Yes, it's the Ford method: you hire the smartest people you can to lay out the best plan, and a bunch of interchangeable grunts to just execute. But it turns out that the person that has to do that work 40 hours a week has a much better chance to find ways to make it more efficient, and if you build a culture where that's encouraged, that's what they do. If there is "one secret trick", it's probably that an employee that feels that they own their work does a much better job than one that acts like a cog in the machine someone else designed.
Difficult to believe unless you've ever worked in an industrial setting.
This also doesn't sound like something Tesla needs yet, as this seems to be great for building different types of cars based on demand rather than maxing a single car output.
Why? That's how engineering works; small improvements aggregated over time.
Note that this is less efficient if you correctly forecast how many cars of each type you sell. An assembly line optimized to produce a lot of one car is cheaper IF you actually sell a lot of those cars. Which way to make the trade off is a complex decision with pros and cons. As technology changes different factors become important and the best changes.
Additionally, you cannot order most Toyotas, the dealer usually doesn't even know what color or trim levels they are going to get in advance.
Its the Trader Joe's model. Have super high quality (and/or well priced) goods and consumers will bend a lot on choice. In fact, studied have shown that too many choices "freeze" consumers and they just get frustrated.
I'm sure a lot of consumers would take a 2nd or 3rd choice color Toyota, over ordering whatever they want from a domestic brand.
>a Toyota spokesman said that the brand was not focused on chasing volume for the sake of it. "We believe that our sales volume is just the result of our focus on making ever-better cars and providing better customer experiences."
And that has mostly been true - focus on better cars and presumably better production techniques over many decades. It may seem obvious I'm not sure other companies focus like that.
Processes and controls are very important for quality, but as business goals shift and evolve, the processes also need to evolve. But designing processes that can evolve gracefully is not a trivial task, especially in risk-averse organizations.
FYI Kanban came out of the process on Toyota assembly lines.
For comparison Honda has a flexible plant in Marysville, OH, which I've heard has a run rate of one vehicle every 4 minutes (but take that with a very large grain of salt).
Robots also only really work in stop stations, not on moving vehicles (with a few notable exceptions like paint shop).
Does all of this cost more than hiring a person? More than twice as much?
How often does your automation fail? Is it more than 1 out of 1000 cycles? You have over 10,000 automation steps. That would leave 10 errors per vehicle. When automation fails, it often stays down for a while for investigation and repair. Any station down will stop all stations both before and after it (eventually)
With 10,000 automation steps, and a run rate of 1 vehicle per minute, how often can you lose a robot?
Disclaimer, I work for GM; any opinions are solely my own.
I see robots/automation as a solution to a problem. That problem is safety. Either repetitive work that slowly breaks down the human, or "this is not good for you"-work that's directly dangerous.
I like that question from the sensei in that goldratt book: "did the robots make you more productive?".
Trying to invest your problems away is a waste of time and money if you don't know, and continously work with your processes. Or what they call kaizen in the article.
The big issue is improvement of standardized work. If you automate early you get tethered by subpar standards. This is natural when you have workers: you iterate work instructions and what tools to use together as a group. This is basically how Toyota is so good at producing: every worker know what to do and when to do it. They haven't always been like this; they have slowly iterated into what they are today.
Improving on work instructions for a robot is tideaus at best, and really, really costly as a worst case: you either re-program, or you're forced to reinvest if the robot isn't capable of the new movements/steps.
Musk also had to learn some lessons Toyota learned years ago, because he trusted a bit too much in automation.
If you want to automate something, you need to know exactly all the corner cases, every step of what the human is doing to make it work. The robots are precise enough, but it's often not that easy to describe the tasks to them.
Think about a company that produces screws, they don't have a program for every possible screw they make. Same goes for a more complicated item like a metal box with a door on it.
The robotics are fine. The problem is, in the off chance that an error happens, the results are absolutely disastrous. The biggest problem being that there are too many potential things that can go wrong and it's very difficult to program the machine to be ready for every possibility.
Some known potential errors are checked for, but a problem is that when the machine detects an error, the line has to shut down so that someone can run over and resolve it. If they have a human doing the job in the first place, the issue can be resolved immediately.
For the most part, automation is just used for major error detection every step of the way (errors being things like cracks in the engine), but a human assembles everything and checks for any errors that the machine can't detect.
Cut 7 to 3, cut 500$ to 200$ say by rounding. Save 300$ per car.
How many cars do you need to recoup the 100 million$? 100m/300= 300k cars. Just one year of model3 production.
When I did robotics we had a perfectly capable Linux box running PID loops several hundred times a second; but our robot still sucked b/c our on board motion sensors were simply not precise enough to give us accurate data to feed the algorithms. As usual, it's all about the data.
When we were theorizing about a gifted car plant, the example may have vaguely sounded like Toyota’s NUMMI plant, that was, for practical purposes, given to Tesla in 2010 in exchange for shares. A year later, Toyota opened its first simple, slim and flexible plant as a pilot north of Sendai, Japan, and a few years thereafter, Toyota sold its shares in Tesla. If the relationship would have lasted a little longer, and if Elon Musk’s hubris would have been a little less pronounced, Tesla could have learned something.
Before landing in production hell, and pitching a tent to make his Model 3, Musk promised that he would out-Toyota Toyota when it comes to lean manufacturing. He had a catchy name for Tesla’s non-existent miracle plant. He called it the Alien Dreadnought. I ask Akahane what Toyota calls its super-flexible line.
“We don’t really have a name for it,” Akahane says, and he doesn’t seem to think it needs one.
I completely agree with you, I'm just surprised how often I see people try to do this. As someone with lots of experience in advanced robotics, people ask for my advice on automating things quite a bit. I always tell them they're approaching the problem wrong, and they never listen until it's too late and usually (because it's often a startup) the company just outright fails.
You are not the first company in the world to try to automate <insert blank>, it just turns out it's roughly 2 orders of magnitude harder than you think it is. No, I will not build a production ready system that involves an unsolved robotics problem with a ~$100k budget.
He didn't have a third rule that says "If there's no process, automating a new will expose your hubris" but it's implicit.
and how exactly would they do that? their non-automated lines barely work.
the point of my comment, which i thought was clear, was a counter to the continual tesla hype in that "can't wait until tesla addresses <this> problem" as if they've conquered all problems that have come before. toyota has it together and has a significant amount of r&d that goes into their advanced assembly lines. it's a bit laughable to think of tesla suddenly taking them on in automation given their historical troubles. or am i wrong?
also, those numbers are fine, but tesla isn't even the largest electric car manufacturer in the world, by sales numbers. and they don't approach traditional car makers. for example, kia sells around 600,000 cars in a single year, and that is including say three times as many models as tesla has available. tesla isn't some manufacturing darling story as far as i can tell. they have no ability to yearly iterate like other car companies. or do they? how do they update their models?
i think the point remains: it is flippant to suggest they can just suddenly innovate on an automated line.
Heck, their line was catching fire on a weekly basis a few months ago. Academic citations hardly necessary.
Um... the Gordian knot was not untied, but rather cut by a sword. It's supposed to be a bold, out-of-the-box solution to a seemingly impossible problem. I don't know if the author of the article chose the wrong word on purpose.