I'll online after hours is brought to you by Bridge Stone Tires Solutions for your journey. Gary job back. We're back. We're doing a show again.
You were in Las Vegas last week seeing all kinds of new technology, and we're going to be talking a lot about technology in today's show. Boy,
are we over there? I can't wait to get the show going because we
have got a terrific guest. But first let's introduce our other colleague, Joe
White from Reuter's. Joe. Always great to have you on the show here
and it's good to have you back. And our special guest for the show
today is Matthew Vatcha paran Pel, the CEO of care Soft and Matthew cares off amazing company. You guys, you tear down vehicles, you do competitive
benchmarking. You've especially zeroed in on the new energy vehicles coming out of China.
You've looked at Tesla's and you all the automakers in the world, it seems, are coming to you for your information now right, we work with er companies, more than several. You're being modest there. You work with
just about everybody now companies. So when John says that you tear down cars
specifically, you know what does that mean and how low do you go to?
What I've been on the show before, some of the vehicles we do a full high energy scan ct scan and we get the entire cad SA data and so on, and the whole idea there is not only just to provide the data, but to be able to do the simulation and look at the change the design parameters and look at performance and cost. As an engineer,
fundamentals is you change the design and then you see the impact on performance and you see the impact on cost. And engineers is all about how do you
optimize the best performance for the lowest cost. And that's what this industry,
competitive industry is all about. So we have of the last when we came
in, we came into this technology and just data, and there's a lot of data providers in the market. But what we're really focused on and the
last five years is to help OEMs and Tier one suppliers reduce costs by using this data. So a lot more focus on results. But now in the
last two years one and a half two years, we've also started seeing the trend of what automakers are doing, like what Tesla is doing or what China is doing. And so if you're driving from New York to Cleveland and then
you drive to Detroit and then you go to Chicago, you know pretty much that either you're going to Minnesota, you're going in Iowa, or you're going to Kansas City. Pro fact, more than likely, you're not going to
go to Miami or Boston. Okay, So now we've got into the more
in One of the things we'll talk about later today is what we think they're going to do in the future and how they're going to take out on the thirty percent of in manufacturing investment out or cost out and so on. So
are we going to be right in what we predict? You know, like
one of the things we'll talk about, we've been working on it for over a maybe nearly two more two years, and we have got a precise realization of what fairly accurate realization of where industry is heading. And are we going
to be correct? Absolutely not, But directionally we know where they're heading.
But if you're talking about I mean, if you're talking about thirty percent kind of take costs thirty percent of the production costs out, that's not small that's that's step change. That's that's that's a you know, to pick up on
your analogy. That's a real fork in the road. Yes, yeah,
So I think the new automakers and especially Tesla announced it last year in their investors Day on their new way of looking and manufacturing and so on. So
we have been working on the digital twin of these way because Legacy OEM and Tesla which showed what they're doing, and we can see the evolution from say the S to the X to the three to the Y, and we can see the changes. So for example, the after we see a huge steps
change out to the Model three, the Model three Tesla talks about are Elan Musk talks about production hell, and I think there was in the Tesla Y.
You can see a great, great improvement in twenty twenty where they went to modular build and giga castings to simplify parts and so on and so forth.
Then you go to twenty twenty one, the two piece giga casting becomes a single piece giga casting in the rear, and then in twenty twenty two or a lot of part you see the front giga casting, the rear giga casting and no floor. So when you look at that path and then you
see what the announced is very clear they're going. It appears to us,
at least to us that we may be right, we may be wrong, but we that they're going to unbox the vehicle. So we have now full
data. We have built an entire car which is what we think the new
Tesla the future is going to be, which is totally unboxed. We built
the whole digital twin for it last week. It met all US crash requirements.
So we have a very very good idea of what the new Tesla is going to be. Like can you just pick I'll let John ask the question.
I swear it, but able to pick. You use the term in
box, which is the Tesla terma, and I think you've come up with another. But I think for and I've seen both diagrams or presentations from yourself
but also from Tesla. What it seems like what you're talking about is that
traditionally, you know, you'd have a body in whit would be built up and it would be you know, a box. It would be a car,
and then then it would go into paint and then it would go into final assembly. That box would go through those processes. Isn't what you're talking
about that that the box doesn't get built until way later in the process and it doesn't go through paint. Talk about that. So we call this the
game model, which is the global automotive modular revolution that's happening. So going
back to frant principles and when we look at like, let me give you an example of how we think the leaders think. And here in this case
the leader is undoubtedly Tesla. So when they came out of the vehicle with
no floor, what the question I think they asked was, Hey, why do we have a floor? And why do we have under piece of metal
on the top of the battery and two pieces of metal with some air in between. Why can't we replace it at one? So they asked these fundamental
questions. So I think in the game model or box built from when you
had a horse drawn carriage, there was a box that went behind the horse and the first cars was you remove the horse and you put an engine.
So and then we're later to style you covered the engine, and then that's how the body in white kind of evolved. This is not being challenged for
a one hundred years. Okay, the model of assembly line and so on.
That's the most efficient thing, including Toyota coming to see Henry Ford's assembly line, dearborn and so on. I think maybe Elan or maybe some of
his key leaders challenge and say, okay, we have this box. Go
on, like you said, okay, we build it in the body shop with robots, then we put it on the pain shop. Then you put
it in the assembly line. And in the assembly line, there's a term
that they was being used offered by Tesla just called operated density. So essentially,
to assemble anything around the vehicle, you have to go around the vehicle.
