I see this as more of a commentary on the lack of people able to do the automation, and the ways automation is done currently.

On a production line with 1000 different operations you'd have a thousand low skill people using their eyes, brains, and fingers to develop the assembly process.

You could never get 1000 roboticists working on getting an assembly line going. I don't know how you could even find that many, but if you did manage to do it, you'd probably end up with an assembly line that would spit out 60 iphones a second.

Instead what you might have is a setup where no individual process is getting the attention it truly needs. Each step is probably just barely working because the pressure to get 1000 automation steps working means that as soon as it works even poorly you've got to move on to the next step.

Disappointing lack of technical depth in the report.

> Typical problems that arose include how Apple's use of glue required precision the machinery couldn't reliably match

Aren't robots commonly used to place adhesives (even replacing welds in metal fab) exactly because they can apply it far more precisely than humans? Picturing an iPad, I'd guess the issue would have been flexibility in placing glue in 3D space, around odd angles and tight corners, and not precision.

I find this to be relevant to the self driving problem - Apple/Foxconn could not detect when things had gone wrong on the automation line and stop it, let alone have the line's robots fix it. However, we expect a self driving car to detect when it encounters a novel situation on the road? And it surely will.

If they could not detect it in the confines of a highly controlled factory assembly line (not manufacturing but assembly) then how can a car detect novelty on a cityscape or even a highway?

Common mistake, trying to replace humans with machines. Typical of penny-pinching bean counters and talentless middle-management chair warmers. But I don’t think Apple has ever understood automation (as any 20-year AppleScript veteran can tell you), so I’m not surprised Cook’s crew has failed to capitalize.

Complex automation works best when placed in the hands of skilled humans, as an amplifier of human ability. Let them use the machines to accelerate all their mundane repetitive crap, while retaining the human ability to make reasoned decisions and handle corner cases and errors intelligently.

But perhaps a more logical place to start is by automating away the penny-pinching bean counters’ and talentless middle-management chair warmers’ jobs? Dog knows they’re reliably useless at it themselves.

Elon Musk also found out something like that I guess https://techcrunch.com/2018/04/13/elon-musk-says-humans-are-...

This reminds me of that "overestimate in the short term, underestimate in the long term" quote about technology.

This article is talking about the world in 2012. The world in 2012 was radically different to the world of 2020. Humans were still the best Go players on the planet, the landscape of image recognition looked rather different and the hardware was in a completely different place.

The skills to automate this stuff are developing right now. We're basically looking at a reset of these lessons that were learned in the early 2010s. The next wave has a much stronger foundation. Computers are now, potentially, better at pattern recognition. For all we know the insurmountable is currently being surmounted.

Can't fight the feeling this is just an Apple-blogger's justification for how its fine that there is a level of suffering going into the manufacture of their phone, as we know from the factories having to install suicide nets.

Bottom line is, humans are cheaper than robots in the parts of the world the make your iPhone. If you ever visit the factories where this sort of thing is made its all shockingly manual, because that's what is cheapest.

Based on what the article said, I have to ask. Is there lots of glue applied inside Apple products? Is that primarily in small devices for waterproofing? Not knowing much about manufacturing, I’d think that most people would expect parts to be secured together via solid metal screws or something other secure.

> How Apple learned automation can't match human skill

Super generic title. Has it replaced all its software with humans?

The article essentially says that if Apple can’t build reliable robots to build mobile computers more efficiently that people, then it can’t really be done. This is, of course, horsepuckey, but what do you expect from an Apple blog?

It seems to me that Apple Silicon, will eventually start with “Device on Chip” type solutions (i.e. there will no longer be a motherboard). Including vertically integrating OLED construction into the wafer as well.

Similarly, vertically integrating battery construction and housing into the device body, like TSLAs battery day announcement.

Between these integrations, I’m not sure there will be much remaining to automate.

> It didn't work. Typical problems that arose include how Apple's use of glue required precision the machinery couldn't reliably match. And the tiny screws needed required the automation to correctly pick and position them but that same automation couldn't detect problems the way a human hand could.

Seriously? Did anybody even read this garbage before publishing?

Those are two pretty different domains. In manufacturing automation, some of the things that are hard include gripping objects, handling fluids and pastes, and adapting to design changes.

For self driving cars, the controls are pretty similar, even across car models. Gas, brakes, and steering. It doesn't happen that a supplier ran out of engines and a decision is made to replace the car's propulsion by jet engines, thrust vectoring, or a hovercraft. It doesn't matter too much for self driving cars to be within 0.1 inches of the center of the road, but if your electrical components are offset by 0.1 inches or there's 0.1 fluid ounces too much glue because this batch of glue is more liquid than the previous one, the electronics probably won't work in the end.

And in that same vein, why haven't we focused on the infinitely easier realm of rail automation and safety?

We jumped right to the hardest problem set. Probably because it's the most sensational and easiest to get broad financial support by selling people the promise of less rush hour drain.

I wonder if there are companies focusing on solving the opposite problem. In other words, AI to focus on things humans don't perceive (leaving the driving to the human). For instance, figuring out the person in another car is drunk, then alerting you to avoid them. Or detecting emergency personnel needing you to get out of the way (can't tell you how often I see folks blocking or oblivious).

This goes along with my experience in new cars in that the best improvements are those that enhance my ability to drive (such as a backup camera).

the smaller electronic device is, the higher the precision you need. For such a compact device such as iPhone, the precision is not enough to automate the production yet. For self-driving/flying, there is always some lee-way. The demand of lowering error variance is low.