The use of artificial intelligence in the manufacturing industry is becoming increasingly important, even in highly specialized niches such as micro injection moulding. At US manufacturer Accumold, which has specialized in the production of complex micro-components for medical, electronic and optical applications for decades, AI is used specifically to improve existing processes without replacing human expertise.
“At Accumold, we see AI as an enabler, not a substitute,” says Roger Hargens, President and CEO. “It’s about empowering our people to work smarter, make faster decisions, and provide our customers with better outcomes. AI is a tool in our toolbox, not the craftsman.”
This data-based analysis enables the teams to create reliable forecasts for delivery times and project costs – a significant advantage in a market environment that demands increasingly shorter development cycles and greater precision.
The actual decision-making process remains in the hands of experienced engineers. AI models merely serve to increase efficiency by making information available more quickly. For Accumold, this means that development cycles are easier to plan and there is more room for the technical and creative development of solutions, for example in the optimization of production for microstructured components.
“We’re not interested in adopting technology for technology’s sake,” Hargens adds. “We’re interested in anything that makes us a better partner to our customers. AI helps us do that by improving efficiency and allowing our experts to focus on what really matters, innovation, collaboration, and getting things right the first time.”
This approach offers a particular advantage in fields of application with high regulatory requirements, such as medical technology or micro-optical components for wearable electronics: data-based planning not only increases the reliability of supply chains, but also supports the early identification of potential manufacturing risks. Accumold sees the combination of data-driven analysis and experience-based engineering as a practicable way to adapt manufacturing technologies to current market requirements – without being guided by short-term technology trends.
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