Now, so what happens if you could split the vehicle and you can see it clearly, you can split the vehicle into a front module, a rear module, a battery module, and put the two sides together and assemble these each individual components separately. Then it's more efficient because around this box,
when you send the box through the pain shop, for example, eighty percent of that box is paying is air, eighty five percent whatever volumetrically, that's waste because you're heating up the oven. Okay, you're creating carbon footprint,
you're creating all those things. So this is all the things that we have
been similarly working on for to say, and that's how we have concrete data from the product digital twin. We built the entire manufacturing digital twin and we
can and then the plant investment. We have laid out every station in the
line of this built and how it reduces plant surface area. The manufacturing plant
surface area were on at least thirty five to forty percent. And then there's
an opportunity now because you're building modules, you can introduce robots in thirty you can you can or even other simple automation yes, yes, simple automation in and so on so and the most important thing one it takes out It reduces a number of hours it takes to assemble a car. And also it reduces
significantly reduces the plant investment. So just we did also a calculation based on
this data and everything working backwards, because we have laid out all three assembly lines that is the legacy OEM's assembly line, the Tesla Why assembly line, and the future Tesla assembly line. And we from a financial perspective, and
with Tesla's announcements that they want to build twenty million vehicles by twenty thirty, the savings in investment just in manufacturing. Plant investment is around eleven billion dollars,
and that's based on the amount of equipment that they are purchased in Austin, which they are filed with the county in Austin for their manufacturing, for their for their building permits. So if you work backwards, it's around if
you need eighteen million more units, and assuming half a million units per plant, thirty six plants, thirty six plants, the thirty six billion dollars, we estimate at least a thirty percent reduction in investment, which means tes level save at least eleven billion dollars. It's half a million if you're if you're
taking if you're not sending through the paint shop a big box, but instead you're sending racks of closely packed parts, which is kind of what I think you're talking about. Don't you get a throughput advantage? Maybe the half a
million is not the bank part, sure, so the thing So there are two ways to look at this. This is where we similarly, we have
built a digital twin for manufacturing. So it depends on whether you're a greenfield
or a brown field. So what the numbers I gave you is assuming Tesla's
usually building only green field sites. So we're trying to understand as a coming
back John to an earlier question, as a benchmarking company. The problem with
benchmarking is you're looking at data that's three years old. It's a rear view
mirror, okay, and it's a rear view mirror. So what the important
thing is to look in the future. And so that's what we're looking at
now coming to this. If you're looking at greenfield, now the pain shop
goes from a big pain shop to a smaller pain shop. So redio investment,
radioto, operating costs, reduce carbon footprint, all the things that make reduce cost and so on. And now if you have a brown field,
you can run two side by side and then you increase productivity. Matthew,
is this approach to constructing vehicles predicated on them being electric vehicles versus being ice vehicles? I will okay at this. So when we so very very interesting
question. The fundamental premise here is that you can unbox the body. Okay,
So if you look at so just just to let you know, the companies that don't do a floor is the other one that's there is the byd.
They have also taken out done a vehicle where the body has no floor.
Okay, but in order to unbox a vehicle you need to be able to have enough tonal stiffness and the battery and so the two giga castings have tremendously enabled the ability to split the body out because without those giga castings and the battery being kind of a stiff member to give to tornonal stiffness, in our simulations and the future simulations that we have done, the vehicle would struggle to meet crash requirements because the body has two functions. One it has to
protect first and foremore safety. It has to protect the occupants the customers driving
the vehicle, and second it has to prevent you, protect you from the elements. So we have been working on this for nearly two years, building
the digital trends, doing all these simulations, doing all these things. Would
say, by the time we finished this this year, we close to two hundred thousand man hours doing this work. It's essentially like we had a whole
team of experts from the industry. Terry who was on the show, Who's
sorry, Yeah, Terry was formerly executive vice president a GM ran out programs and he has a whole team of experts. We have a whole engineering team,
and I think we lose by the end of the movie here we will spend close to two hundred thousand man hours to essentially it's like we have a whole team that's kind to build a new car and say hey, this is what we think is happening and give a leg up to all the other automakers and say hey, don't let's not just wait for one of the two years to get the Benchmarin. Let's kind of predict So you start thinking this way,
and we're working with the senior levels with some OEMs who are very very advanced level discussions way. They want to understand what it is, they want
to buy this data, and they want us to help work with them to craft the future solution. It depends on how open the OEM is. So
that's very interesting that legacy OEMs are approaching you. As you pointed out,
Tesla, every time it does something new, it's it's clean cheat it's either a new vehicle or a new plant or both. The legacies, of course,
are stuck with existing facilities. They cannot go out and build green field
sites. Ford's doing one for example, you know, the Blue Oval City,
but they're not going to be able to do that very much. How
much of the unboxed process could they do in a brown field site. So,
John, so I like to what I've told you so far. We
have solid data on greenfield and we have had the best oms I would say the second or third west Om in the world after Tesla challenges on this data and this future model, and we stood up to every question of the ocon on the brown field. We need more time. We're still we're working.
We have a whole team that's working on that too. I tell how we
don't have a we have a solution. We have we are working on several
solutions. But like for example, Terry and his team where we're working for
nine months to even make sure. It took us nine months to even make
this new model pass virtual crash simulations because everything was failing because you're trying to build a new vehicle and c you're learning. When we started this in when
we spent so many hundreds of thousands of hours, we did not even know we had a solution. We did this as an R and D project.
Okay, because everybody in the industry has always been asking, Okay, there's benchmarking data, but what's the future look like? So we just did this
as a we did this for fun. Let's put it that way. So
I wonderfu. So let's go back to the where you do have data.
Okay. And so when when you say, you know again the thirty percent
cost reduction overall, if you could break that down, where does that cost come out. Does it come out because you I think you mentioned you build
a smaller paint shop. Does it come out because you need fewer welding robots?
Does it come out because you need fewer people operators at different stages of the assembly the final assembly process, and talk about sort of where where the chunks of cost saving? Okay, So this is to two areas of cost
Okay, let's I'll just this is what we can give you right now.
One is is a thirty percent reduction in plant investment. Okay, So that's
capital investment capital investment. And then there is thirty percent reduction in process time
okay. Okay, that's work hours. People will off work hours just by
going from a legacy from a legacy OEMs traditional build to a modular build and then also the automation involved. So so let's look at it this way.
