MIT wants technologists to be the nurse practitioners for manufacturing
Wed, July 29, 2026 at 3:28 PM GMT+3 11 min read
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As technology rapidly evolves and reshapes the manufacturing industry, the way people work is also changing. More robotics are being tested and deployed on shop floors and production lines are becoming more automated, and yet the skills to foster these transformations are lacking across industries.
Typically there are engineers who design operational systems and technicians who operate the equipment. But what if there was another type of worker that could fill in the gaps and integrate the advanced manufacturing technologies?
That is what John Liu, a principal investigator and research scientist at the Massachusetts Institute of Technology, set out to address through the Technologist Advanced Manufacturing Program.
"I want to create the nurse practitioner for manufacturing," Liu said.
Last year, MIT established the Initiative for New Manufacturing to help develop new technologies and systems that improve domestic productivity. The initiative has received millions of dollars in financial support from corporate partners such as GE Vernova and Siemens.
In fall 2025, MIT launched the TechAMP program with funding from the U.S. Department of Defense in an effort to bring experienced technicians into leadership roles with a focus on advanced manufacturing needs in the aerospace and submarine industries.
The 12-month program is designed for technicians or operators with three-plus years of experience. It features online lectures, interactive virtual simulations and hands-on labs run by partner schools such as Cape Cod Community College and UMass Lowell.
While the educational sites are currently in the Northeast, Liu said MIT has broader plans to expand the program across the United States. Recruiting is underway for the second cohort, which is set to begin in September.
Manufacturing Dive recently spoke with Liu about MIT's TechAMP program, how it began and what feedback has been like from employer participants in the first cohort.
The following interview has been edited for clarity and brevity.
MANUFACTURING DIVE: What began your journey with TechAMP?
JOHN LIU: At some point I had a few really pivotal conversations.
One was with SENAI, which is the central industrial training organization in Brazil. They had reached out back in 2020, and they said, "Hey, we're really concerned about these technologies coming into manufacturing. How do we prepare a workforce for it?" And so I got really excited, like, "Oh, look at all these things we're doing — the Masters of Engineering, the MicroMasters program, etc." But at some point, they're like, "Yeah, you keep on talking to us about master's-level programs, but look at the workforce in Brazil. It's like you're just talking about like 20,000 people. What about the 4 million or the 7 million folks in our country that don't have university degrees?"
So that was the first bucket of cold water. Another conversation was with the president of AFL-CIO, which is the large union umbrella that includes United Auto Workers, American Federation of Teachers and others.
The president visited MIT and asked for a meeting to try to understand how manufacturing is changing and how that's going to impact his workers. So we had a meeting then, and my pitch to him was that technologies can change, but if we can dig down to timeless principles that endure — no matter how the industry changes — then you can essentially future-proof the workforce.
And at this point, I developed what is now known at MIT as the lobster pitch. Conventional wisdom says you give a man a fish, you feed him for a day. Teach a man to fish, you feed him for a lifetime, right? And my pitch to him was like, if you were to apply that analogy to advanced manufacturing, it's really more like this person has to fish this year and hunt deer in two years and trap lobster in five years, right?
So if we know that that's happening, should we really train the way that we have for the past century or so? That kind of got me to think, one, that the things we're doing at MIT may not be so relevant for the larger workforce. Two, that based on this conversation, maybe there are things that we could do if we're trying to distill these principles that we've been teaching at MIT, but for a larger workforce.
And then the third conversation that was really useful, I was meeting a graduate from the master's program in advanced manufacturing design. A few years after she graduated, she went from a process engineer to essentially heading up a plant and all sorts of things were out of control. Her way forward was to essentially create a plant-wide design of experiment that would change multiple processes at the same time. And there was kind of an uproar in her factory from workers who are used to changing one thing at a time.
But based on the statistical tools that we teach, you can actually do this in a very efficient way that doesn't require like 60 experiments, but let's say eight or seven. To overcome the pushback, she went into coffee hours with her workers and taught the principles that she picked up in her master's program.
I'm having coffee with her at this time. It just dawns on me like, okay, is this what it takes for MIT graduates to succeed in manufacturing? They have to basically do ad-hoc education for their workers? Surely there must be a more formal way to do this?
So those three things kind of combine and start to get me on a journey of how MIT could actually make a difference in workforce education writ large.
MIT has identified an emerging technologist role to address the missing middle between engineers and technicians. Can you elaborate on this and how you see the next generation of manufacturing?
One of the biggest aspects that we're concerned about is that productivity across U.S. manufacturing has stagnated over the past one or two decades. There's a bunch of data on this, but peers like Germany and Japan are increasing, and the U.S. has kind of flatlined.
