How do semiconductor companies plan for aging? There has never been a truly efficient solution, and according to this article, problems are getting worse. For example, electronics in cars continue to get more complex (and more safety critical). But cars are used in very different ways after being sold, and in very different climates.
When a device is used constantly in a heavy load model for aging, particular stress patterns exaggerate things. An Uber-like vehicle, whether fully automated or not, has a completely different use model than the standard family car that actually stays parked in a particular state a lot of the time, even though the electronics are always somewhat alive. There’s a completely different aging model and you can’t guard-band both cases correctly.
Aging is dealt with by heuristics, which typically add a “safety margin” to designs. But it’s not accurate, and leaves money (chip area = $ per chip) on the table.
Moreover, margin typically isn’t just one thing. It’s actually a stack.“The foundry, with the models that they give us, includes a little bit of padding to cover themselves,” said ANSYS’ Geada. “And then the library vendor adds a little bit of padding and nobody talks about what that is, but everybody adds up this stack of margin along the way. “
Source: Circuit Aging Becoming A Critical Consideration
But of course, the semicon industry has been dealing with emerging challenges like this for its entire existence. Each new problem starts at a low stage of knowledge, beginning with Stage 0 (nobody knows the problem exists) and usually ending at about Stage 6.
A nice graphical illustration of what happened when NYC subway rules were changed in seemingly small ways. The time/distance buffers that used to exist between consecutive trains shrank, to the point that a small “blip” causes cascading effects in subsequent trains. TOM once more. (Thanks to Arpita Verghese.)
My friend at NYU, Prof. Melissa Schilling, (thanks, Oscar) and I have a running debate about Tesla. She emphasizes how smart and genuinely innovative Musk is. I emphasize how he seems to treat Tesla like another R&D driven company – but it is making a very different product. Melissa is quoted in this article:
Case in point: Tesla sent workers home, with no pay, for the production shutdown last week. My discussion is after the break.
During the pause, workers can choose to use vacation days or stay home without pay. This is the second such temporary shutdown in three months for a vehicle that’s already significantly behind schedule.
Source: Tesla Is Temporarily Shutting Down Model 3 Production. Again.
By now, Tesla’s manufacturing problems are completely predictable. See my explanation, after the break. At least Wall St. is starting to catch on.
Also in this article: Tesla’s gigafactory for batteries has very similar problems. That surprises me; I thought they had competent allies helping with batteries.
But one engineer who works there cautioned that the automated lines still can’t run at full capacity. “There’s no redundancy, so when one thing goes wrong, everything shuts down. And what’s really concerning are the quality issues.”
Source: Tesla employees say Gigafactory problems worse than known
Once again, Tesla demonstrates no understanding of volume manufacturing! Newspaper: “Tesla reworks 40% of its parts.” Tesla response: “But we inspect every car carefully before shipping it!”
Tesla fires back against a CNBC report that cited unnamed employees’ complaints about the electric carmaker cranking out a high number of parts that need to be repaired or replaced. Tesla say…
Source: Tesla: flawed parts report is flawed regarding cars’ quality
But as Deming and others pointed out decades ago, you cannot achieve good final quality by doing lots of inspection. There are many reasons for this, including that inspection/testing is not 100% accurate. The whole field of statistical process control, which eventually morphed into today’s “Six Sigma,” was invented as an alternative to massive inspection.
So if Tesla claims that it can make parts so poorly that 40% need rework, but still have defect-free cars, it is an admission of ignorance. This continues Tesla/Musk’s consistent pattern of not understanding that high volume manufacturing is not just “low volume manufacturing repeated many times.” (See my October post about Tesla’s attempts to ramp up Model 3 production.)
My suggestion for people with a Model 3 on order: don’t expect it to be on time, or have good build quality. Sorry.
It has always been clear that Musk does not understand high-volume manufacturing. Building rockets is very hard, but building 100,000 cars is very hard for a different reason! His predicted ramp rate was absurd. In the last 6 months, I think he has started to realize this.
Tesla has little chance of hitting its 5,000 weekly output during the fourth quarter. The chief reason: Its current production line can’t build vehicles at that rate unless it runs two 10-hour shifts seven days a week, which is
Source: Tesla | Hiccups Threaten to Slow Model 3 Launch | Industry content from WardsAuto
According to the article, Tesla has also deliberately ignored much of the accumulated wisdom about how to ramp in auto production. That might be OK for his second high-volume vehicle.
More details on Tesla’s ramp plans:
Tesla now has 2 choices, both bad:
- Go ahead and start building and shipping as fast as possible. The result will be multiple problems that require expensive hardware recalls.
- Add another 6? months to the schedule to run the as a pilot line for learning, rather than for volume. Expect zero salable output during that period. (As one of the comments said, they can give/sell those cars to employees.)
Added December 27: Tesla “still in manufacturing hell.”
Latest of many articles about Tesla manufacturing problems.
Here is a comment on that article: Musk needs to face up to having made a MAJOR mistake when he skipped some steps in the original manufacturing ramp-up.
He is probably also making another major mistake at present: adding new machines to the manufacturing process, before he has the existing machines working perfectly. This seems logical to people with no manufacturing experience, but it does not work. For one thing, it diverts his key resource, which right now is manufacturing engineers.
Elon Musk clearly has a blind spot about manufacturing. Building a giant factory for the first use of a new process does not work, and theoretically it cannot work. Even if it did work, it would be non-competitive. Once a factory is built and machines installed, subsequent new discoveries/knowledge cannot be incorporated, except at the margins.
To reach the 100-megawatt goal, sources indicate that the pilot production line in Fremont would eventually need to yield between 800 to 1,000 high-efficiency Whitney panels per day. But the team was not able to automate the process consistently enough to produce more than dozens of Whitney panels per day, according to people familiar with the matter. Most of the production resulted in “scrap,” they say. “The big problem was simply that they couldn’t scale up the technology to the point where you could run it in a factory,” a source familiar with the development explains.
Source: Can Elon Musk Get SolarCity’s Gigafactory Back On Track?