If you have gig castings, you need to buy the process get casting the six expense. But you're taking out a lot of robots out okay in the
body shop, So individual individual welding robots get replaced by a get casting well, multiple parts come in. Plus you're doing I cannot share a lot of
this because it's part of that results of our simulation. We share this with
our customers who are buying this from us. But you're significantly reducing the number
of wells that on the way. Yes, you're significantly reducing the number of
parts, and by unbossed you're reducing in the green field the pain shop footprint.
Okay, pain shop footprint. Then when you go from a serial assembly
line and we have every station and every part laid out with the assembly time.
So I've had one whom some oas when you approach some o ems here not as open. Well most are closed, some are open. They will
argue with you and say this is not possible. And even locally we had
we were we were in the US, we were discussions and they said this is not possible. So we didn't show them the data. But it's very
difficult to convince them because they come from this assembly line mindset. And then
you're to find you are to work with OEMs that are work with OEMs that are open, so that they can say, okay. So if first of
all, okay, reducing the body shop, reducing the size of the pain shop, then doing the body assembly, sorry the body putting the body together and the modules and the sites in general assembly. That is not something that
anybody is used to. I was going to ask you about that because at
some point you're welding or doing fastening in the space or in the process part of the process that used to be final assembled. That is one of the
toughest things we took to figure out. It took us several how to put
all these modules together and have them crash worthy. Yes, so putting it
so there are countless iterations, countless concepts that we put together several So go into some more details because I always figured, you know, I'm not nearly the expert you are. I'm not the expert because we have a team of
expert but I thought structural adhesives would be a big part of it. Okay,
So, John, I don't want to share all the details, but it took a lot of effort and finally, uh, you know, Terry is happy. If Terry is happy, I'm happy. Yeah. So that
his team, the team he has. We have experts from different OEMs who
have retired as head of CE, from companies who are head of body architecture, head of a lot of engineering capability, materials experts and so on.
So they have signed off on this. So and these are people who have
launched products throughout their life. So let me ask you. No, we're
throwing the word giga casting around like potato chips, like everybody on Earth is familiar with what gigacasting is. Now, OEMs are building electric vehicles right now
with out giga castings, So what is it that they are doing that?
The giga casting provides Tesla in BYD and Zker with an advantage over the traditional way of making an EV, which sort of sounds absurd because evs are so new there's really no tradition. Okay, So just to so the companies that
have launched giga castings like Tesla, then Zica has followed, and then news there and then Chapon is and Swan, the the UH and then if you see recently one of the local EAMs announced they're buying a casting manufacturer, and then there are different announcements going on. World War has announced that they are
going they're putting in the bank. The press talked about is talking about the
module. What the giga casting allows is is to go to a modular build
okay, and the giga casting so when you look at it, and I don't have the picture in front of me, but if you look at the progression of where they're going again, you know, going from New York to Cleveland to Detroit to Chicago, what is the end in mind? The end
in mind was to build a vehicle that could be So this is that is very easy to assemble like legos Okay, so if you look at the Tesla Wife from last year, they have we integrated the entire thermal management module with a battery, with the HVAC compressor, with the body structure, with the accumulator, the children, the thermo octobal, the pumps, everything. So
it is to build a car like Lego blocks. And this is the journey
to the twenty five thousand dollars ev okay, make it less parts, sort of more modularity, less parts, less weight, less complexity, more automation.
That's the only way we're going to get the price of an EV down to twenty five thousand or even twenty thousand. Last week I was at CES.
We had the vydcgill at our sten eleven five hundred dollars EV four hundred kilometers of range. People that are amazed at how they build it. But
BID still makes money on these vehicles. So that's that's the holy grail.
Well yeah, well, I would just comment that an EB that could be sold for twenty five thousand, or an EB that could be sold for forty thousand dollars and the company actually makes some money because the production costs is you know, closer to twenty right. I mean, that's what we're talking about.
I mean, that seems to be the problem the legacy companies have is that they're you know, they're losing ten thousands in a couple of cases, tens of thousands of dollars per vehicle building them the way they build them now, and that seems to be the big problem that they're going to shrink that cost. Sure, So I Joey, I will not read a position to
comment on those that part because you know, you hear what companies losing money with evis. But what we really track is say, due to product design,
Due to product design, how does that enable lower costs in manufacturing, lower costs in investment, less labor less parts, everything. Because if you
look at Tesla's announcement where they want to go to twenty million units globally by twenty thirty, they're going to sell twenty million units only the prices around twenty thousand or twenty five thousand dollars. There's no way you can sell fifty thousand
dollars Tesla wives and sell twenty million units. Impossible. Yeah, well,
the twenty million is kind of a stretch goal. That's not for you to
say. Yeah. So what I'm saying is it's like my first boss in
the United States, tolermy Matthew, if you shoot for you reach for the stars, you'll end up in the moon. So I think it's important to
have stretch goals. But the point is it's not about the goal itself,
it's what the vision of that vision of how So when we work with Legacy OEMs, the goals are you know, three or I came from a legacy OEM. Okay, the goals were incremental, but what is really phenomenal here
is that the goals are exponential huge. It's not like three or five percent,
it's like thirty forty and bring it with the new technologies and everything.
It's it's phenomenal. What's happening? So where do you think this is going?
Right now? With uh? Is there any way? I guess what
I'm trying to say, what you're describing is it doesn't look like there's any way possible for legacy automakers to catch up. So John, I can't.
I don't look I am not here in a position to comment on those things.
It's the other thing I'll tell you is that the industry is in so much change. The only constant is change. Okay, okay, you're were
to earn learn fast because every day we are learning. Every day or we're
learning. You have to unlearn things because the way you were in which you
designed vehicles for an ice engine is very different to an EV. So you're
to unlearn things. But the most important thing is you've got to move fast.
If you there's no point in coming out of the twenty five thousand dollars twenty years from now. You'll be dead by then. So I move fast
as actually wants. It's a good segue to because I wanted to bring you
back to something so you said it earlier. So I think you outlined kind
of an evolution of the Model three to the Model Why and the evolution of the of the production that you've been able to document. Go back and because
what you're what I think you're describing is that Tesla's product cycle. I mean,
at one level, you know the Model three hasn't changed the way it looks, right, But in fact it sounds like under the skin there they're on a very rapid evolution cycle. So can you elaborate on that quickly?
