TRIZ is a much less fashionable approach to innovation than, say, design thinking, but it does have a pleasing Russian moniker: теория решения изобретательских задач, or theory of inventive problem solving to English speakers.
TRIZ was developed by Genrich Altshuller, who analysed enormous numbers of patents, looking for repeating patterns in how engineers solved problems. From these, Altshuller developed several tools to help engineers solve problems more efficiently.
These include a ‘contradiction matrix’ and a set of ‘inventive principles’ which work together to prompt the brain into finding efficient ways to solve problems.
For example, something that must be both strong and lightweight is a contradiction: making things stronger often involves adding material. Entering these requirements into the contradiction matrix points to relevant principles, such as composite materials, or disposable parts.
Also from his study of patents, Altshuller developed eight trends that illustrate how many technologies evolve over time. One trend shows that while inventions often start as an immobile solid, the next generation is flexible, and the one after that is often a liquid or gas form – eventually the same problem may solved with a type of field.
To take a simple example (from Karen Gadd’s TRIZ for Engineers), blackboard pointers were originally rigid sticks, then developed joints to become hinged or telescopic devices, before (I think they skipped the liquid or gas phase) finally becoming electrical field devices in the shape of laser pointers.
Immobile System → Jointed → Many Joints → Fully Elastic → Liquid / Gas → Field
Does this trend help us predict the future of robotics?
In the late 30s, the Westinghouse Electric Corporation built an ungainly robot called Elektro, which was certainly pretty immobile (though it could smoke cigarettes). In ’54, a robot called the Unimate, which had the first jointed arm, was developed for General Motors. Modern industrial robots are now multi-jointed, and some androids appear completely flexible.
Perhaps with modular robots, such as MIT’s M-Blocks – which assemble themselves like jumping beans into the most appropriate shape for a specific task – we’re seeing the beginning of a more mature phase of robotics.
As modular robots develop and miniaturise, might we see nanoscale (a nanometre is 1,000,000mm) M-Blocks, so small they effectively form a robotic ‘field’ that can assemble itself into the most appropriate shape for the task at hand?