transcript: lamp stack of manufacturing - make:hiw

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+Intro: "Hi everyone, I'm Nick Pinkston. I was the founder of a 3D printing and injection molding startup called CloudFab that was actually just acquired, and previously I co-founded a community-workshop called HackPittsburgh. They asked me to come out today to take off where the previous speakers left off - to show a vision of what the future of manufacturing might actually look like." "So to start off, I want to talk about an industry that, even after the industrial revolution ran its course, worked at a painfully slow pace. It used 100% manual labor with just simple hand tools, but in just the past 50 years the industry went from nearly 100% manual to nearly 100% automated with engineers directly designing and maintaining the means of production. So what is this industry? Well, I'm being a little coy because it's actually the computation industry. We went from slide rules to laptops in 50 years, because computer scientists discovered certain techniques that put the engineers in the driver seat when the machines started taking care of themselves. I'm here today to show you that this isn't limited to the production of processed data like many imagine, but that nearly all these techniques can be brought into the realm of manufacturing to fully empower hardware companies from startups to multinationals. +Intro Alt "So this is the Jacquard loom, and " +Mind the Gap: "We have a gap in production today - on the one end you've got mass producers like Toyota that use very advanced automation to make one part millions of times super cheap, and on the other you've got job shops that can work on a much smaller scale but the parts are too expensive for most markets. So this is problem that I've been trying to solve for a while. There are the techno-utopians who think that 3D printers in a few years will be able to replace the mass production processes, but in reality these processes are going to be with us for a while - so we need to find ways to lower the barriers of accessing this equipment affordably. In the world of software, we've got the same problem with servers. You used to have to buy physical machines and maintain them yourself. Fast forward to today, and we've got cloud computing which allows you to scale your

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Page 1: Transcript: Lamp stack of manufacturing - Make:HIW

+Intro:

"Hi everyone, I'm Nick Pinkston. I was the founder of a 3D printing and injection molding startup called CloudFab that was actually just acquired, and previously I co-founded a community-workshop called HackPittsburgh. They asked me to come out today to take off where the previous speakers left off - to show a vision of what the future of manufacturing might actually look like."

"So to start off, I want to talk about an industry that, even after the industrial revolution ran its course, worked at a painfully slow pace. It used 100% manual labor with just simple hand tools, but in just the past 50 years the industry went from nearly 100% manual to nearly 100% automated with engineers directly designing and maintaining the means of production. So what is this industry? Well, I'm being a little coy because it's actually the computation industry. We went from slide rules to laptops in 50 years, because computer scientists discovered certain techniques that put the engineers in the driver seat when the machines started taking care of themselves. I'm here today to show you that this isn't limited to the production of processed data like many imagine, but that nearly all these techniques can be brought into the realm of manufacturing to fully empower hardware companies from startups to multinationals.

+Intro Alt

"So this is the Jacquard loom, and "

+Mind the Gap:

"We have a gap in production today - on the one end you've got mass producers like Toyota that use very advanced automation to make one part millions of times super cheap, and on the other you've got job shops that can work on a much smaller scale but the parts are too expensive for most markets.

So this is problem that I've been trying to solve for a while. There are the techno-utopians who think that 3D printers in a few years will be able to replace the mass production processes, but in reality these processes are going to be with us for a while - so we need to find ways to lower the barriers of accessing this equipment affordably.

In the world of software, we've got the same problem with servers. You used to have to buy physical machines and maintain them yourself. Fast forward to today, and we've got cloud computing which allows you to scale your

Page 2: Transcript: Lamp stack of manufacturing - Make:HIW

company within minutes. Today there's billions of dollars of servers sitting in data centers worldwide for the production of data. In the near future, there will be production centers doing exactly the same for physical production.