Are they changing? So the first thing is, Joe, is forget the
auto industry mindset. This is part of the unlearning that I had to do.
Does not think like an automotive company. They think like the iPhone.
Here every day, make a change. Okay, So that's why if you
see the three has not have the new Highland which we have already torn down, which has a different shape. But if you look in the vehicle is
changing every day, it's continuously improving. They don't have the because they don't
have a dealer network, they don't have to like one of the reasons why, at least I felt that when I came from we had model years and we had release dates for new changes, coordinated changes from a particular point in diamond years, because we had to train if we made a change every day.
Just imagine the nightmare with a dealer network. So one vehicle would be
this and next vehicle and the technician look, look look at this, oh ym, everything is different. Okay. So because they don't have a data
network and they're such a technology enabled company, I envisioned that they have systems where every vehicle serial number maybe even has its own service man or description and so on. So there the resistance to implement change is very less. So
they don't have this mindset of modeling a change. It's a continuous improvement.
And if you look, they went from two piece giga casting on the y to a single piece to two giga castings and no floor. They did that
in twenty four months. Okay, that's what. Yeah, they did that
twenty four months. A leg or even less because we get the vehicles and
we with a legacy OEM I don't know. Some of them may not even
able, may not even be able to make the decision in twenty four months because the old day. So one of the things that I think the industry,
the metrics on which industry is changing has changed. Before it was on
scale and using the same platform for multiple markets. Like you've heard the Volkswagen
platform, you sell it, ormamqv platform, you sell it in all parts of the world, you customize for the price point, you sell the Pollo golf everywhere and so on, and there's one of scale. How many million
can you build on this and that's how you made money. Today the paradigm
or the rules of the game have change where it's a technology enabled product and it's about how soon can you get speed into the product, speed of implementation of technology into the product. A good example is China. I'm amazed at
I go to China. Like after COVID, I've been going every two months
or so. The pace of change is so high. And that's why you
see because they're able to the Chinese consumer is the China. I think for
the first time, the Chinese brands have cross fifty percent market share after all, because before it was all the joint ventures with because they're able to implement.
Technology changes so much fast. So when your rules of the game have
changed and speed is your differentiator and technology is a differentiator the old ways of working where you know, we need to have a we need a process too.
So I worked for a legacy company before, and I remember if I had to get something to the CEO C or the company, I had to table three months in advance to get it into the XCOM meaning for a program of okay, So three months is a lifetime in these days in terms of the processes are So it's about being agile, it's about moving fast. And
then also how are you feeling the pulse of the market. Where I was
earlier this year at the gong Zho not a show, there's a company launched a new product. It's phenomenal. You all know the company, you all
know the product. The product was in CS. It was there. It's
a huge One of the Tier one suppliers was displaying all the technologies on it because it's phenomenal. And I asked the head of this product and I said,
comparediately is a great product because I know him from a German luxury manufacturer I said, this is great, it was phenomenal. You did it in
record time and he said, yes, I did it in twenty two months.
Wow, twenty two months new product, the from sketch twenty to twenty three months, he said, from scratch launching the product. And he's working
for Chinese OEM and he said, you know, it's just there. They
air ability to virtually test and do the specifications and everything is so fast.
And so that's the pace at which things are moving to. And this gentleman's
a German gentleman. He had a European team and a lot of it's a
Chinese company, a lot of Chinese and everything, and the car is phenomenal.
That's why it was displayed at CES. Well, talk more about this
right now. We've got to take a quick commercial break and give a shout
out to our great sponsor bridge Stone. How do you bridge down tire stop
shorter on what roads? Is their hydrotrack technology that you don't have to know
how the science works, just where the brain is what really matters is their bridgestone. Okay, we're back talking all kinds of things, really interesting things
with Matthew from Keras off Gary. You probably got a question there, and
you're just talking about something. You said something very interesting about scale is not
the game anymore, that it's more technology that makes the difference in speed and agility. Historically, this this industry has been saying, Okay, you got
to make a bazillion of something in order to make any money on it.
Okay, So so let me just let me just so, I'll just give you the reason why. Jeegy just told earlier, like twenty minutes ago that
they're losing money on evs. So if I'm losing money on a thousand evs,
why would I want to make a hundred thousand evs and lose more money?
It makes no sense. It makes no financial sense. So the point
is, so the point I was making is you know the and then okay, so let's go back to the technical. Let me approach this from a
I'm a CEO, so I think financially also, so I have to be profitable to survive though several years we invested in the business and now turning the turning the corner. But let's look at it technical appearance. The uh,
there are varying questions. Fortunately, you build cars on platforms, okay,
for evs, when you built a platform, you try to use the same components for different for the range of vehicles. Okay, for maybe there are
companies that you see and D size SUV, same platform. But for an
EV, weight is a killer because weight drives more battery, which means it kills range, more battery, more costs on and so forth. Weight is
a factor. So the question is if you built a platform and then you
had a platform that scales from a D SUV to a B SUV, your B SUV is going to be inefficient. Okay. Engineering wise, it's impossible
to have the same platform and make it scale from a D to B and use the same component, same war similar sized components to get the scale from a purchasing standpoint or volume standpoint and so on. So it's difficult. And
now the flip side, the other killer is so you're inefficient on the smaller size and where do you sell the most volume and the smaller one or the bigger one. So it's a double whammy. So the old rule, this
is what I meant by the old rules by which we were doing that.
Because it's an EV and weight is so critical and battery is so critical.
