases, they aren’t necessarily incentivized to take risks and adopt new means and methods. They’ve generally built a very rigorous way to deliver the project, and they know they can deliver it based on past experiences.

I think we’re finally starting to see more of a push from upper management to change–I see this in a lot of my customer briefings with the largest engineering firms in the world.  The difference between today and even five years ago is leadership has realized “either they need to disrupt or be disrupted.” And they’re much more empowered to try and be more innovative, and that’s why you see them making bigger investments in technology and partnering with companies like Autodesk. They realize, by looking out at the industry and their peers, that if they don’t do something different, then they will end up being followers vs. leaders. 


V1 Media: You mentioned contracting vehicles and legacy ways, but what are some of the main difficulties that go with those for automation and adoption?

Agelopoulos: I believe we need to incentivize and reward individuals who work on projects differently so that they think differently. I also believe we have generational challenges; we have an aging workforce, and we’re starting to see more younger engineers who have been exposed to more technology entering the workforce. I think that’s driving an attitude change to technology adoption, this new breed of engineers embraces technology, they have lived and breathed it since they were born, they don’t know what the world looks like without it. Companies now need to differentiate themselves in recruiting talent. Those young engineers entering the workforce want to work for companies that are innovators so technology has become a great talent recruiting tool.  


V1 Media: How far do you think automation, in regards to infrastructure and engineering, can go? And what might its future look like?

Agelopoulos: If you think about an engineering project today, a lot of the engineering knowledge is locked in the head of individual engineers that aren’t scalable. If you want to scale their knowledge you need to start by getting it out of their heads and making it available across the whole company. That requires that we move to a more data centric process and delivering technology platforms that allow us to take that data and turn it in to information and eventually knowledge.  As we continue to see more digitization in the industry, you will begin to see more impact from artificial intelligence and machine earning for example. I don’t know if it’s five or 10 years from now, but I think as an engineer, your role will be different. You won’t be manually drafting and or even modeling, your role with be to define input criteria and use technology to achieve the best outcome. The future of design will be what we call outcome based design, think of it as beginning with the end in mind and optimizing for that.

What I envision the future looks like as a civil engineer is that I’m going to define “I want to go from point A to point B, I want to move this many people and goods per day, tell me based on the environment whether I should build at grade, below ground or above ground, should I build a road, a tunnel, or a bridge, which is the best option for time and cost? Design it for me based on the codes and criteria the owner expects, simulate its operation for the next 30 years, and tell me what the ROI looks like.” That’s what I think the future looks like. 


V1 Media: So if you were able to speak directly to our engineering audience, what would be your advice on how they should look to benefit from automation, and how could you help them avoid common problems?

Agelopoulos: The first thing I would say is that they should not look at automation as something that is going to replace their jobs. It’s going to change what they do and how they do it, but they should embracing it. They will ultimately spend their time on higher-value and more impactful activities. 

As an engineering and infrastructure community we need to help and coach the next generation of engineers. We should all be looking to move our industry faster towards automation. We need to disrupt ourselves rather than be disrupted. The more we can collaborate as an industry, the more we can help each other avoid the pitfalls of failure. The faster we move as an industry towards automation, the better we will service the worlds increasing demands. Our duty as civil engineers is to make the world a better place for our kids and the generations to come, embracing technology is a key element in how we get there.  

 

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