Rapid Iteration for an
Internet of Things
Jeff McAlvay, Tempo Automation
What is the Internet of Things?
As with any new field, there are many names,
and concepts are still being formed
• Interne...
A framework for understanding:
John Boyd’s OODA Loop
The one who cycles fastest succeeds
Observe
Orient Decide
Act
Automating the OODA Loop
• Boyd came up with the OODA loop to describe
effective human thought and action
• The internet h...
Internet begins automating OODA
Enter
Orient Decide
Read
Observe Act
Machine learning
Human senses
Internet of Things
completes OODA automation
Orient Decide
Observe Act
Machine learning
What is the internet of things?
• Connection of sensors and actuators to the
internet
– Observe (sensors) and Act (actuato...
Example: grocery store inventory
management
Grocery inventory management:
Internet
Enter
Orient Decide
Read
Observe Act
Algorithm decides when
to purchase more
Employ...
Grocery inventory management:
Internet of Things
Orient Decide
Observe Act
RFID captures
current inventory
Inventory is st...
What do you get from it?
• Observation and action benefit from the ability to
happen
– Sensing cost is lower -> can collec...
Applications: Business
• Inventory/Logistics
– Walmart’s RFID on inventory
– Parlevel systems vending machines
– UPS’s GPS...
Applications: Consumer
• Quantified self / predictive medicine
– Fit bit
– Nike Fuel band
• Smart Home
– Lockitron
– Nest
...
Big opportunity
• Lots of devices: 31B devices connected by
2020 (Intel)
• Lots of money (Cisco):
– $613B in 2013
– $14.4T...
What’s required for the Internet of
Things?
• Necessary components that exist/are on the way
– Software and hardware colla...
Collaboration tools = open source
modules + version control
Software Hardware
Data science = large scale, computer-
aided inference
• Facebook/google – what ad does this person
want to see?
• Pandora ...
Cheap sensors and actuators
• Developed for military, industrial plants
• 3D Robotics’ Chris Anderson: Phones have
made th...
Standardized interface between
sensors/actuators and internet
Internet Microcontroller
Sensors and
actuators
Wireless:
Blu...
Attempts at standardization
• Raspberry Pi
• Beagle Bone Black
• Pinoccio
• Sparkcore
Software iteration: fast and free
• Continuous deployment (e.g., IMVU deployed
code 50 times per day); made possible by:
–...
Software scalability: effortless
• For small, medium, large traffic sites, trivial to
add capacity on Amazon Web Services ...
“With hardware, it’s a weeks-to-months
iteration cycle, instead of the hours-to-days
cycles that we enjoy in Web Developme...
Why is hardware iteration glacial?
Hardware iteration: expensive
It’s as if pressing compile cost $1400.
Boards 3 days 1 week 2 weeks 1 month
1 $1872.53 $138...
Hardware scaling: tedious
“Many hardware startups stumble when they
try to go from prototype to large-scale
manufacturing....
What about Arduino?
Arduino benefits
• Great UI (simple programming language, one
click firmware flashing; Banzi: “it’s users not
megahertz”)
...
Why not Arduino
• Not digital fabrication
– Changes in CAD still faster than changing wires
– Can’t send picture of your b...
What about hand
surface mount assembly?
• Surface mount components are small and
getting smaller. E.g., 0402 (roughly 0.04...
How can we get rapid, free iteration &
effortless scalability with hardware?
• Where is hardware’s single line deploy scri...
A model: desktop printing
It used to be slow, expensive,
and not scalable…not unlike
electronics manufacturing today
• Dozens of hours to typeset ea...
Now…
Document printing:
hardware interaction
Document printing:
software interaction
Print
How many?
Done!
“In 1987, my father bought a Macintosh SE and
a LaserWriter IISC. With the help of the page
layout program Aldus Pagemaker...
What if electronics manufacturing
were like document printing?
Introducing
Electronics manufacturing:
hardware interaction
Electronics manufacturing:
software interaction
Make
How many?
Done!
How does it work?
PCB Fabrication Solder paste application
Pick and place Reflow Testing
Facebook Open Compute Hardware
Hackathon: some steps automated,
some steps manual. When we’re
done, all steps will be auto...
Example project: Centaur II
Plugs into a car’s diagnostic port (OBD II) and
makes information about a car (e.g., braking,
...
PCB Fabrication
Solder paste application
Drilling
Pick and Place
https://www.facebook.com/groups/opencompu
te/permalink/568193126566004/
Reflow
Ready to go!
How can we get rapid, free iteration
and effortless scalability for hardware?
• Where is hardware’s single line deploy scr...
Follow us on:
tempoautomation.com
twitter.com/TempoAutomation
facebook.com/tempo.automation
http://bit.ly/172IWvs
Bay Area...
References and Resources
• John Boyd http://www.amazon.com/Boyd-Fighter-Pilot-Who-
Changed/dp/0316796883/
• GE http://www....
Rapid iteration for an Internet of Things
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Rapid iteration for an Internet of Things