The decision making framework may not be as may not be right for this new way, new way of a new way of working. Now a lot of
consideration come in, especially now with the So if I did I've worked in manufacturing before. So if I had a plant, is I don't have enough
scale to run enough EV's on a plant, then I need flexibility to run both ICE and EV So then I need some commonality of component and SW and so forth. So I don't know whether Gary I answered your question. So
it sounds like that now you have to be optimized with each product, and using the platform strategy, you're suboptimizing in order to have greater bandwidth. Well,
on ice you can sub optimize, but weight is not such a critical factor because you measure weight in the ice vehicles by categories for emissions and the fourth. But here every gram matters, every kilo matters because for every kilo
week computer that you need four dollars of extra battery to move it. So
it's a disadvantage. So you want to be optimum at So can I go,
let me ask this? So if I have a car plant, it's
set up on you know, traditional and I and I buy your study, and I'm persuaded that You're absolutely right. It's that we need to, you
know, move as quickly as possible to this different approach to assembly and achieve the achieve the or I need to build one because I know you've only done this in a green field. You know we have done this. Okay,
fine, this is where I'm this is where I'm headed. Do you have
to can you can? I? Do I have to throw away scrap right
off, trash all the equipment and all the assembly systems and welding robots in the whole nine yards that I already have? Or does your does your model
sort of assume that, yes, you could you know, you can use conventional technology if you if you've got a factory full of robots, you could probably reuse x percent of them. I'm just sort of wondering how much of
a sort of a but you know, kind of a you know, modeled model T full stop kind of retool you're talking about here, which it seems like that would be a disincentive for a legacy o EM, but maybe it isn't. So I'm just kind of curious, kind of what what's the cost
penalty for saying, Okay, Matthew is right, we need to change direction.
We need to do it now. How big a cost penalty from this?
Okay? So I think there's quite a few things. Joe before Joe
before I answer the question. Okay, First of all, is we based
on all that we are saying? Okay? The number one issue we hear
from customers is benchmarking is good, but it's a rear view mirror. Okay,
nobody drives a car looking at the rear view mirror, do you.
We don't. We look at the front wind shield and they're saying, okay,
tell me where this car is going. So with we have a very
good team. I'm very proud of our team. We have a lot of
your engineering company. First, we have around two thousand, three hundred engineers.
We have a lot of experts, and we happen to do benchmarking.
So we are kind of saying this is what we think is going to happen.
It's up to the OEM once they work with us and buy all the data and we work with them in a we not only just the data with the consulted mold and engineering moard. It's up to them too. I tell
CTOs opening I said, look, this is what we have made. This
work virtually next step for you to and a lot of our customers they have two three five billion dollar R and D budgets, And what I tell them is, look, you're spending so much money doing this more of the same here, Why don't you look at this new work. We're build ten or
fifteen mules cars, prototype cars. Go test it out on your track.
How does it handle? How does it do? Crash? How does it
do? This is if this is truly If Tesla has announced it Investor's Day
and you want to catch up, like La Musk has done something phenomenal.
Right, he gave the forty eight word architecture to other companies. Jim Farley
twe that sorry, I put it run x X platform now and so on and so forth. So really, let's look, I'm an engineer. What
is R and D. It's about innovation. What is innovation? It's about
trying things that you don't know. So this is one more experiment. And
if you have an R and D budget of three or four billion dollars, hey take this. We have given you. We think we have the cook
book the recipe for this new way, build it, try it and what do you have to lose? It's another experiment. If it works, you're
going to save thirty percent, You're going to save on one plant, You're going to save three hundred million. Is the risk? What's the risk and
what's the reward? It's huge And then traditional automakers are risk covers. They
don't want you know, they don't want to take me risk because I work.
I was with one leg a C a M and had a manufacturing told me this will not work. One hour. I just walked out of the
meeting and I said, look, the risk covers. And that's the reason
why this individual is not a leader in the industry, because he's he's a fast he's a follower. But I think that part of the reason they're risky
versus What I was trying to ask is that that it's and it's a question, not a statement. And the question is does does moving to the process
that that you're modeling, that you were, that you've that you figured out, does that basically do I then have to go to Wall Street at the next cor I said, well, I've just put you I've just written off two billion dollars in sunk investment because we're going to go to you know, an entirely different assembly approach. I guess I'm not trying to figure out that's
an a constacle that they have to overcome. Okay, so let me ask
you a flip question, Joan as a businessman, Okay, I am a legacy. Oh yeah, okay, I'm building a car and you Tesla comes
out of this new approach and have reduced your manufacturing time thirty percent and your plant investment. You're coming to the market. Do I start losing share?
Okay? So? Which is so? Which? Yeah? So? Which
is so? As in oe M, I have to make a decision and
say, there is this threat out there now how okay, so what is the so? What is the big? So? So we have done this
for a green field? We have now that we will be finishing. In
fact, I'm on Wall Street next month to present to a bunch of investors on this approach. And is one the the question that comes out, the
question that I would ask, is we after we finishing? I said to
uh, this one, We're then going to work to come up with a solution. If we can come up with a solution for a brown field.
And there are always look, there are if you're working with a clean leader paper green Field, it's a no brainer, but it's when it's brown Field, there are compromises we'll have to make. Okay, how do we modify
the paint shop, how do we do general assembly? How do we modify
those if we take the robots and can we repurpose them? All these we
are we're working on it. We don't have a solution yet, I can.
I can tell you one hundred percent confidence. You know, we're one
hundred percent confidence in the green Field. Excuse me, and a couple of
our customers who are early adopters, they are very they're very eager to work with us and so on. They have they've bought into our analysis and they
feel we are in the right path. So, so is it possible for
a company that, you know, Joe said, they've got lots of equipment and it's sitting there and it's building cars, and they don't want to throw it away because it's still the stamping process is still stamp very well on the welling machines, weld very well, and so they want to keep this.
But is it conceivable that they could take your model and just do a small pilot project to determine its fees ability and then extend it from there. Sure,
I think that's possible. Or the other thing is we are discussing with
two OEMs. One is planning to use it for one of their low volume
production luxury marks. Okay, so they are not planning to use it on
their main one, which is around two hundred and fifty thousand units. They
are planning to try this out first. They're planning to be prototype, but
they're going to use it on the product itsels on fifty to seventy five thousand units. So it's assuage, it's making sure you are able to balance the
risk. This will be a lot of learning. Nobody has done this before.
