The buzz around artificial intelligence (AI) often centers on futuristic visions and theoretical debates, making it easy to overlook its practical impact on industries right at the core of our economy, such as the manufacturing sector.
Traditionally perceived as “equipment heavy and tech light,” manufacturing is undergoing a silent revolution, fundamentally reshaped by the advent of AI technologies. In this landscape, AI isn’t just a tool but a transformative force that redefines efficiency, innovation, and sustainability.
In an interview with Rhonda Dibachi, CEO of HeyScottie, she explained one of the reasons AI is having such a big impact on manufacturing. “AI works on data, and it works more magic with more data. Guess what? Your typical manufacturing company is a prolific data-generating machine,” Dibachi explained.
The deployment of AI in manufacturing is not just theoretical but a reality that has been unfolding for decades, especially in areas such as optical inspection and predictive maintenance. These applications of AI not only enhance efficiency but also significantly reduce operational costs by preempting failures and optimizing equipment performance.
Dibachi noted, “AI, specifically the branch called machine learning (ML), has been widely used in optical inspection systems for two decades. It’s used now in predictive maintenance operations – correlating machine behavior with downtime, finding correlations between any number of operating parameters and machine downtime.”
Beyond maintenance, AI is redefining the design and development processes within manufacturing. Dibachi points to the acceleration in design speeds as one of AI’s most significant contributions, enabling quicker verification that designs meet all necessary standards and regulations.
“The biggest impact of AI will be the increased speed of design thanks to better design tech,” Dibachi states, underscoring the potential for AI to streamline product development and enhance market fit and sustainability.
However, the narrative of AI in manufacturing is not uniformly positive across the board. When discussing the position of the U.S. in the global manufacturing landscape, Dibachi offers a nuanced view: “We do very, very well on innovation… but productivity is another matter.”
Despite leading in innovation, the U.S. faces challenges in productivity, with many attributing this stagnation to a slow adoption of new technologies and a lack of investment in education. This gap underscores a critical area where AI can play a pivotal role in reclaiming lost ground.
HeyScottie exemplifies the practical application of AI in manufacturing, targeting the metal finishing sector with an AI-powered marketplace. Commenting on the innovation behind their service, Dibachi said, “We’re making it easier to buy metal finishing services by providing instant pricing using an ML-based pricing engine.”
HeyScottie’s solution simplifies the complex task of pricing custom services, showcasing AI’s potential to streamline and enhance manufacturing processes.
Dibachi is unequivocally optimistic about AI’s role in manufacturing, viewing it as a transformative force. “Absolutely, positively, transforming,” she affirms, stating that by leveraging the vast amounts of data produced by manufacturing operations, AI can optimize every aspect of production, from tool paths for CNC machines to compliance checks.
The efficiency brought forth by AI not only improves operations but also has the potential to attract significant investment, aligning manufacturing more closely with the fast-paced tech industry.
During the conversation, Dibachi also reflected on her journey as a woman leader in STEM and the CEO of a pioneering company. Despite facing challenges, her passion for innovation and problem-solving has remained unwavering.
“My experience has been overwhelmingly positive… I love the challenge of it,” Dibachi shared, offering encouragement to other women in the field to embrace the challenges and contribute to the ongoing transformation.
