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Call Me Chi

Kip Hanson
By Kip Hanson Contributing Editor, SME Media

Contributing Editor Kip Hanson conducted the following interview on behalf of Smart Manufacturing.

Okwudire and two of his PhD students
Okwudire and two of his PhD students carrying out research on 3D printing, one of the University of Michigan professor’s primary research areas.


In his native Nigerian language Igbo, Chinedum Okwudire’s given name means “God guides me.” While matters of faith weren’t discussed here, Okwudire spoke plenty about additive manufacturing (AM), a subject he knows a great deal about.

As a professor and Miller Faculty Scholar at the University of Michigan in Ann Arbor, Mich., where he directs the Smart and Sustainable Automation (S2A) Research Lab, Okwudire was eager to opine on that topic as well as automation, mechatronics, nanometer-level machining and the effect of vibration on CNC machine tools.

Smart Manufacturing (SM) kicked off the discussion on a more down-to-earth level with a question about teenagers and music.

Chinedum Okwudire

Chinedum “Chi” Okwudire, SME Additive Manufacturing Technical Community, Leadership Committee Advisor, Professor of Mechanical Engineering and Miller Faculty Scholar, University of Michigan

SM: Good morning. There’s a piano behind you. Do you play?

Okwudire: Yes, but I need to get back to playing more regularly, so I put it there for inspiration. Also, I have teenagers who had piano lessons when they were younger, and I’d like to see them play more as well. But as all parents know, kids choose their own interests, and all we can do is give them the chance to try different things. Ironically, the younger one decided the other day that he wants to play trumpet, so you never know which direction they’ll go. The nice thing about music is that it’s pretty easy to migrate to another instrument, especially at that age. So, we’ll see what happens. Life is funny.

SM: Speaking of life choices, what got you interested in additive manufacturing?

Okwudire: I’m passionate about many areas of manufacturing, but I see significant opportunities in bringing advanced automation and control technologies to the AM industry. Why? Because I think it’s needed. With traditional manufacturing methods, you can take a lot of time dialing in the process, after which you might go on to make millions of parts. That’s not the value proposition with AM. Here, manufacturers need to achieve high yields quickly. Otherwise, you begin to lose the benefits.

SM: When you say the word automation, most people think of robots and material handling systems. What’s your definition?

Okwudire: We believe that advanced control methods that can make corrections on the fly will allow users to quickly achieve the higher yields just mentioned and do so at lower cost and higher production rates. That means using sensors and feedback control to improve the process as it’s occurring, because right now, most of the commercial systems are open loop—they assume that everything remains consistent during the build and that the output will be equally consistent.

But that’s not always the case. By automating in-process parameter adjustments such as laser power or speed—not to mention the possibility of predicting and proactively avoiding build failures—it’s possible to eliminate the variables that lead to defects.

Okwudire works with researchers in Uganda
In an effort to promote sustainable manufacturing in Uganda, Okwudire works with researchers there to make products from local resources.

SM: Please elaborate on the “prediction” part of that last statement. How do you achieve that?

Okwudire: We’ve done extensive research and are actually in the process of translating our work to industrial applications where we use software modeling to predict, for example, how the heat will flow during metal 3D printing. We can then proactively adjust the process parameters to make the heat flow more uniformly. This helps reduce distortion, residual stress and several other factors that produce defects in laser powder bed fusion.

But no model is perfect, so as I said, we’re also using sensors to measure what’s happening in real time. This might be an infrared camera that can look at the build area and see how the heat is distributed and then use that information for process adjustments.

SM: You’re talking about a 3D model that contains details about every single layer in a build. That’s a massive amount of data. How do you deal with the enormous number of compute cycles needed to simulate all that?

Okwudire: Yes, the problem with advanced models is that they can become very computationally expensive. It can take days to run a large simulation, and even though it might be very accurate, it’s not very useful to manufacturers.

