Additive manufacturing (AM) and AI are two of the most exciting fields in technology today. 3D printing has revolutionized manufacturing and design, allowing for the creation of complex objects with ease. Meanwhile, AI tools such as ChatGPT, MidJourney, Stable Diffusion, and Resemble have shown their potential to transform the media landscape. With simple natural language text input, these tools can generate art, articles, and stories in a matter of seconds.

The potential for innovation, however, is limitless when 3D printing and AI converge. By leveraging AI, AM designers can optimize their creations to be stronger and more efficient. AI can even make the medium more accessible to everyone by reducing the high-skill ceiling of slicer tuning down to simple check boxes. Together, 3D printing and AI can drive the next generation of manufacturing.

To delve deeper into the potential of this exciting technology, we reached out to various experts in the AM industry, including thought leaders, journalists, and enthusiasts. Here are their insights on where the industry’s heading.

As industries around the world work to make their process and products not only automated but also autonomous, there has been an explosion in the use of detection and ranging systems during the last 20 years. Detection and ranging systems date back to radar systems that were developed during World War II.

RADAR stands for radio detection and ranging. More modern systems have been developed around light sources, leading to laser radar, light detection and ranging (LIDAR), and laser detection and ranging (LADAR) systems. On the surface, all of these systems are based on similar philosophies, and articles often group them together. But, LIDAR, laser radar, and LADAR actually have some significant technological differences that affect the applications for which they are suited. So, we wanted to take a deep dive on these terms and identify what detection and ranging systems are for and how they differ from each other.

Amedical device company is expected to deliver innovative, life-changing devices while ensuring compliance and achieving true quality. This task bears loads of responsibility—all of which must be kept and documented within your quality management system (QMS).

A QMS contains everything that internal teams, partners, and regulators alike must know to get a product to market and achieve its intended purpose of delivering better outcomes to clinicians and patients. The choices you make about the QMS you decide to implement will resonate throughout your product’s life cycle.

In an increasingly digital world, medical device professionals find themselves bearing the burden of paper-based systems when they could be automating their processes with a purpose-built software solution.

As a medical device professional, you have either realized the benefits of a software solution or been tasked with, advised, or ordered to find one. Lightly put, selecting the wrong solution could jeopardize the success of your company, leaving your team frustrated with rework, prolonged project timelines, and failure to maintain compliance.

Graphene and related 2D materials have the potential to disrupt technologies such as energy storage devices, composites, and electronics through their exceptional material properties. Depending on the material, these can include properties such as high electrical conductivity, high mechanical strength, and high thermal conductivity.

However, when 2D materials are produced at industrial scale, their properties can differ from materials produced in a laboratory.

Liquid phase exfoliation (LPE) is one of the most widely used methods for producing 2D materials at scale. With this method, bulk powders, such as graphite, are perturbed in an organic solvent to generate shear forces and break the 2D layers apart into smaller nanomaterials—a process known as exfoliation. However, nanoplatelet dispersions produced with this method often contain unexfoliated bulk particles, exhibit a large variation in particle size, and the surface chemistry can vary with the addition of functional chemical groups introduced during synthesis.

Manufacturers understand that their businesses won’t grow if their workforces don’t grow along with them. That’s why the talent shortage in the metal fabrication industry continues to be a pressing concern—and three-quarters of respondents in the National Association of Manufacturers’ 2023 First Quarter Manufacturers’ Outlook Survey cite attracting and retaining a skilled labor force as a “primary business challenge.”

Increasingly, metal fabricators are turning to automation as a solution to this persistent problem. By integrating cutting-edge technology into all aspects of their operations, companies do more with less and help ease the physical burdens on older workers, allowing them to extend their careers—in addition to making manufacturing a more attractive career option for a younger generation that’s fluent in all things tech.

Not many years ago, there was a CEO so exceedingly fond of finding the right strategy that he spent all of his money on consultants to tell him what the strategy should be. One day there came two consultants, and they said they could craft the most magnificent strategy imaginable. Not only would it solve all of the problems and produce great prosperity and profitability; it had yet another feature: It would make no sense to anyone not qualified to be in his job.

“This would be just the strategy for me,” thought the CEO. “If I adopted it, then I would be able to discover which managers in my company are unfit for their posts. I could tell the ones I can trust from those who must be fired. Yes, I must have this strategy.” And he paid the consultants a large sum of money to start work at once.

The consultants set up their laptops and pretended to produce all sorts of presentations, though the presentations were actually jargon, buzzwords, and gibberish. They demanded all sorts of information about customers, sales, products, and market sectors while they worked their PowerPoint far into the night.

Business owners and employees alike have long debated over how best to achieve quality standards and what those standards ought to be. However, as much as linear thinking may help when measuring degrees of improvement, increases in profit, or low turnover rates, it can’t tell you that your company may need slightly different quality requirements than another—or why. That can only come from individualized, often-surveyed human analysis. And in an age where self-appointed doomsday prophets assert that AI will soon take over people’s livelihoods, the need for actual human analysis is a good thing!

As workplaces shift to offer more perks in the form of “company culture,” it can be easy to dismiss words like “values” and “mission statement” as irrelevant to a generation that touts company lunches, casual Fridays, and vending machines for the intended audience. But that’s not the case. In fact, company values like integrity, providing quality services or a quality product, and making sure a job gets done are all intrinsically tied to quality.

Wharton experts used machine learning to help uncover the secret formula for successful healthy habit formation, and it turned out there’s no one formula.

“There’s this widely spread rumor that it takes 21 days to form a habit,” says Katy Milkman, a Wharton professor of operations, information, and decisions. “You may have also heard it takes 90 days to form a habit. There are popular books that tout these numbers that don’t have a sound basis in research. What we find is there is no such magic number.”

Milkman spoke to Wharton Business Daily on SiriusXM about her recently published study. Wharton professor Angela Duckworth, who co-founded Penn’s Behavior Change for Good Initiative with Milkman, is one of six co-authors on the piece.

What are the stories we tell ourselves? It’s a simple question, yet one rich with possibility. In my years of creating leadership development programs, one of the “stories” that continually surfaces with leaders is “I need to do X for my direct reports because they are not yet ready/willing/able to do it for themselves.”

At first blush, this story seems an open-and-shut case. And, for some leaders tasked with leading inexperienced employees, perhaps this story is true. One of the ongoing dilemmas of leadership is determining when to turn over a decision or task to an employee. Questions to consider range from, “Is this person ready to accept responsibility?” to “What happens if this person drops the ball?”

You folks know I love asking questions. From this post about forgoing answers in favor of asking questions, to my quote, “Asking the right question about the future is more powerful than having the right answer about the past,” I’ve found questions to be a more powerful leadership tool than many others that are out there. Heck, if you read my book One Piece of Paper (Jossey-Bass, 2021), you’ll find it’s full of questions designed to help you become a better leader.

Out of all the questions I know of, the shortest one of all is a great way to stay out of trouble as a leader. I’m talking about the kind of trouble that earns you a reputation as a jackass, an insensitive lout, or someone too obtuse to care about people: “Why?”

We’re generally smart people—that’s why they put us in leadership roles. Smartitude can get problematic, though, when you assess situations too quickly, draw conclusions, then act without taking a moment to stop. Think. Get grounded.

Allow me to demonstrate how I could have avoided looking like a complete idiot if only I’d asked, “Why?” instead to being a “decisive leader.”