For our latest Trailblazers feature, we speak with Burcu Akinci, professor of civil and environmental engineering and associate dean for research, College of Engineering at Carnegie Mellon.
Akinci discusses her views on the state of innovation in the industry, as well as its challenges, and her battle against accepting the status quo. "When efficiencies are not apparent and quantified, it is easy to ignore them," Akinci says.
Dr. Burcin Kaplanoglu, vice president, Oracle Industries Innovation Lab, led the conversation.
I'm currently professor of civil and environmental engineering at Carnegie Mellon. I'm also associate dean for research at the College of Engineering. I did my PhD at Stanford and after that joined Carnegie Mellon as an assistant professor. I completed my bachelor’s in Turkey in Civil Engineering.
During my PhD studies at Stanford, I discovered the power of virtual models, building information models, and virtual design and construction. After I arrived at Carnegie Mellon, I also discovered the power of sensing technologies.
Since then, I've been working in integrating sensing and virtual models to support engineering decisions. That's how my career evolved in terms of the research areas I've been looking at. My research focuses on developing approaches to streamline construction, facility operations, and infrastructure management decisions.
Over the last 20 years, especially over the last 10-15 years, it's been fascinating to see all the new technologies that are being deployed in the field. To a certain extent, not everything makes it to the field immediately, and not everything is incorporated right away.
Some things take longer for the industry to embrace, and building information models was one of them. When I started my PhD in the mid-1990s, we were doing research on building information modeling (what was then called product modeling).
While it took a long time for our industry to adopt that concept, once it was demonstrated that the building information modeling can help in alleviating some major pain points for multiple stakeholders, that adoption significantly accelerated.
On the other hand, we have seen a much faster adoption in other technologies, such as data capture through drones. A year into when we started the research in this area in early 2010s, there were already companies buying drones and capturing images/videos of construction sites or large-scale infrastructure system, such as bridges.
People wanted to see what's happening in the field from angles that they do not typically see – and hence, increase their situational awareness in ways that were not possible before. If you hit a good pain point, or if you have a good value proposition for a user, innovation occurs in a much faster way than if innovation requires multiple parties to buy into it, per se.
It’s an exciting time for our industry because we're seeing more innovation.
The adoption is much faster if technology alleviates a known pain point for a single stakeholder. That's at least what we have seen with the drone usage. Yet, several challenges regarding innovation still exist in our industry.
Certainly, we're in a risky business with low profit margins. Bad decisions might cause somebody's life. You cannot get riskier than this. When you're in that situation, it's easy to fall into the, "Oh, I want to be conservative and don't want to take risks or invest in something that I don't know." That's still the case.
When we want to embrace innovation, sometimes the codes and regulations are not up to speed with that.
Codes and regulations are occasionally based on the older ways of doing things, like testing components or performing data collection in a specific way. This approach impedes us from picking up a technology and running with it.
My final pet peeve around challenges is that, sometimes, we accept the status quo. There are inefficiencies in our businesses. We don't quantify them. We just accept that it's going to happen.
When inefficiencies are not apparent and quantified, then there is no incentive to address them. A little bit of that still exists. We're struggling with saying, "Okay, there's actually a value add, if you do it in some other form."
See innovation in action at the Oracle Industries Innovation Lab.
Stay tuned for part two of this interview, in which Akinci discusses why AI and machine learning work well when you have a lot of data, and combine that data with domain models.
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Corie Cheeseman is a senior content marketing manager for Oracle Construction and Engineering.