Fero founder Berk Birand discusses the future of robotics and the smallest-ever data set with Authority Magazine:
Thank you so much for joining us in this interview series! Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started in high tech?
I was doing my Ph.D. at Columbia in the networking space, focusing on the internet of things. At the time, I was developing software decision-making systems to help physical networks operate more efficiently. That’s where I got excited about the notion of software systems working with machines and optimizing machines. I realized that the impact of software helping factories could be huge, from both an environmental and efficiency standpoint.
Can you share the most interesting story that happened to you since you began your career?
At Fero Labs, we optimize factories using machine learning software, which obviously needs a lot of data. Once, we were doing a pilot with a huge auto OEM company and this manufacturer sent us the smallest data set we have ever seen. It was a picture of a coffee-stained napkin on which an engineer had scribbled some numbers. They expected us to do machine learning with that….
Can you tell our readers about the most interesting projects Fero is working on right now?
Our customers, as manufacturers, tend to focus on the profitability side of things. They want to save money! But lately, we’ve also seen a lot of interest in the sustainability benefits of factory optimization, such as reducing emissions and energy use.
Recently, our work with leading steel manufacturers to reduce emissions was featured in a report by the Global Partnership on Artificial Intelligence. Steel production accounts for more than a fifth of greenhouse gas emissions from manufacturing, making it a prime target for reduction. The report found that our software reduced the use of mined ingredients in steel production by 34%, preventing 450,000 tons of CO2 emissions.
How do you think this might make an impact in the industry?
This can have a huge impact on tackling climate change. If Fero Labs’ model were scaled to the rest of steel production in the U.S., we could prevent 11.9 million tons of emissions per year — equivalent to a quarter of New York City’s yearly CO2 emissions.
An achievement like this could help AI and machine learning gain widespread acceptance as a tool for good and not just a buzzword.
What are the 5 things that most excite you about the overall robotics industry as it relates to manufacturing? Why?
- The interplay of robotics and machine learning. Having robots doing things means now there’s a lot of data, which you can then use in a machine learning context to reduce waste and improve quality.
- Collaborative robotics. This new technology can digitize sectors that are currently highly dependent on manual labor, including semiconductor manufacturing and apparel.
- Waste reduction. Speaking of apparel, advances in robotics are leading to technological innovation that’s reducing waste and emissions throughout the industry.
- Preventing supply chain issues. By replacing missing workers, robots can prevent the logistical issues that have slowed supply chains in recent months.
- Bringing back manufacturing to the U.S. Robots can also replenish our factories’ workforce, reducing our dependence on foreign supply chains.
What are the 5 things that concern you about the robotics industry as it relates to manufacturing? Why?
- Job loss. We need to use robots in a smart way that replaces missing spots in the workforce, rather than replacing existing workers.
- Bugs. A factory dependent on robots will also need to hire a lot of engineers.
- Cybersecurity. This is an obvious one.
- Physical safety. Beyond hackers, there’s also the danger of poorly programmed robots harming factory employees.
- Cost. Many manufacturers may think of robots as being cheaper, but in fact, they incur many incidental costs, including maintenance and upgrades.
In today’s environment, hackers break into the software running the robotics, for ransomware, to damage brands or for other malicious purposes. Based on your experience, what should manufacturing companies do to uncover vulnerabilities in the development process to safeguard their robotics?
- Vulnerabilities can be introduced in three different stages of the robots’ lifecycle: the development/production of the robot itself, its programming in a specific plant, and then its operation. You need to have the most safeguards during the operations of the robot.
- When you’re programming a robot, you’re mainly concerned about the physics and movement. But the biggest concern is when they are integrated into the control systems of the plant. You’ve built the robot, plugged it into the network. At that time, it’s extremely crucial to use software systems to prevent any vulnerabilities on the production site, like those that Iot-connected devices are notorious for. In fact, this last point applies to non-robotic, industrial control systems (such as steel furnaces).
Can you advise what is needed to engage more women in the robotics and manufacturing industry?
- Increasing diversity is a top concern in other engineering fields as well. I think it’s important to look at other sectors and see how they have increased diversity. Some methods I’ve seen are job boards, online communities, and organizations that foster networking in the industrial sector.
How can our readers further follow your work online?
- You can follow me on LinkedIn and check out the Fero Labs blog for more insights on data and manufacturing!
Originally published in Authority Magazine.