Nobody has done this before. Or what we are helping the OEMs with
or our customers, those who are interested in this is we're helping them saying, hey, this is coming. This is instead of being surprised two years
from now in Tesla lunch or a year from now, for two years from now in Tesla lunches. The model to hey, this is this is what
worst comes to words. Let's say I know we will be at least eighty
percent correct. Worst comes to words. This is one more R and D
experiment you tried, and as organizations we learn if you're not willing to learn, if everything is bulletproof, that means you're not taking enough risk. So
if you knew everything there's no risk involved, then where is the innovation?
But not only learning, there has to be the unlearning because they say we've done it this way for yes x amount. Yeah, that's been a big
issue in some meetings, especially where the head of manufacturing is, you know, so convinced that their way of working, and they Joe, I'm sorry to say this, the immediately harp point all the rise reasons why it cannot be done. I have to I have a equipment. I'd write that offer.
No, please just look at it this way. This is a new
innovation that when giga casting came out, people said it would not work.
Now many people are adopting it. The question is so. And then one
other reason, Joe, is a very important reason. When you look at
the valuation of several of the automotive companies stock valuation, there are some companies if you take out the cash because I also happen to be an MBA, Okay, you take out the cash and their balance sheet, their value is very minimal. You know that, right? Okay? The question today that
the market is asking is is not whether the company will survive the next three years, will the company survive the next ten years? Okay? And if
your sores covers that you're not willing to make that jump and even experiment and where everybody is trying different things and so on, then that only reinforces the belief of the investors that you're not going to survive in ten years. My
question, now, yeah, I love this idea of constant innovation, constant change. You know, you've talked about the first version of the Model three
and then how it's evolved the model why even more and so forth. But
how do you justify writing off all the sunk costs that's in there before you've recouped that investment. So you know, Tesla had tooled up all the stamping
dies and the welding equipment and all that. If it's going to be doing
these changes literally within months, not waiting for a full model cycle or even half a model cycle, seems to me you're just going to be burning up capital. You're not going to get a return on that capital. You're already
introducing something new and even though that new way of doing it is cheaper to do, you still haven't paid for the capital that you've already put into the program. Okay, So John, I think so I can talk a little
bit of what we understand from Tesla because we have bought Tesla Wise in China.
We brought Tesla Wise in the US from Austin, and we bought a Tesla Wye from Fremont. We bought a Tesla Wife from Berlin. It's very
difficult to figure out which plant, but pretty soon we configure out. Not
every so when they set up, say Shanghai does not have a gear casting, they're still using that. It's Austin that has a giga casting. So
it's just waiting for a greenfield plant to introduce these. So what we can
kind of understand is that I think a lot of the engineering is in Fremont, if you see, like I think, even though there's a new plant in Austin, a lot of the engineering is still done in California. So
a lot of the experimentation, we think, is done in Fremont, which is an old New meat plant. And my first new car in the US
was from the New meat plant because and I bought at an American car.
So I bought a Chevy Prism. That is what a geoprism, what you
say an American car. The only thing American on it was the Chevrolet badge.
Everything else is America, right. Just to bring this up, you
know, I was with Joe ad on the conference today. A lot of
the industry in Detroit or around the world, especially like it's like Tesla is kind of a villain. No, absolutely not. Tesla is an American company.
Okay, I just want to I'm an American, I have become an American citizen, I'm an immigrant to this country. We've got to be proud.
It's an American company. It's leading the automotive industry, so we should
be very proud instead of realifying that company. I totally agree. Yeah,
okay, So now just imagine if Tesla was in some other part of the world, it would be called by d it would be viewed as I think that's I think we know the answer to that. Yeah, But the point
is it's Tesla is an American company, so you know, they're at the forefront of innovation. And I'll just tell you one other thing. Even this
warning, I use reach ot with my Chinese customers. The top benchmarked company
even for the Chinese is still Tesla. Okay, it's still Tesla. Before
COVID, they would ask us about other companies, other OEMs. Today the
Chinese don't even bother They're interested in Tesla or themselves, right, not Volkswagen, not GM. And then they feel they're far ahead of the others and
so on, and they say, hey, we are much better than them, so we want to know. You only learn from people who are better
than you. You don't learn well. Kinds of drinks too, right,
I mean in the sense that the Germans have always been known for their body structure, their powertrain, their the right and handling. To the Chinese customer,
that doesn't really matter. You know, they're stuck in stop and go
traffic all the time. Connectivity, infotainment, you know, the latest electronics,
that's what counts now. Technology, integration, voice integration, voice man
they're bringing in. The technology piece is huge for the Chinese. And then
styling. So for example, uh, you know, we talked about a
lot of things that Tesla's doing well. So one of the things is they
have not changed the external body style. That's been a big detriment to them
in China because for China, having a car is in some cases, when it's your first car, it just to state that you have arrived. And
so if you had a car and three years later you bought a new car, if it's the same shape. If I bought a car and three years
later it's the same sheep, you don't know that I bought a new car.
Part of the reason, Okay, I really don't care about the car I drive. You know, I am not the type. This is when
I was a four student right right with my first job. But today I
don't have a car. I drive a different car every week because I'm always
benchmarking. Can I can I ask you a question? So I want to
You've talked a lot about sort of the resistance from kind of the heads of manufacturing that you present to. But there's some who are totally there are some
let me get just crick. There is some other heads of manufacturing is hey,
this is this is awesome. I need to know everything about it because
this is huge. Thirty percent I can take thirty percent less people so that
you meet all types of people in this so and you mentioned people, but I'm going to let carry ask about that, but I'll ask this question, which is where I was headed. I mean, it does, though it's
not just the manufacturing part of the house that has to change. You have
to have the engineering side of the house has to change to design, to design the vehicle so that it can be used giga casting so that it can right, I mean, so you're actually you're you're you're really talking about a fundamental change, not just in the manufacturing process part of of the operation, backing up into the vehicle engineering and vehicle design and validation and all that stuff.
