8 ms·
Toyota's Takaoka #2 Line: The Most Flexible Line in the World
- crb002 8y agoTakaoka Line 2, when Category Theory meets auto manufacturing. Love the carts they move cars on. Curious if Tesla attempts such a line next.
- protomyth 8y agoThe article spends its last three paragraphs talking about Tesla: 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.
- Judgmentality 8y agoYou should never try to automate something before that something is already working. You can't optimize something that doesn't exist. It's the equivalent of scaling a company before you even have a product, let alone product-market fit. 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.
- bryanlarsen 8y agoElon just claimed that designing a rocket manufacturing process is 10X as difficult as designing a rocket, and that designing a car's manufacturing line is 100X as difficult as designing the car. I'm fairly certain he didn't believe that 10 years ago. :)
- rangersanger 8y ago“The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.” - Bill Gates. 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.
- nikofeyn 8y ago> Curious if Tesla attempts such a line next. and how exactly would they do that? their non-automated lines barely work.
- colordrops 8y ago> their non-automated lines barely work. citation?
- zemvpferreira 8y agoTesla production problems are well documented: https://www.wired.co.uk/article/tesla-model-3-production-stock-problems-engineering https://www.wired.co.uk/article/tesla-model-3-production-sto... Heck, their line was catching fire on a weekly basis a few months ago. Academic citations hardly necessary.
- jsight 8y agoNow you are just making things up. Citations are really necessary when you start claiming things are catching fire on a weekly basis.
- nikofeyn 8y agoi think they must be referring to tesla factory fires happening in fall of 2018, which is easily searchable (how i found it). apparently there were reports of frequent fires before a big one.
- jsight 8y agoI am aware of fires both last year and this year. I am not aware of fires on a production line on a weekly basis. That claim is simply an absurdity.
- nkoren 8y agoThat's FUD BS. You don't produce nearly a quarter of a million cars if your production line "barely works". The truth is that they're now routinely exceeding a thousand Model 3 cars per day. https://www.bloomberg.com/graphics/2018-tesla-tracker/ https://www.bloomberg.com/graphics/2018-tesla-tracker/
- deleted 8y ago[deleted]
- deleted 8y ago[deleted]
- Xunxi 8y agoWhat I would've loved to see is the comparative efficacy captured in motion for (lets say) a "layman's observation" of production. Just a glimpse into how it works out on the "flexible line"
- nabla9 8y agoThis maybe: https://www.youtube.com/watch?v=t0E66vaiXeg https://www.youtube.com/watch?v=t0E66vaiXeg
- csours 8y agoThat's a very nice video of a production plant, but I don't think it's the one in question.
- csours 8y agoAs far as I can tell they only talk about the Takaoka #1 Line, which has a rate about 1 car every 57 seconds. This is just about normal for a regular car plant. 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).
- lnsru 8y ago“They would tell you that robots are great for repetitive tasks like welding, or painting, but they fail at picking and handling small parts.” Are robots really that bad nowadays? I imagine, it would be a problem in VGA-only camera years. Now we have tens of megapixels, lidars, tons of computing power (cheap!).
- nexuist 8y agoI think the bigger problem is in sensor precision, particularly those sensors responsible for reporting what state the arm in (i.e. so the computers onboard can calculate the position of the arm relative to the object it needs to pick up). Sensors with low tolerances are extremely expensive and those particular robot manufacturers may have opted for less accurate sensors to save on costs. They may work perfectly fine for moving things like doors and frames; but the differences make themselves known as soon as you try to interact with bolts and etc. 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.
- jbay808 8y agoDid you remember to low-pass filter the derivative gain? Properly accounting for sensor noise is just as important as getting low-noise sensors.
- metaphor 8y agoForgive me for perhaps being naively optimistic, but I'd probably give industrial robot design engineers applying optimal control methods to solve performance robustness issues the benefit of the doubt that their error budget would properly account for and derate any critical sensor.
- 2YwaZHXV 8y agoAs someone who works with modern industrial robots, like you'd find in a car factory, the sensors they're using for the arm positioning are unbelievably precise. I can have the robot stopped, with the brakes on, and push on the end of the arm with my fingers and see the joints registering the deviation (and not by 1 or 2 counts, but many more), while I don't perceive any significant movement of the robot.
- not_kurt_godel 8y agoI don't doubt the line is much more efficient and flexible as claimed, but the article doesn't do a very good job explaining exactly how the gains are achieved beyond hand-waving about clever contraptions that are faster than robots and the ability to dynamically move stations around. It seems difficult to imagine that hordes of industrial engineers haven't done the calculations on each of these methods countless times at all car manufacturing companies. There must be deeper, more subtle factors that explain why Toyota's particular combination of techniques yields such superior results. Perhaps it's just the culmination of a lot of long-tail optimizations that only Toyota has had time and capital to let mature or maybe there really is just "one secret trick" that underpins it all - the article doesn't really give a good sense of what it might be. In either case it'd be interesting to see a detailed breakdown with numbers comparing the various lines with explanations for why particular decisions were or weren't made to truly understand why the system works so well.
- georgeek 8y agoThat's the whole concept of kaizen, or improvement: https://en.wikipedia.org/wiki/Kaizen https://en.wikipedia.org/wiki/Kaizen
- _pmf_ 8y ago> There must be deeper, more subtle factors that explain why Toyota's particular combination of techniques yields such superior results. Why? That's how engineering works; small improvements aggregated over time.
- nkoren 8y agoNo, that's how certain types of engineering optimisations work, but as a process is susceptible to getting stuck in local minima. This is clearly a different type of optimisation, requiring the simultaneous adoption of a number of different yet complementary techniques.
- linksnapzz 8y agoFor anybody that cares, much of this process has its origins in Taiichi Ohno's work in the '70s. His original "Toyota Production System" book of 1978, which is still in print, is short, accessible, and enormously enlightening. Likewise, a comparative study of why the Toyota system works in comparison with other manufacturing approaches is the 2nd edition of Womack's "Machine that Changed the World". Also, other books by Shingo, Imai, Deming et al. have lots of good information.
- athenot 8y agoI know that car analogies for software is an over-done metaphor but while reading this article I'm thinking of heavy processes for software deployment that are hard to change and in my mind I'm screaming "this is what agile looks like!" 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.
- sodosopa 8y ago> this is what Agile looks like FYI Kanban came out of the process on Toyota assembly lines.
- redwall_hp 8y agoQR codes, too.
- pwaivers 8y ago> "After pulling a few strings to get into the Takaoka plant, you will see the Gordian knot become untied." 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.