Image credit: Macrofab
In this interview, Misha Govshteyn, the CEO of MacroFab, and Brenden Duncombe, the Director of Customer Engineering, speak with Ian Dickson about the innovative world of electronics manufacturing, particularly focusing on PCB (Printed Circuit Board) prototyping in the context of Autonomous Vehicles. Download the full report to read all our sponsor interviews.
Misha Govshteyn: Of course. My name is Misha and I'm the CEO of MacroFab. I’ve been here for about five years.
Brenden Duncombe: My name is Brendan Duncombe. I'm the Director of Customer Engineering here at MacroFab and I've been here about six months.
Misha Govshteyn: MacroFab is a digital platform for electronics manufacturing, and we're powered by the world's only factory marketplace. In most cases, companies contract with individual manufacturers.
With MacroFab, it is very different. We are a platform that gives customers access to hundreds of production lines in multiple countries. So you can literally upload your design to MacroFab and we will match you with the right factory. The best part is that MacroFab is responsible for every aspect of production. You're working with us, and we deliver the product to you.
That spans everything from prototype to production, so you don't have to switch factories. You don't have to move from one supplier to another. We have customers moving from the earliest stages of prototyping to multi-million dollar orders, all on the same platform, working with MacroFab exclusively.
So somebody like Brenden would be leading the charge with them. They may be working in different factories, multiple factories, and in parallel, but they are always working with the same team.
Brenden Duncombe: I can start here. In PCB prototyping, electrical engineers or hardware designers often begin with dev kits on their desks or start with an idea. As they move through the prototyping into the production process, at a certain point, they'll need to get their design actually on a fully integrated PCB for testing or design validation. And there will usually be many stages of that. Frequently, as you go through the process, you will learn things from the early ones.
You may do one just for electrical design, then you will do another prototype where you're confirming that it fits in your mechanical enclosure, or you may have to produce some prototypes for RF testing. So, for each one of those stages, you will need to get a very low volume of PCBs made to do integration, testing, and validation.
Misha Govshteyn: The design process for all of the world's products is now computerized. Some CAD products help you design mechanical parts, even for woodworking, right?
There are digital products. So you're sitting in your computing environment. You can do 3D renderings of things — the same thing for electronics. So, a lot of the design process happens in people's heads. It occurs in computing environments where you can do simulations.
But at some point, the simulation is not enough. So you’ve got to take that virtual design where you can see what your circuit board looks like and make assumptions about how it works. And you have to produce a functional prototype. So you can plug it into other auxiliary devices connected to other parts.
Physical products require physical prototypes. So, usually, the design process is iterative. You design something, build a physical prototype, and see how it works, but it usually works differently than you expect.
So you have to build multiple iterations of it, and really, the faster you can go from the digital version of it to the physical version of it and iterate quickly, the more you're compressing time for design iterations. ngineering time is costly, and this goes for every stage of production.
We're talking about prototyping right now. Switching factories and waiting for things to happen in factories is the most expensive thing in the world.
You change the design, and now you have to wait a long time for the factory to reflect that design; that is an actual cost, and that's part of what MacroFab is compressing because everything happens on the same platform.
It doesn't matter which factory you need. We have hundreds of production lines to prototype and eventually build a production.
Misha Govshteyn: We're the first and only platform connecting customers to hundreds of production lines. Usually, all of this is people work.
What happens when an engineer needs a factory? Either an engineer gets on a plane, or their supply chain gets on a plane, and starts traveling halfway around the world to find out which factories are good and which are bad.
You can't tell when you walk into a factory. You can even hear people say things like this factory had the right smell. That's usually a sign that they have yet to determine whether it is a good factory. Factories are data. Factories are output.
We're the only way to aggregate many factories in one place and understand what they are good at building, what they are bad at building, and what kind of equipment they have.
Can they even notionally build the right product, given the design parameters? Some factories have old equipment, and some factories have modern equipment. Humans aren't fast enough to understand all of this, but our software is much faster and does it algorithmically, so how we match up customers and factories is much faster than everybody else. And one big realization we made is that none of that works without humans at the end of the day.