Right, it's pretty significant in management well, right to allow this to happen. Sure, so one day, let's you know, the product at
the beginning is at the top of the food chain. Unless you change it
in the design and engineering, manufacturing cannot come back and make any reap of these benefits. So definitely it has to be bought in. And what we
are kind of like, as we say, look, benchmarking is very interesting because it's kind of detective work, Okay, it's trying to find figure things out. And what we see from all this, especially with all the trend,
is that there's a heavy level of integration between design engineering, manufacturing and automation in each zone of the vehicle. So I'll just tell You'll give you
an example. When Tesla is one of the first companies that came out of
the central computer zone and architecture for electrical electronics, what did they do.
The whole powertrain controllers was built by one tier one steering with somebody else, the break with somebody else and so on. So Tesla is one of the
people to say, hey, why do we have all these separate controllers, Let's integrate them and have zonal controllers and a central compute in the power distribution center and so on. So by going and looking at this integrated in an
area of the car, they were able to reduce costs just in harnesses.
For example, from the X to the Y X to the Y they reduced the Karnas cost five and fifty dollars or so okay, same way. When
you look at the way Tesla is evolving, and the Chinese saw you heard about the Shopong G six which Folkswagen invested in, they're pretty much very very fast follower of Tesla. They took the module they built a giga casting is
no floor, everything very very quickly and they did it in a phenomenal eighteen months or so. Phenomenal Okay, so same way. So you what they
did in the electrical electronics architecture is what we think they're doing on the vehicle, on the mechanical instructure components. But they're doing that by integrating design,
engineering, looking at the manufacturing automation. How do we bring all this together
to take cost out, reduce the number of parts, increase the modularity, reduce the labor and so on. And that's what we think they're doing.
And even in the engineering functions. So for example, traditional companies have a
body group, a chassis group, electrical group, with thermal management group and so on. So if you look at the front thermal management module of the
Tesla, you have body group there, you have the thermal management group.
We have electrical group because batteries there. You have chassis because their accumulator is
there. They got everybody to work together. That does not usually happen in
traditional areas. So they're optimizing all that. Yes, yeah, So what
you're saying is they're approaching vehicle design from a total system standpoint, yes, not from discrete components or silence within the company. So you remember you remember
earlier we talked about scale before. The whole point is, hey, let's
set make component and let's put it on all our ten million vehicles or five million vehicles. Now you want to optimize it for that so vehicle, and
you're trying to make sure that the vehicles are reduce waste, reduce costs, and it's integrated and swan. So I'm not saying scale is bad. You're
trying to use components, but as much you want to optimize the vehicle more than just a part. So it's vehicle level optimization, system level optimization,
not pot optimization. So let me change this a little bit. We've been
talking almost entirely about engineering. We have some viewers who are consumers, and
it seems to me that a consumer hearing about things changing very quickly, about things being done very fast, might make them think, what is the quality, reliability and durability of these things that are being done fast versus those things that have been made in the traditional way for years and years and years?
I mean, do you measure that? Can you make a determination of that?
So we we So I'll answer the first question as as an employee of care Soft, and then I can answer this as an individual. Okay,
So we do not do quality, durability or reliability testing on any of this.
We are looking at the design and so on and so forth. Okay,
that's all good. So from a standpoint of the other things, I
don't know, we don't know. We if we start doing that, we
will need a lot more money to do it, and we don't know what we you know, the data we have, we need a way to use the data and monetize it. Now, from a personal standpoint, I look
at it and say, hey, every vehicle, again from an engineering perspective, not as an employee of care Soft, is any engineer who has done this. They would have virtually validated it. They would have physically tested it,
and so on and so forth. There are companies that have recalls in
spite of all their processes and everything. And so if I just take the
test of why they just sold a million more than a million units last year, so obviously that team has done their testing and so on and so forth, and that's why the car was able to sell a million units and so on. So we don't do that, Gerry, but the comfort level would
be is And also it's like this right. Anytime you make a change there
is a risk. So for example, sometimes I get an updoate down on
my update on my iPhone and twenty four hours later there's a new update because something doesn't work. So there is no free lunch if you want a new
feature, Yes, there is something. So if I get a say,
if I switch to a new phone, let's say a new phone comes over EMS. So recently, I was last week at CS and had dinner with
a Chinese customer. He showed me the new Huawei phone. I tell you,
if it was available here in the US, i'd swostreated immediately. It
was fantastic. He showed me the photos from his phone. It converted to
a tablet. It was phenomenal. No, if I make the change,
I have to learn new things because it's a different operating system, and I don't think it's available in the US. So huahweh was banned from the US
pretty much. Yeah, So my point is I was very very impressed.
The point I was making is any time you make a change, there is risk, is learning, and that's why so for me it change is the only constant. But Matthew, don't you think it's new technology? Has enabled
this as well. So you know backstory, everybody in the auto industry learned
the Toyota production system, which preached consistency above everything else. If you want
to get to six sigma, which as you know, is probably the ultimate that you can bring any manufacturing process six sigma, statistically, you don't change anything, get really really good at building it, you slowly work all the bugs out of it. And so what Toyota preached was that change brings variability,
variability brings quality problems. But today, and this is what I'd like
to get your input on, with software defined vehicles, with vehicles being designed or developed with digital twins, you can check out a lot of things.
You can simulate everything that would happen. That can give you the confidence to
make these changes on a flying basis and not wait for a mid cycle change.
So John again, so when we analyze vehicles, we are able to see the design changes. We have very little visibility. I visited last year,
maybe four or five factories. I did visit them, but I don't
know how they are taking these change in designs, making sure the quality processes are being implemented manufacturing processes so that they are robust and so on. I
have I left manufacturing a long time ago, so I I that's our focus is more on the design and we expect that you would they would check the design before they release. And that is it's been a good quality quality is
it given today? And one of the things is I think you saw it
at c S. You see all the Chinese cars, look at the level
of quality that they all look good time for one. Yeah. So a
couple of times we've kind of danced around the topic of the impact of the sort of the unboxed processor, the different process on people. And I want
to I want to ask you. I mean, as you've as again as
you've modeled it, you've modeled the system that that you have built, it sounds like it uses a lot fewer people. And so talk about that and
just talk talk about that and where are those people? Where do those people?