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“Rapid Iteration for an Internet of Things – Tempo Automation”
Presented Wednesday, July 10, 2013

As rapidly as the fastest growing platform shifted from desktop to mobile, mobile itself now finds the attention shifting to a highly-diverse plethora of devices that are carried, worn, and used in brand new ways. New devices and ecosystems are emerging in entirely new form factors. Because their impact is often based on scale of use, device prototypers are now in need of ways to rapidly produce prototypes at scale. In short, this means rapidly iterating the Internet of Things.

Many fields already benefit from high speed iteration that scales – Lean Startup for business, Agile for software, and 3D printing for mechanical design. Tempo Automation has now developed a robot that brings this capability to electronics.

The current options for making low volumes of circuit boards are unattractive, to put it mildly. Either wait weeks to get a board back from a board house, or strain your fine motor skills trying to build multiple boards yourself. Tempo Automation aims to fix this problem with “Electronics Factory”, a reliable, easy to use, desktop robot. Think “MakerBot”, but optimized for electronics. The objective is to provide a robot that etch traces, applies solder paste, places components, reflows, and even tests. Tempo Automation releases each of these capabilities as they become available.

Our presenters, Co-founder and CEO Jeff McAlvay and Co-founder and CTO Markus Rokitta, will demo the latest production unit, and describe how rapid iteration will transform not only the startup landscape, but advance the impact of the emerging realm of things that generate and report connected data.

Jeff McAlvay, Co-founder and CEO, Tempo Automation (http://tempoautomation.com/). Previously, Jeff worked in industrial supply company McMaster-Carr’s leadership development program. There, his roles included warehouse operations design, sales, and product management. He currently runs the Bay Area Factory Tours Meetup group, and coordinates office hours that connect hardware startups with industry experts.

Markus Rokitta, PhD; Co-founder and CTO, Tempo Automation.
Markus received his PhD in Engineering from the University of Queensland in Australia. Since then, he has designed and manufactured a small form-factor MRI machine and has managed medical device programs at companies including Carl Zeiss and BIT Analytic Instruments, in countries including the US, Germany, and China.

Location:
Qualcomm Inc.
3165 Kifer Road Santa Clara,

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Rapid iteration for an Internet of Things