So we have humans in a loop, and guys like Brenden actually do travel to factories. But Brenden knows precisely what he's looking for when he walks into one. So I think we take a lot of the heavy lifting from customers, irrespective of how difficult their job is or how complex the requirements.e had a very well-known automaker that at one point reached out to us and said, “Hey, I have this unusual PCB.It is a 30 by 5 form factor that doesn't fit into most factory machines. Can you build this?” Out of our hundreds of production lines, we had three that could create that particular board, which would have been a months-long exercise for a traditional supply chain team.
With our software, that happens very quickly. Again, we're the only business out there that operates this way. Usually, you work with factories individually, but most importantly, it is not just a thing that matches up customers and factories. We are the ones responsible for production. We are the ones producing it in this factory network. We have design engineers, we have manufacturing engineers, we have quality engineers, and ultimately we are the ones delivering products to the customer. It is the all-in model for churning and manufacturing into a cloud-like service.
Brenden Duncombe: Yeah, and I would say also one of the more unique aspects is that typically in this process, when you move from prototyping to production, most customers are used to, working with a prototyping shop, and then they have to learn all the same lessons over again when they move to production.
They have to get prototypes from the production house to make sure that they know how to build it correctly, even though they already have prototypes from their prototyping house.
And it is very unique that we handle both aspects of that. You can stay with us for any volume of PCB, and we move through your production lifecycle with you.
Expanding on, obviously one of your USPs is that customers can go from prototype to production without sharing files with factories or people needing to find the right supplier. Could you explain that process in a little bit more detail and some of the technologyfor example, do you use a lot of AI with this)?
Misha Govshteyn: Well, to be clear, our customers do share files with us, but we are one of the most secure platforms for doing so. My background is outside of manufacturing. I come from the cybersecurity world. Brenden comes from the electronics world. So, data privacy and cyber security are the main domains. But at the end of the day, you're sharing your design files with one party.
That's MacroFab. We are extracting only the relevant information that the factories need to decide whether they can build it and sharing just that abstract with them. That's in contrast with what usually happens in a supply chain world. Coming from a cybersecurity background, I know how blind we are to what happens in a supply chain universe.
But in reality, no thought happens about what your partners need to see and what they don't. What you get many times is a multi-gigabyte package of everything. You get giant design files.
They blast this to every supplier for price discovery. They're just trying to figure out who can build this product and do it at the lowest possible price. The privacy implications of that are immense. So we always get asked: “What is my risk?” What you're doing now is incredibly risky.
You're sending files to all sorts of factories. Some of these factories may not even be real. With us, it is a very different story. You send it to MacroFab. Take that digital package. Share only the relevant information with factories that need to see it.
So, software determines who gets to see this information. We use many algorithms and a lot of machine learning to do that. But ultimately, it is not just algorithms. Many times, it is data classification and knowing who should see something.
Brenden Duncombe: Commonly, we will see customers share data that is optional for quote. You will see firmware files.
You will see things about their assembly. All of that, we strip out and only share the stuff that’s required to manufacture the piece that they're quoting.
Misha Govshteyn: But the current supply chain and data privacy state is terrible. Right now, by definition, I was blown away when I saw what we received from customers as quote requests.
It is a massive amount of unnecessary information. As Brenden said, sometimes they'll package source code with it. There are better reasons to share your most intimate secrets with your suppliers than price discovery.
Misha Govshteyn: We are most dominant, I would say, in the industrial space. So that's probably our biggest segment. We have a lot of automotive companies that work with us, and we have done much work with autonomous trucking companies.
And especially at the earliest stages of design, which is a high-tech, very iterative industry, our ability to turn around prototypes very quickly is important. Many times, these companies are tech startups. So the electronics team want to modulate how they work and how the software team works.
Software teams these days use concepts like continuous deployment and rapid iteration. So they match their cadence. Because often, it is not just about building a PCB prototype; firmware gets burned onto it.
So, the software team has to be in lockstep with it and vice versa. If your software team executes very quickly, but your hardware team is slowing them down, everything slows down. And we're talking about some of the most expensive resources in the business slowing down across the board. We work with many startups, many drones, and many robotics companies.
Oil and gas is a big field for us. We're in Texas, so that's natural. A lot of innovation and digitization happens in oil and gas.
