Accelerated Learning by Experimentation
In most technologies and most industries, experiments play a central role in organizational learning as a source of knowledge and as a check before changes are implemented. There are four primary types of experiments: controlled, natural, ad-hoc, and evolutionary operation. This paper discusses factors that affect learning by experimentation and how they influence learning rates. In some cases, new ways of experimenting can create an order of magnitude improvement in the rate of learning. On the other hand, some situations are inherently hard to run experiments on, and therefore learning remains slow until basic obstacles are solved. Examples of experimentation are discussed in four domains: product development, manufacturing, consumer marketing, and medical trials.
Keywords: Learning, Experimentation
Full published version: Bohn Accelerated Learning by Experimentation. in Learning Curves: Theory, Models, and Applications edited by Mohamad Y. Jaber, CRC Press, 2011.
Preprint version, through SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1640767.
This is a rewritten version of my 1987 paper about manufacturing. Although I never published that paper, it was very influential in the 1990s, including becoming the (plagiarized) framework of a book and several articles by Stefan Thomke. This book chapter expands and extends the original concepts, including new material from Michael Lapré.
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?
Selling “light,” not light bulbs, is one way that companies providing long-lasting bulbs hope to stay in business, even after “socket saturation” sets in.
Source: Trying to Solve the L.E.D. Quandary – The New Yorker
TL;DR It will take 5+ years for standards to get sorted out in home automation. Until they are, devices from different companies will not be compatible. Anything that you buy and install now will be inconvenient (you will need multiple interfaces) and become obsolete in a few years.
Now that there are many genuinely useful and modestly priced home automation devices (and I don’t mean smart refrigerators), we are ready to enter the rising portion of “the S curve” where penetration increases. Most of the devices can be retrofit, which will make uptake much easier.
But right now, most vendors have their own protocols. Common protocols are needed at 3 layers: the user interface, such as a mobile phone/computer app (or web site), physical communication such as Bluetooth, Zigbee, or Wi-Fi, and data protocols (API’s, essentially). Most vendors appear to be moving toward a hub and spokes arrangement, where the hub handles communication to the user and outside the home, so there will also be competition for whose hub customers buy. Finally, I would add security as its own “layer,” since it is so important and currently completely neglected.
With the new A9 and A9X chips in its iPhones and iPads, Apple has mobile chips that are better than Intel’s. In fact Apple’s chip business is a very impressive technology story. I don’t have time to put together a full analysis, but I have collected some recent articles.
Many sources are suggesting that Apple’s current chip generation (A9 and A9X) is better than Intel’s in low-power (mobile) performance. I guess it’s not news that Intel is behind Qualcomm in mobile, but I still find it surprising that Apple’s own chips are apparently better than X86 for Macintosh low-end laptops!