  1. 1. Rapid Iteration for an Internet of Things Jeff McAlvay, Tempo Automation
  2. 2. What is the Internet of Things? As with any new field, there are many names, and concepts are still being formed • Internet of things (Kevin Ashton at MIT) • Internet of everything (Cisco) • Industrial internet (GE) • Smarter planet (IBM)
  3. 3. A framework for understanding: John Boyd’s OODA Loop The one who cycles fastest succeeds Observe Orient Decide Act
  4. 4. Automating the OODA Loop • Boyd came up with the OODA loop to describe effective human thought and action • The internet has begun to automate it • The internet of things will finish automating it
  5. 5. Internet begins automating OODA Enter Orient Decide Read Observe Act Machine learning Human senses
  6. 6. Internet of Things completes OODA automation Orient Decide Observe Act Machine learning
  7. 7. What is the internet of things? • Connection of sensors and actuators to the internet – Observe (sensors) and Act (actuators) are happening in devices – Orient (databases) and Decide (machine learning) are happening in the cloud
  8. 8. Example: grocery store inventory management
  9. 9. Grocery inventory management: Internet Enter Orient Decide Read Observe Act Algorithm decides when to purchase more Employee counts inventory Employee Enters count into handheld Inventory is stored in database Purchasing agent sees inventory on screen Purchasing agent places order
  10. 10. Grocery inventory management: Internet of Things Orient Decide Observe Act RFID captures current inventory Inventory is stored in database Algorithm decides when to purchase more Algorithm automatically places order
  11. 11. What do you get from it? • Observation and action benefit from the ability to happen – Sensing cost is lower -> can collect data at bigger scale (temporally and spatially) – Allows you to be super-responsive (feedback loop is tighter) -> accuracy/robustness increase – As sophisticated software lives in simplistic hardware (see Twilio’s Jeff Lawson: http://www.slideshare.net/twilio/2013-02-software- people-10-minute-version slides 36-45), radical changes in functionality are possible through remote updates • Orient and decide benefit from huge storage and computational power
  12. 12. Applications: Business • Inventory/Logistics – Walmart’s RFID on inventory – Parlevel systems vending machines – UPS’s GPS tracking on trucks • Maintenance (conveyor motors report health) • Energy (smart meters / power grid)
  13. 13. Applications: Consumer • Quantified self / predictive medicine – Fit bit – Nike Fuel band • Smart Home – Lockitron – Nest • Tesla with smart dash board (can send updates to it) • Wearables / Augmented Reality? – Watches (e.g., Pebble, MS, Apple, Samsung, etc.) – Glasses (e.g., Google, Epson) – UC Boulder Robotics: a shirt for folks who can’t hear well that vibrates when there’s a loud noise (e.g., fire alarm, car horn)
  14. 14. Big opportunity • Lots of devices: 31B devices connected by 2020 (Intel) • Lots of money (Cisco): – $613B in 2013 – $14.4T in 2023
  15. 15. What’s required for the Internet of Things? • Necessary components that exist/are on the way – Software and hardware collaboration tools – Data science – Cheap sensors and actuators – Standardized interface between sensors/actuators and internet – Software iteration: fast and free – Software scalability: effortless • Limiting factors – Hardware iteration: glacial and expensive – Hardware scalability: tedious
  16. 16. Collaboration tools = open source modules + version control Software Hardware
  17. 17. Data science = large scale, computer- aided inference • Facebook/google – what ad does this person want to see? • Pandora – what music does this person want to listen to? • Netflix – what move does this person want to watch? • Airbnb – what house will this person want to stay in?
  18. 18. Cheap sensors and actuators • Developed for military, industrial plants • 3D Robotics’ Chris Anderson: Phones have made them cheaper
  19. 19. Standardized interface between sensors/actuators and internet Internet Microcontroller Sensors and actuators Wireless: Bluetooth Zigbee WiFi Cell Electrical: I2C SPI GPIO
  20. 20. Attempts at standardization • Raspberry Pi • Beagle Bone Black • Pinoccio • Sparkcore
  21. 21. Software iteration: fast and free • Continuous deployment (e.g., IMVU deployed code 50 times per day); made possible by: – Single line deployment scripts – Automated testing • Marginal cost per deployment is basically zero
  22. 22. Software scalability: effortless • For small, medium, large traffic sites, trivial to add capacity on Amazon Web Services Elastic Compute Cloud • Limit: when you have huge traffic (e.g., if you’re Google, Facebook), it makes sense to host yourself. Even there, you have lot’s of tools: – Rackspace OpenStack for software – Facebook Open Compute for hardware – Hadoop for distributed data storage/analysis
  23. 23. “With hardware, it’s a weeks-to-months iteration cycle, instead of the hours-to-days cycles that we enjoy in Web Development.” –Sally Carson Pinoccio, Internet of Things Company Hardware iteration: glacial
  24. 24. Why is hardware iteration glacial?