We don’t do many consumer electronics. I think of that as almost an entirely different industry. I think building one type of product for millions and millions of people is fundamentally a different job than making something like an automotive product where each carhas , on average, something like 85 circuit boards.
And I think that number is growing. There's an immense amount of chips in cars. There's a tremendous number of PCBs. Even mundane things like you turn on your blinkers. There are PCBs involved in that. Even traditional cars, much less autonomous cars.
Misha Govshteyn: I'll defer most of the answer to Brenden, but when you really think about what autonomous cars are built from, it is a lot of very high-powered computing units. Some of the automotive computing units are as powerful as crypto crunching devices and they have many sensors.
None of these things talk to each other without electronics. Obviously, PCBs are where you mount a lot of this infrastructure, so it is probably better for Brenden to explain it in more detail, but it simply doesn't work without PCBs.
Brenden Duncombe: At the end of the day, nothing works without circuit boards connecting it all together. As Misha said, the number of PCBs in cars is skyrocketing.
The amount of information in cars is skyrocketing, and many autonomous vehicles have moved to higher bandwidth interconnects. Every car used to be a CAN bus, and now people are laying down automotive ethernet and things like that in order to increase bandwidth in cars. And that's in large part due to the number of sensors streaming video from every corner of the car. LiDAR sensors, for instance, require sensor computing. Like mainframes in your car or processing in your car, whatever is doing the decision-making, your AI computes modules. All of that is getting fed back in every single one, especially the sheer amount of distributed sensing on the car. All of that either requires the support circuitry on the sensor or computer in order to make that usable for decision-making
Misha Govshteyn: I think for the traditional automakers, the conventional manufacturing approaches are fine. They move much slower. When you think about traditional automakers, controlled releases are really what they're working against. And I've worked with several people in software from the auto industry.
They're usually frustrated by how slowly things iterate and change on cars. But every one of those automakers has crossed over into the digital software-driven world in the last couple of years.
Toyota is the largest, and it has a separate auto company that started specifically for that purpose. The same thing is happening with hardware teams as well. A lot of the production factories are still heavily controlled. A lot of the prototyping it does is actually happening very rapidly, and it needs a software-enabled, digitized approach to it. By the way, as a data point, how many companies out there can receive and give you a price quote on your electronic design over a set of API calls?
There's only one, and that's us right now. So we're the only company out there that's truly software-enabled for electronics manufacturing. And that means that if automakers want to move faster, this platform is most aligned with that motion.
Brenden Duncombe: I think it is very clear that now the software is moving a lot more quickly than the hardware is. To keep up with that, especially when it comes to the sensing capability and setting the compute capability (such asquicker turnaround times and getting that performance to validate your models against your machine learning models, your AI models), it is critical to evaluate the performance of those.
As those models get better and better, whether they can go with lower resolution sensors or find out they need higher resolution, all of that change to what is required to feed those models requires faster prototyping.
What's your opinion on when we'll save mass adoption and rollout of autonomous vehicles?
Misha Govshteyn: We're certainly seeing a rollout now. Major rollout is happening in Texas, Arizona, and California,. As for now mass adoption; people have been wrong about that forecast for so many years.
I'm hesitant to put a number out there, but I think within five years or so.I actually don't think there's going to be a switch that makes everything autonomous. We are going to see transportation segments moved towards autonomous cars in a major way.
So I think a certain portion of driving will be done by autonomous vehicles, probably about a third or so in the next five to seven years. That’s my guess.
Brenden Duncombe: I'm also hesitant to make predictions on something that has been so famously incorrectly predicted before.
Similarly, we're seeing a lot of rollouts already. A lot of these have been in limited areas or with certain speed and streets and so on. As we move forward, I'd like to see if there has been more discussion about the type of infrastructure to support autonomous cars. In addition, I'd like to see if more adoption of better-connected infrastructure helps ease the adoption. And so, as we move into a world wherewe're seeing the rollout before getting more comfortable, it is okay to make an investment in some infrastructure to help support this and make the adoption easier. That will certainly help speed things along.
Obviously regulations change and technology improves all the time, but what are some of the other big challenges that will affect the rollout of autonomous vehicles in the future?
