There are three factors shaping the future of manufacturing technology, based on the news and notes I gathered over nearly a week at IMTS in Chicago: the increasing confluence of product design with process design, and further with process control; the growing sophistication of automation devices (i.e., robots and similar systems) for responsive, interactive, and collaborative manufacturing; and real-time integration of data across multiple platforms to streamline information for real-time analysis, which has implications for productivity and product quality.
As amazing as all this is, to me it is almost numbing. The information is speeding up. The systems are communicating. The devices are adjusting. Does anyone even blink at these trends? Among the individuals that I interview and trust on these topics there is a palpable sense these developments are beyond the ability of standard human explanation, which I interpret to mean that we are giving some portion of our reasoning skill over to these systems.
At the same time, we settle upon expressions to describe this expanse of information we do not fully understand — the current label is “Big Data”, but there are companion terms like “the cloud” and “disruptive” that help convey different aspects or functions of these concepts — and this allows us to get back to the tasks or objectives that we can apprehend clearly, and control.
Of course, the acceleration of data is not simply a manufacturing phenomenon, and within the frame of manufacturing I think it’s an overwhelmingly positive development. It has been, and will continue to be, the foundation for significant energy and cost savings in manufacturing, which has add-on benefits for resource conservation, and creates opportunities for economic growth by freeing up capital for new or expanded ventures.
It’s not an obvious boon to creativity, however, meaning the effects of Big Data mainly contribute to higher profit margins for established enterprises, which to me is a reminder that human nature tends to favor the known over the unknown: we learn something new, and we try to apply it to solve the problems we have sooner than to start some new experience, which might lead to failure. And so the great potential of Big Data remains mostly unknown, because the full implications of how it works are too esoteric.
This will not remain the case forever, and in fact there is a great deal of progress being made in material science as consequence of Big Data. Foundries and diecasters have the possibility of producing new alloys and composites, and better processes are being researched for producing established materials, or for forming products from those materials.
Even so, the challenge of Big Data remains not how to apply it, nor even how to understand it. The task for us is how to establish control over it – which we must do in order to avoid being subjected to its power. The implications of this for manufacturing should be clear, but for individuals, for humanity, the stakes are greater.
There is a spreading sense of doom in our world, and a seemingly algorithmic decline in the ability or even interest by responsible authorities, in government mainly, but also in industry and commerce, to perform the duties attached to their positions. Recently I wrote that we are on the verge of losing the meaning of the word “crisis”, and that was before we had airline-borne contagions in our midst and knife-wielding crazies dashing through the front door of the White House. If you have a sense that nobody is in charge of anything any longer, you’re not alone, and it’s not without reason. But our sense of control starts with the things nearest to us. We cannot expect others to be responsible on grave matters if we concede our capability on the simpler ones.