Manufacturing guy-at-large.

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Photos from a visit to CCAT

Added on by Spencer Wright.

A few months back I had the pleasure of visiting the Connecticut Center for Advanced Technology, which is located on the UTC/Pratt & Whitney East Hartford campus. CCAT began as a facility focused on researching laser drilling, but has moved deeper into 3D printing, and specifically directed energy deposition, in the past few years. 

In addition to a full subtractive (manual and CNC) shop, CCAT has a few cool additive tools that I was particularly interested in. The first is an Optomec 850R LENS system. The 850R is a large format directed energy deposition machine which can be used for both new parts and repairs. It's also useful for material development, as DED machines can create parts with a small amount of powder (while powder bed fusion machines generally require a large amount of powder).

(Click on the photos for larger versions + descriptions)

The other thing I was excited to see was their Kuka HA30 robot, which has a coaxial laser cladding head attached to it. This robot can be used for either etching/engraving or cladding, meaning that it can either subtract or add material to a part. Especially when combined with the two-axis rotary table shown below, this thing can create some really complex parts.

It was really cool seeing these specialized technologies being used in real life. Thanks to CCAT for having me!

Notes from Tesla's Fremont factory

Added on by Spencer Wright.

Today I had the pleasure of visiting Tesla's Fremont factory, where every single Model S is built. While they don't allow photos on the tour, I did take this pano to prove that I'm not fabricating the whole thing (but seriously though, a Google Image search does a decent job at showing you what it looks like inside):


Anyway, a couple of thoughts came to me on the tour, and I wanted to share them:

  1. First of all, the whole place is an information overload. It's noisy (not at all unbearable, but still), and the tour is a whirlwind - the whole thing took just over an hour. Moreover, the entire building is filled with visual clutter. It's all stunningly beautiful, but there's just so much going on, and it's nearly impossible to see, analyze, and understand what you're looking at, what's being done to it, and which direction it's headed in the assembly line, before the train of golf carts that you're being dragged around in speeds off to the next thing. This is not meant to be a criticism of either the tour or the factory itself, and I'm sure an automotive engineer would have an easier time soaking things in than I did, but for the majority of the tour I struggled.
  2. Lot of emphasis on sheet metal. Elon Musk loves his aluminum, and the tour itself is expressly directed towards the hydraulic presses that Tesla uses to turn rolls of aluminum sheet (from what the tour guide said, I suspect it's 16ga) into a car. 
  3. The tour also emphasized the economy that Musk/Tesla employs in building up their capabilities. The core story here is that American manufacturers (GM is called out by name, mostly due to the fact that they're the former owner of the NUMMI site, which you should learn about) don't want/need big equipment or industrial space in the US anymore, and so Tesla has been able to buy this stuff for a song. So the purchase of their largest hydraulic press (the biggest in North America); the decision to use a Lotus platform for the Roadster; Tesla's use of the factory itself; - all of these are described (not inaccurately) as shrewd financial decisions.
  4. Interestingly, the only other brand names that get shout-outs on the tour are all Robotics companies: Kuka, ABB, and Fanuc. That fact - combined with the legendary stuff (all apparently real) about many of these robots having X-Men names - and the fact that the tour also highlights the human craft that goes into a range of sexy (and not-so-sexy) features of their cars - gave me the distinct feeling that Tesla consciously makes their industrial automation efforts seem as anthropomorphic as possible.
  5. This has been reported before, and it's worth noting again: Tesla's current production is about 1,000 vehicles per week. In the NUMMI days, this same facility turned out about 6x that.
  6. One thing that I was somewhat surprised by: Towards the end of our tour, the guide paused to explicitly note Tesla's purpose: To help expedite the move from a mine-and-burn hydrocarbon economy towards a solar electric economy. To be sure, I personally find this statement to be the most compelling thing about Tesla/Musk, if not the most compelling thing about any public company in the world (if you haven't read Musk's Secret Tesla Motors Master Plan, I'd really implore you to do so). But to hear it called out on a factory tour, to an audience which was made up almost exclusively of Tesla owners (besides a Tesla employee who had brought their family, I believe I was the only person *not* picking up a Model S right after the tour), seemed downright canny. Which leads me to my real observation:

Tesla is not, first and foremost, a manufacturing company; to wax on about the factory tour would miss the point. Their focus is simple: Musk has a singular vision for how the global energy lifecycle should work, and Tesla is doing whatever's necessary to bring it to fruition. Tesla is an energy company, and they're a "we're doing this because we believe in it and goddammit nobody else will" company. Which is really admirable, and it pleased me to see them use their factory - which, in spite of its relatively low throughput, is certainly a spectacle to behold - as a way to convert people to their mindset.

Directions in automation adoption

Added on by Spencer Wright.

I've been spending a lot of time looking at industrial automation the past few days, and had an idle thought:

I've touched on this before, if only obliquely, when writing about's role in manufacturing logistics. Much attention is being paid to companies who want to simplify (or circumvent) some part of the product development value chain. Many of these are companies I admire, and think are doing really valuable things. Take Within, whose 3D design software generates structures that are driven directly from functional constraints (but can't, as far as I can tell, deal well with thin-walled structures). Or Willow Garage's PR2, the really slick research robot (that takes charmingly long - 20 minutes per bath towel - to fold laundry).

Each of these is an incredibly impressive feat, and one that follows an ambitious (and I would argue honorable) line of thinking:

If we can encode all of the information needed to complete a routine yet complex task, then we can use machines to automate the process, freeing up our minds to do other (presumably more important) things.

But consider an alternate proposal:

If we can get machines to mimic a series of behaviors that humans can plan and execute with relative ease, then we can decrease the amount of rote mechanical work that humans need to do.

This is the tact taken seriously by Baxter, the admittedly not-too-serious (but cool nonetheless) humanoid task robot built by Rethink Robotics. Baxter learns by physically training his movements, presumably by the technician who he's "collaborating" with:

Even the traditional robotics companies, like Kuka, are moving in the direction of using robots simply to execute the complex tasks that humans calculate and perform with ease. Here a Kuka robot is trained how to clean a permanent mold by a BMW employee:

Both of these robots' use cases share a key feature: There's still a human doing the "hard" planning and calculation about how the task will be completed. In each case the robot doesn't understand the physical constraints or goals per se. Baxter has some awareness of his surroundings for sure, but all he knows is that his arms hit something; he doesn't have the vision or awareness of why that happened or how to correct for it.

Similarly, the Kuka bot doesn't understand that he's cleaning a mold, or have the facilities to learn how to do better work. He's just repeating a toolpath that he knows a human told him to do. Which, in this case, is good enough - and a hell of a lot faster than waiting for a computer vision expert to give him the intelligence required to do better.

I'm not sure what the implications of this are for the companies working to automate the design and supply chain. But the philosophical difference is striking, and I must say that the more hands-on model is very compelling - and I expect it to be so for the foreseeable future.


Parenthetically: All of the industrial 3D printing market is currently driven off of this same model: An intelligent, experienced technician makes manual edits to 3D CAD data in order to get a part to print within its design constraints. Anyone who suggests that build optimization is "right around the corner" is, in my opinion, *not* to be trusted. We're in a world of basic research still, and an automated design-print-post process chain is many years away.