The world took note when IBM supercomputer Deep Blue beat Gary Kasparov at chess – 20 years ago. Now Google’s AlphaGo AI software has beaten world champ Lee Sedol at Go. This is the ancient Chinese board game that’s considered far more complex than chess.
Computers don’t make mistakes. Robots don’t take breaks, and don’t need vacation. What company wouldn’t invest in robotics? But they are finally getting smarter, as well. A new lab robot can not only perform a variety of tests on 20 different samples at a time, it can collate, analyze, and summarize the results, then generate printed and digital reports on all 20 samples. Human lab workers only need to load and unload the machine.
The future factory
Most manufacturing is a very involved process of design and fabrication. It’s becoming more complicated as our devices become more complicated. That requires more automation at every point of manufacture. Creating even one product, let alone several, can be a dynamic process requiring a number of different materials, variable specifications, conveyor systems, and then the whole process of order fulfillment – packing, shipping, and so on.
Even that is getting more automated with bar code generators and scanners. A cubing system is even more advanced. These intelligent systems benefit shipping processes. Cubing can ID objects and calculate weight and dimensions even on moving objects.
We have all been expecting robots to take our jobs. Is it starting to happen?
The answer is both yes and no; or, more accurately: not yet.
Process Integration
One thing modern technologies have increased is the demand for customizable products. This requires a whole new approach to the manufacturing process that needs an efficient workflow between design, engineering, and fabrication. These can no longer be thought of in terms of silos, or separate departments with specific steps to take.
It’s easy to imagine an assembly line of robots putting together furniture according to pre-programmed steps, but it’s much harder to imagine the same methods being used to continuously design and produce new wedding cakes. You need humans.
The value chain
As manufacturing becomes more complex, so do market value chains. Innovation used to come from visionary R&D labs. Today there is a more open approach in the interconnected world of mobile devices and the internet. Designs and strategies are more often driven by a cohesion of data analytics, consumer habits, and collaboration between different companies, specialized consultants and entrepreneurs, and even lone inventors.
And it all depends on some inherently human traits that no robot has yet reproduced – creativity, artistry, and empathy. Robots may be able to combine different design elements into new ideas, and even produce a prototype. But a marketable product – something with consumer value – requires creating something that people will really want and be comfortable using. That clearly takes a human perspective.
Iterative improvement
Mechanical automation is a solution for providing a limited set of repeated tasks. It ensures levels of quality and productivity, but in a limited scope. “Robotic” suggests mindless repetition. But robots can’t introduce better methods or techniques.
Iterative improvement requires that every process be reviewed at intervals or even continuously to see if prior results, good or bad, can’t suggest methods for improving any or all stages of production. Robots don’t take into account customer feedback, supply chain issues, industry developments, or profit margins. Humans naturally adapt and improve. Robots don’t.
Business is human-centric
The 4th Industrial Revolution may be all about a synthesis of science, engineering, and computing to come up with more capable tools. That’s all a robot is. They can do many things well, including strategy. But there is, and likely never will be, a robot that can do it all. And even some future super-robot will not replace humans, for the simple reason that it requires human minds to connect with human customers.