A Closer Look at Professional Development at IPC APEX EXPO 2024: 3D Printing and AI

Estimated reading time: 7 minutes

While the finishing touches were being made to the show floor at IPC APEX EXPO, just as much activity was happening in the conference rooms of the Anaheim Convention Center on the days before the show officially opened.

The hallways and classrooms were filled for standards committee development meetings and Professional Development Courses, and IPC hosted evening receptions for Emerging Engineers, ECWC, and those who are attending for the first time in a special “newcomers” event.

The following are two reports on PD Courses, one from Sunday, and another from Monday.

Dylan Nguyen, a freshman at Oregon State University assisting in the I-Connect007 booth, took some time to share his thoughts after attending a course titled “Intro to 3D Printing,” in these remarks:

What I Learned About 3D Printing
On Sunday morning, approximately an hour after arriving in Anaheim, I attended one of the first Professional Development lectures titled "Intro to 3D Printing," led by Kat Ermant from Peloton. I have some prior experience in additive and subtractive manufacturing gained through my studies in STEM and robotics, and was keenly interested in exploring how this technology is applied in industry. Given the popularity of 3D printing in education, particularly among my generation, I was eager to learn about its potential relevance to our future careers.

The Professional Development lecture was divided into two informative sessions. The first, entitled "Harnessing the Language of Additive Manufacturing," provided a thorough introduction to fused deposition modeling (FDM) and stereolithography (SLA) 3D printing. Ermant discussed the manufacturing workflow associated with each method, covering aspects such as setup procedures, post-processing techniques, and the respective strengths and weaknesses of FDM and SLA printing.

The subsequent session, titled “Prototype Applications for Product Development.” focused on the applications of 3D printing in the design process. While I was already familiar with 3D printing prior to the lecture, I was really fascinated with how this technology was applied in industry. Ermant underscored the uses of 3D printing in the product development cycle, particularly in something known as rapid prototyping. 

Notably, 3D printing offers a cost-effective, iterative approach that faithfully reflects the final design, whether mechanically or visually. In contrast to traditional “low tech” prototyping methodologies like clay modeling or cardboard mock-ups, computer-aided manufacturing creates a more streamlined and iterative design process.

Ermant also expanded on the other applications of 3D printing technology, including low-volume manufacturing, design customization, and its use as a stopgap during supply chain disruptions. Drawing upon examples from the COVID-19 pandemic, she underscored the instrumental role of 3D printing in swiftly producing essentials such as personal protective equipment (PPE) and testing swabs. 

As a student, my first exposure to 3D printing was exactly this. In the height of the pandemic, my high school FIRST Robotics team repurposed our lab's 3D printers to manufacture PPE for frontline workers within our community. Each face shield took approximately three hours to print. While slower than other manufacturing methods, the accessibility of 3D printing made it possible for a robotics team to continue working, despite interruptions such as the pandemic lockdown.

By the end of Ermant’s presentation, I felt like I better understood the potential strengths of 3D printing. While it may not replace traditional forms of manufacturing, its versatility makes it ideal for applications such as rapid prototyping. I’m excited to see what we can do with this technology as it continues to grow and change.

The Possibilities of AI

Marcy LaRont, managing editor of PCB007 Magazine, attended a presentation on artificial intelligence (AI) by industry veteran Jennie Hwang, Ph.D., DSc. of H-Technologies Group. As AI seems to be top of mind for everyone these days, including for manufacturers, I was happy to spend my morning taking a deep dive into both the concept and the reality that is AI.

Taking attendees through the genesis and history of AI, some of the younger crowd were likely surprised to learn that AI is not a new concept but rather a term coined by the “father of artificial intelligence,” John McCarthy, in 1956. Hwang explained that the explosion of AI, as we think about it today, can be pinpointed to Nov. 20, 2022, when OpenAI launched its ChatGPT software, which has since taken the world by storm. According to venture capital groups, between 2022 and 2023, there were more than 100 startup companies, all dedicated to developing AI software.

More diverse than the average person may realize, it was explained that the AI pyramid of smart technology actually begins with machine learning (ML) and then deep learning (DL), followed by neural networks (layered algorithms and data processing for inferential learning), digital twin, internet of things (IoT), and finally, generative AI, which has the potential to develop a more human-like thinking ability and is, therefore, the pinnacle of the AI pyramid.

AI is perhaps the single biggest technology driver for denser chips, requiring ever greater amounts of power to process and assimilate data. As an example, ChatGPT 4 was released by OpenAI on March 14. Whereas GPT-1 started with an ability to work with 117 million parameters and 1,024 sequences, GPT-4 works with parameters estimated to be in the trillions with upward of 8,000 to 32,000 sequences.

She also spoke of the necessity of human learning to maximize our ability to make generative AI work for us, referencing “prompt engineering” and evolving tools there, helping you refine your queries to get the intended information. She cautioned users of AI tools to know their chosen tool’s strengths and weaknesses and try to discover whether there is bias in the way the tool gathers and processes data, as there often is.

Of course, there is a long list of both pros and cons, with the pros seemingly outweighing the cons based on what we know today, which is admittedly not a lot. Commonly referenced cons include accuracy, plagiarism concerns, and increased spamming. (Phishing emails have experienced a staggering increase since the launch of ChatGPT.) Another con is that all the benefits we experience are also being leveraged by those with more nefarious objectives, including hackers, making the gains we will see in areas such as cybersecurity very important.

Though Generative AI is important for many aspects of business and will likely inform every area of our lives as it continues to develop, it is ML, DL and NN that more often enter into the manufacturing landscape today. ML and DL are algorithm-driven learning from data – whether that data is provided by a human or gathered by the machine itself. Deep learning and neural networks have increasingly complex layers of data streams and output a tremendous amount of data that is processed algorithmically, developing statistical and mathematical models to recognize patterns and predict outcomes. Though dependent on different levels of human partnership, the human factor is still a part of machine learning, deep learning, and neural network AI.

What is for certain is that the modern AI movement will have a tremendous market and workforce impact. Gen AI stands to double the rate of U.S. productivity growth after widespread adoption, with an estimated 20-40% of certain job functions that should be able to be completely automated. This time around, it is the white collar/business sector that will feel the hit. Job functions in communication and marketing, things such as grant writing and perhaps social media marketing, as well as software engineering (writing code), process engineering, cybersecurity, IT, Human Resources, and consulting, have all been identified. It is estimated that 75% of AI’s value will be experienced in many of these professions.

Today, the United States still stands as the technology leader in AI, while a fierce battle rages between the U.S. and China for supremacy in this area. Russian president Vladamir Putin was recently referenced, saying, “Whoever becomes leader in this sphere will rule the world,” a sentiment which certainly underlies the significant pros and cons that this technology brings to bear in the greater scheme of things. In the end, as Dr. Hwang declared, “The outputs from Gen AI tools will require skillful careful human intervention to maximize the technology benefits and mitigate pitfalls.“

To read more about AI from Jennie Hwang, click here for her recent column on the very subject..