We know that a main driver of productivity is technology adoption. It's hard to quantify this across all technologies, but one way that we've looked at it is you can treat, for example, robotics adoption as a proxy. It's a little hard to count penetration of IoTs or other technologies. But we can count robots.
The International Federation of Robotics does surveys across countries, and you can see that the U.S. at this point is number eight. And by robot density, we have a fourth of what the leading country South Korea has.
How in the world is the U.S. going to be competing when our technology adoption is so low? It's interesting to me when people talk about a manufacturing worker shortage, so we'll work on AI automation. Yeah, but China is already ahead in many ways in developing algorithms, and they are now graduating 10 times more engineers than we are across the country. So if you have less engineers and you have less technology adoption, it's a really really hard sell for us to get to competitiveness.
So we started to dig into why firms aren't adopting more technologies. What's holding companies back on productivity? And one of the recurring mantras that we heard was in the beginning — we wish engineers had more hands-on skills. We wish technicians had analytical skills. And initially, it looked like there's a gap in skillset, but then as we dug further, we started to realize that even from a technology integration perspective there's a gap as well.
So you have technicians, and they're tied to their piece of equipment, whether that's a mill, lathe, etc. And all they do is troubleshoot that thing and make sure it's up and running and they can work. Then you talk to the engineers and they're thinking about design and optimizing systems.
If I'm an SME and I'm looking to buy a robotic arm, where should it go? What's the cost of implementation and deployment? There's huge friction right now, and it's not clear which class of workers actually does what. So four or five years ago, I started to raise the question: Are we just thinking about this the wrong way? Maybe we need another worker class in the middle that's a hybrid of both of them.
Often productivity is at the boundary between these unit processes and overall systems or design because the technologies are new. When thinking about the future of manufacturing, it's no longer a welding machine with more voltage or more current. Instead, it's a robotic arm that changes upstream or downstream dynamics or Internet of Things.
Folks that are going to be implementing these technologies, they really need to have that intimate shop-floor level of understanding, but they also need to have the systems level of understanding. And we just don't normally have any workers with both in mind.
It's very different from regular workforce development programs. Most of them are focused on upskilling entry-level workers, and that space is very crowded at this point. We're looking at developing this elite workforce who bridges the gap. What we're trying to do is upskill the technician.
We could talk about it from the lens of career advancement too. Manufacturing has a bad rap for fostering dead-end careers, and there's data to support that happening. But imagine the star technician with three to five years experience — the company loves this person and wants to bring them into a leadership role. The problem is they get appointed and have none of the necessary skills or training. So there must be a formal way to educate, but then bring them into career advancement.
Someone who's a technologist, maybe they're at the company for five to 10 years, they look at a junior engineer and decide "oh, I want to do that." They go back to school, finish a four-year bachelor's degree, and come back as an engineer, right? All of a sudden, there's this one continuous career advancement, potentially a new worker class, potentially a new way of broadening participation in an engineering workforce as well.
Imagine if there were engineers who had 20 years of shop floor experience before they became an engineer. That would be a totally different kind of engineer instead of coming straight from the university.
I want to create the nurse practitioner for manufacturing. At some point medical professionals were like, we might not need an MD for every single time we need to prescribe a medicine or diagnose something, right? And in fact, we have a huge shortage of doctors in rural areas. We can upskill that nurse, and you know that person can be a bridge occupation. And in my mind, we need them for manufacturing as well.
You're at the end of the first 12-month cohort. What has feedback been like?
There's potential cost savings from student capstone projects where they work with their employers to find high ROI opportunities within the company. Those have been anywhere from $50,000 to $500,000 in value capture.
But there's another aspect that surprised me, which is that some employers are already bringing their student workers into new roles and functions. I thought employers were going to be in wait-and-see mode, but some of them have already moved.
One example: An SME gave us feedback that they are already starting to bring the student worker, who hasn't finished the program yet, into potential vendor conversations. A lot of things have happened for that to happen, right? On one hand, it means that person has gained a level of understanding of systems, operations, finances, things that we're teaching, and demonstrated that to the employer. Somehow the employer is being open-minded enough to rethink this person and how he or she does that operation.
When I heard this, I was like "Wow, that's actually not what I designed this for." But if that's the case, because that person really knows what's happening on the factory floor, they can go all the way up to the enterprise and engage with the owner at that level — that's fantastic.
Another one, which was more in line with what I was dreaming, was an SME bringing their technologist student into a role where they're interacting with four technicians and a process engineer.
In another example, a student took on a job that normally requires seven different types of people to work, and it ranges from process and systems to compliance and documentation. And according to an operations lead I spoke with, this person just took it all on. I'm not saying that it's seven times more work, but I think what his point was is that it's seven times less people. So imagine the efficiency gains and broad understanding that companies are able to capture.
There's a lot of stories coming in from the field these days from companies who are very, very happy.
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