So, you have to approximate, which is precisely what we’re doing with a method that we developed called SmartScan. It uses a simplified model that can run fast enough to be useful but still gives us the information needed to predict and correct errors in advance. And then, if you marry that with a sensor and automation that can adjust the build in real time, you get the best of both worlds.

SM: Tell me more about SmartScan. Did you develop it?

Okwudire: My students and I developed the software, and we have since founded a startup company called Ulendo Technologies Inc. to bring it to market. This group also helps to translate some of the work we’re doing here at the university to industry. For instance, Ulendo is currently partnering with several 3D-printer manufacturers who are very interested in including SmartScan (branded as Ulendo HC, for heat compensation) as part of their software ecosystem.


Okwudire receiving the SME Outstanding Young Manufacturing Engineer Award in 2016
Okwudire receiving the SME Outstanding Young Manufacturing Engineer Award in 2016.


SM: And how about manufacturing more broadly? I understand that you have significant experience in non-additive processes. What are you doing there?

Okwudire: One of my first experiences at the University of Michigan was working with a company out of Pittsburgh that builds high-precision motion stages for semiconductor manufacturing, machine builders and so on. They were having some challenges with developing low-cost, nano-scale positioning technology and we supported them with a few ideas and methods to achieve that. But I’ve also focused my efforts on detecting and eliminating vibration in these systems and in CNC machine tools more broadly. That work has led to some advancements in 3D printing.

SM: Please explain. How does vibration affect additive manufacturing?

Okwudire: The answer goes back to my graduate school days at the University of British Columbia. My doctoral thesis advisor is a manufacturing expert who has spent much of his time on ways to eliminate vibration in CNC machining—he actually developed a software tool that some large aerospace companies are using to reduce the instability that leads to chatter and tool breakage.

I did my doctoral studies on that same subject and worked for the machine builder DMG Mori after graduation for a while, and one of the things we addressed was how do you deal with the vibration that usually occurs as you move machine tools faster. The traditional approach is to add mass or change the machine design to compensate, but those mechanical solutions are limited in terms of space and cost. Our idea was to use software to detect and then offset the vibration, thereby avoiding any hardware constraints.

SM: That makes sense, and congratulations on your product developments, but how does vibration affect additive manufacturing?

Okwudire: In most cases, it doesn’t really, because 3D printers are so slow. But as you raise axis speeds in an attempt to increase throughput, you run into the same problems seen on a CNC lathe or machining center.

Such was the case when a student came into my lab saying he wanted to work on making 3D printing faster. We took the algorithms I just described and tested them on a printer and saw that, by compensating for the resultant vibration, we were able to double print speed without sacrificing quality.

We released a YouTube video showing our work and quickly found out just how much hunger there is for greater speeds within the additive manufacturing community. We’ve since commercialized it as part of Ulendo’s offering through a tool called Ulendo VC, which is short for vibration compensation.

SM: How does it work?

Okwudire: Simply put, we trick the machine. We predict motion-induced vibration and have the control send a signal to counteract it. For instance, if we anticipate that there will be upward motion in one axis due to vibration, we command that axis to move downward by an equal amount, thus canceling it out.

SM: And lastly, I want to go back to what you said earlier about making in-process adjustments. Isn’t that a no-no in terms of part qualification, in that you’re not allowed to change the process after the first article inspection?

Okwudire: I’ve heard the same thing, and my argument is that current qualification methodologies are like trying to put new wine into an old wine skin. Dialing in and freezing process parameters makes sense for mass production, but that approach presents some challenges with additive manufacturing. Yes, it works fine for certain high-volume applications—the GE fuel nozzle is one that comes to mind, but here again, that’s not AM’s value proposition.

It’s a very flexible technology. You can do so many things with it that are impossible or at least impractical with traditional manufacturing that, in my opinion, the industry needs to develop new qualification methods. Otherwise, we won’t reach AM’s full potential.

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