Where do those people come out? I mean, do they come out
and final somebody that can on some other part of the process. I guess
it's not your job to figure out what to do with them, but I would assume that that's a significant issue that you're that the OEM would have to think about a lot of them the major label savings is coming from the assembly area, final assembly, final assembly area. There's a lot of things that
because some of that is also in the pain shop because we have because it's simplicity the process, you don't have the full body and so on. Then
early on in the body shop, a lot of the some of the body shop things we're stealing it. So those changes are happening the thing. So
yes, there will be a question of the people. So these are the
major areas where we are saving people. The exact simulation by this I can
we have done the full comparison of every station and just in preparation for the show and when as it tuesday, I reviewed all the data and essentially you can see a traditional the assembly plant is so big. So so let's say
I'm just going to use a number says a million square feet or something, and then the other one is for the same volume with a modular build would be around say six hundred and the other one would be say five hundred thousands.
So you're seeing those savings across the board. The one thing I will
just tell you is from if everybody is doing that and they are able to take the manufacturing cost out and the labor out There is no way that if you're in no EM you can say, hey, I'm going to follow the old process. You'll have to make the investment to get there, because there
is a concept in financi which is called sun cost. And sometimes if there's
a better solution out there, even if you don't recup the cable, you have to buy the bullet. And if what you're doing is obsolete or not
competitive, you have to buy the bullet right it off and then forward.
When you present your ideas to automaker customers, you know how important is the people side of this to the to them so they recognize it's a problem.
They recognize, you know, like say, for example, especially when they present to European customers, they have a social contract and a lot of customers that we have legacies, have OEMs and so on. But I think the
first thing on their mind, the first focus right now, is hey, this is a new way of doing things is going to be more efficient.
I need to investigate it, I need to learn more, I need to an experiment and everybody, I'll just tell you. So when we were talk
at the executive level, they rarely see the financial reason and when we go to the lower levels at the operational level, they are like saying it will not work because they are blinded by so the bodyshop person will give you reasons why it won't work because they're all nobody's looking at the whole elephant. One
is looking at the tail, one's looking at the and swann. So the
executive at the top level really sees the financial reason to do it, and then it's a question of it like anything else, it's change management and adoption.
You're to try experiments, see whether it works, and then who's going to be the follower first. I can just tell you I think the first
person who's going to implement this is one of our Chinese customers. Okay,
it doesn't happen yet. Well, I was with them last week. I
can just tell you I was with them last week, and they re shored it to them last year late last year and China later this month. In
China, and they want to They are like, let's go. What you're
saying is Chinese. Excuse me? A Chinese car company will adopt this unboxed
process or no, will be one of the first to try this out in terms of while so one of the things about them is they're willing what they really like. So one of the things it's phenomenal with Chinese and if you
see, the Chinese have learned a lot of things from the joint venture companies, and those Chinese people went, those Chinese executives who were in those companies went and set up these Chinese brands. And then there you have the Neo
and all that, who are set up by internet entrepreneurs. But what are
a lot of people in to help in manufacturing and so on and so forth.
There were the willingness to learn and change is so huge that I think they will move the fastest. That's my part. The China are also under
a lot of competitive pressure as well. I mean, I guess they're looking
for that edge. And so presumably these companies don't have the same sunk costs
that you mentioned Joe and John were talking about, meaning they don't have legacy factories the way that companies in the West. So Garry, I think this
is the first thing is hey, this a new concept. There's a new
way of doing things. Can I at least validated Try the vehicle, build
it that way, see whether the vehicle works. Then let me evaluate the
many fact we have done a lot of work for them. But in terms
of openness to try it out, I think we have met with many customers and I presented it. I think we the Europeans with the Americans, be
the Japanese, the Koreans were, the Chinese, these and any Indians so on. These are the major automotive companies. I would say the Chinese,
they when I approach some of the other When we approach the Chinese, they're like, what do I need to do this and what are the benefits?
Approach the other other OEMs, a lot of the other legacy OEMs and other countries, they're like, they'll give you reasons why it cannot be done.
So it's that openness to try something new and not to not to just shoot out and I shoot down an idea because if test represented at the investors Day a year ago, and you know we we this was a concept that was suggested in Europe. There was a on this in two thousand and nine and
twenty eleven. I don't know whether you know. It came from one OEM
and a couple of Tier one supplies, So okay, So when I presented it to Europe. One of the things they said this was I met the
gentleman who had worked on the project at that OEM and he said, this is something played around before and then we sheltered it because it was too much of a change. So again, gig're casting everything. Tesla has the guts
usually to do take the risk and do it and so on and so forth.
So coming back, so I think they will be one of the first people to take the risk and do this. We're good. I think we're
going to have to wrap this up, even though this is a fascinating conversation.
But Matthew, thanks so much for coming on the show. Really good
to have you back on again. Thank you, John, Joe, always
good to have you. Gary, Thank you, Gary. You and I
will just keep on doing this. So we're good. Thanks for being on,
and I want to thank everybody who's tuned in. Auto Line After Hours
is brought to you by Bridgestone Tires Solutions for your Journey
About this episode
Insights from Matthew Vatcha, CEO of Kerasoft, reveal how Tesla's innovative manufacturing techniques, such as unboxing and giga casting, are reshaping the automotive industry. The discussion highlights the significant cost reductions and efficiency gains these methods offer compared to traditional assembly lines. Vatcha emphasizes the challenges legacy automakers face in adapting to these changes, particularly regarding sunk costs and workforce implications. The episode also touches on the competitive landscape, especially with Chinese manufacturers rapidly adopting new technologies, potentially leaving legacy OEMs behind.