In my previous blog, I reached out to this community of engineers to gauge the experiences and expectations you have regarding artificial intelligence (AI) at work. The feedback was interesting and not exactly what I expected. More than half of you (55%) are somewhat familiar with the concept of AI in engineering (why did I think that number would have been ascribed to familiar?). The other 45% of you are equally split with 15% in each: very familiar, familiar and not familiar.
It was the “not familiar” stat that surprised me. Did I expect all readers to be familiar with AI? Maybe. But that stat also showed me that we need to continue to bring our readers content about emerging technologies such as AI and machine learning.
I see some of you are already integrating AI into your workflows: “My present design uses video Machine Learning,” one of you wrote. Another uses “In Condition Based Monitoring, to predict trends,” and yet another writes: “It is being employed in both our products for surgical planning and real-time image analysis for surgeons. And we’re using it to hyperautomate dozens of time-consuming manual back-office tasks.”
Some of you expressed how AI can improve design processes: “By understanding the design processes AI can automate a lot of tasks,” “Speeding up design time with more information in a quicker time compared to traditional research methods,” and “Streamline many kinds of mundane repetitive tasks of limited value-add relative to effort expended, support data mining, support decision making and critical thinking, write SW code” were a few comments I received.
Others are dipping their toes into the concept of AI in engineering: “Most I feel like it can help spur ideas for a design at the beginning of the R&D Process if a complete new design is necessary, and topology optimization for manufacturing processes to reduce the amount of material to be used while retaining strength” and “not sure. If based only on requirements, it might shorten the time to design Material Flow Diagram. It might take longer to set out the requirements. It might also not be able to select the right technology.”
AI Is Taking Orders
Recently I had the chance to witness AI and ML in action at a fast food restaurant’s drive-thru. The establishment had rolled out an AI-driven order-taking system that seemed to work like a well-oiled machine, efficiently minimizing hold times and improving the overall customer experience—at least this customer.
I was intrigued, so I took a moment to ask the manager at the window (I promise there was no one in line behind me) for her take on the system. She said the system had dramatically improved since its initial implementation just a few weeks before.
We talked about the large language models and advanced machine learning algorithms that allow the system to continuously learn from each interaction. She noted how interesting it was that this location’s system works “differently” than another location, and that she is amazed at how fast it is learning their regular customers and types of ordering.
It seems this adaptive intelligence not only refines order processing but also personalizes customer interactions based on historical data and preferences. What a compelling case study on the potential for AI to streamline operations in various settings, including manufacturing.
Unlocking AI’s Power in Design
To the reader who indicated you are not yet familiar with AI and who answered both of my questions with “you tell me,” I’d like to extend a warm welcome to the world of intelligent tools and technologies that can help with designing to the fullest potential. From what I have seen at various trade events, what I have read during my research and what I have heard from subject matter experts in the field, AI can vastly improve design processes by automating repetitive tasks, providing insightful data analysis and generating innovative design alternatives.
Transformative examples include advancements in workflows. Generative design software utilizes AI to explore thousands of design variations based on specific constraints, which can lead to more efficient and innovative outcomes.
It's important to recognize that while AI offers exciting opportunities, traditional skills and knowledge remain invaluable. The combination of AI and traditional techniques empowers us to approach problems from multiple angles, enabling us to leverage technology without losing the human touch that is necessary in design.
As we continue to explore the topic of AI, we want to hear from you. Your experience and preferences help guide us in crafting content that resonates with our audience. Please take a moment to share your thoughts in this brief survey. Until next time, stay curious.