Misha Govshteyn: It needs to be regulatory, first and foremost. Cruise just had to suspend its operations in Texas. You know, it is all related to technology. Meeting the real world is full of conditions that even the best software in the world can't necessarily predict. And sometimes that means the irrationality of courts and law enforcement. So, in this case, Cruise didn't even cause the accident. It was a human driver that caused the accident. But Cruise was involved as this kind of secondary actor, and they still had to deal with the outcome.
I'm certainly not an expert in the evolution of automotive products, but autonomous vehicles are going through the same journey as when cars originally became dominant products. Eventually, regulators stepped in and started to slow things down. That's probably the biggest variable. Ultimately, regulatory controls are the biggest thing standing in their way.
Ironically, I'm not necessarily down on regulatory controls. I think there is at least one area, for example, where they could be immensely helpful. For example, right now there's no regulation out there for where you send your intellectual propertyand how much of it is to send to which countries.
So we treat other countries as just a place to get lower costs when we should treat other countries at the very least as competitors and, in some cases, adversaries. More regulatory controls in that domain would actually be a net positive. Right now cost is the thing that supply chains care about most.
I think in the future they will all move faster if they stay closer to home. Working with companies like MacroFab, they can match their speed requirements. From experience, often in order to do the most secure thing you have to be forced to do it by regulatory controls.
So, I think regulation is obviously a double-edged sword.
Brenden Duncombe: I think regulation is the main thing. I also think that when we start talking about mixed-use, it is easy to envision a world where levery car's autonomous, and so they all work together just fine.
But I think the public response is also part of it, right? utonomous cars are a massive change and they drive exactly the same way humans do it, so that will take some getting used to.
I think there's a lot of human adoption needed with being on the road and your usage patterns, but also driving that adoption. ven if the regulators approve it, there can also be a lot of pushback fromother drivers that could also come to issue. So it is both sides of the market. Other users of the same infrastructure, needto be prepared to share that.
Misha Govshteyn: To extend what Brenden said, it'll also follow the typical hype curve. Right now, there's a lot of excitement about it. Everybody wants things to happen smoothly and very quickly. And that's almost never the way technologies get adopted. We've mentioned it, but this is the point that we reiterate. Right now, the hardware world is the long pole attempt.
It is one of the things that takes the longest. And perceived constraints by the supply chain drive a lot of it. People throw up their hands and say, I don't really know how to build this any faster. I know the software is ready, and it is already very quick.
But my hardware cannot be. The answer to that is it can be. It can be with MacroFab. A lot of it comes down to whether supply chain teams are able to move quicker, just as fast as software teams, and just as fast as hardware teams want to move. That is an executive change. Only a top-down message can really break through to that because until you change the requirements for supply chain teams and say speed is more important than cost, there will always be this mismatch between how quickly the business wants to go and what the supply chain team is optimizing for.
I know how these people get their bonuses, which is the most important thing in the world, and it is still not based on the speed of iteration, it is not based on how quickly they turn prototypes or anything else around, it is all about the bottom line at this point and ultimately there is a big mismatch between the expectations and reality of supply chain.
Brenden Duncombe: Similarly, the software world has adopted CICD and continuous integration and continuous deployment in order to tackle this fast iteration. It is very common now. Anyone who starts a project, most of the time it is a software project. The first thing you do is you set up your deployment chain, right?
You have all of that built-in. Similarly, the electronic world and hardware world can keep up with that. More engineers should feel comfortable iterating hardware more quickly, deploying the exact same technology that they use for software, hardware, and infrastructure for testing and getting away from this mindset.
They're like, “well, we still have to support this legacy hardware forever. We made a mistake in the prototype, and we patch it with software” tech debt the years.
That mindset needs to change a little bit in these areas, and industries that are moving more quickly and iterating can use MacroFab for that support.
Misha Govshteyn: And supply chain is one of the blockers for that because even the engineers that want to do that eventually get told that sounds great as long as it integrates with our ERP. That is maybe the most expensive requirement. With MacroFab when they want to move fast, we can enable that with our APIs.
The supply chain team has to be part of that answer. You can't have an agile enterprise and a traditional supply chain team. Those two things are incompatible.