+Interfaces Matter:

"The problem manufacturing has right now is that our interfaces suck - you're playing telephone between the designer to the guys on the factory floor. Here's a continuum of different manufacturing interfaces:

- We've got Google on the full-manual route of search for companies.- MFG.com - puts you in touch with factories, check out reviews - but not much more.- PCH gives you access to a ton of experience and connections by using experience people and systems.- ProtoMold - can do low-volume production of simple parts using design files and minimal human interaction.- Ponoko & CloudFab - are as close as you get to full-auto production where you input CAD and get parts back. As you go down this list - you'll see that designers and engineers get closer and closer to the production process. The trend is that over time more and more of production will be fully accessible through interfaces that give the designers and engineers the most direct interface and transparency to production.

+Making a Manufacturing "Stack":

Most websites today run on some version of what's called a "LAMP Stack" - which are layers of software between the server hardware and the internet apps that we all use. The idea is the each layer takes care of a certain set of tasks - the operating system is the foundation, there's a database, the application code, and the interface with the internet.

This concept of building task-specific layers on top of hardware can work just the same for manufacturing hardware too - just like servers today. So let's get into the meat of this talk by looking at the overall vision of what this looks like.

- Abstract: Make the machines easy to interface with.- Automate: Remove the repetitive tasks.- Network: Link the machines together to build an flexible assembly line.- Compile: Automate the conversion of the design into machine commands.- Debug: Catch errors quickly.

Page 3: Transcript: Lamp stack of manufacturing - Make:HIW

+Abstract:

What I mean by abstract here is to build an interface that the computer can work with - making the physical reality in data. It's like when a person becomes a line in a database somewhere. They've been abstracted, but now you run algorithms on them. We can talk about the big data of manufacturing if we have time at the end.

In practical terms, we need to take things like a milling machine and make an interface that let's it be controlled fully by a computer. So we can change tools, load parts, send it designs, etc. - all without needing to be next to the machine.

+Automate:

The Golden Rule of Software: Don't Repeat Yourself!

In software, you write a piece of code and then turn it into a simple command to be used later. In manufacturing, we're repeating ourselves every time we make something like a mold - using very similar steps with slight modifications.

Now that we've got machines abstracted - we're able to write programs that remove this repetition so engineers and operators can focus on higher level tasks without worrying about specifics unless they want to.

+Network:

So we've got one machine that mostly runs itself - imagine if we did this for each production tool? For instance, having a mill, EDM, pick-n-place, board fab, and robotics would allow you to mostly automate the process of basic electronics products. Such a system - due to the baked-in automation - would be a rapidly reconfigurable production line.

+Compile:

So I'm sure the more experienced amongst you are asking - well maybe the machines run themselves - this largely happens already (like Toyota), but who's going to program and configure them? This was a problem for early programmers as well. They were handwriting code at a level just above binary, and it was something a mathematician needed to do to get any efficiency. What happened though is we invented whats called a Compiler - it turns a human-readable code into binary code specific to type of computer you specify.

Page 4: Transcript: Lamp stack of manufacturing - Make:HIW

In manufacturing we have what's called CAM. It's like a compiler. It takes CAD and turns it into G-Code - the language of milling machines. We need to make SuperCAM that improves over time to able to be this better than humans ever could. This is exactly how compilers were built for computers - slowly they evolved super-human strength. This allowed engineers to spend more time solving the problem and less dealing with the computer hardware.

+Debug:

The beautiful thing about software is that you type a bit of code - and you run it in seconds to get feedback on what's wrong. In hardware, this is loop measured in weeks or months. This has to get faster in order for these systems to be as accessible as we need them to be.

Now that we see that our production line is fully abstracted, automated and networked - we're actually able to do our setup in minutes to hours, and as simulation tools get better - we'll be able to simulate production as quickly as we debug software today.

+RecapSo to recap:- manufacturing methods today are actually pretty good - the bottleneck is that our process was designed for producing a million of something.- However, we now have the technology to build a system that makes production far more automated and empower our designers and engineers to push the limits of whats possible. This lowers the barriers to building product, speeds time to market, lowers setup & inventory costs.