Whether manufacturing can become more precise than it is today depends primarily on advancements in other fields. While some manufacturing is accurate on the nanoscale, other types aren’t.
The main limitation of manufacturing accuracy is material constraints. In many applications, it simply isn’t possible to make manufacturing more precise without using more exotic and expensive substances or processes.
This issue is particularly prevalent in industries like aerospace and engineering. Designers would like to create vehicles and structures with finer tolerances but can’t because existing materials aren’t amenable to the required processes.
That, however, could change if laser technology advances considerably. The creation of better crystal-based systems could potentially produce beams only a few millionths of a meter wide, enabling the cutting and welding of materials with extreme precision and accuracy.
We could also see the development of systems that could increase the strength of materials on smaller scales, making it possible to produce items or higher accuracy without scuffing or damaging the material itself.
“As a company that works on precision screws, we understand the engineering challenges involved in making items of higher accuracy,” component brand Accu says. “We know that the difference between producing a basic screw or bolt and an accurate one is tremendous.”
Miniaturization is another frontier that could potentially make manufacturing more accurate than it is today. The proper techniques could potentially bring more products to the same standards as the nanotechnology already inside silicon computers.
“We think that miniaturization will play a big role in the future, helping to make manufacturing more precise than it is today,” Accu says. “However, it all depends on the industrial system’s ability to produce more accurate tools. It can be done, but it will take an enormous effort on the part of engineers and scientists to get it right over the next twenty years or so.”
The path miniaturization could take outside of the chip fabrication world is uncertain. That technique relies on etching away at wafers, which naturally lends itself to periodic improvement and higher accuracy over time. However, conventional approaches to manufacturing simply don’t allow that.
One approach is nanotechnology. If you can build one small machine that can construct another smaller machine, it might be possible to get below the scales currently offered by today’s tools.
However, researchers believe the first nanotechnology that takes this form could be more than thirty years away, even with AI-powered assistance. Companies simply don’t have the resources to make it happen.
Another approach could, again, be better lasers. These could more precisely modulate the cutting energy going into materials, helping to create cleaner breaks. Thinner lasers would enhance that further, allowing machinists to fire extremely narrow pulses of light at objects without causing the damage of regular saws to the surrounding substrate.
Computer-aided design (CAD) could also play a role in making manufacturing more precise than it is today. Computer models could enable engineers to simulate how materials might react to various processing techniques in more detail.
A full simulation would be challenging without quantum simulations. However, the industry could leverage artificial intelligence to provide partial simulations, estimating how various processing would affect the quality and integrity of the underlying material while also ensuring products met the proper specifications.
CAD, of course, is already playing a significant role in fostering better accuracy. However, it is still in its infancy and can’t affect outcomes directly.
Do We Need Higher Accuracy In Manufacturing?
While higher accuracy seems like a good thing, there is a strong case to suggest that we don’t need it – at least not as much as we might think. For example, existing methods already minimize waste and maximize material usage within a few percentage points of theoretical upper bounds.
Accu believes that higher accuracy might lead to slightly better structures and products, but the benefits could be marginal. “Our screws and other components are already being produced well inside known tolerances for materials.
That means that the microscopic imperfections are unlikely to make any meaningful differences in most applications. It’s simply not necessary to make further improvements until there are genuine engineering reasons to make them.”
This means that improvements in price, strength, durability, performance, and weight will likely come from other areas. While precision still matters, it is exhibiting diminishing returns. Each nanometer improvement in accuracy produces fewer real-world benefits.
This effect is already becoming apparent in computers. While Moore’s law had a good run for more than sixty years, it is now running out of steam and starting to plateau. Engineers need to develop new paradigms to ensure that the growth in computing continues and reaches the theoretical maximum for matter, as outlined by Ray Kurzweil in his concept of computronium.
We might not also need any higher accuracy than we have now if new materials come along. Graphene, for instance, could upend the existing economy as we know it, enhancing the strength of machines and turning robots into superhuman devices capable of walking into burning buildings or carrying entire trucks on their backs. More exotic materials (yes, they exist) could take this a step further, particularly if infused with nanotech.
Finally, AI is almost certainly going to play a role in making manufacturing more precise (or getting around precision issues) in the future. Generative systems can often develop novel solutions to design problems that human engineers simply can’t conceive.
This approach means that many engineers are betting on the house of AI, believing that it will start providing breakthroughs that circumvent the need to whittle materials down to tiny tolerances.
AI could also make direct contributions to material science or engineering to improve existing designs. Artificial intelligence systems might play around with existing concepts or borrow science from elsewhere to generate new ideas that prove to be game-changing.
As we have seen, manufacturing can become more precise than it is today. However, that precision will eventually stop at the level of the atom. It is unlikely that further refinements beyond that are even theoretically possible.
Main image by Lenny Kuhne on Unsplash