  25. 25. Hardware iteration: expensive It’s as if pressing compile cost $1400. Boards 3 days 1 week 2 weeks 1 month 1 $1872.53 $1387.31 $911.42 $801.27 10 $3348.60 $2366.40 $2109.30 $1728.55 100 $10,006 $6570.94 $4279.00 $3686.75
  26. 26. Hardware scaling: tedious “Many hardware startups stumble when they try to go from prototype to large-scale manufacturing. There is no AWS-equivalent for hardware. To get manufacturing right, entrepreneurs often end up living in China for months and even years.” -Chris Dixon, Andreessen Horowitz
  27. 27. What about Arduino?
  28. 28. Arduino benefits • Great UI (simple programming language, one click firmware flashing; Banzi: “it’s users not megahertz”) • Can prototype quickly (just unplug and replug wires into breadboard) • Great community (open source blocks of code for using different sensors)
  29. 29. Why not Arduino • Not digital fabrication – Changes in CAD still faster than changing wires – Can’t send picture of your breadboard to manufacturer • Through hole vs. surface mount – Industry moved to surface mount in the 80s (except some big caps and connectors) -> very basic selection of components (Sparkfun and Adafruit have tried to blunt this with breakout boards, but still can access only fraction of modern components) – Big, fragile -> makes integration into IoT devices difficult (not in Pebble or Google Glass…) – Can’t scale due to high raw component costs and manufacturing costs (through hole is handle assembled vs. machine assembled) -> will have to convert from through hole to surface mount when scaling (time consuming!—prototype should match production when possible)
  30. 30. What about hand surface mount assembly? • Surface mount components are small and getting smaller. E.g., 0402 (roughly 0.04” x 0.02” = 10 hairs by 5 hairs) • Requires fine motor control (can’t do after coffee) • Should engineers be designing boards or training for a sweat shop? • Not scalable
  31. 31. How can we get rapid, free iteration & effortless scalability with hardware? • Where is hardware’s single line deploy script? • Where is hardware’s AWS EC2?
  32. 32. A model: desktop printing
  33. 33. It used to be slow, expensive, and not scalable…not unlike electronics manufacturing today • Dozens of hours to typeset each page • Required $100k+ photo typesetters • Example of the process: http://commfaculty.fullerton.edu/woverbeck/ dtr5.htm
  34. 34. Now…
  35. 35. Document printing: hardware interaction
  36. 36. Document printing: software interaction
  37. 37. Print
  38. 38. How many?
  39. 39. Done!
  40. 40. “In 1987, my father bought a Macintosh SE and a LaserWriter IISC. With the help of the page layout program Aldus Pagemaker, he designed company letterhead, business cards, and product spec sheets for his small company (five employees total). With the Mac/LaserWriter combo, a small business like his could afford to design and produce professional quality literature on par with that of a major corporation.” – Benj Edwards
  41. 41. What if electronics manufacturing were like document printing?
  42. 42. Introducing
  43. 43. Electronics manufacturing: hardware interaction
  44. 44. Electronics manufacturing: software interaction
  45. 45. Make
  46. 46. How many?
  47. 47. Done!
  48. 48. How does it work?
  49. 49. PCB Fabrication Solder paste application Pick and place Reflow Testing
  50. 50. Facebook Open Compute Hardware Hackathon: some steps automated, some steps manual. When we’re done, all steps will be automated.
  51. 51. Example project: Centaur II Plugs into a car’s diagnostic port (OBD II) and makes information about a car (e.g., braking, lights, locks) accessible on the web. Applications include collision detection.
  52. 52. PCB Fabrication
  53. 53. Solder paste application
  54. 54. Drilling
  55. 55. Pick and Place https://www.facebook.com/groups/opencompu te/permalink/568193126566004/
  56. 56. Reflow
  57. 57. Ready to go!
  58. 58. How can we get rapid, free iteration and effortless scalability for hardware? • Where is hardware’s single line deploy script? • Where is the hardware’s AWS EC2?
  59. 59. Follow us on: tempoautomation.com twitter.com/TempoAutomation facebook.com/tempo.automation http://bit.ly/172IWvs Bay Area Factory Tours www.meetup.com/Bay-Area-Factory-Tours Hardware Office Hours http://bit.ly/15chw4W
  60. 60. References and Resources • John Boyd http://www.amazon.com/Boyd-Fighter-Pilot-Who- Changed/dp/0316796883/ • GE http://www.gereports.com/meeting-of-minds-and-machines/ • Cisco http://gigaom.com/2013/06/28/ciscos-internet-of-things-vision-is- more-about-services-than-gear/ • Intel http://newsroom.intel.com/docs/DOC-2297 • http://postscapes.com/ • IMVU http://www.startuplessonslearned.com/2009/06/why-continuous- deployment.html • Advanced PCB required files http://www.4pcb.com/pcb-file-generation/ • Screaming circuits required files http://www.screamingcircuits.com/Home/HowItWorks#whatweneed • Contract manufacturing costs from Screaming Circuits / Sunstone • Apple LaserWriter http://www.macworld.com/article/1150845/laserwriter.html
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