Truly Advanced Manufacturing: How Artificial Intelligence, Virtual Reality and 3D Printing Might Combine to Change the Way We Make…Things
A team of Australian scientists recently announced plans to use 3D printing and virtual reality to bring a dinosaur back to life. No, it won’t actually be alive, but it will feel like it is. The team will 3D print a tactile version of the creature, and a virtual reality experience will make the model feel real.
Also recently, a startup called Virtualitics launched a new tool that combines virtual reality with artificial intelligence to help people visualize and discover insights in big and complex data. According to the company’s CEO, Michael Amori, their solution helps users, “…visualize as many as 10 dimensions in VR/AR all via a Shared Virtual Office, which allows even untrained users to spot patterns in data that can give companies a competitive edge.”
In other news, a UK startup recently strapped 3D printing nozzles to robotic arms and programmed them to print very large structures. But to ensure accuracy, the process was painstakingly slow. To speed things up the team employed artificial intelligence to analyze the objects as they were being printed. This allowed the system to detect defects and compensate for them in subsequent layers, reducing the build time by half. It also used less material, reducing the weight of the structure.
Arguably, artificial intelligence, virtual reality and 3D printing are among the hottest areas in technology today. They may occupy different positions on Gartner’s famous “hype cycle” curve but all three are getting significant investment and media coverage.
There’s plenty of reason to be bullish. Pundits are forecasting significant growth in all three areas. Artificial intelligence is expected to be a $16 billion industry by 2022 and the virtual and augmented reality market could reach a staggering $162 billion by then. The 3D printing market is no slouch either. Analysts predict it could be worth $30 billion.
That’s impressive enough when considered independently, but what about the economic impact on other markets? Each of the three could become a “platform enabler” – assisting other business models, providing them with capabilities that they don’t possess today.
For example, contact and call centers are an $8+ billion market. The industry employs over 3 million workers in the USA, the Philippines, and India alone. Labor makes up over 70% of the cost of the average call center.
Bots, powered by artificial intelligence, seem poised to eliminate a huge portion of that cost. While it would eliminate millions of jobs, the disruption would be a boon for technology providers, giving them a much larger share of the pie. No wonder investors are excited.
But what if all three converged and became platform enablers in the same market at the same time?
Consider the consumer products industry for a moment. It’s a $2 trillion market. If artificial intelligence were used to conceive and improve products, virtual reality was used to foster collaboration and improve the user experience, and 3D printing was used to manufacture the resulting products, what kind of impact could it have?
Product Lifecycle Management
It’s common to hear people say things like, “that product is so simple. Why didn’t I think of that?” While it may seem easy, the pathway from idea to execution is typically far more involved. In fact, most professionals follow a formal product development process to get from concept to sellable product.
Each step requires significant capital and labor. Could artificial intelligence, virtual reality and 3D printing be combined to better optimize product performance and improve speed to market, while reducing the overall costs of research and development?
Scoping The Problem
Remember Deep Thought from Douglas Adams’ Hitchhiker’s Guide to the Galaxy? After 7.5 million years of working on the answer to the “ultimate question of life, the universe, and everything,” it came up with “42.” Unfortunately no one knew what the question was, so they had to build another computer (Earth) to calculate the ultimate question.
One of the big advantages of artificial intelligence lies in its ability to sift through and find insights in large data sets. In fact, the more data the better. But to achieve the desired outcome, the problem must be properly defined.
It’s estimated that only one out of every 1,500 ideas actually becomes a product. Less than 2% of those actually become successful. Opportunity cost plays a huge role in filtering which products eventually make it to market. Risk is another big factor. If you’ve identified a problem that doesn’t actually exist, you’ll probably fail.
While AI isn’t mature enough (yet) to identify problems on its own, it can play a significant role in research. Thanks to the Internet, there is an unimaginable amount of data on hand.
Imagine what you might learn, for instance, from the millions of searches conducted on Amazon each month. Even though the site contains over half a billion products, there are many times when customers can’t find what they’re looking for. Sometimes it’s because the product just doesn’t exist.
Another way to identify the problem is to talk with would-be users. It can be challenging though as consumers often struggle to articulate their needs. Questions must be asked that expose the situation, the problems, and the implications. Only then will something that’s intrinsic become extrinsic.
AI-driven “bots” have already become adept at asking complex, multi-level questions. Is it unfathomable that they could also be used to assist with product research?
To some extent, virtual reality and 3D printing are already being employed to compress this stage of the lifecycle. CAD designs can be imported into virtual reality software, allowing users to experience digital prototypes. Once rendered they can also be 3D printed for further optimization.
But part of the challenge involves building better interfaces for VR. While platforms like Oculus Rift, HTC Vive and Playstation VR allow us to see products in a virtual setting, perception from other senses is further behind.
Better peripherals are needed for touch, taste, sound, and smell. As these come to market, they could go a long way towards improving the virtual experience.
