Despite all our best intentions, accidents happen. Analysis of accidents in large complex systems such as power stations or plane crashes led to an understanding that "no one failure, human or technical, is sufficient to cause an accident. Rather, it involves the unlikely and often unforeseeable conjunction of several contributing factors arising from different levels of the system."

James Reason's Swiss Cheese Model is a memorable visual metaphor that illustrates how each safeguard may contain a latent flaw, or hole, and that an unfortunate circumstance, may result in these holes lining up to disastrous effect. It's also a nice reminder that multiple layers of defence will be more effective, but even with our best efforts, there's still potential for something to go wrong.

Excerpt from Revisiting the "Swiss Cheese" Model of Accidents (pdf), Reason, Hollnagel and Paries, 2006.

Coronavirus example from the Cleveland Clinic.

The Swiss Cheese Model

Back in 1865, a chap called William Stanley Jevons noted that while there had been a number of improvements in coal efficiency in steam engines and the like, instead of reducing consumption the effect was to increase consumption instead — Jevon's paradox.

While it’s not a surefire outcome, there are plenty of parallels like more efficient batteries leading to more overall battery use, washing machines leading to doing more washes rather than less time spent washing, or the ability to recycle some plastics leading to more overall plastic consumption.

This is sometimes known as the rebound effect.

Also see the fifth fuel: energy efficiency, and save some landfill.

Jevon’s Paradox

In my everyday life I’d have been hard pushed to put my finger on the difference between accuracy and precision but, in engineering at least, you learn that there is a clear difference between the two.

Precision describes how variable an outcome is, or how close repeated measurements or actions are to each other.

In contrast, something may be very precise but not be accurate to your intent or to the true value of a thing. That’s accuracy — how close you are to the true or intended value. If you’re hitting near your intended target then you’re accurate.

Hmm…one of those things where a sketchplanation works a whole lot better than words.

For the more spiritually inclined: Everything is aiming.

Or for the more statistically inclined: Measures of central tendency (mean, median, mode), and Common distributions (normal, skewed, pareto).

That accuracy is true to intention and precision true to itself I learned from Simon Winchester in Exactly: How precision engineers created the Modern World.

Accuracy and precision

Did you you know, a rubber duck can help you solve your problem? Or, a teddy bear, or, heck, a table, whatever. Have you ever been called over to someone’s desk to help them solve a problem, and as they explain what they were doing to you they figure out the answer themselves?

Rubberducking is the simple technique of explaining your code, or whatever you’re working on, to a rubber duck, and, in the process of explaining it, finding the answer yourself. Rubberduck debugging is a term in software development as the process of figuring out a solution to a bug or problem. Surprisingly effective, and way cheaper than hiring a contractor for the day.

Rubberducking

A way of helping decide what to do next based on Must do, Should do, Could do and Would do.

Strangely, so many of the things you’d really like to do when put in this organisation end up in the Would bucket.

MOSCOW Prioritisation.

An amazingly simple, and ridiculously useful and successful mechanism that converts linear motion to rotational motion. It’s basically what allows us to take a force produced by, say, steam, or an explosion, and make a wheel turn. Stick a few of these together and time the rotation of each correctly, carefully controlling the explosions and the exhaust and you have an internal combustion engine that powers our cars. There’s a lot amazing to me about it, but I am still impressed with how effectively it takes something moving back and forth, and makes something spin round, and vice versa.

The piston

I learned about 2.5D, or two and a half dimensions, from my engineering days. Turns out it’s really quite common to make 2.5D things because, for example, it’s easy to drill or mill down into something, and a pain to turn something on it’s side and drill from the other side. Or, as with vacuum forming it’s easy to suck plastic onto a mould, but a pain to get it off if you’ve got any overhangs as you can’t lift it straight up again. Hence the plastic sandpit in our garden is a 2.5D object rather than true 3D. Civilisation in general looks rather 2.5D from the air as we tend to build up, but don’t find overhangs that easy or practical eg the pyramids.

2.5D

The idea of resolving contradictions I was taught by Darrell Mann. This neat example from Simon Dewulf.

Sketchplanations tagged with engineering