This is one of the big areas where technology can “eat its own dog food.” Using virtual reality to develop peripherals for VR could expose opportunities for the development of other kinds of products.
Because it’s digital, the process would automatically generate data which could be consumed by AI, further improving the quality of products and the speed at which they go to market.
To some degree, man is limited by his experience. If you assume the end product must be manufactured in a certain way, you design around those parameters.
3D printing removes many of the barriers. It allows designers to utilize new structures and geometry, allows them to manufacture products in smaller batches, and even allows for customization and personalization.
But why think that way if, in the end, you’re still going to mass produce?
For 3D printing to truly challenge traditional manufacturing, the quality must get better, the machines must get faster, they must be more reliable, and output must become less expensive.
Is there reason to believe that at some point, whether it’s asked or not, that artificial intelligence might start to attack this big, looming opportunity?
Well, to the disruptors go the spoils.
Production and Distribution
Perhaps the biggest opportunity lies in the supply chain. Mass production, packaging, shipping and redundant inventory all add significant cost to the products we consume. As we become more immersed in virtual reality, the need for some of those physical products could disappear. Books, movies and music have all gone digital. Is it that inconceivable that other physical products could as well?
Those that remain could benefit from a smarter supply chain. Instead of being manufactured in one location and shipped around the globe, products could be made when and where they’re needed.
One might argue that artificial intelligence really isn’t needed to build out a distributed network of digital manufacturing centers. Governments and academic institutions could certainly do it now. Private enterprises are already working to make it happen.
Consider UPS for a moment. They already have 3D printers in nearly 100 of their UPS Stores. They’ve also partnered with a startup to develop a production center inside their hub in Louisville, Kentucky.
But perhaps their biggest move was a collaboration with SAP to manage it all. Now they’re opening it up to other companies with the goal of “establishing and promoting 3D printing and on-demand manufacturing as an integral part of the digital manufacturing landscape.”
Could AI learn from the vast amount of data contained in the world’s largest enterprise resource planning platform? You bet. And, at what point does it go from being a user to an administrator?
Cognitive With a Big C
As far as cognitive abilities go, machine learning is still in early childhood. Some believe that for AI to truly reach its potential, it must graduate to what IBM calls, “Cognitive with a Big C.”
At that point, artificial intelligence can go beyond research and insight. It starts making decisions. In the context of cyber-security this could allow for self-healing systems where AI not only detects a threat, but also knows how to repair itself.
Is there reason to believe that artificial intelligence could go beyond software and begin solving its own hardware problems? If AI recognizes that a digital manufacturing technology offers certain benefits, but the hardware isn’t available, could it build it? Would it have the tools?
Consider HP’s new Multi-Jet Fusion 3D printers. Over 60 of the plastic parts in the machines are themselves 3D printed. HP didn’t do it for show. They did it because 3D printing was the most economical way to produce those parts in smaller batches. Once 3D printing becomes more available and connected, AI could use it to make whatever is needed, including more advanced 3D printers.
Of course all of this conjures up some scary scenarios. As AI migrates towards decision making, will it have our best interests in mind? Can we control it?
A recent experiment sheds some light. Google’s Deepmind AI group paired two different artificial intelligence programs against each other in two different survival scenarios. In one, where cooperation was beneficial, they worked together. In another, where they were competing for resources, they became hostile.
What’s Our Role?
With all three technologies, humans will spend less time working and more time managing the activity. But we’re not very efficient watchdogs.
Consider Ford’s recent work on fully autonomous driving. Self-driving cars are apparently so soothing that engineers keep falling asleep. Perhaps our inability to manage AI is part of what is so troubling to luminaries like Bill Gates, Elon Musk and Stephen Hawking, causing them to issue public warnings about the technology.
Truly Advanced Manufacturing
Innovation around artificial intelligence, virtual reality and 3D printing will continue to expand. They’re already being combined in new and interesting ways. At some point people will use the technologies to attack big problems and disrupt huge markets.
Consumer products are one of the largest. Is it that unthinkable that one day, the result will be a truly advanced manufacturing network? A machine assisted (or managed) system that drives the innovation, improvement, production and distribution of…things?
At that point, the real question becomes, will the technology serve us or will we serve it? Maybe soon, that will be the actual question of life, the universe, and everything. Time will tell. Discuss in the Advanced Manufacturing forum at 3DPB.com.
John Hauer is the Founder and CEO of Get3DSmart, a consulting practice which helps large companies understand and capitalize on opportunities with 3D printing. Prior to that, John co-Founded and served as the CEO of 3DLT. The company worked with retailers and their suppliers, helping them sell 3D printable products, online and in-store.
John’s original content has been featured on TechCrunch, QZ.com, Techfaster.com, 3DPrint.com and Inside3DP.com, among others. Follow him on Twitter at @Get3DJohn
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